wegcenter/unigraz technical report for ffg-alr no. 3/2007 · 2014. 4. 18. · ar receiving system...

Wegener Center for Climate and Global Change University of Graz Leechgasse 25, A-8010 Graz, Austria Atmospheric Remote Sensing and Climate System Research Group ACCURAID Project Report

Wegener Center for Climate and Global Change, University of Graz, Leechgasse 25, A-8010 Graz, Austria E-Mail: [email protected], Web: http://www.wegcenter.at

WegCenter/UniGraz Technical Report for FFG-ALR No. 3/2007

FFG-ALR study:

ACCURAID – Aid to ACCURATE Climate Satellite Mission Preparations [Contract No: ALR-OEWP-WV-327/06 – January 2007]

STUDIES REPORT

[WP3: STUDIES]

ACCURATE LEO-LEO Infrared Laser Occultation Initial Assessment: Requirements, Payload Characteristics, Scientific Performance Analysis,

and Breadboarding Specifications

G. Kirchengast and S. Schweitzer

Wegener Center for Climate and Global Change (WegCenter), University of Graz, Graz, Austria

April 2007

ACCURATE LEO-LEO IR Laser Occultation (LIO) Initial Assessment Project ACCURAID – Aid to ACCURATE Climate Satellite Mission Preparations

Wegener Center for Climate and Global Change, University of Graz, Leechgasse 25, A-8010 Graz, Austria ii Contact E-Mail: [email protected], Wegener Center Web: http://www.wegcenter.at

(intentionally left blank; back page if double-sided print)


Wegener Center for Climate and Global Change, University of Graz, Leechgasse 25, A-8010 Graz, Austria iii Contact E-Mail: [email protected], Wegener Center Web: http://www.wegcenter.at

Table of Contents

1 INTRODUCTION AND CONTEXT: THE ACCURATE MISSION .......................... 1

2 LIO OBSERVATIONAL AND SYSTEM REQUIREMENTS..................................... 3

2.1 Observational Requirements ..................................................................................... 3

2.2 System Requirements ................................................................................................. 5

3 CONCEPT AND CHARACTERISTICS OF THE LIO PAYLOAD ........................... 7

3.1 LIO Measurement Principle and Characteristics.................................................... 7 3.1.1 Measurement Principle and Favorable Properties............................................................................... 7 3.1.2 LIO Channel Selection for Target Species.......................................................................................... 8 3.1.3 Further Characteristics ...................................................................................................................... 15

3.2 LIO Payload Technical Concept and Performance............................................... 17 3.2.1 LIO Link Budget............................................................................................................................... 17 3.2.2 LIO Tx Laser System........................................................................................................................ 18 3.2.3 LIO Rx Receiving and Detection System ......................................................................................... 20

4 LIO SCIENTIFIC PERFORMANCE ANALYSIS...................................................... 23

4.1 Retrieval Performance Estimation System............................................................. 24 4.1.1 Performance Modeling Algorithms................................................................................................... 26 4.1.2 Step-by-Step Modeling Results......................................................................................................... 33

4.2 Differential Transmission Retrieval Performance................................................. 37

4.3 Trace Species Profiles Retrieval Performance....................................................... 39

4.4 Wind Profiles Retrieval Performance..................................................................... 42

5 SPECIFICATIONS FOR LIO SYSTEM BREADBOARDING ................................. 45

5.1 LIO Tx System Demo Breadboard Specifications ................................................. 45

5.2 LIO Rx System Demo Breadboard Specifications................................................. 49

6 SUMMARY, CONCLUSIONS, AND OUTLOOK ...................................................... 53

REFERENCES ....................................................................................................................... 55


Wegener Center for Climate and Global Change, University of Graz, Leechgasse 25, A-8010 Graz, Austria iv Contact E-Mail: [email protected], Wegener Center Web: http://www.wegcenter.at



Wegener Center for Climate and Global Change, University of Graz, Leechgasse 25, A-8010 Graz, Austria v Contact E-Mail: [email protected], Wegener Center Web: http://www.wegcenter.at

List of Acronyms ACCURATE Atmospheric Climate and Chemistry in the UTLS Region and

climate Trends Explorer ACE Atmospheric Chemistry Experiment (Canadian solar occultation mission) ACE+ Atmosphere and Climate Explorer (occultation mission studied by ESA 2002–2004) ALPS ACCURATE LIO Performance Simulator BW Bandwidth (observational bandwidth, nominally corresponding to half the

sampling rate) DLR/IPA DLR Oberpfaffenhofen / Institut für Physik der Atmosphäre DFB Distributed Feed-Back laser ECMWF European Centre for Medium-Range Weather Forecasts (Reading, U.K.) EGOPS End-to-end Generic Occultation Performance Simulator Envisat Environmental Satellite (of the European Space Agency) EUMETSAT European Organisation for the Exploitation of Meteorological Satellites ESA European Space Agency FASCODE FASt Atmospheric Signature CODE FFG-ALR Austrian Aeronautics and Space Agency of the Austrian Research

Promotion Agency FFG FOV Field of View (remote sounding area sensed by receiver antennae or optics) FWHM Full Width at Half Maximum (line width measure for spectral lines and laser lines) Galileo European future global navigation satellite system GHG(s) Greenhouse gas(es) GNSS Global Navigation Satellite Systems (Global Navigation System, GPS, and Galileo) GOMOS Global Ozone Monitoring by Occultation of Stars (instrument on Envisat) GPS Global Positioning System GRO GNSS-LEO radio occultation (here Galileo & GPS L band signals, ~1.2 / 1.6 GHz) HITRAN High-resolution Transmission molecular absorption database IDL Interactive Data Language (an interactive visual analysis software package) InGaAs Indium-Gallium-Arsenide (IR optical detector material; also Extended InGaAs) IR Infrared l.o.s. wind line-of-sight wind (denoting the wind speed along occultation rays) LEO Low Earth Orbit (or satellite in Low Earth Orbit) LIO LEO-LEO infrared laser occultation (here laser crosslink signals within 2–2.5 μm) LRO LEO-LEO radio occultation (here microwave crosslink signals within 17–23 GHz

and 178–183 GHz) LS Lower Stratosphere (WMO: 100–10 hPa / ~15–35 km) LT Lower Troposphere (WMO: 1000–500 hPa / ~0–5 km) MetOp Meteorological Operational satellite (of EUMETSAT) MIPAS Michelson Interferometer for Passive Atmospheric Sounding MW Microwave spectral region (3–300 GHz; here the 17–23&178–183 GHz regions) NEP Noise Equivalent Power (figure indicating optical detector sensitivity) NWP Numerical weather prediction RF Radio Frequency RFM Reference Forward Model RH Relative humidity RMS, rms Root Mean Square (average spread measure for statistical or total error) SI Système Internationale (International system of fundamental physical units) SNR Signal-to-noise ratio SWIR Short wave infrared spectral region (1.5-3 μm; here referring to the 2–2.5 μm region) TBL Top of atmospheric boundary layer TOA Top of the Atmosphere (in ACCURATE LIO generally referring to 60 km height) Tx, Rx Transmitter (Tx) resp. Receiver (Rx); also Transmitter resp. Receiver satellite


Wegener Center for Climate and Global Change, University of Graz, Leechgasse 25, A-8010 Graz, Austria vi Contact E-Mail: [email protected], Wegener Center Web: http://www.wegcenter.at

UT Upper Troposphere (WMO: 500–100 hPa / ~5–15 km) US Upper Stratosphere (WMO: 10–1 hPa / ~35–50 km) UTLS Upper Troposphere & Lower Stratosphere region (WMO: 500–10 hPa / ~5–35 km) WegCenter/ Wegener Center for Climate and Global Change, UniGraz University of Graz (Austria) WALES Water vapour Lidar experiment in space (ESA water vapor mission concept) WMO World Meteorological Organization X/K band Microwave band covering the frequencies 7–40 GHz H2O, CO2, CH4 water vapor, carbon dioxide, methane (ACCURATE target species) N2O, O3, CO nitrous oxide, ozone, carbon monoxide (ACCURATE target species) HDO, H2

18O “heavy-hydrogen” and “heavy-oxygen” water vapor main isotopes (ACCURATE target isotope species for water vapor)

13CO2, C18OO “heavy-carbon” and “heavy-oxygen” carbon dioxide main isotopes (ACCURATE target isotope species for carbon dioxide)


Wegener Center for Climate and Global Change, University of Graz, Leechgasse 25, A-8010 Graz, Austria vii Contact E-Mail: [email protected], Wegener Center Web: http://www.wegcenter.at

List of Symbols ΔTrabs Absolute [dB] difference between absorption and reference channel; also termed

differential transmission or differential log-transmission ΔTrw1w2 Differential log-transmission of the two ACCURATE wind channels (Trw1 – Trw2) ΔTrw1w2,0,Mod Zero-wind transmission difference between the two wind channels ΔΔTrw1w2 Double-difference (Trw1–TrRef) – (Trw2–TrRef) concerning the wind channels; also

termed delta-differential transmission or delta-differential log-transmission λ Wavelength λAbs, λRef ACCURATE “on-wavelengths” and “off-wavelengths”, respectively λw1, λw2 Wavelengths of the ACCURATE wind(1) (=w1) and wind(2) (=w2) channels ν , ν Frequency, wavenumber (here generally wavenumber [cm-1] used) Ar Receiving system optics reception area (reception mirror/telescope area) c0 Vacuum speed of light (SI definition: 299 792 458 m/s) cdB2% Constant converting units [dB] to [%] (= 10⋅ln10 = 23.026) c%2dB Constant converting units [%] to [dB] (= 1/(10⋅ln10) = 0.043429) dr Diameter of the circular receiver optics (dTr/dν )wi,Mod Transmission derivatives for the wind channels (i ∈ {1, 2}) dzfilt, dztarget Vertical resolution (as for filtered sampling rate fs,filt), target vertical resolution (1-2

km for ACCURATE) D* Detectivity of the detector (technical spec indicating optical detector sensitivity) Dtr Distance between transmitter and receiver (here LEO-LEO inter-satellite distance) eΔT_w1w2_rel,0,Mod Relative error [%] of the zero-wind w1–w2 log-transmission difference modeling edTr/dν_w_rel,Mod Relative error [%] of the w1 and w2 log-transmission derivatives modeling efL_rel,Knowl Relative laser frequency knowledge uncertainty error [1] efL_rel,Stabil Relative laser frequency stability rms error [1] (at raw sampling rate) EΔΔT_resid Delta-differencing (of differential log-transmissions) residual error EΔΔT_w1w2 Delta-differential log-transmission error EΔΔT_w1w2_abs Absolute [dB] delta-differential log-transmission total error EΔΔT_w1w2_rel Relative [dB/dB] delta-differential log-transmission total error EΔT Differential log-transmission total error EΔT_abs, EΔT_rel Absolute [dB] and relative [dB/dB] differential log-transmission error EΔT_resid log-transmission differencing residual error (from scattering, turb.scintillations, etc.) EΔT_w1w2,0,Mod Model error of the zero-wind w1–w2 log-transmission difference EσAbs Absorption cross section error EAbsC Species absorption coefficient error EdTr/dν_abs,Mod Absolute [dB/cm-1] differential log-transmission derivative model error EdTr/dν_rel,Mod Relative [(dB/cm-1)/(dB/cm-1)] differential log-transmission derivative model error EdTr/dν_wi,Mod Model error of the log-transmission derivatives for wind channels (i ∈ {1, 2}) EfL_abs,dz_target Absolute laser frequency error [cm-1] at targeted vertical resolution EfL_dB,dz_target Laser log-frequency error [dB] at targeted vertical resolution EH2O H2O profile retrieval error (combined error from more than one λAbs channel) ESp Species profile retrieval error ESp,MonAv Monthly-mean species profile retrieval error ET_Abs, ET_Ref SNR-based log-transmission error for absorption (Abs) and reference (Ref) channel ET_wi Total log-transmission error for wind channels (i ∈ {1, 2}) ET_wi,0 Zero-wind log-transmission error for wind channels (i ∈ {1, 2}) ET_wi,fL Laser frequency-based log-transmission error for wind channels (i ∈ {1, 2}) ET_wi,SNR SNR-based log-transmission error for wind channels (i ∈ {1, 2}) EV_los Line-of-sight wind profile retrieval (absolute) error [m/s] EV_los_rel,Statist Statistical wind retrieval relative error [%]


Wegener Center for Climate and Global Change, University of Graz, Leechgasse 25, A-8010 Graz, Austria viii Contact E-Mail: [email protected], Wegener Center Web: http://www.wegcenter.at

EV_los,Statist Statistical wind retrieval (absolute) error [m/s] EV_los,System Single-profile systematic (absolute) wind error [m/s] fs,filt Filtered sampling rate (= 2 Hz, corresponding to 1 Hz bandwidth) fs,raw Raw sampling rate (= 50 Hz, ACCURATE baseline sampling rate) gAbelTr Error amplification factor due to absorptive Abel transform (from EΔT_rel to EAbsC) gcorr Error reduction factor in case of double-differencing of correlated single-differences Gds Downsampling gain (gain from downsampling fs,raw to fs,filt) Gresol Resolution gain (gain from re-sampling dzfilt to dztarget; can also be negative) H Scale height (atmospheric scale height) HDef Defocusing scale height (scale height of height dependence of defocus. loss) LA Aerosol extinction loss LBgr Total background loss (from all loss processes except target species absorption) LBgrAbs Background absorption loss from all absorbing species except the target species LBgr+TSp Background absorption loss from all absorbing species including the target species LDef Defocusing loss LR Rayleigh scattering loss Ltr Propagation loss (from geometric dilution of the signal over distance Dtr) LTS Turbulence/scintillation loss LTSp Target species absorption loss Nbin Number of profiles per grid box per month (for climatological averaging) Pt, Pr Transmitted and received power, respectively p Pressure (total air pressure) q Specific humidity SNRAbs, SNRRef Available SNR for absorption (Abs) and reference (Ref) channel SNRbasic Basic available SNR, at target vertical resolution dztarget SNRf_s,raw SNR at raw sampling rate T Temperature Tr Transmission (here generally used in terms of log-transmission [dB]) Vlos Line-of-sight wind velocity Vscan LEO-LEO vertical scan velocity (set/rise velocity of occultation rays) wr Gaussian beam (e-2) radius at the receiver (of transmitted laser signal beam) z Height, altitude (geoid undulation difference between ellipsoidal height and mean-

sea-level altitude not relevant in the initial assessment context of this report) Z Geopotential height


Wegener Center for Climate and Global Change, University of Graz, Leechgasse 25, A-8010 Graz, Austria 1 Contact E-Mail: [email protected], Wegener Center Web: http://www.wegcenter.at

1 Introduction and Context: The ACCURATE Mission

The ACCURATE mission employs the occultation measurement principle, known for its unique combination of vertical resolution, accuracy and long-term stability, in a novel way. It systematically combines use of highly stable radio signals in the MW 17–23 & 178–183 GHz bands (LEO-LEO radio crosslink occultation, LRO) with laser signals in the SWIR 2–2.5 μm band (LEO-LEO infrared laser crosslink occultation, LIO) for exploring and monitoring cli-mate and chemistry in the atmosphere with focus on the UTLS region (5–35 km). The MW radio occultation is an advanced and at the same time compact version of the ACE+ X/K band occultation, which was described in ESA (2004a,b) and OPAC (2004b) and which is a key heritage for ACCURATE. The MW 17–23 GHz signals were complemented by 178-183 GHz signals based on U.S. heritage (JAOT, 2002; OPAC, 2004c). The new LIO IR laser crosslinks together with the LRO microwave crosslinks form the novel core of ACCURATE. Optionally also a Galileo/GPS component (GNSS-LEO occultation, GRO) is planned in order to demonstrate the use of Galileo-LEO radio occultation. Figure 1 provides a schematic over-view of the ACCURATE system. The mission concept was recently proposed to ESA (ACCURATE, 2005) in response to a Call for Earth Explorer Core Missions (ESA, 2005) and received, in a stringent scientific and technical peer assessment process, very positive evaluation and recommendations for further study (ESA, 2006). It was acknowledged that ACCURATE can act as a cornerstone contribu-tion to the priority “Atmospheric Chemistry and Climate” of the “Priorities for 2005 Call” (section 6 in ESA, 2005) and also provide vital contributions related to the atmospheric sub-system of the Earth system for the priorities “The Global Water Cycle” and “The Global Car-bon Cycle”. For background information on the utility of occultations in the field of remote sounding of atmosphere and climate an introduction can be found in OPAC (2004a). That paper intro-duced the general principles, capabilities, properties, and exploitation possibilities of occulta-tion methods in order to furnish basic knowledge and insight on how they may contribute to a better understanding of the Earth’s atmosphere and climate system and to better prediction of its future evolution. Given that background it becomes clear that the ACCURATE mission concept is conceived based on the best features learned so far on signal source, atmospheric signal propagation and radiation-atmosphere interaction, receiving system properties, and data processing methodologies. The solid experience on which ACCURATE builds is not least a result of the vast heritage available from well more than a decade of mission preparatory activities supported by ESA. For example, at the radio occultation side mission concepts have been under study since the first Earth Explorer Core Mission round in 1996; a more detailed account of the “ESA his-tory” of mission concepts is found in the introduction section of OPAC (2004b). But also at the optical occultation side and with laser-based sounding technologies, strong heritage exists from Envisat and Earth Explorer activities in the framework of ESA.



Figure 1. Schematic view of the ACCURATE system, with sidebar information.

By its design and based on its novel way of synergistic exploitation of the properties of the occultation measurement principle in the radio and IR domains together (LRO+LIO), ACCURATE is set to initiate and establish an unprecedented global data set of profiling the atmospheric physical, chemical, and climate state over the UTLS domain at high vertical resolution, accuracy, and long-term stability. We term these data, due to their unique utility for climate trends monitoring and climate model validation and improvement based on their un-biased nature, also climate benchmark data. The observed parameters will comprise, measured simultaneously and in a self-calibrated manner based on Doppler shift and differential log-transmission profiles:

1) the fundamental thermodynamic variables of the gas (temperature T, pressure p / geo-potential height Z, humidity q) obtained from LRO, which will back LIO derivation of

2) the line-of-sight wind (Vlos), which due to the baselined LEO-LEO orbital geometry essentially represents the meridional wind, a fundamental dynamical variable, and of

3) the main six greenhouse gases H2O, CO2, CH4, N2O, O3, and CO, which are also key species of UTLS chemistry, together with the primary water vapor and carbon dioxide isotopes HDO, H2

18O, 13CO2, and C18OO, which are important tracers of the sources of these gases (e.g., whether anthropogenic or natural in case of CO2).

Furthermore, profiles of aerosols, cloud layering, and turbulence are obtained, mainly based on direct (single-channel, non-differenced) transmission profiles. All profiles come with accu-rate height knowledge (< 10 m uncertainty), since measuring height as a function of time is an intrinsic part of the ACCURATE observing system. In this report, a concise summary of requirements in section 2 is followed by a description of concept and characteristics of the LIO payload in section 3. Section 4 describes an initial LIO scientific performance analysis and the encouraging results obtained. Based on the previous sections, section 5 summarizes specifications for breadboarding of representative LIO laser crosslinks. Finally, section 6 provides conclusions and suggests next steps towards realization of the ACCURATE mission, which could start immediately.



2 LIO Observational and System Requirements

2.1 Observational Requirements The observational requirements for the LIO component, i.e., for the greenhouse gases (GHGs) and isotope species as well as l.o.s. wind observations of ACCURATE, represent the current state of definition (April 2007). They will be further refined in the future, e.g., in case of ESA during preparatory technical and scientific studies by ESA and Partners. Table 1 below presents the LIO requirements in context with the LRO requirements. The lat-ter are closely based on the heritage from ACE+ work (ESA, 2004a; see Table 4-2 on p. 21 therein) and are included in this LIO report, since the accuracy of the LRO temperature, pres-sure, and humidity profiles is an essential prerequisite for accurate LIO trace species and wind retrieval as is explained in more detail in section 3. Adequate pressure accuracy is im-plicitly ensured by the required temperature and humidity accuracy, as is the accuracy of other relevant LRO variables such as refractivity determining the ray paths of LIO occultation signals. The main further advancement of the LRO requirements since ESA (2004a) is that the humid-ity height domain is extended up to 18 km, enabling to cover also high-reaching convective cloud systems (including tropical cloud systems reaching up to the tropical tropopause at 16–17 km), and that the humidity accuracy is specified as relative rather than absolute accuracy to ensure a high-quality product also at heights above 12 km where moisture concentrations become very small. Furthermore, the LRO requirements focus now on the UTLS (lower tro-posphere included on best-effort basis), for optimal synergy with the LIO measurements. The primary LIO measurement parameters are the ten trace species H2O, CO2, CH4, N2O, O3, CO, HDO, H2

18O, 13CO2, C18OO, and the l.o.s. wind Vlos, for which vertical profiles shall be available consistent with the quantitative LIO requirements of Table 1. Particularly relevant for climate applications, the long-term stability requirements ensure that all LIO profiles shall be essentially unbiased (free of time-varying biases). Secondary LIO measurement parameters are aerosol, clouds, and turbulence, for which vertical profiles of aerosol concentration, cloud layering, and turbulence strength shall be retrieved on a best-effort basis. Due to this best-effort retrieval, no quantitative requirements have been included for these secondary parame-ters in Table 1. Their useful accuracy is ensured implicitly by the required trace species and wind accuracies, however. The cloud-layering profiles shall be available with sufficient qual-ity to adequately flag cloud-perturbed vertical levels. Derived LIO products shall include UTLS (5–35 km, 500–10 hPa) vertical columnar amounts, as well as separately UT (5–15 km, 500–100 hPa) and LS (15–35 km, 100–10 hPa) vertical columnar amounts, respectively, of all trace species profiles.



Table 1. ACCURATE LRO and LIO Observational Requirements

LRO LIO Temperature Sp. Humidity Trace Species1) l.o.s. Wind

Requirement Target Thres Target Thres Target Thres Target Thres Units Horizontal domain global Horizontal sampling (mean distance of adjacent profiles) to be achieved within:

700 1600 700 1600 700 1600 700 1600 [km]

time sampling 24 [hrs] No. of profiles per grid box2) per month 40 30 40 30 40 30 40 30

Vertical domain 5-50 7-40 5-183) 7-12 5-35 7-304) 10-40 15-35 [km]

Vertical sampling

LT UT LS US

0.5 0.5 0.5 1

1 1 1

2.5

0.5 0.5 0.5 -

1 1 1 -

0.5 0.5 0.5 1

1 1 1

2.5

0.5 0.5 0.5 1

1 1 1

2.5

[km] [km] [km] [km]

best-effort basis - - best-effort basis 5

5 5

10 10 10

2 2

5 5

RMS accu-racy5)

LT UT-bottom UT-≥10km LS US

1 0.5 0.5 1.5

2 1 1 3

10 10 10 -

20 20 20 - best-effort basis 3 7.5

Temp [K] Humi [%]

Species [%] Wind [m/s]

0.1 0.15 2 3 0.5 1 0.5 1 Long-term stability (per decade) [K/dec] [%RH6)/dec] [%/dec] [(m/s)/dec]

Timeli-ness

Climate NWP7)

15 1.5

30 3

15 1.5

30 3

15 1.5

30 3

15 1.5

30 3

[days] [hrs]

Time domain8) > 3 [years] 1) Trace species to be measured by LIO include the ten gases H2O, CO2, CH4, N2O, O3, CO, HDO, H2

18O, 13CO2, C18OO. 2) Grid box defined as square of horizontal sampling requirement (box of size Horizontal sampling [km] × Horizontal

sampling [km]). 3) Meeting the target upper boundary requirement implies full coverage of high-reaching convective cloud systems, up to

and including the tropical tropopause (16-17 km), with LRO humidity measurements within and through such clouds. 4) For the trace gas CO / O3, the concentration of which strongly decreases above / below about 15 km, the threshold upper

/ lower boundary requirement shall be 20 km / 10 km. Regarding the H2O isotopes (HDO, H218O), for which the sensitiv-

ity focus is the UT, these shall be retrieved within required accuracy over the best possible height range up to 12 km. 5) Understood to be the accuracy at a vertical resolution consistent with the required sampling (i.e., a resolution of 2x Ver-

tical sampling [km]). The LRO temperature accuracy requirement shall be understood to decrease linearly from the UT-bottom = 5 km value until it reaches the UT-≥10km value at 10 km; above, the height dependence shall be constant over the UTLS. The LRO humidity accuracy requirement for the LS and the LIO wind accuracy requirement for the US, re-spectively, shall be understood to apply up to the vertical domain upper boundary target requirement. For LIO, all accu-racy requirements apply to clear-air measurements; cloud-perturbed vertical levels shall be flagged (e.g., via a co-retrieved cloud layering profile) and accuracies at these levels shall be as good as possible on a best-effort basis.

6) For LRO humidity measurements, stability is specified in terms of relative humidity (RH), a quantity with well-defined linear range over the vertical domain. There are standard formulae to convert between RH and specific humidity as func-tions of temperature and pressure.

7) NWP is secondary but still important mission objective. Also, often NWP analyses are used for the forcing of climate GCM runs. Therefore, the primary climate mission objectives will benefit as well from the fulfilment of the NWP timeli-ness requirement.

8) Climate monitoring and research prefer long-term observations over many years and decades; the pioneering ACCURATE mission should thus be followed by similar missions. The ACCURATE mission objectives themselves, however, can be fulfilled within the given time frame (3 years or more).



2.2 System Requirements The system requirements for the LIO component, i.e., for the LIO Rx and LIO Tx systems, were derived from the observational requirements summarized in Table 1 and are consistent with those requirements. The derivation was supported by the heritage knowledge on transfer-ring observational to system requirements gained in ACE+ studies (e.g., ESA, 2004a; ACEPASS, 2005a), by the measurement characteristics and link budget analyses reported in section 3, and by the LIO retrieval performance studies reported in section 4, respectively. Some requirements are associated with constellation geometry and general mission analysis, where also the ACE+ heritage was helpful as well as technical advice from industry. The LIO system requirements representing the current state of definition (April 2007) are summarized in Table 2 (Tx), Table 3 (Rx), and Table 4 (joint Tx-Rx), respectively. They will be further refined in the course of future studies.

Table 2. LIO Tx System Requirements

Tx system element Requirement Comment Laser pulses power 1 W

duration 1.5 ms repetition rate 50 Hz

1.5 mJ pulse energy, one pulse every 20 ms

Emitted laser line FWHM ΔfL/f0 < 3 × 10-8 FWHM, full-width at half maximum Laser frequency knowledge δfL/f0 < 1 × 10-8 (3σ) event-to-event fL uncertainty stability rms dfL/f0 < 2 × 10-8 pulse-to-pulse fL instability drift D(dfL/f0)/Dt < 2 × 10-8

/ 20 sec fL drift within occ. event duration Laser intensity stability rms dIL/I0 < 0.1% pulse-to-pulse IL instability drift D(dIL/I0)/Dt < 0.1% / 20 sec IL drift within occ. event duration Laser beam divergence (at e-2 radius, full angle)

~4.5 mrad ~14 km diameter at atmospheric tangent point

Intensity distribution rms variation < 0.1% stable Gaussian intensity distribution (of beam intensity near the optical axis)

drift < 0.1% / 20 sec drift within an ~2 mrad cone about optical axis of beam

Laser line mode-hop free tuning range ΔfFLTR/f0 > 1.25⋅10-3 FLTR = full laser tuning range Laser beam pointing knowledge < 0.3 mrad (3σ) drift < 0.05 mrad / 20 sec (3σ) Wavelength range 2–2.5 μm

(4000–5000 cm-1)

sufficient number of laser lines (sig-nals) for observing all target species according to obs. requirements (max. 24 lines)

Optical axis co-alignment of laser beams for all laser lines

< 0.03 mrad < 100 m inter-offsets at atmospheric tangent point

residual mis-alignments knowledge < 0.03 mrad (3σ)



Table 3. LIO Rx System Requirements

Rx system element Requirement Comment Reception telescope (e.g., Cassegrain-type)

Front-optics (mirror) diameter 36 cm circular shape (baseline) FOV ~1.2 mrad ~3.75 km diameter at atmos-

pheric tangent point pointing knowledge < 0.3 mrad (3σ)

pointing drift < 0.1 mrad / 20 sec (3σ) Optical chain and Frequency de-multiplexing

basic signal integration time 2 ms contains 1.5 ms pulse duration observational bandwidth per received laser signal ΔfB/f0

6 × 10-5

bandpass filter sideband/out-of-band attenuation

> 40 dB

for each received laser signal, basic signal integration time for shot reception, followed within 10 ms by a basic signal integration time for background reception, at 50 Hz rate synchronized with the Tx pulse repetition rate and trigger time sequence of the signal simultaneous reception of up to four laser shot and up to four background signals within any given basic signal integration time slot (frequencies and temporal sequence of the pulses of the up to four shot signals to be sensibly designed a priori)

sufficient number of filter/de-multiplex units (max. 8 units) for up to four signals per unit to receive all Tx laser signals (max. 24 signals), and corresponding background signals, according to the pre-defined Tx pulse rate and trigger time sequences of the signals

Total optical loss from front-optics to detector

< 20% Target requirement (< 50% if unable to meet < 20%)

Detector NEP < 5 x 10-13 W / 2 ms i.e., per single-shot reception Rise time/response time < 1 μs Dynamic range NEP–5⋅10-9 W / 2 ms linear response over this range

Table 4. LIO Tx-Rx Joint System Requirements

Tx-Rx joint system element Requirement Comment Real-time (on-board) position knowledge of Tx and Rx

< 100 m (3σ) needed at both the Tx and Rx side (for accurate mutual pointing)

Real-time (on-board) along-ray velocity knowledge of Tx and Rx

< 1 m/s (3σ) needed at both the Tx and Rx side (for accurate Doppler-shift estimation)

Minimal vertical domain of Tx-Rx crosslink measurements

4–60 km corresponds to < 30 sec measurement time per LIO occultation event for the baselined ACE+ type LEO-LEO configuration

Time-tagging accuracy of Tx and Rx data (at 50 Hz sampling rate)

< 10 μs accuracy (absolute time knowledge) of time stamps

Drift of time-tagging of Tx and Rx data (at 50 Hz sampling rate)

< 30 ns/s time stamp differences, relative to the occul-tation event start time stamp, are < 1 μs over the occultation event duration



3 Concept and Characteristics of the LIO Payload

The LIO payload consists of an SWIR laser transmitter system providing 21 laser signals (baseline) at selected frequencies in the 2–2.5 μm band (4000–5000 cm-1) on each Tx plat-form and a corresponding optical receiver and detector system on each Rx platform (see ACCURATE, 2005, for a general mission overview). 3.1 LIO Measurement Principle and Characteristics 3.1.1 Measurement Principle and Favorable Properties The main aim of the LIO laser cross-links is to accurately measure — simultaneously with the LRO MW band cross-links — height resolved concentrations of greenhouse gas and isotope species in the UTLS region by the differential log-transmission profiling principle. The target species (baseline) are the six main greenhouse gases H2O, CO2, CH4, N2O, O3, and CO as well as the water vapor and carbon dioxide isotopes HDO, H2

18O, 13CO2, and C18OO. In addi-tion Vlos (line-of-sight wind) is measured. Complementary to this species and Vlos profiling, aerosol, cloud layering, and turbulence profiling are important tasks, which will use the meas-ured transmission data mainly in a direct way, i.e., without the log-transmission frequency differencing. Dedicated SWIR laser occultation signals within 2–2.5 μm are near-ideal for this purpose due to:

- the 2–2.5 μm refractivity (Edlen’s formula in the ‘non-dispersive range’ > 2 μm) be-ing nearly identical (< 0.1% difference) to K band refractivity (Smith-Weintraub for-mula), implying closely similar signal travel paths of LRO and LIO signals (except for the “wet term” due to orientation polarization of water molecules in MW refractivity; thus LRO water vapour aids LIO in moist air, see below).

- the solar radiation scattered into the receiver telescopes being minimal and the re-ceived atmospheric thermal radiation being negligible (“hole between the two Planck spectra”), leaving comfortable SNR also in full daylight and providing independence of atmospheric emission characteristics.

- suitable spectral (vibration-rotation) absorption lines being available for sensing of all ten targeted trace species in the UTLS domain, with the sensitivity in limb sounding being two orders of magnitude higher than in nadir, also allowing sensing of the H2O and CO2 isotopes.

- the spectral characteristics being well suited to allow pairs of channels for differential transmission profiles have both high transmission contrast and closely-spaced fre-quency ratios f1/f2 > 0.99, very effectively suppressing scintillations and all other broadband effects.

- laser signals being point sources leading within 2–2.5 μm to Fresnel diameters of < 5 m (~3.5 m in LEO-LEO geometry) and allowing single-shot SNRs of ~1000 (in vac-



uum above TOA) with average Tx powers of order 100 mW only; such SNRs in 2–2.5 μm are far out of range of natural point sources such as stars.

- highly accurate and stable semiconductor lasers (Distributed Feed-Back, DFB, La-sers), wavelength meters (based on solid-state glass etalons), femtosecond lasers (for extremely accurate SI traceable frequency-lock by the frequency comb technique), and highly sensitive infrared detectors (Extended InGaAs) being available in the SWIR up to ~2.2–2.6 μm, which can fulfil LIO Tx and Rx system requirements (see section 2.2). Those components currently available off-the-shelf up to ~2.2 μm only (wave-length meter, femtosecond laser frequency comb) have no basic feasibility problem to be extended to 2.5 μm (Toptica, 2005; Toptica, pers. communications, 2006).

The LIO measurement sequence is such that in addition to each laser signal pulse measure-ment (“shot measurement”) also a background measurement is required (“after-shot meas-urement”; within 10 ms, i.e., at < 20 m height shift of the Rx ~3.75 km diameter FOV, given typical immersion/emersion rates of occultation events). This after-shot measurement is taken in order to enable control of the signal-to-noise ratio (SNR) of each single shot, which is needed for optimal quality control. The LIO profiling will be strongly aided by the simultaneously measured LRO refraction, absorption, and defocusing data, which will provide accurate geo-location (height < 10 m uncertainty), and unbiased pressure (with rms < 0.3%) and temperature (with rms < 0.75 K) information (cf. section 4.3) for the spectroscopic modeling of absorption lines in the SWIR in the LIO retrieval processing. Furthermore, LRO will provide upper troposphere humidity profiles at least up to 12 km with an accuracy of < 10% (section 4.3; ESA, 2004b; ACEPASS, 2005a). This will assist the accurate geo-location within 5–12 km, where the propagation paths of LRO and LIO may differ due to the “wet term” in MW refractivity (which can lead to refractivity increases at 5 km under tropical conditions of up to ~20%). 3.1.2 LIO Channel Selection for Target Species The LIO Tx frequencies need to be carefully selected to match absorption lines (“on-wavelengths” λAbs) of the target species as well as to provide reference lines (“off-wavelengths” λRef) at frequencies where the atmosphere is essentially transparent except for scattering and small, easy-to-model residual background absorption. The ratio λAbs/λRef is required to be close to unity within 1% (i.e., 0.99 < λAbs/λRef < 1.01) in order to ensure that the differential transmission effectively corrects for all broadband effects (defocusing, absorp-tion background, residual scattering, scintillation). Table 5 shows the baseline LIO frequency selection performed in the course of an initial fea-sibility assessment study, and Figure 2 graphically illustrates (for a reference tangent point height of 15 km) a typical limb transmission spectrum within 2–2.5 μm together with the lo-cations of the selected channels.



Table 5. Baseline selection of LIO absorption and reference channels

Absorption Lines Reference Lines Ratio Trace Species

absν [cm-1] λAbs [μm] refν [cm-1] λRef [μm] λAbs/λRef

H2O(1) (2) (3) (4)

4204.840 4775.803 4747.055 4733.045

2.3782 2.0939 2.1066 2.1128

4227.07 4770.20 4731.05 4731.05

2.3657 2.0963 2.1137 2.1137

1.0053 0.9988 0.9966 0.9996

CO2 4771.621 2.0957 4770.20 2.0963 0.9997 wind(1) 4771.617 2.0957 4770.20 2.0963 0.9997 wind(2) 4771.625 2.0957 4770.20 2.0963 0.9997

CH4 4344.164 2.3019 4322.92 2.3133 0.9951 N2O 4710.341 2.1230 4731.05 2.1137 1.0044 O3 4029.110 2.4819 4067.80 2.4583 1.0096 CO 4303.623 2.3236 4322.92 2.3133 1.0045

HDO 4237.016 2.3602 4227.07 2.3657 0.9977 H2

18O 4090.872 2.4445 4118.36 2.4282 1.0067 13CO2 4723.415 2.1171 4731.05 2.1137 1.0016 C18OO 4767.041 2.0977 4770.20 2.0963 1.0007

Figure 2. LIO Tx-to-Rx transmission spectrum (light green) over the full ACCURATE spectral range from 2 to 2.5 μm (4000 – 5000 cm-1) for a tangent height of 15 km. The vertical bars mark the 21 baseline channels summarized in Table 5, adopting a different color for each target species channel, different linestyles for isotopes of a species (solid, primary isotope), and the color yellow for the six reference channels, respectively. The symbols annotating the channels are ordered top-down according to increasing wavelength, for each of the six “channel packages” (one per reference line). The Refer-ence Forward Model RFM (www-atm.physics.ox.ac.uk/RFM), linking to the HITRAN 2004 database (www.harvard.edu/HITRAN), was used for computing the transmissions, with a U.S. standard atmos-phere (std.atm) complemented by minor species as basis (CO2 updated to 380 ppm; see Figure 3).



It is shown that in this baseline channel set 15 absorption lines and 6 reference lines were adopted, which together cover measurement of the 10 target species over the UTLS domain plus the Vlos measurement. This selection has been based on extensive simulations with the RFM/HITRAN (links see caption of Figure 2) line-by-line transmission modeling software, based on FASCODE/U.S. standard (and MIPAS) reference atmospheres. The FASCODE at-mospheres are illustrated in Figure 3. The wavelength ratio criterion 0.99 < λAbs/λRef < 1.01 is fulfilled in all cases, the vast majority of the cases even shows ratios within 0.995 < λAbs/λRef < 1.005. According to HITRAN 2004 uncertainty parameters, the spectroscopy of all selected lines is reasonably good, ensuring they are a robust baseline. Improved spectroscopy shall certainly be performed pre-launch for firmly selected lines (which can be conveniently done using the DFB laser diodes themselves in a suitable lab spectroscopy setup; cf. section 3.2.2). The basis for the channel selection was that the laser lines are used with their natural linewidth as emitted by the baselined DFB laser diodes, which is ΔfL/f0 ~ 2 x 10-8 (FWHM) in the SWIR range of interest. This was termed Small-Linewidth (SL) approach in the ACCURATE proposal (ACCURATE, 2005). We mention this because in ACCURATE (2005) a so-called Broad-Linewidth (BL) approach was the baseline, assuming some artificial broadening of the laser line, since the best linewidth to use was not entirely clear at that time. Meanwhile it is consolidated that the BL approach is obsolete and just using the laser natural linewidth provides optimal sensitivity and is technically most simple.



Figure 3. Illustration of the FASCODE atmospheres, including the U.S. standard atmosphere (also termed “FASCODE model 6”). Shown are temperature, pressure, and target species profiles within 0 to 60 km for the U.S. standard atmosphere (std; heavy black), used as main basis for the assessment results shown in this report, as well as for the five latitude/season-specific standard atmospheres, tropical (tro; red), mid-latitude summer (mls; blue), mid-latitude winter (mlw, dashed green), sub-arctic summer (sas, orange), and sub-arctic winter (saw, dashed violet), respectively. The latter five have been used (complemented by the five so-called MIPAS reference atmospheres; J.J. Remedios, Univ. of Leicester, UK, pers. communications, 2005; see also MIPAS-Ref, 2004) for assessing sensi-tivities to the variability of the atmospheric parameters. For computing total transmissions, also the FASCODE standard profiles for minor absorbing species (about three dozen of further species) have been included. CO2 was still included with a concentration of 330 ppmv in the standard atmospheres and has thus been updated to an up-to-date concentration of 380 ppmv in all of them (upper-middle-right panel).

Figure 4 depicts the transmission profiles for the absorbing target species and the reference channels as function of height over the required vertical measurement domain (up to 60 km, see Table 4 in section 2). Figure 5, as a complement, puts these transmission profiles into con-text with the total transmission (from all atmospheric species plus continuum absorption) and depicts also the residual “foreign” transmission profiles in each channel, i.e., the difference between the total transmission and the one of the target species only. Together Figure 4 and Figure 5 illustrate that the selected channels allow to well cover the UTLS domain within vertical domain requirements for all species (section 2, Table 1). In this context a transmission range from about 0.25 dB (~95% transmission) at the top to about 13 dB (~5% transmission) at the bottom is the best-exploitable range for accurate measurements. Some gases cannot reasonably be expected to be always measured over the full UTLS range, including O3 (limited for < 10 km), CO (limited for > 20 km), and H2O isotopes (limited for > 10–12 km), which is reflected in the vertical domain requirements in section 2.



Figure 4. LIO Tx-to-Rx transmission profiles for the absorbing target species in the selected absorp-tion channels (heavy lines) and total transmission profiles for all species plus continuum for the refer-ence channels (light lines), respectively. Transmissions computed using RFM/HITRAN-2004/std.atm (as for Figure 2). Figure 6 depicts the CO2 line in detail with respect to the Vlos measurement capability. For this latter purpose the “wind(1)” and “wind(2)” channels are exploited, placed symmetrically about the CO2 line center separated by approximately the Doppler full-width of the line. At these frequencies at the line wings the 1st spectral derivative is maximum (order 150–400 dB/cm-1 in the UTLS; see Figure 6, right panel). Thus the selected pair of frequencies is the one where the differential transmission, ΔTrw1w2 = (Trwind(1) – Trwind(2)) reacts most sensitively to a l.o.s. wind-induced Doppler shift: zero Vlos corresponds to ΔTrw1w2 ~ zero, due to line symmetry, and red-shifts (blue-shifts) by forward (backward) Tx-Rx l.o.s. wind speeds corre-spond to increasingly non-zero ΔTrw1w2 proportional to wind speed. In practice the baseline is that ΔTrw1w2 will be evaluated via a double-difference ΔΔTrw1w2 = (Trwind(1)–TrRef) – (Trwind(2)–TrRef) (see section 4), since all three CO2 line signals share the same LIO Rx filter and are thus received in a temporal sequence (within 7.5 ms, using three subsequent 2 ms integration + 0.5 ms pause time slots). They may thus see slightly different atmospheric conditions (tangent height shift ~15 m over 7.5 ms), in particular potentially re-lated to small-scale scintillation. The associated very-close-by reference channel (wavelength spacing |(λwind–λRef)/λRef| < 0.05%; cf. Table 5), received simultaneously in all time slots needed, will safely eliminate all broadband effects including scintillations.



Figure 5. LIO Tx-to-Rx transmission profiles for the absorbing target species (heavy lines, same as in Figure 4), complemented by the total transmission profiles by all species plus continuum (light lines, close to or shadowed by heavy lines) and the difference between the total transmission in the channels and the one of the absorbing target species only (light lines, close to or at 0 dB). Transmissions com-puted using RFM/HITRAN-2004/std.atm (as for Figure 2).

Figure 6. LIO Tx-to-Rx transmission spectrum zooming into a narrow 0.1 cm-1 wavenumber range about the 4771.62 cm-1 CO2 line exploited for CO2 and wind sounding. Transmissions Tr(ν ) (left) and their 1st spectral derivatives (dTr(ν )/dν ) (right) are shown within 5 – 35 km in 5 km heights steps as well as at 7 km (red, 5 km; red-orange, 7 km; orange, 10 km; yellow, 15 km; green, 20 km; light blue, 25 km; dark blue, 30 km; violet, 35 km). The three vertical lines (black) mark the channels CO2 (mid-dle), wind(1) (left), and wind(2) (right), respectively; cf. Table 5. Transmissions computed using RFM/HITRAN-2004/std.atm (as for Figure 2).



Figure 7. LIO Tx-to-Rx transmission spectrum zooming into a small 10 cm-1 wavenumber range about the 4771.62 cm-1 CO2 line exploited for the planned CO2-H2O-Wind 2.1 μm LIO demo breadboard (section 5). From the selected channel baseline it contains (upper panel) the CO2, wind(1), wind(2), H2O(2), and C18OO target species channels, respectively, as well as their reference channel (cf. Table 5 and Figure 2, leftmost “channel package” near 2.1 μm). In addition it contains several 13CO2 lines (lower panel, orange), from which one within 4770–4775 cm-1 could also be tested by the LIO demo breadboard despite of not being the optimal 13CO2 baseline channel near 4723 cm-1 (cf. Table 5). Transmissions computed using RFM/HITRAN-2004/std.atm (as for Figure 2).

Figure 7 highlights the transmission spectrum in the 10 cm-1 wavelength range from 4766.5 to 4776.5 cm-1, which was selected as the frequency range for the demo breadboard (see section 5). The main demo breadboard lines (for CO2, H2O, C18OO, and Vlos) are illustrated in the upper panel, the lower panel complements them with further highlighting the 13CO2 lines within range, including the three optional lines listed in section 5.2. In summary, the set of selected frequencies is a very reasonable baseline channel ensemble, as is also underlined by the encouraging performance analysis results in section 4. This channel set will thus be used in a next step for full retrieval performance studies (based on develop-ments in the EGOPS software; ACCURAID, 2007; EGOPS, 2007), where further optimiza-tion of selection might then be performed if found useful. Also the lines near 4770 cm-1 are evidently well suited for implementing an LIO demo breadboard with very good cost-benefit ratio, capable of demonstrating all main technical and scientific properties of the new LIO occultation concept.



3.1.3 Further Characteristics As with any IR system, the LIO signals will be blocked in case of clouds along the propaga-tion path. The LIO baseline design thus is such that no time-continuous link is required be-tween LIO Tx and Rx but rather each single shot measurement is acquired individually (so that individual shots could be blocked without affecting the quality of any other shot). The vertical distribution of clouds during an event will be quantified/flagged by a cloud layering profile, indicating the presence (and as possible attenuation strength) of clouds for each single shot, derived mainly from the degree of “anomalous” absorption in reference channels. Wind induced Doppler shift is of no further concern for trace species retrieval, since the maximum wind-induced line shift in the given layout with near meridional orbital planes is dfW/f0 < 1 x 10-7 even for (tropical, subtropical, or polar) Jet stream velocities in the tro-popause region of up to 100 m/s. Moreover, the Vlos measurement (see previous section 3.1.2 and Figure 6) will allow to determine this wind-induced Doppler shift to < 2 x 10-8 (per single shot) as dfW is the primary parameter derived from the wind-lines transmission difference ΔΔTrw1w2 (section 3.1.2) from which, in turn, Vlos is computed (section 4.1.1). Thus in species retrieval even the small wind-induced offsets against the nominal absorption line centers can be accounted for in the retrieval processing to < 2 x 10-8 frequency error, without utilization of external wind information. Such external wind information is, on the other hand, a very reasonable fallback in case the Vlos measurement capability would fail dur-ing a mission (e.g., due to wind channel loss), since the wind accuracy required for the pur-pose is fairly low (~10 m/s or even less). Such accuracy could be supplied to the retrieval process by routine low resolution atmospheric analysis fields such as, e.g., T42L91 fields from the ECMWF, which would anyway be part of the quality control system. The kinematic Doppler shift due to relative orbital motion of the satellites, amounting to about |dfDkin/f0| ~ 2.25 x 10-5 between satellite (Tx or Rx) and atmosphere (tangent point), can be accurately (to < 1 x 10-8) compensated for by a respective frequency offset of the lines of both the forward-looking (rising events) and backward-looking (setting events) laser arrays, i.e., the laser line target frequencies prescribed to the wavelength meter-assisted femto-second laser stabilization unit during occultation events will include the offset. The offset is available to an accuracy δf/f0 < 1 x 10-8 in real-time due to the quality of the real-time and predicted orbital positions and velocities of the Rx and Tx satellites, which shall be available to < 100 m position and < 1 m/s velocity error, respectively (see section 2, Table 4). This is routine standard today for orbital heights > 600 km, e.g., for the real-time/predicted orbit determina-tion of the EUMETSAT/ESA MetOp satellite (www.eumetsat.int). The requirements on the detector depend on the desired SNR at the detector for which a value of 500 (27 dB) at TOA, for each single-shot measurement at a 50 Hz sampling rate, was found an adequate baseline (see sections 3.2 and 4). This ensures < 0.1% baseline transmis-sion accuracy at required vertical resolution (1–2 km, cf. section 2.1; cf. also section 4.1.2), even if 50% of the shot signals are not passing the “after-shot background measurement” quality control, for example due to cloud perturbation. Suitable detector technology is briefly discussed in section 3.2 below.



Baseline transmission accuracy, being essentially a specification on instrumental noise, prac-tically corresponds to the measurement accuracy for transmission at stratopause region heights (45–60 km), where the accuracy is not limited by atmospheric influences but by in-strumental noise (see Figure 4; ACCURAID, 2007). In the UTLS (5–35 km), atmospheric effects will contribute in varying degrees to the transmission accuracy, and to the final trace species retrieval accuracy from differential transmissions (e.g., gradual SNR decrease due to defocusing, absorption and scattering, scintillation effects, etc.; see section 4). It is important, however, that the baseline instrumental accuracy is maintained throughout the occultation event, since all atmospheric effects, except for target species absorption, will largely cancel due to the log-transmission differencing of the closely spaced absorption and reference channels (0.99 < λAbs/λRef < 1.01, see above). Thus the low instrumental noise, due to a single-shot SNR of 500 at TOA, will be the key to accurate trace species profiles.



3.2 LIO Payload Technical Concept and Performance This overview is based on results of an initial technical feasibility assessment at the Univer-sity of Graz, Austria, supported by the ACCURAID project and supported by technical advice received from scientific partners and colleagues from companies with relevant laser expertise (see Acknowledgments before the References section). We note that the described link budget (section 3.2.1) and Tx and Rx layouts (sections 3.2.2 and 3.2.3) are initial versions which will receive further refinement in the future. However, the main result of the initial assessment is the strong and robust evidence obtained that the LIO system is technically feasible. It is based on this feasibility that the breadboarding speci-fications summarized in section 5 below could lead to an immediate start of work and deliver a complete CO2-H2O-Wind LIO 2.1 μm demo breadboard within a 10 months timeframe. 3.2.1 LIO Link Budget The LIO Tx and LIO Rx technical layouts are associated with a baseline link budget derived in the course of the initial assessment study as shown in Table 6. The link budget is closely related to the system requirements (section 2.2, Table 2, Table 3, Table 4) and is for estima-tion of the SNR at the SWIR detector of an individual single-pulse shot measurement.

Table 6. Link budget and Top-of-Atmosphere (TOA) SNR estimation for LIO Tx-Rx system

Element / Link Process Budget (dB) Budget (W) Emitted laser pulse power (over 1.5 msec), also denoted transmitted power 0 dBW 1 W Propagation loss1): laser beam divergence full angle 4.5 mrad (e-2), 6200 km Tx-Rx distance, 36 cm diameter (circular) Rx optics -94.8 dB 3.3 x 10-10 W/W

Received pulse power -94.8 dBW 3.3 x 10-10 W Reception loss: Tx pulse duration / Rx integration time (1.5 ms / 2 ms) -1.25 dB 0.75 W/W Total optical loss – front optics to detector (assumed 20%) -0.95 dB 0.8 W/W Pulse power at detector -97.0 dBW 2.0 x 10-10 W NEP of IR detector (2 ms, diameter 0.25-0.5 mm, detectivity D* ~ 2 x 1012) -124 dBW 4 x 10-13 W Required SNR at detector (for single-pulse reception at 50 Hz sampling) 27 dB 500

1) Propagation loss Ltr = Pr/Pt, occurring due to the divergence of the Gaussian beam with full (e-2) angle αt over the Tx-Rx distance Dtr, where Pt is transmitted power (W) and Pr is received power (W), is computed via Ltr = 2 Ar / (wr

2 π), where wr = Dtr (αt /2) is the Gaussian beam (e-2) radius at the re-ceiver, Ar = (dr

2/4) π is the Rx reception area with diameter dr of the circular optics, and the factor of 2 derives from the ratio of the intensity of the Gaussian beam near the optical axis (Wm-2), received by Ar, to the total transmitted power (W) in the beam (see also ACCURAID, 2007). Table 6 confirms that the requirement of a single-pulse SNR of 500 at TOA can be realized consistent with the system requirements with laser pulse powers of 1 W and Noise-Equivalent-Power (NEP) of IR detectors of < 5 x 10-13 W per 2 ms. The initial analysis indi-cates that these are the driving feasibility specs since the other required specifications on beam and aperture widths, and related pointing accuracies (see requirements in section 2.2), are known to be feasible from ACE+ Phase A studies or found not difficult to meet.



On total optical loss, 20% was found as a reasonable first baseline based on industry advice, as high transmission/low-reflection standard quartz for IR works well up to 2.5 μm. The total optical loss will, in particular, depend on the layout of the two- to four-signal filter/de-multiplexing units (e.g., one adviser was expecting up to 50% optical loss, i.e., up to 3 dB instead of 1 dB). Heritage from the WALES Phase A studies might be useful, where a four-signal filter/de-multiplexing unit was designed for the four WALES frequencies near 935 nm (ESA, 2004c). The initial link budget of Table 6 leaves room for sufficient margin, however, to allow for this type of preliminary uncertainties. A margin of several dBs might be realized in a refined link budget for example at the detec-tor: Properly selected and customized detectors can reach a NEP of < 2 x 10-13 W per 2 ms, a gain of 3 dB over the assumption above (cf. section 3.2.3 on the LIO Rx system). The following LIO Tx and LIO Rx brief descriptions focus on available SWIR laser perform-ance and detector specifications for the 2–2.5 μm range as well as give an overview on the system layout, in order to provide basic background information on the relevant key tech-nologies. 3.2.2 LIO Tx Laser System The LIO Tx laser system is found basically feasible due to the availability since recent years of high-performance Distributed Feed-Back (DFB) semiconductor laser diodes with the capa-bility to be tuned to any frequency in the required SWIR range (currently they are available for frequencies up to 2.8 μm). This type of laser diodes have long been used for telecommu-nications and can be regarded as the optical analogues of voltage controlled oscillators in ra-dio-frequency (RF) technology; the emitted wavelength depends only on well controlled pa-rameters in a robust and reproducible way. Fast tuning is possible either by temperature or current control and very large mode-hop free tuning ranges (several nanometers) are obtained (more information on DFB lasers is, e.g., available via www.toptica.com/laser_diodes.php > DFB/DBR; see also Toptica, 2005). DFB lasers can meet (often significantly exceed) all laser frequency and laser intensity related requirements of the LIO Tx system summarized in section 2.2. Even without wavelength me-ter/femtosecond laser lock, already a frequency stability of dfL/f0 < 2 x 10-7 is achieved and the drift was demonstrated to be smaller than this specification within a measurement period of several hours (Toptica, 2005). Similarly, intensity rms accuracies < 0.1% and intensity drifts < 0.1% per several hours were demonstrated. The natural line width of DFB lasers ΔfL/f0 ~ 1-2 x 10-8 (FWHM) well meets the < 3 x 10-8 FWHM requirement (section 2.2). The adequate type of frequency stabilisation to within the requirements (section 2.2) of δfL/f0 < 1 x 10-8 (knowledge), dfL/f0 < 2 x 10-8 (rms stability), and D(dfL/f0)/Dt < 2 x 10-8 / 20 sec (drift) can be achieved by a wavelength meter-assisted femtosecond laser-stabilized high-performance lock using the frequency comb technique (Toptica, pers. communications, 2006). This innovative locking approach enables a robust stabilization to < 1 x 10-8 without major efforts (theoretically significantly higher accuracy can be achieved if needed). The approach allows that one single frequency comb (one femto-second laser) can serve all ACCURATE laser channels, which can formally be arbitrary target frequencies within 4000–5000 cm-1 set by software. Regarding the wavelength meter, a stan-



dard-accuracy off-the-shelf SWIR wavelength meter is sufficient for its purpose to help uniquely determine which “teeth” of the frequency comb are closest to the target frequencies. The wavelength meters and femtosecond laser frequency combs are currently available for wavelengths up to ~2.2 μm (Toptica, 2005; Toptica, pers. communications, 2006). While no technical problems are seen to extend the technology to 2.5 μm, these developments should be initiated soon in order to also cover the ACCURATE channels at > 2.2 μm in the near fu-ture (10 of the 21 baseline channels; see Table 5 and Figure 2 in section 3.1). From the climate benchmark measurements point of view, where traceability to primary stan-dards is desired, the frequency-comb based locking approach is an ideal choice as well, since the comb can be locked (at < 1 x 10-8 accuracy) to an optical clock standard frequency (e.g., the 894.6 nm Doppler-free absorption line of Caesium), ensuring SI traceability. Using the DFB diodes with their natural lasing line width of ΔfL/f0 ~ 1-2 x 10-8 (FWHM) and tuning them over full line shapes is also a very good option for pre-launch improvement of spectroscopy of selected absorption lines as required (e.g., line center frequency knowledge to ~1 x 10-8, absolute line intensity knowledge to < 2-5%). This could be tested in the laboratory utilizing the DFB diodes manufactured for the LIO demo breadboard. The spectroscopic pa-rameters of all relevant lines in the demo breadboard wavenumber range (4766.5–4776.5 cm-1) could be confirmed and improved this way. The LIO Tx system for any selected line would in general terms be set up as follows: The DFB diode is fixed to the selected frequency and operated in continuous wave (CW) mode at an output power of ~5 mW during occultation events (~15 sec warm up time, max. 30 sec measurement time, i.e., ~45 sec power-on for each occultation event). One operation option is then that the power is amplified according to a trigger time sequence, typically every 20 ms for ~2 ms, with a semiconductor amplifier to ~1 W, the last 1.5 ms of this amplified pulse will be chopped out for emission. Alternatively, the amplification to ~1 W is run in continuous mode over the ~30 sec per event, again with 1.5 ms pulses chopped out for emission accord-ing to the trigger time sequence needed for any given laser channel. The selection of either of these options will depend on laser/amplifier lifetime and total power consumption considera-tions; the LIO Tx demo breadboard can be built to allow assessing both options. The laser operates in TEM00 mode and the emitted beam has a stable Gaussian intensity distribution which can be tailored in terms of beam divergence to the LIO requirement. Toptica (2005) have described a preliminary design for an LIO Tx system breadboard in more detail (see section 5.1). The power consumption of this laser system (single laser channel unit) would currently be near 50 W in the laboratory (no power safe efforts involved) but it is clear that it can be re-duced for a satellite unit to < 15 W. The budgets in section 3.3 of ACCURATE (2005) have assumed 15 W per unit. The current baseline system would then consist of two arrays of 21 (e.g., 7 x 3) units for the 21 selected channels (section 3.1.2), one array for each setting and rising occultations (which never operate at the same time). This leads to 315 W power during occultation; with the time fraction of occultation time per day for one Tx serving two Rx plat-forms being ~ (115 events/day x 0.75 min) / 1440 min, this then yields an average LIO Tx power demand to the platform of ~20 W.



3.2.3 LIO Rx Receiving and Detection System The LIO Rx detector system is found well feasible due to a new class of high-sensitivity SWIR detectors reaching detectivities D* > 2 x 1012 without liquid gas cooling. For the LIO Rx purpose, the initial analysis has found thermoelectrically cooled (to about –50 deg C) Ex-tended InGaAs (Indium-Gallium-Arsenide) diodes most suitable. For detector diameters of 0.25-0.5 mm, found adequate for the LIO Rx system, these deliver a D* ~ 2 x 1012 (for more information see, for example, www.lasercomponents.com/wwwuk/products > Detectors and photodiodes). This leads for integration times of 2 ms (500 Hz bandwidth) to a Noise-Equivalent-Power (NEP) of ~ 4 x 10-13 W as required in the link budget (Table 6). Carefully selected and customized Ext. InGaAs detectors can reach NEPs < 2 x 10-13 W per 2 ms. An array of 24 detectors is needed for the 21 selected lines received, fed by seven filter/de-multiplexing units (see next paragraphs). The total power consumption of these, which is mainly driven by the energy needed for detector cooling, has been estimated to ~50 W. As a total system, the layout of the LIO Rx system is preliminarily viewed as follows. A re-ceiver telescope with a 36 cm aperture, for which different optical realizations are possible, receives the incoming signals (and background radiation) within an ~1.2 mrad diameter FOV. A simple yet effective and compact design for this telescope may be a standard Cassegrain-type primary parabolic mirror/secondary hyperbolic mirror layout. A beam-splitter/broadband-filter then divides the received signal into a “blue” part comprising ~2.0–2.2 μm (11 channels; cf. Figure 2) and a “red” part comprising ~2.25–2.5 μm (10 channels; cf. Figure 2), respectively. This layout enables a sensible de-multiplexer design, with the “blue” and the “red” signal brought simultaneously, each by temporal in-field separation, to their appropriate filter/de-multiplexing unit according to the scheme summarized in Table 7 below. As Table 7 shows, the baseline signal reception scheme, operated at 50 Hz sampling rate, i.e., within every 20 ms time slice during occultation event duration, is organized into eight 2 ms reception-and-integration time slots with each followed by 0.5 ms pause (“dead time” between slots). Table 7 illustrates in particular the signal de-multiplexing logic in one such 20 ms time slice. It shows that four de-multiplexing units are needed for the “blue” channels (“dm1” to “dm4”) and three for the “red” channels (“dm5” to “dm7”), respectively, and that they are fed in a way that while a “blue” unit receives shot signals (red/dark boxes in Table 7) a “red” one re-ceives background signals (yellow/light boxes in Table 7), and vice versa. In other words, the 2-ms time slots are used to simultaneously receive signals from two to four channels (includ-ing absorption channels, λAbs, and the related one or two associated reference channels, λRef) by those two filter/de-multiplexing units synchronized to be active for a given time slot. A specific trigger time scheme for each channel (rows in Table 7), common and pre-defined to both Tx and Rx system, ensures the proper time sequence of laser shot signals so that the seven filter/de-multiplex units are fed as scheduled, with in-field separation used to switch the incoming signals of the time slot to the correct filter/de-multiplexing unit.



Table 7. Baseline De-multiplexing Scheme for LIO Rx System

Species λ [μm] Time sequence (eight 2 ms reception-and-integration time slots with each followed by 0.5 ms pause; in total 20 ms time slice)

H2O(2) 2.0939 wind(2) 2.0957

CO2 2.0957 wind(1) 2.0957 Ref(1) 2.0963 C18OO 2.0977 H2O(3) 2.1066 H2O(4) 2.1128 Ref(2) 2.1137 13CO2 2.1171 N2O 2.1230

dm1 dm2 dm3 dm4 dm1 dm2 dm3 dm4 CH4 2.3019

Ref(3) 2.3133 CO 2.3236

HDO 2.3602 Ref(4) 2.3657 H2O(1) 2.3782 Ref(5) 2.4282 H2

18O 2.4445 Ref(6) 2.4583

O3 2.4819 dm5 dm6 dm7 dm5 dm6 dm7

In this way each channel gets its shot measurements received for one 2 ms integration time slot every 20 ms (50 Hz sampling rate), followed within 10 ms by an after-shot background measurement over 2 ms, in line with the requirements (section 2, Table 3). As Table 7 shows, the two reference channels (λRef) near 2.1 μm will have three (2.0963 μm) respectively two (2.1137 μm) 2 ms shot/background measurements per 20 ms, each for a different filter/de-multiplex unit, in order to provide simultaneous reference measurement to different absorp-tion channels (λAbs). The filter/de-multiplexing units separate their 2–4 individual signals at the (accurately known) laser wavelengths and feed them into 24 detectors, one for each of the 21 channels plus three additional ones for the two λRef channels received by three respectively two units. These 24 detectors provide on-output both the shot and background measurements as digital data stream at 50 Hz sampling rate. The filter width for each wavelength is within 0.12-0.15 nm (for 2–2.5 μm), which is broad enough to accommodate either red-Doppler-shifted setting occultations or blue-shifted rising ones (see section 3.1.3) and still well rejects solar scattering into the telescope, which is very small at > 2 μm.



4 LIO Scientific Performance Analysis

An initial LIO trace species and wind profiles retrieval performance estimation has been car-ried out, which was based on a simplified end-to-end simulation approach implemented in an ACCURATE LIO Performance Simulator (ALPS). Section 4.1 describes the ALPS tool and its simplified yet reasonably realistic modeling chain in detail. Development of the ALPS tool was enabled by the data processing experience and insight gained at University of Graz in the course of the X/K band LRO investigations during the ACE+ phase A scientific support studies 2002–2004 (ACEPASS, 2004, 2005a,b,c; ESA, 2004a), complemented by the insights from the ACCURATE LIO preparatory work so far (see previous sections; ACCURATE, 2005; ACCURAID, 2007). ALPS development used this knowledge and enables modeling of simulated transmissions for all target species and wind observation, and on their expected retrieval accuracy under different atmospheric condi-tions from tropical to sub-arctic winter. The ALPS-based transmission, trace species, and wind retrieval performance results are reported in sections 4.2, 4.3, and 4.4, respectively. Cloud detection and elimination of cloud-blocked laser shots (as well as cloud properties re-trieval, if one turns the interest around) are separate retrieval processing steps not accounted for in the ALPS tool and the initial performance analysis in this section. It is known, though, that the information in the ACCURATE laser-link channels over 2–2.5 μm, and from the background measurement sequences, will allow accurate cloud detection and cloud effects separation (and retrieval of valuable information on clouds). For more comments on cloud effects see section 3.1.3. Beyond the parameterized ALPS approach and the results reported here, complete LIO end-to-end simulations for LIO trace species and wind observations and retrieval are in prepara-tion as integral part of the End-to-end Generic Occultation Performance Simulator software (EGOPS5; see EGOPS, 2007). These exploit the synergy with the LRO MW end-to-end simulations in EGOPS5 as prepared in the frame of the ACEPASS (2005a,b,c) work, and up-graded recently to also cope with the higher 178–183 GHz MW band (183 GHz water vapor absorption line in addition to 22 GHz line) and with LRO differential transmission processing (ESAProdex, 2006). Substantial upgrade of the present EGOPS5 system is required to enable full LIO+LRO profiling simulations, including in cloudy atmospheres. The results from the initial phase of this EGOPS work, with first upgrades of forward modeling and observation system modeling components, were reported in ACCURAID (2007).



4.1 Retrieval Performance Estimation System In order to assess the achievable accuracy of LIO retrieval results, the ALPS system was de-veloped and implemented as a software tool in Interactive Data Language (IDL). A schematic view of it is shown in Figure 8. Starting from a basic SNR, the tool enables to estimate all losses and errors relevant for LIO occultation measurements and subsequent species and wind profiles retrieval based on the transmission profiles.

The forward modeling of transmission due to the absorbing species, and of spectral transmis-sion derivatives needed in addition in case of the wind channels, is computed as an input for ALPS by applying the Reference Forward Model (RFM, 1996, 2007) on the basis of the HITRAN 2004 molecular spectroscopic database (HITRAN, 2005) and the six FASCODE standard atmospheres (Figure 3). These forward modeled transmission measurements for each target species, such as those visualized for the FASCODE model 6 (U.S. standard atmos-phere, std.atm) in Figure 4 and Figure 5 in section 3.1, are fairly realistic.

This has been verified by comparing the RFM results to transmission simulation results using 3D ray tracing and realistic 3D LEO-LEO geometries in the newest version of EGOPS5 (ACCURAID, 2007). The RFM transmission simulations closely fit the EGOPS simulations, confirming that in turn the ALPS retrieval performance results rest on a reliable basis. Fur-thermore, RFM transmission spectra have been compared in the 4000–4400 cm-1 range to real transmission spectra from the Canadian ACE (Atmospheric Chemistry Experiment; http://www.ace.uwaterloo.ca) solar occultation instrument (ACE Fourier Transform Spec-trometer, 0.02 cm-1 spectral resolution), showing very good agreement (data provided by P. Bernath and R. Hughes, Univ. Waterloo/Can, pers. communications, 2006).

Modeling of the loss processes other than the target species absorption loss (defocusing, Rayleigh scattering, etc.) was included as part of ALPS. The error propagation through the individual retrieval processing steps, for transmission, species, and wind profile retrieval, was modeled by a propagation-of-variances approach, which employed in-depth knowledge of the retrieval process to adequately model relevant component errors and gain factors.

Furthermore, two remarks are in order on systematic and representativeness errors, respec-tively. Except for l.o.s. wind depending on frequency knowledge in an absolute manner, sys-tematic errors are not separately treated in ALPS since the self-calibrating log-transmission differencing principle applied to the occultation data will deliver long-term stable profiles essentially free of time-varying biases. Systematic spectroscopy parameter errors may leave residual time-constant biases, which do not affect trend studies, but also these are expected to be made very small by careful pre-launch spectroscopy (cf. section 3.2.2). Regarding repre-sentativeness errors, such as due to deviations from local spherical symmetry, the error esti-mates do, as in ESA (2004a), not include this type of errors. Representative “errors” depend on what is chosen as “true” reference state and can be either negligible or significant depend-ent on this choice. This is the reason why they are not considered part of observational error, and likewise not part of the observational accuracy requirements (section 2.1, Table 1).

In the following, the ALPS performance estimation chain is described in detail (subsection 4.1.1) and, as an example application, step-by-step results are shown for retrievals from the CO2-line channels (subsection 4.1.2).



Diff. log-Transm. Relative Error

Raw SNR @ 50 Hz

Filtering to nominal z-resolution (1-2 km)

Basic SNR(at nominal resolution)

Modeling of atmospheric loss processes

(Defocusing, Rayleigh Scatt. ,Aerosol Ext., TurbScint,

and Background Absorption Loss)

Total Background Loss

Target Species Absorption Loss Modeling

(Forward Modeling by RFM/HITRAN/FASCODE)

Target SpeciesAbsorption Loss

Absorption CrossSection Error

Absorption CrossSection Error Modeling

Monthly-mean Species Profile Error

Non H2OSpecies

Species Profile Retrieval Error

Statistical Averaging(over req. No. of profiles

per bin)

H2O

H2O Profile Retrieval Error

Delta Diff.Transmission Error

Zero-Wind Diff. Transmission Model Error

Diff. TransmissionDerivative Model Error

Transmission ErrorModeling

Differencing Residual Error

Differential log-Transmission Error

Statistical WindRetrieval Error

Delta Diff. TransmissionTotal Error

Laser Freq. Knowledge Uncertainty

Error Modeling

Single-profile System. Wind Error

l.o.s. Wind Profile Retrieval Error

Inverse AbelTransform Error Propagation

Modeling

Trace SpeciesRetrieval ErrorModeling

Diff. TransmissionRetrieval ErrorModeling

SNRModeling

ForwardModeling

l.o.s. WindRetrieval Error

Modeling

Figure 8. Schematic view of the LIO retrieval performance estimation modeling chain as implemented in the ALPS (ACCURATE LIO Performance Simulator) tool.



4.1.1 Performance Modeling Algorithms SNR (Signal-to-Noise Ratio) Modeling

Starting point for the computation is the SNR required at the detector, SNRf_s,raw, which is assumed to be 27 dB at a sampling rate, fs,raw, of 50 Hz (section 3.2, Table 6). SNRf_s,raw must be converted to a basic SNR, SNRbasic, consistent with the required vertical resolution of 1-2 km (section 2.1, Table 1). For this purpose, the downsampling gain, Gds, is first computed,

filts,

raws, ds log10[dB]

ff

G ⋅= , (1)

which results from downsampling of fs,raw to a filtered sampling rate, fs,filt, where we adopt fs,filt = 2 Hz as baseline, equivalent to a unit 1 Hz observational bandwidth according to Nyquist’s sampling theorem. Secondly, the resolution gain, Gresol, is computed,

filt

target resol log10[dB]

dzdz

G ⋅= , with (2)

filts,

scanfilt 5.0 f

Vdz⋅

= ,

Vscan [km/s] = {0.3, 2.8, 3, 3.15, 3.2, 3.2} at z [km] = {0, 25, 30, 35, 40, 120} (linear interpolation between z levels),

which scales the vertical resolution matching 1 Hz bandwidth, dzfilt, to the required vertical resolution, dztarget, where dzfilt is obtained based on the LEO-LEO vertical scan velocity, Vscan, empirically modeled to represent the typical set/rise velocity of occultation rays during LEO-LEO occultation events. Note that if dzfilt is greater than dztarget (1-2 km), occurring at heights where Vscan > 2 km/s, Gresol becomes negative, i.e., a loss.

The basic SNR at required vertical resolution dztarget is then obtained from adding downsam-pling and resolution gain to the raw SNR,

resoldsrawf_s, basic ]dB[ GGSNRSNR ++= . (3)

Based on SNRbasic, the available SNR for arbitrary LIO absorption and reference channels (for ACCURATE those of Table 5 in section 3.1), SNRAbs and SNRRef, is computed,

TSpBgrbasic Abs ]dB[ LLSNRSNR −−= , TSpBgrbasic Ref ]dB[ +−= LSNRSNR , (4)

where LBgr, LTSp, and LBgr+TSp (all in units [dB]) are the total background loss, target species absorption loss, and background plus (small residual) target species absorption loss in refer-ence channels, respectively. These losses are obtained from forward modeling as described next. Forward Modeling

The total background loss LBgr is modeled as the sum of defocusing loss, LDef, Rayleigh scat-tering loss, LR, aerosol extinction loss, LA, turbulence/scintillation loss, LTS, and background



absorption loss coming from residual absorption by other gases than the target species in con-sideration, LBgrAbs:

BgrAbsTSARDefBgr ]dB[ LLLLLL ++++= . (5)

In case of a reference channel, LBgr+TSp is used, which has just added to LBgrAbs in Eq. (5) the target species absorption loss as well, which is for reference channels a small residual absorp-tion similar to all the other gases contributing to LBgrAbs. Note that since LBgr of an absorption channel and LBgr+TSp of its associated reference channel will be closely the same due to the small channel spacing (0.99 < λAbs/λRef < 1.01), the total background signal will be eliminated to high accuracy by log-transmission differencing between the channels, leaving besides the target species signal only a very small differencing residual error to be co-modeled in LIO retrieval processing. The target species absorption loss LTSp and the background absorption loss LBgrAbs are com-puted from the RFM/HITRAN/FASCODEatm modeling system as described in the section 4.1 introduction above. They are supplied by the RFM system to the ALPS system, via a common file interface, for all required absorption and reference channels. Rayleigh scattering loss LR, aerosol extinction loss LA, and turbulence/scintillation loss LTS – the latter representing (in an upper limit/worst case sense) the net attenuation of signals due to rapid scintillation fluctuations (at sub-second time scales), rooting in atmospheric turbulence – are modeled in ALPS in the same way as implemented in EGOPS. Section 2.2 of ACCURAID (2007) described this modeling in detail, which shall thus not be repeated here. The difference of ALPS to EGOPS is that ALPS parameterizes the 3D along-ray integration over extinction coefficients by a simple effective ray path length multiplied with the extinc-tion coefficient profile. For ray tangent heights > 5 km relevant to ACCURATE, where bend-ing angles are < 15 mrad, 300 km was found a good single value for this effective path length (confirmed against 3D ray tracing) and thus adopted as the baseline setting in ALPS. Defocusing loss LDef, finally, is empirically modeled based on a piecewise fit (piecewise in height) to typical LRO defocusing loss profiles from realistic end-to-end simulations in the ACE+ phase A studies context (e.g., ACEPASS, 2005a). Using this LRO MW heritage di-rectly for the SWIR domain is possible due to the close similarity of MW and SWIR refractiv-ity (cf. section 3.1.1; ACCURAID, 2007), leading to closely the same defocusing. Below 10 km and above 25 km, LDef is modeled with exponential dependence,

)exp(]dB[ )(Def

00Def H

zzLzL −−⋅= , (6)

where z is the height, L0 is the defocusing loss at the reference height z0, and HDef is the “de-focusing scale height” (adopted settings for 0–10 km: L0 = 10 dB, z0 = 0 km, HDef = 11 km; for ≥ 25 km: L0 = 0.75 dB, z0 = 25 km, HDef = 7 km). Between 10 and 25 km, LDef is modeled linearly in two segments, from 10 to 20 km decreasing from the 10-km value (from Eq. (6), ~4.0 dB) to 1.5 dB, and from 20 to 25 km decreasing from 1.5 dB to 0.75 dB, respectively.



Differential Transmission Retrieval Error Modeling

Based on the available SNR for any absorption and associated reference channel, SNRAbs and SNRRef, as obtained from Eq. (4), the differential log-transmission total error, EΔT, is derived,

2T_resid

2T_Ref

2T_Abs T ]%[ ΔΔ ++= EEEE , with (7)

10 T_Abs

Abs

10100]%[SNR

E−

⋅= ,

10 T_Ref

Ref

10100]%[SNR

E−

⋅= ,

EΔT_resid [%] = {2, 1, 0.5, 0.3, 0.2, 0} at z [km] = {0, 5, 10, 20, 30, 120} (linear interpolation between z levels),

where ET_Abs and ET_Ref are the SNR-based log-transmission errors for absorption and refer-ence channel, respectively, and EΔT_resid is the log-transmission differencing residual error, which may be left after log-transmission differencing by residuals from broadband effects (e.g., scattering, scintillation) not entirely cancelled. EΔT_resid, expected to come mainly from scintillation error since this process has the strongest combination of wavelength dependence and shot-to-shot intensity fluctuations, is assumed to range from 1% near 5 km to 0.2% at 30 km and above, which is rated to be a reasonable margin for this error. The differential log-transmission relative error, EΔT_rel, which corresponds to the optical thickness relative error needed as input to trace species retrieval error modeling, is subse-quently obtained from EΔT [%],

( )absT_abs T_rel 100]%[ TrEE Δ⋅= ΔΔ , with (8)

T%2dB T_abs ]dB[ ΔΔ ⋅= EcE ,

AbsRef abs ]dB[ SNRSNRTr −=Δ ,

where EΔT_abs is the (absolute) differential log-transmission error in units [dB] (c%2dB = 1/(10⋅ln10) = 0.043429 is the conversion constant from [%] to [dB]), and ΔTrabs is the differ-ential log-transmission between the absorption and reference channel. Trace Species Retrieval Error Modeling

Based on the EΔT_rel from Eq. (8), which is computed by the ALPS tool for all target species, the species absorption coefficient error, EAbsC, is derived as first step towards species profile retrieval,

T_relAbelTr AbsC ]%[ Δ⋅= EgE , with (9)

5.2AbelTr =g ,

where gAbelTr is the error amplification factor (gain factor) resulting from the Abelian trans-formation, which is used to convert the differential log-transmission profile, proportional to optical thickness and along-ray columnar content, to the species absorption coefficient profile (an “absorptive Abel transform” with a vertical derivative of log-transmission in the inte-



grand). The value of 2.5 is adopted based on the results of OPAC (2004d), where the error amplification factor was studied for different numerical implementations of the Abel trans-form, leading to a value of about 2.5. This is also consistent with experience from ACEPASS (2005a) work, related to the implementation of the absorptive Abel transform in EGOPS.

Implicitly it is here assumed that the differential log-transmission between λAbs and λRef chan-nel is essentially equal to the direct log-transmission of the target species at the λAbs channel. This assumption is a very good approximation for ACCURATE, due to the careful absorption vs. reference channel selection, where essentially all target species absorption occurs at λAbs and essentially none at λRef. The species profile retrieval error, ESp, is computed from the absorption coefficient error EAbsC of Eq. (9) via also accounting for the absorption cross section error, EσAbs,

2Abs

2AbsC Sp [%] σEEE += , with (10)

EσAbs [%] = {0.8, 0.8, 0.4, 0.4, 1.6, 8} at z [km] = {0, 5, 10, 40, 60, 120} (linear interpolation between z levels),

where EσAbs is empirically modeled to be < 0.4-0.8% within 5-10 km and < 0.4% within 10-40 km (with increasing error upwards). This error is so small, because the absorption cross section is accurately co-modeled in LIO retrieval processing, since temperature and pressure profiles are known to < 0.3% accuracy within the UTLS height range from the co-located LRO MW measurements (see Figure 10). Above 40 km, the errors increase significantly as the LRO pressure and temperature measurements increasingly degrade in accuracy. In addition, the monthly-mean species profile error, ESp,MonAv, is estimated from ESp, consis-tent with the observational requirements (section 2.1, Table 1) for the number of profiles to be averaged per grid box per month, Nbin, for which the target requirement Nbin = 40 was adopted as baseline value. Given the unbiased, statistical nature of ESp, ESp,MonAv is estimated as

bin

Sp MonAvSp, ]%[

NE

E = , (11)

which leads to a monthly-mean error about six times smaller than the single profile error. In case of water vapor (H2O), four pairs of absorption and reference channels (rather than one; cf. section 3.1, Table 5) are used to cover the full UTLS height range, since H2O concen-trations have such a strong height dependence (cf. section 3.1, Figure 3). The errors from these four individual H2O channel pairs, Ej, are optimally combined (inverse-variance weighted combination) to obtain a single composite H2O error profile:

( ) 14

12

H2O 1[%]−

=∑=j jEE . (12)

Such optimal combination was applied for H2O not only for obtaining single composite pro-files for species and monthly-mean species errors but also for differential log-transmission total and relative errors, respectively.



Line-of-sight Wind Retrieval Error Modeling

The starting point for the simplified wind retrieval error modeling in ALPS is the “wind re-trieval equation”, Eq. (13). This equation expresses that the retrieval of the line-of-sight wind velocity, Vlos, is based on the observed double-difference of the log-transmissions of the wind(1) and wind(2) channels, ΔΔTrw1w2 [dB] = (Trw1-TrRef) – (Trw2-TrRef) (cf. section 3.1.2, Figure 6), created by wind-induced Doppler shift d wν = –( 0ν /c0)⋅Vlos, as well as the modeled spectral transmission derivatives at the two wind channels, (dTr/dν )w1,Mod and (dTr/dν )w2,Mod, units [dB/cm-1],

( ) ( )Modw2,Modw1,

Modw1w2,0,w1w

000 dddd)(

d/ddd]m/s[ 200

w0

los νννννν

ν TrTrTrTrc

TrTrccV

−Δ−ΔΔ

⋅−=⋅−=⋅−= , (13)

where c0 [m/s] is the speed of light, 0ν [cm-1] is the wavenumber of the line center of the ab-sorption line used for the wind retrieval (i.e., the CO2 absorption line), and ΔTrw1w2,0,Mod [dB] is the modeled difference between the transmissions of the wind lines in case of no wind. The latter term is zero if the used absorption line is ideally symmetric, i.e., not perturbed by any other line wings in close spectral neighborhood. Otherwise, as is the case for the selected CO2 line, it is a small correction term to ΔΔTrw1w2, which is co-modeled in the evaluation of real data (cf. section 4.4; ACCURAID, 2007). The main approximation intrinsic to Eq. (13) is that the line-of-sight wind is at any height level assumed to belong locally to the occultation ray tangent point as well as to be strictly related to a constant Doppler shift d wν , whilst in reality the Tx-to-Rx along-ray propagation of the wind(1) and wind(2) signals, for any ray tangent height level, is through a spherically-shaped atmosphere so that the signals experience varying Doppler shifts due to varying line-of-sight wind velocities along the ray path. A new “wind retrieval” Abel transform may ac-count for these dependences but for the initial performance estimation we find the approxima-tion to work fairly well, as we confirmed by comparison to EGOPS simulations, which treated the wind signal propagation in a realistic 3D mode (ACCURAID, 2007). Eq. (13) serves as the basis for implementing the Vlos statistical error estimation via modeling the relative Vlos error, EV_los_rel,Statist, as the sum of the relative error of the numerator dTr, the delta-differential log-transmission total error, EΔΔT_w1w2_rel, and of the denominator dTr/dν , the differential log-transmission derivative model error, EdTr/dν_rel,Mod. The constants c0 and 0ν are of no further relevance for this error estimation. Absolute Vlos error, EV_los,Statist [m/s], is then readily derived by multiplying EV_los_rel,Statist with the Vlos(z) wind profile itself. A sys-tematic error from laser frequency knowledge uncertainty δfL, EV_los,System [m/s], is added separately (systematic during each occultation event, but statistical from event to event; cf. section 2.2, Table 2). Delta-differential log-transmission error EΔΔT_w1w2. EΔΔT_w1w2, the error associated with ΔΔTrw1w2 in Eq. (13), is composed of two main compo-nents, the laser frequency-based log-transmission error, ET_wi,fL, due to residual laser fre-quency instability, which is kept very small by high-accuracy (femtosecond-laser) frequency locking and stabilization (section 3.2.2), and the SNR-based log-transmission error for the



wind channels, ET_wi,SNR, similar to the one for other absorption channels (cf. Eq. (7), ET_Abs). In addition, due to the double-differencing process, the small SNR-based transmission error for the wind reference channel, ET_Ref (Eq. (7)), and a double-differencing residual error, EΔΔT_resid, play a role.

ET_wi,fL, where i denotes both ET_w1,fL and ET_w2,fL, is computed consistent with the required vertical resolution (section 2.1, Table 1), accounting for the downsampling and resolution gains (Eqs. (1) and (2)), based on the relative laser frequency stability rms error, efL_rel,Stabil, given at raw sampling rate,

( ) dz_targetfL_abs,Mod,wdB2% fL,T_w dd]%[ ETrcE ii ⋅⋅= ν , with (14)

01

dz_target fL_abs,10

dz_targetfL_dB,

10]cm[ ν⋅=−E

E ,

resoldsStabilfL_rel,dz_target fL_dB, )log(10]dB[ GGeE −−⋅= ,

where cdB2% = 10⋅ln10 = 23.026 is the conversion constant from [dB] to [%], (dTr/dν )wi,Mod denotes the w1 and w2 transmission derivatives (cf. Eq. (13)), and EfL_abs,dz_target / EfL_dB,dz_target is the laser frequency error at the required resolution in units [cm-1] / [dB]. For efL_rel,Stabil, the baseline setting efL_rel,Stabil [1] = 2⋅10-8 at 50 Hz sampling rate was adopted, according to the ACCURATE laser frequency stability requirement (section 2.2, Table 2). The transmission derivatives are computed from the RFM/HITRAN/FASCODEatm modeling system as noted in the section 4.1 introduction above. ET_wi,SNR, where i denotes both ET_w1,SNR and ET_w2,SNR, is computed analogously to the SNR-based transmission error in Eq. (7), but accounting additionally for the wind-induced Doppler shift d wν = –( 0ν /c0)⋅Vlos,

( )10

ddd wMod,w

SNR,T_w 10]%[ ,0T_w

νν ⋅−

⋅=i

i

Tr

iEE , (15)

where ET_wi,0 [%] denotes the SNR-based transmission error for the w1 and w2 channels at zero-wind (Vlos = 0), computed the same way as ET_Abs in Eq. (7). The combination of both laser frequency-based error ET_wi,fL and SNR-based error ET_wi,SNR then results in the total log-transmission errors for the wind channels, ET_w1 and ET_w2,

2SNRT_w2,

2fLT_w2,

2SNRT_w1,

2fLT_w1, ]%[ ,]%[ T_w2 T_w1 EEEEEE +=+= , (16)

which are the dominating contributions when finally forming, accounting for the double dif-ferencing, the delta-differential log-transmission error EΔΔT_w1w2,

ΔΔT_resid2T_Ref

2T_w2

2T_w1 2]%[ T_w1w2 EEEEE +⋅++=ΔΔ , with (17)

)2(]%[ ΔT_residcorr ΔΔT_resid EgE ⋅⋅= ,

where ET_Ref [%] is computed based on Eq. (7) and appears twice since two single-differences enter the double-differencing. The double-differencing residual error EΔΔT_resid [%], which



would in case of no error correlations be 2 times the single-differencing residual error EΔT_resid computed in Eq. (7), has applied an error reduction factor gcorr, since due to the very close frequency spacing of absorption and reference channels at the CO2 line (|λwi–λRef|/λRef < 0.05%) the single-differencing errors EΔT_resid will be highly correlated. gcorr = 0.25 is set as baseline value, expected to be conservative given the very close wind channel spacing. Zero-wind differential log-transmission error EΔT_w1w2,0,Mod. EΔT_w1w2,0,Mod is computed based on assuming a relative error of the zero-wind wind(1)-minus-wind(2) transmission difference modeling, eΔT_w1w2_rel,0,Mod [%], which would be left when co-modeling this correction term by the RFM/HITRAN system:

Modw1w2,0,Mod,0,T_w1w2_rel

dB2% 100]%[ ModT_w1w2,0, Tr

ecE Δ⋅⎟⎟

⎠

⎞⎜⎜⎝

⎛⋅= Δ

Δ . (18)

The baseline setting adopted for eΔT_w1w2_rel,0,Mod is 5%, which is a conservative estimate on expected RFM/HITRAN line-by-line modeling accuracy for supplying the zero-wind w1–w2 differential log-transmission model profile ΔTrw1w2,0,Mod [dB]. Given that temperature and pressure are accurately known from ACCURATE LRO data (< 0.3 to 0.4% up to about 40 km, cf. Figure 10), the real accuracy achieved will presumably be higher. In ALPS, the term ΔTrw1w2,0,Mod is computed based on the RFM/HITRAN/FASCODEatm modeling system. Relative delta-differential log-transmission total error EΔΔT_w1w2_rel. EΔΔT_w1w2_rel is subsequently obtained from the sum of the errors EΔΔT_w1w2 and EΔT_w1w2,0,Mod (converted to [dB], cf. Eq. (8)), divided by the numerator dTr of Eq. (13):

( )Modw1w2,0,w1w2T_w1w2_abs T_w1w2_rel 100]%[ TrTrEE Δ−ΔΔ⋅= ΔΔΔΔ , with (19)2

ModΔT_w1w2,0,2ΔΔT_w1w2%2dB T_w1w2_abs ]dB[ EEcE +⋅=ΔΔ .

Both absolute reference terms, ΔΔTrw1w2 [dB] and ΔTrw1w2,0,Mod [dB], are modeled using the RFM/HITRAN/FASCODEatm system.

Relative differential log-transmission derivative model error EdTr/dν_rel,Mod. The starting point for computing EdTr/dν_rel,Mod is the assumption of a relative error of the wind(1) and wind(2) spectral transmission derivatives modeling, edTr/dν_w_rel,Mod [%], which would be left when modeling these derivatives by the RFM/HITRAN system,

( ) Mod,wMod_w_rel,dTr/d1- dd

100]dB/cm[ Mod,_wdTr/d ivTr

eE i ⋅⎟⎟

⎠

⎞⎜⎜⎝

⎛= ν

ν , (20)

where EdTr/dν_wi,Mod denotes the absolute log-transmission derivatives model error at the w1 and w2 channels. The derivatives (dTr/dν )wi,Mod are the same as already used in Eqs. (13) and (14) above. The baseline setting adopted for edTr/dν_w_rel,Mod is 3%, which is a conservative estimate on expected RFM/HITRAN accuracy for supplying the derivatives for the wind channels. Given that temperature and pressure are accurately known from LRO data (cf. Figure 10), and that the value of the derivatives near the Doppler half-width frequencies (turning points of lineshape function) is rather insensitive to the exact frequency knowledge (cf. Figure 6), the real accuracy achieved will presumably be higher.



EdTr/dν_rel,Mod is subsequently derived based on the sum of the model errors EdTr/dν_w1,Mod and EdTr/dν_w2,Mod, divided by the denominator dTr/dν of Eq. (13):

( ) ( )( )Modw2,Modw1,

dddd100]%[ Mod_abs,dTr/d Mod_rel,dTr/d νννν TrTrEE −⋅= , with (21)2

Mod_w2,dTr/d2

Mod_w1,dTr/d-1

Mod_abs,dTr/d ]dB/cm[ ννν EEE += . Statistical wind retrieval error EV_los,Statist. EV_los,Statist [m/s] is computed based on the relative wind retrieval error, EV_los_rel,Statist [%]. The latter is the sum of the delta-differential log-transmission total error EΔΔT_w1w2_rel [%] and the differential log-transmission derivative model error EdTr/dν_rel,Mod [%],

22Mod_rel,dTr/dT_w1w2_relStatist V_los_rel, ]%[ νEEE += ΔΔ , (22)

from which the former directly follows by multiplication with Vlos:

los)01.0(]m/s[ StatistV_los_rel,Statist V_los, VEE ⋅⋅= . (23)

Single-profile systematic wind error EV_los,System. EV_los,System [m/s] is computed from the relative laser frequency knowledge uncertainty error, efL_rel,Knowl [1], for which the baseline setting is 1⋅10-8 (3σ), in line with the laser frequency 3-sigma knowledge requirement (δfL/f0) < 1⋅10-8 (3σ) (section 2.2, Table 2),

⎟⎟⎠

⎞⎜⎜⎝

⎛⋅=

3]m/s[ KnowlfL_rel,

0 SystemV_los,e

cE , (24)

where the Doppler shift relation Vlos = c0⋅(δfL/f0) has been used, and the division by 3 scales the given 3σ knowledge uncertainty to the 1σ standard error. Line-of-sight wind profile retrieval error EV_los. The final data product of the wind retrieval error estimation, EV_los, is the sum of the statistical and systematic wind retrieval errors, EV_los,Statist and EV_los,System:

22SystemV_los,StatistV_los, V_los ]m/s[ EEE += . (25)

This total l.o.s. wind retrieval error estimate is to be compared to the l.os. wind retrieval accu-racy performance requirements of section 2.1, Table 1. 4.1.2 Step-by-Step Modeling Results Table 8 illustrates step-by-step example results of the ALPS system, i.e., as computed by the ALPS algorithms described in subsection 4.1.1. These results have been obtained for the ACCURATE CO2 absorption channels near 2.1 μm, using the FASCODE model 6/U.S. stan-dard atmosphere, and, regarding wind, assuming a height-constant l.o.s. wind blowing with a speed of 30 m/s towards the Rx (the wind retrieval error results are essentially independent of the detailed wind profile assumption, however; cf. section 4.4).



Table 8. Step-by-step LIO Retrieval Performance Estimation Results (example case: CO2 line at 2.1 μm, std.atm., constant +30 m/s wind profile)

Parameter Altitude 35 km 30 km 25 km 20 km 15 km 10 km 7 km 5 km Raw SNR (at 50 Hz sampling) 27 dB 27 dB 27 dB 27 dB 27 dB 27 dB 27 dB 27 dB Basic SNR (at 1-2 km vert.resol.) 33.0 dB 33.1 dB 33.3 dB 33.7 dB 34.0 dB 34.0 dB 34.0 dB 34.5 dBDefocusing Loss 0.2 dB 0.4 dB 0.8 dB 1.5 dB 2.8 dB 4.0 dB 5.3 dB 6.3 dB Rayl. Scattering Loss 0.00 dB 0.00 dB 0.00 dB 0.00 dB 0.01dB 0.02 dB 0.03 dB 0.04 dBAerosol Extinction Loss 0.00 dB 0.00 dB 0.02 dB 0.06 dB 0.09 dB 0.12 dB 0.30 dB 0.76 dBAero.Ext.Loss: Exam. Volcanic1) 0.00 dB 0.01 dB 0.11 dB 0.91 dB 1.21 dB 0.12 dB 0.30 dB 0.76 dBTurb./Scintillation Loss 0.03 dB 0.05 dB 0.07 dB 0.09 dB 0.12 dB 0.17 dB 0.21 dB 0.23 dBBackground Absorption Loss 0.00 dB 0.00 dB 0.00 dB 0.00 dB 0.02 dB 0.09 dB 0.26 dB 0.59 dBTotal Background Loss 0.21 dB 0.42 dB 0.84 dB 1.66 dB 3.00 dB 4.44 dB 6.09 dB 7.97 dBAvailable SNR for channel λRef 32.8 dB 32.7 dB 32.4 dB 32.0 dB 31 dB 29.6 dB 28.0 dB 26.7 dBTransmission Error for λRef 0.05 % 0.05 % 0.06 % 0.06 % 0.08 % 0.11 % 0.16 % 0.21 % Target Species Abs. Loss at λAbs 1.0 dB 1.4 dB 2.1 dB 3.0 dB 3.9 dB 5.1 dB 7.4 dB 10.0 dBAvailable SNR for channel λAbs 31.8 dB 31.3 dB 30.3 dB 29.1 dB 27.1 dB 24.4 dB 20.5 dB 16.5 dBTransmission Error for λAbs 0.07 % 0.07 % 0.09 % 0.12 % 0.20 % 0.36 % 0.90 % 2.26 % Differencing Residual Error 0.2 % 0.2 % 0.3 % 0.3 % 0.4 % 0.5 % 0.8 % 1.0 % Diff. log-Transmission Error 0.2 % 0.2 % 0.3 % 0.3 % 0.5 % 0.6 % 1.2 % 2.5 % Diff. log-Transm. Relative Err. 0.9 % 0.7 % 0.6 % 0.5 % 0.5 % 0.5 % 0.7 % 1.1 % Species Abs. Coefficient Error 2.3 % 1.7 % 1.4 % 1.2 % 1.3 % 1.3 % 1.8 % 2.6 % Abs. Cross Section Error 0.4 % 0.4 % 0.4 % 0.4 % 0.4 % 0.4 % 0.6 % 0.8 % Species Profile Retrieval Error 2.3 % 1.7 % 1.5 % 1.3 % 1.3 % 1.4 % 1.9 % 2.7 % Species, target requirement2) < 5% < 5% < 5% < 5% < 5% < 5% < 5% < 5% Species, threshold requirement2) best effort < 10% < 10% < 10% < 10% < 10% < 10% best effort

Mon-mean Species Profile Err. 0.4 % 0.3 % 0.2 % 0.2 % 0.2 % 0.2 % 0.3 % 0.4 % Delta Diff. Transmission Error 0.2 % 0.2 % 0.3 % 0.3 % 0.4 % 0.5 % 1.2 % 2.8 % Zero-wind Diff.Transm.Mod.Err. 0.01 % 0.01 % 0.02 % 0.03 % 0.06 % 0.08 % 0.09 % 0.07% Delta Diff. Transm. Total Error 5.09 % 4.41 % 4.07 % 3.9 % 4.7 % 7.7 % 17.6 % 43.3 % Diff.Transm.Derivative Mod.Err. 2.1 % 2.1 % 2.1 % 2.1 % 2.1 % 2.1 % 2.1 % 2.1 % Statistical Wind Retrieval Error 1.7 m/s 1.5 m/s 1.4 m/s 1.3 m/s 1.5 m/s 2.4 m/s 5.3 m/s 13.0 m/sSingle-profile System. Wind Err. 1.0 m/s 1.0 m/s 1.0 m/s 1.0 m/s 1.0 m/s 1.0 m/s 1.0 m/s 1.0 m/sl.o.s Wind Profile Retr. Error 1.9 m/s 1.8 m/s 1.7 m/s 1.7 m/s 1.8 m/s 2.6 m/s 5.4 m/s 13.1 m/sl.o.s.Wind, target requirement2) 2 m/s 2 m/s 2 m/s 2 m/s 2 m/s 2 m/s best effort best effortl.o.s.Wind, thresh. requirement2) 5 m/s 5 m/s 5 m/s 5 m/s 5 m/s 5 m/s best effort best effort

1) As an example of effects of a volcanic event, extinction loss by a high aerosol load extinction profile (“post-Pinatubo”), with its main effect in the lower stratosphere, is also shown (source NOAA-ESRL, 2005). In the error estimation chain, the aerosol extinction loss without volcanic enhancement (previ-ous line) was used. In general, sporadic volcanic events will, dependent on strength and characteristics of volcanic eruption, populate from time to time the UTLS at different heights within 5–25 km with aerosol lasting a few weeks to up to ~2 years. At ACCURATE wavelengths > 2 μm, the total aerosol attenuation effects are always expected < 2 dB, however, so the effects on performance will be visible but fairly limited (errors increased by up to a few 10% of their typical magnitude).

2) From ACCURATE observational requirements (section 2, Table 1). Starting with a single-shot SNR of 27 dB at TOA at 50 Hz sampling rate (section 3.2.1, Table 6), losses and errors for CO2 species retrieval, and related wind retrieval, are listed in Table 8 for eight representative heights over 5–35 km. This example for CO2 is intended to show in detail typical losses and errors for LIO occultation measurements; the other ACCURATE LIO channels behave similar. In the following, some important aspects of the performance estima-



tion are discussed based on Table 8, focusing on typical characteristics of various loss com-ponents and error estimates.

The first main part of the performance estimation is the assessment of the differential log-transmission profile accuracy, which then forms the basis for the subsequent atmospheric pro-files retrieval, i.e., the retrieval of target trace species and l.o.s. wind. The main source of dif-ferential log-transmission error is the gradual decrease of SNR during the occultation event with decreasing altitude towards 5 km (cf. Table 8), which increases the transmission error in particular in the absorption channel λAbs. The transmission error in the reference channel λRef stays much smaller, since absorption loss is limited to ~1 dB or less in these channels (cf. Figure 4), which are thus dominated by defocusing, scattering, and scintillation loss.

The log-transmission differencing between the closely spaced λAbs and λRef channels will es-sentially eliminate all broadband effects (caused by defocusing, scattering/extinction, other absorbing species, scintillations). There is merely a differencing residual error left, modeled according to Eq. (7) and presumably dominated by residual scintillation errors, which at > 2 μm probably have relatively the strongest combination of wavelength dependence and shot-to-shot intensity fluctuations. Also the residual scintillation errors are very small after differ-encing, since the Fresnel zone diameter difference of ACCURATE λAbs and λRef channels is always < 0.5% and since atmospheric turbulence is a “frozen in” process for the specified laser pulse durations of < 2 ms (section 2.2, Table 2). Envisat/GOMOS stellar occultation transmission data in the visible (spectrometer and fast photometer data; with much more scin-tillation strength than available at > 2 μm; cf. OPAC, 2004e) are backing these estimations. Refined analysis, including GOMOS transmission data reaching down to 5 km and scintilla-tion modeling, will be used in future to consolidate residual scintillation error estimates (and may lead to less error for the comparatively long wavelengths of interest at > 2 μm).

As can be seen from Table 8, Rayleigh scattering, which in principle has a strong wavelength dependence (~λ-4) leaves only negligible residual errors as its magnitude is very small at > 2 μm and since it can also be readily co-modeled due to the accurate knowledge of air density from the ACCURATE LRO retrieval. Aerosol extinction (Mie scattering and absorption), which is of interest for its contribution to overall SNR decrease (especially in case of extreme volcanic events, see caption of Table 8), induces a smooth broadband effect not significant for differencing residual error. The arguments given here hold essentially for both scattering loss during propagation (loss to the laser signal intensity) and, during daylight, solar backscat-tering into the receiver telescope. Separate initial estimates have been made for solar back-scattering – which is measured together with any other incoming background signal by the after-shot background measurement if exceeding the detector noise level, and may be cor-rected – showing that for the LIO Rx baseline design the signal in full daylight may be (at 5 km altitude at 2 μm, worst case) up to ~3 times the detector NEP level (section 3.2.1, Table 6), which will be reduced by the differencing to below noise level. Thermal radiation is negli-gible under all conditions at ACCURATE wavelengths < 2.5 μm.

Likewise, defocusing loss is a well understood broadband effect, which is also readily co-modeled, if desired, since accurately measured by the LRO data. Defocusing is important for its contribution to SNR decrease but of insignificance for differencing residual error.

In summary, the SNR-based differential log-transmission error will thus at upper altitudes (30 km and above), where all atmospheric loss effects are very small, be proportional to ~ 2



times the individual-channel transmission errors, associated with SNRs of > 31 dB at the re-quired 1-2 km resolution (see lines “Available SNR” in Table 8; see also Eq. (7)). This yields ~0.1% differential log-transmission errors without differencing residual error, showing that with magnitude 0.2% at 30 km and above we have conservatively modeled the latter error to dominate the SNR-based error. Note that the Tx laser system itself will enable to fulfill a re-quirement of received pulse-to-pulse intensity fluctuations of < 0.3% (including both fre-quency and intensity uncertainties from the requirements in section 2.2, Table 2), leading to < 0.07% error at 1-2 km resolution, which sensibly matches the SNR-based error at Rx side and is as well minor to the modeled differencing residual error. The ALPS approach of utilizing the SNR at the Rx at TOA as the basic starting point of error estimation, combined with the conservative modeling of the differencing residual error, is thus a very adequate treatment.

At heights below 30 km, the errors gradually increase, in particular in the UT below 15 km, where all background effects described above become increasingly relevant and where, in particular, the signal in the λAbs channel becomes significantly absorbed by the target species (cf. Figure 4). Table 8 shows in boldfaced type the differential log-transmission error (Eq. (7)), and the differential log-transmission relative error (Eq. (8)), respectively, which are ar-rived at based on all influences discussed. As Eq. (8) implies, the latter error will be minimal within the UTLS but then also increase upwards (contrary to the former error), since the dif-ferential log-transmission, the denominator of Eq. (8), becomes gradually very small at upper altitudes as target species absorption diminishes (cf. Figure 4).

The second main part of the performance estimation is the trace species and the l.o.s. wind retrieval error computation, respectively, which is based on the transmission errors.

Concerning the trace species profile retrieval, Table 8 exhibits the error amplification from differential log-transmission relative error to the species absorption coefficient error by the Abelian transformation (Eq. (9)) as well as the absorption cross section error from uncertain-ties in temperature and pressure and the species profile retrieval error, individual profile and monthly-mean, eventually obtained (Eqs. (10) and (12); shown boldfaced in Table 8). The observational requirements shown for reference (from section 2.1, Table 1) are seen to be well fulfilled by the CO2 retrieval within target requirements.

The error propagation of the l.o.s. wind profile retrieval chain is illustrated in Table 8 line by line via its main component errors described in subsection 4.1.1, which lead to estimation of the statistical l.o.s. wind retrieval error (Eq. (23)). Adding the single-profile systematic l.o.s. wind error, which is determined by the uncertainty in laser frequency knowledge (Eq. (24)), provides the total l.o.s. wind profile retrieval error (Eq. (25)) shown boldfaced in Table 8. Comparison to the observational requirements indicates them to be well fulfilled.

No monthly-mean error is computed by the ALPS system for l.o.s. wind, since wind is a vec-tor quantity and l.o.s. wind will vary in direction from occultation event to occultation event so that a simple scalar average is not sensible. In practice, ACCURATE based on sun-synchronous counter-rotating LEO satellites (ACE+ type configuration; ACCURATE, 2005) will deliver monthly-mean meridional wind fields (Brewer-Dobson circulation), possibly in-voking in the averaging limited prior vector wind field information (e.g., from ECWMF analyses). The single-profile systematic wind errors are expected to vary from event to event so that also this component will be significantly reduced in monthly averages.



4.2 Differential Transmission Retrieval Performance Figure 9 shows the differential log-transmission retrieval errors for all ACCURATE target species, which have been computed using the ALPS system described in detail in subsection 4.1. Both absolute errors of the log-transmission (after Eq. (7)), equivalent to relative errors in the transmission itself (thus in units [%]), and log-transmission relative errors (after Eq. (8)) are illustrated. The main characteristics of these errors, in particular their overall height dependence, were already discussed in the previous subsection 4.1.2 by way of the CO2 retrieval example, which is in Figure 9 visualized as part of the middle row panels showing the results for CO2 plus its isotopes. Figure 9 now enables to inspect the transmission retrieval performance for all species, based on the diversity of the six FASCODE atmospheres, over the full height do-main of interest. It is seen that the absolute log-transmission errors (left column) are generally < 1% from 10 km upwards, with varying degree of error increase below this height, depending on the strength of target species absorption increase as well as on the transmission contrast of ab-sorption vs. reference channel. The errors increase moderately down to 5 km, except for the H2O isotopes (upper left panel) and for O3 (lower left panel) below 8 km, which dive into unfavorable SNR conditions at these low heights. The log-transmission relative errors (right column) are generally < 1% from 10 km upwards as well, with moderate increase downwards and again H2O isotopes (especially H2

18O) and O3 degrading below 8 km. However, here also the influence of the characteristic decrease of CH4, N2O, and CO concentrations over the lower stratosphere is well visible (lower right panel; see also Figure 3), leading to errors of up to about 3% at 30 km height, further increas-ing beyond. This reflects the marked decrease of the magnitude of the denominator in Eq. (8) with height, which for the other species such as CO2 and O3 occurs higher up beyond 35 km. Also the H2O isotope channel sensitivity is limited as expected to < 12 km (cf. Figure 4). Since the log-transmission relative errors are the starting point for the species retrieval error estimation (see Figure 8 and Eq. (9)), we can expect to find the relative magnitudes of these errors for the different species directly reflected in the relative magnitudes of the respective species re-trieval errors inspected in the next section. Overall, the high transmission retrieval accuracies of < 1-2% over most of the height domain under all FASCODE atmospheric conditions are encouraging that the ACCURATE LIO observational requirements can be met.



Figure 9. Differential log-transmission errors (left column; units [%] = cdB2%⋅[dB]) and differential log-transmission relative errors (right column; units [%] = 100⋅[dB]/[dB]) for all ten ACCURATE target species, grouped into water vapor (top row), CO2 (middle row), and other GHGs (bottom row), respectively. The profiles shown are the mean errors from the six FASCODE atmospheres (Figure 3), the “range bars” every 3 km show the spread from the minimum to the maximum value obtained from the six atmospheres at every such height level. The vertical dashed lines mark approximate threshold accuracy requirements (to be fulfilled to meet the species retrieval requirements), whilst the horizontal dotted/dashed lines indicate vertical domain target/threshold requirements, respectively (cf. section 2.1). The LIO channel set used was composed of the 21 baseline channels summarized in Table 5.



4.3 Trace Species Profiles Retrieval Performance As discussed in section 4.1, the trace species profiles retrieval performance estimation starts from differential log-transmission relative error (Figure 9, right column), from which via ab-sorptive Abel transform (Eq. (9)), and via accounting for cross section uncertainties (Eq. (10)), species profile errors are derived (Eqs. (10) to (12)).

The cross section uncertainties depend on temperature and pressure accuracy of the LRO data, and indirectly also on the humidity accuracy, which co-determines temperature and pressure accuracy below about 12 km and which is also important to align small differences of LIO and LRO signal travel paths that can occur below about 12 km (cf. section 3.1.1). Figure 10 shows, as a pre-requisite to LIO performance, the pressure (top), temperature (mid-dle), and humidity (bottom) retrieval performance from LRO, in the context of the related observational requirements, where those on pressure are derived approximate requirements consistent with the ones for temperature and humidity (section 2.1, Table 1). As seen in Figure 10, temperature and pressure are available to < 0.2 to 0.4% accuracy over the UTLS so that the cross sections can be modeled within the accuracy adopted in Eq. (10).

Figure 11 shows the species profile retrieval errors for all ACCURATE target species, which have been computed using the ALPS system. Both individual profile errors (after Eq. (10)) and monthly-mean profile errors (after Eq. (11)) are illustrated. For H2O (top row), in addition Eq. (12) was invoked to compute the (four-channel-combined) profiles shown. Figure 11 en-ables to inspect the species retrieval performance for all species, based on the diversity of the six FASCODE atmospheres, over the full height domain of interest.

In terms of individual species profiles accuracy (left column), we find that all target species (except the H2O isotopes), are generally retrieved within the UTLS outside clouds (recall we used clear-air assumptions) to an accuracy of < 1-5% at the required 1-2 km vertical resolu-tion, that is within target requirements. H2O isotope species are limited as expected (cf. the associated transmission errors, Figure 9) to within 5–12 km height and O3 degrades below 8 km. CH4, N2O, and CO reach target requirements up to about 30 km, despite their strong con-centration decrease, and threshold requirements are exceeded only beyond the vertical domain upper boundary threshold requirement of 30 km.

Regarding the monthly-mean species profiles (right column), these are found generally accu-rate to < 0.25–0.5%, with the same exceptions as for the individual profiles (H2O isotopes, O3 < 8 km, CH4, N2O, CO in lower stratosphere), since the monthly-mean errors are evidently just a scaled version of the individual ones (Eq. (11)). Furthermore, we can indirectly estimate from these results, that UTLS GHG columns will generally be accurate to < 0.25% as errors at individual height levels in the profiles will tend to cancel in the vertical integration.

Together the performance estimates indicate that ACCURATE, when fulfilling the system requirements laid out for it (section 2.2, and link budget, Table 6), can deliver its atmospheric profiles well within observational requirements, in most cases within target requirements, which are set to outperform any existing instruments that target the same parameters. These encouraging results thus underline the potential of the ACCURATE technique to provide benchmark measurements of unprecedented quality for future monitoring of climate, GHGs, and chemistry variability and change.



Figure 10. LRO retrieval performance estimates obtained with the EGOPS software from a statistical ensemble analysis. Pressure (upper row), temperature (middle row), and specific humidity (lower row) results are shown. The left panels illustrate the diversity of atmospheric conditions covered by the profiles in the ensemble, the middle panels the absolute retrieval error, and the right panels the relative retrieval error, respectively. The errors are shown in terms of statistical analysis results. In particular, standard deviation (heavy blue), mean bias (heavy green), and bias uncertainty (two times the standard deviation of the bias, light green) are shown. The standard deviations are depicted as ± envelopes around the mean bias profile. The dotted/dashed lines over the vertical mark target/threshold accuracy requirements, whilst the horizontal dotted/dashed ones indicate height domain target/threshold re-quirements, respectively (cf. section 2.1). The results were obtained using differential transmission-based retrieval including all five ACCURATE LRO channels (cf. Figure 1). This is why the retrieval performance is further improved (in particular for humidity > 10 km) compared to previous ACE+ LRO results (e.g., ESA, 2004a), where three X/K band channels were used for the retrieval.



Figure 11. Retrieval performance estimates for all ten ACCURATE target species, grouped into water vapor (top row), CO2 (middle row), and other GHGs (bottom row), respectively, where both individual profile error estimates (left column) and monthly-mean profile error estimates (right column) are de-picted. The profiles shown are the mean errors from the six FASCODE atmospheres (Figure 3), the “range bars” every 3 km show the spread from the minimum to the maximum value obtained from the six atmospheres at every such height level. The vertical dotted/dashed lines mark target/threshold ac-curacy requirements, whilst the horizontal dotted/dashed ones indicate vertical domain target/threshold requirements, respectively (cf. section 2.1). The LIO channel set used was composed of the 21 base-line channels summarized in Table 5.



4.4 Wind Profiles Retrieval Performance According to section 4.1, and as illustrated in Figure 6, the l.o.s. wind velocity is retrieved via exploiting transmission (double) differences between the two ACCURATE wind channels, wind(1) and wind(2), respectively. Related to this, the ALPS wind retrieval performance es-timation is based on the “wind retrieval equation” (Eq. (13)), finally leading to the l.o.s. wind profile retrieval error (Eq. (25)).

For assessing wind retrieval performance using ALPS, first four simple synthetic wind profile models have been designed, which are illustrated in Figure 12. These four models cover dif-ferent characteristic height dependences, from simple constant to strongly varying, and thus enable to check the dependence of errors on the prevailing wind conditions. This dependence should in general be small for absolute error (in [m/s]), since wind-induced Doppler shift is directly proportional to absolute wind speed so that errors in retrieved Doppler shift (Eq. (13)) will lead to very similar wind errors independent of the strength of the wind.

Figure 13 employs the four wind models of Figure 12 (one panel per model) in order to in-spect the log-transmission differences between the wind(1) and wind(2) channels for the di-versity of the six FASCODE atmospheres for both the modeled wind profiles (heavy lines) and the case of zero-wind (light lines). The differences essentially visualize the terms ΔΔTrw1w2 and ΔTrw1w2,0,Mod of Eq. (13). They were computed based on the zero-wind trans-missions modeled with the RFM/HITRAN/FASCODEatm system (zero-wind case), adding the transmission difference due to the wind-induced Doppler shift (four wind model cases). The latter were computed by multiplying the Doppler shift with the transmission derivatives at the wind channels (such as in the exponent of Eq. (15)).

The results show that there is a small zero-wind difference < 0.1 dB, since the selected CO2 line is not ideally symmetric (cf. ACCURAID, 2007), and that the typical wind signals are at the order of a few 0.1 dB in transmission for order of 10 m/s wind speeds. The panels display-ing the differences for the constant and sinusoidal wind cases may be directly compared with the transmission differences shown in Figure 8 of ACCURAID (2007), which were computed using the EGOPS software in a realistic 3D mode. It is found that the simplified modeling results within this initial performance estimation are similar to the EGOPS 3D results, with the largest discrepancy occurring for the strongly height-varying sinusoidal wind, where the 3D modeling through the spherically symmetric wind field smoothes over the transmission differences leading to smaller amplitudes. Nevertheless, the ALPS approach is confirmed as a good approximation.

Figure 14 finally illustrates the l.o.s. wind profile retrieval error estimates for the four wind model profiles. The retrieval error is generally found to be < 2 m/s (target requirement) be-tween 15 and 35 km (height domain threshold requirements) and close to 2 m/s between 10 and 40 km (height domain target requirements), respectively. Below 10 km, the retrieval per-formance strongly decreases, since the delta-differential log-transmission total error (Eq. (19)) strongly increases downwards, in line with the marked SNR decrease (cf. Table).

In summary, the additional capability of wind profiling over 10 to 40 km with about 2 m/s accuracy at 1-2 km resolution further re-enforces the unique utility of the ACCURATE LRO+LIO technique for atmosphere and climate monitoring and research.



Figure 12. Illustration of the simple wind profile modeling performed for the initial assessment, in-cluding a constant +30 m/s wind profile (solid), a constant –30 m/s wind profile (dashed-dotted), a linearly varying wind profile (dashed), and a sinusoidally varying wind profile (dotted), respectively.

Figure 13. log-Transmission differences between the wind(1) and the wind(2) baseline channels (cf. Table 5 and Figure 6), for the four simple wind profile cases illustrated in Figure 12 (one case per panel, as noted in the upper-left corner). For reference, the differences in case of no wind are shown as well in each panel (light lines within 0 to < 0.1 dB). In order to illustrate the possible variation range, the difference is depicted for all six FASCODE atmospheres (Figure 3) in each case (red, tropical “tro atm”; blue, mid-latitude summer “mls atm”; green, mid-latitude winter “mlw atm”; yellow, sub-arctic summer “sas atm”; violet, sub-arctic winter “saw atm”; black, U.S. standard atmos. “std atm”).



Figure 14. Performance estimates for the line-of-sight wind retrieval, for the four simple wind profile cases illustrated in Figure 12 (one case per panel, as noted in the upper-left corner). The variation of the performance based on the different six FASCODE atmospheres (Figure 3) is shown in each case (red, tropical “tro atm”; blue, mid-latitude summer “mls atm”; green, mid-latitude winter “mlw atm”; yellow, sub-arctic summer “sas atm”; violet, sub-arctic winter “saw atm”; black, U.S. standard atmos. “std atm”). The vertical dotted/dashed lines mark target/threshold accuracy requirements, whilst the horizontal dotted/dashed ones indicate height domain target/threshold requirements, respectively (cf. section 2.1). The LIO channels used were the wind(1) and wind(2) baseline channels, together with their related reference channel (Table 5; Figure 6).



5 Specifications for LIO System Breadboarding

The background for the specifications for LIO Tx and Rx system demonstration breadboard-ing is provided by the LIO observational and system requirements (section 2) as well as the LIO concept and characteristics (section 3). Compared to the preliminary requirements and characteristics described in the original proposal (ACCURATE, 2005), considerable refine-ment and consolidation has been achieved since then, which is accounted for in sections 2 and 3. The initial end-to-end scientific performance analysis reported in section 4 has importantly contributed to this progress. For example, l.o.s. wind (Vlos) was not yet included as an observ-able in ACCURATE (2005), since at that time the achievable accuracy was still too uncertain but has been consolidated meanwhile. The specifications proposed below aim at the development of an LIO Tx-Rx breadboard sys-tem at a favorable cost-benefit ratio, by calling for a simple reduced system (3 tunable Tx laser channels and one Rx de-multiplexing unit only), which still is representative of the full system and enables a comprehensive assessment and demonstration that all essential LIO re-quirements may be met by suitable technology. The specifications for the LIO Tx system demo breadboarding are summarized in section 5.1 and for the LIO Rx system demo bread-boarding in section 5.2, respectively. 5.1 LIO Tx System Demo Breadboard Specifications Selection of representative target species

The demo breadboard approach is to demonstrate the full LIO Tx and Rx system by imple-menting a breadboard for CO2, H2O, and l.o.s. wind Vlos near 2.1 μm as a representative sys-tem which only needs included three laser channels. One of these can always serve as refer-ence channel whilst the other two can be tuned to target absorption lines or the wind lines, respectively. Probing CO2 (including its isotopes C18OO, and optionally 13CO2), H2O, and Vlos with such a simple approach is possible since the ACCURATE channel selection, summarized in detail in section 3 above, placed all required demo channels into a narrow 10 cm-1 wavenumber range spanning 4766.5–4776.5 cm-1 (see Figure 7 in section 3; located within 2.09 and 2.1 μm, in terms of wavelength). Now that the mode-hop free tuning range of the near-2.1 μm laser DFB diodes baselined for ACCURATE (details in section 3.2) is > 10 cm-1, three such laser diodes manufactured for near 4770 cm-1 can basically do the job for all differential transmission (ab-sorption-minus-reference) pairs of the demo breadboard as well as for Vlos measurements. Selecting the species CO2 (plus isotopes) and H2O together with Vlos as ACCURATE demo observables is valuable, useful and representative in several scientific-technical aspects, for reasons including the following:

CO2, the major anthropogenic greenhouse gas, is both a climate-relevant species very interest-ing to measure and a well representative species in terms of the characteristics of the typical



two-channel LIO cross-link required per species (absorption and reference channel). In addi-tion, CO2 is simple to handle as a test gas in any laboratory experiments as well as easy to use in outdoors experiments, e.g., mountain-to-mountain or mountain-to-airplane experiments. For the latter preliminary plans exist together with partners from Inst. f. Physik der At-mosphäre, DLR Oberpfaffenhofen, Germany (U. Schumann and G. Ehret, pers. communica-tions, 2006). Furthermore, it is the CO2 line, which is at the same time used for the Vlos measurements (in this case placing two channels symmetrically about line center at the wings of the line; see section 3, Figure 6), allowing to demonstrate the novel Vlos measurement capability as well. Also the alternative use of the C18OO line for Vlos measurements can be studied thanks to the tunability of the DFB diodes. Finally, measuring H2O, the most important atmospheric trace gas in the Earth’s energy and water cycles and the most important (natural) greenhouse gas, allows to complementarily demonstrate the LIO methodology also for a second key species independent of CO2. Laser channel/laser diode wavelength specifications

Three representative laser channels, tunable in the 4766.5–4776.5 cm-1 wavenumber range for CO2 (plus C18OO and 13CO2), H2O, and Vlos measurements, shall be provided:

- laser channel/laser diode #1, for use as “on-wavelength” λAbs for CO2, H2O, 13CO2, and Vlos measurements and as “off-wavelength” λRef for C18OO measurements: manufactured for nominal center 4773.0 cm-1 (2095.1 nm), tunable over at least ± 3 cm-1 (± 1.32 nm) for setting it to any required λAbs or λRef wavelength (during a meas-urement event) or for tuning it over the range for improvement of spectroscopy within 4770–4776 cm-1 (in laboratory work). For the precise frequencies of the λAbs, λRef tar-get lines see section 3.1.2 below.

- laser channel/laser diode #2, for use as “off-wavelength” λRef for CO2, H2O, 13CO2, and Vlos measurements and as “on-wavelength” λAbs for C18OO measurements: manufactured for nominal center 4769.0 cm-1 (2096.9 nm), tunable over at least ± 3 cm-1 (± 1.32 nm) for setting it to any required λRef or λAbs wavelength (during a meas-urement event) or for tuning it over the range for improvement of spectroscopy within 4766.5–4772 cm-1 (in laboratory work).

- laser channel/laser diode #3, identical to laser channel/laser diode #2. Enables dem-onstration of Vlos measurements, which is based on simultaneous use of two “on-wavelengths” λAbs at the wings of the 4771.62 cm-1 CO2 absorption line (see section 3) together with an “off-wavelength” λRef. Alternatively, it enables Vlos measurements at the C18OO line. For the trace species measurements it provides one channel redun-dancy (should one of the other diodes be lost during a demo experiment).

For a detailed description of the ACCURATE LIO channel selection, including illustration of the 4766.5–4776.5 cm-1 wavenumber range, see section 3 above.



LIO Tx performance specifications

For each of the three laser emission units to be built around the three laser diodes, the LIO Tx system requirements summarized in section 2.2, Table 2, on

- laser pulse properties and emitted pulse power, - laser line FWHM and laser mode-hop free tuning range, - laser frequency knowledge, stability rms, and frequency drift, - laser intensity stability rms and intensity drift, - laser beam divergence and stable beam intensity distribution,

shall be fulfilled and demonstrated. Regarding laser pulse properties, it is desirable to also be able to select pulse lengths different from 1.5 ms, at least within 1 ms to 3 ms (would allow testing different pulse lengths/integration times of the Tx-Rx system). Regarding the nominal beam divergence, it shall be steerable in the breadboard system, de-sired is steerability within the range 4 mrad – 400 mrad (for flexible directivity tuning and flexible cross-link intensity tuning in demonstration experiments, e.g., mountain-to-airplane experiment). Regarding the optical-axis co-alignment of the beams of the two (or three) laser emission units, to be mounted firmly on a single common plate, co-alignment to < 0.03 mrad shall be demonstrated; special knowledge on residual mis-alignment is not required for the breadboard system. Further LIO Tx technical specifications

The time-tagging accuracy (and its drift) shall fulfil the requirements according to section 2.2, Table 4. The lock to any desired target frequency within the 4766.5–4776.5 cm-1 demo breadboard range shall be possible in three different options, in order to demonstrate the performance of each of these:

1. wavelength meter-assisted femtosecond laser-stabilized high-performance lock (frequency lock to required accuracy δf/f0 < 1 x 10-8 (3σ); freq. knowledge requirement of Table 2) 2. wavelength meter lock (frequency lock to expected accuracy δf/f0 < 1 x 10-7) 3. thermal/current tuning (no external freq. stabilization, expected accuracy δf/f0 < 2 x 10-7). The Tx breadboard system shall be implemented in a technically elegant manner in the sense that its volume, mass, and power consumption figures are optimally small as reasonably achievable by best available lab components and best practice lab engineering. In particular it shall be compactly portable, such as for use in outdoors demonstration experiments. The breadboard technical components and technologies shall be selected with the clear view in mind that the subsequent goal is implementation of an LIO Tx system as a satellite instru-ment, i.e., selected key components and technologies shall be in principle compatible with



operating (after space qualification, volume/mass/power optimization, etc.) in a Low Earth Orbit satellite platform environment. They shall also be in principle compatible with using them (potentially after re-tuning, technology wavelength range extensions, etc.) beyond the 4766.5–4776.5 cm-1 breadboard wave number range anywhere within the ACCURATE range 4000–5000 cm-1. The technical components and technologies shall also be selected with the clear view in mind that the satellite instrument is required to operate over a lifetime of at least 3 years (section 2.1, Table 1), in a typical mode as follows (cf. section 3.2 and ACCURATE, 2005): Provide the LIO Tx laser signals for several hundred occultation events (= measurement sequences) per day, each occultation event consisting of < 15 sec warm-up time and ~30 sec measure-ment time at required performance; in the several minutes between such events the instrument can be switched off (power-off, hibernation time). The breadboard shall allow repeated power-on/power-off and demonstrate warm-up times of < 15 sec. The total power-on time per event for real occultation events (warming-up plus measurement time) is < 45 sec. Preliminary offer by industry to implement such a LIO Tx breadboard

Specifications similar to the above (complemented by meanwhile obsolete specifications for a separate option using CO2 lines in the 1500–1600 nm range), have been forwarded, after a company screening for industry expertise, to Toptica Photonics AG (LIO-IBS, 2005a). The company prepared a report proposing an implementation and including a cost estimation, al-lowing several options (Toptica, 2005). Since that report significant further refinement of the Tx demo breadboard concept has taken place so that before the start of implementing the breadboard a fresh industry offer based on the specifications in this section is needed to be prepared. For example, the inclusion of femtosecond-laser stabilization for frequency lock, and the related Vlos measurement capability, is an essential more recent development. Defining a suitable implementation option based on Toptica (2005) and the results since then, in line with the specifications above, shows that no critical areas exist regarding the feasibility and that all technology is available for the Tx breadboarding to start immediately. The cost for a suitable breadboard implementation according to specifications, which can be estimated based on Toptica (2005) cost information and more recent knowledge, is expected to be ~400 kEUR. The estimated duration (by Toptica) of breadboard development, including testing, was seven to eight months.



5.2 LIO Rx System Demo Breadboard Specifications Received laser signal specifications

Compliant with the LIO Tx system specifications above, several representative LIO laser sig-nals, for CO2 (including C18OO and optionally 13CO2), H2O, and Vlos measurements, will be available for reception:

- laser signal #1, “on-wavelength” λAbs, C18OO absorption line, 11 ,νλ : nominal 2097.737 nm (4767.041 cm-1) (precise transition freq. of the C18OO absorption line/HITRAN04: 4767.041369 cm-1)

- laser signal #2, “off-wavelength” λRef, reference channel, 22 ,νλ : nominal 2096.3 nm (4770.2 cm-1), reference channel outside absorption lines

- laser signal #3l, “on-wavelength” λAbs, CO2-wind(1) absorption line, lh 33 ,νλ : nominal 2095.7254 nm (4771.617 cm-1) (nominal frequency on the CO2 absorption line/low-frequency wing:

)/1( 333 νννν Dl Δ−= ≈ 4771.6175 cm-1, i.e., nominal frequency offset of wind(1) line from CO2 line center by near a Doppler half-width of the line: 3/νν DΔ ≈ 0.83 x 10-6; cf. section 3.1.2, Figure 6)

- laser signal #3, “on-wavelength” λAbs, CO2 absorption line, 33 ,νλ : nominal 2095.7237 nm (4771.621 cm-1) (precise transition freq. of the CO2 absorption line/HITRAN04: 4771.621441 cm-1)

- laser signal #3h, “on-wavelength” λAbs, CO2-wind(2) absorption line, hl 33 ,νλ : nominal 2095.7219 nm (4771.625 cm-1) (nominal frequency on the CO2 absorption line/high-frequency wing:

)/1( 333 νννν Dh Δ+= ≈ 4771.6254 cm-1, i.e., nominal frequency offset of wind(2) line from CO2 line center by near a Doppler half-width of the line: 3/νν DΔ ≈ 0.83 x 10-6; cf. section 3.1.2, Figure 6)

- laser signal #4, “on-wavelength” λAbs, H2O absorption line, 44 ,νλ : nominal 2093.889 nm (4775.803 cm-1) (precise transition freq. of the H2O absorption line/HITRAN04: 4775.802970 cm-1)

These six signals are the main demo breadboard signals and require four Rx channels (the CO2, CO2-wind(1), CO2-wind(2) signals share one Rx channel), i.e., the breadboard shall con-tain one representative four-signal filter/de-multiplexing unit of which the full ACCURATE LIO Rx system is baselined to have seven two- to four-signal units (section 3, subsection 3.2.3). At any given 2-ms integration time slot there will always be a maximum of four sig-nals (cf. Rx requirements in section 2.2), the different CO2 signals will be transmitted in tem-poral sequence in subsequent time slots. The alternative Vlos test case of Vlos measurements at the C18OO line is covered by this layout as well, since the wind(1) and wind(2) signals tuned to C18OO will just share the Rx channel of C18OO instead of CO2 in this case) Optionally, the Rx demo breadboard may be implemented in a manner so that also reception of one or more of the following three 13CO2 absorption signals is possible:



- laser signal #5a, “on-wavelength” λAbs, 13CO2 absorption line, aa 55 ,νλ : 13CO2 line at ~2096.1 nm (~4770.8 cm-1; HITRAN04: 4770.812522 cm-1)

- laser signal #5b, “on-wavelength” λAbs, 13CO2 absorption line, bb 55 ,νλ : 13CO2 line at ~2095.5 nm (~4772.2 cm-1; HITRAN04: 4772.175508 cm-1)

- laser signal #5c, “on-wavelength” λAbs, 13CO2 absorption line, cc 55 ,νλ : 13CO2 line at ~2094.3 nm (~4774.85 cm-1; HITRAN04: 4774.858221 cm-1)

Whether to allow for this option, and if so which demo 13CO2 signal to select, will depend on the technical layout of the filter/de-multiplexing unit. If the 13CO2 flexibility can be accom-modated without dedicated extra efforts it shall be implemented. All received laser signals will have properties (pulse duration, FWHM, frequency and inten-sity stabilities) according to the LIO Tx system requirements summarized in section 2.2. LIO Rx performance specifications

For the reception and detection of the laser signals specified above, the LIO Rx system re-quirements summarized in section 2.2, Table 3, on

- front optics and reception field-of-view (FOV), - observational bandwidth and bandpass-filter sideband attenuation - four-signal filter/de-multiplexing unit, - total optical loss from telescope to detector, - time scheme for shot reception and after-shot background reception, - detector noise-equivalent-power (NEP), response time, and dynamic range,

shall be fulfilled and demonstrated. Regarding the front optics diameter (requirement 36 cm according to Table 3) it can, if con-venient, also be reduced for the breadboard down to a minimum of 12 cm. Furthermore, if the optical loss spec of < 20% is found difficult to meet, the reasons shall be explained and an alternative minimal-optical-loss solution shall be baselined fulfilling at least < 50%. Regarding the basic signal integration time scheme (baseline 2 ms for shot reception, 0.5 ms pause, 2 ms next reception time slot, 0.5 ms pause, etc.; after-shot background reception for any signal in a time slot within 10 ms from shot reception), it is desirable to also select inte-gration times different from 2 ms, at least within 1 ms to 4 ms. For more information on the baseline integration time scheme see section 3.2.3. Regarding the filters for observational bandwidth (spec ΔfB/f0 = 6 x 10-5, i.e., ~0.12 nm for the 2.1 μm laser signals), these serve to reject solar backscattered radiation but have to be wide enough to accomodate the kinematic Doppler shifts due to Rx satellite motion relative to the atmosphere (tangent point) for both setting and rising occultation events (ΔfDkin/f0 ~ ± 2.25 x 10-5 for LEO-LEO orbital geometries; the Tx motion relative to the atmosphere is compen-sated for by adequate channel frequency offset, see section 3.1.3). The filters shall be centered at the nominal signal wavelengths (zero ΔfDkin) and the design selected with the view in mind that the subsequent goal is an Rx system with up to seven four-filter/de-multiplex units for the



up to 24 laser signals to be received within 2-2.5 μm (see Tx requirements in section 2.2; see also Table 5 and Figure 2 in section 3.1.2). Regarding the reception FOV of the front optics (spec ~1.2 mrad), it will be useful if this is somewhat flexible in the breadboard system, desired is steerability from 1 mrad up to 100 mrad (for flexible directivity tuning in demonstration experiments, e.g., mountain-to-airplane experiment). Priority in the FOV design is optimized feed of the de-multiplexing and detec-tion units, however. Further LIO Rx technical specifications

The time-tagging accuracy (and its drift) shall fulfil the requirements according to section 2.2, Table 4. The received pulse power for each laser signal entering the front optics can be expected to never exceed 5 nW (5 x 10-9 W), so the high-sensitivity detectors (NEP < 5 x 10-13 W / 2 ms) may be actively shielded/protected to shut against any power exceeding 5 nW (cf. NEP and dynamic range requirements in section 2.2, Table 3). Regarding the after-shot background signals, the Rx system is foreseen to never view the sun directly; the background is thus scat-tered solar radiation only, with power far below 1 nW at observation bandwidths < 1 nm. The output data of the Rx system shall be time-tagged digital time series at 50 Hz sampling rate of the received shot signals and the received after-shot background signals, respectively. The output data shall be stored in data files in some standard, easily readable data format (e.g., netCDF). The numerical precision of the output data shall be such that the full intensity and frequency measurement accuracy available from the measurement system is preserved. The breadboard system shall be implemented in a technically elegant manner in the sense that its volume, mass, and power consumption figures are optimally small as reasonably achiev-able by best available lab components and best practice lab engineering. In particular it shall be compactly portable, such as for use in outdoors demonstration experiments. The breadboard technical components and technologies shall be selected with the clear view in mind that the subsequent goal is implementation of an LIO Rx system as a satellite instru-ment, i.e., selected key components and technologies shall be in principle compatible with operating (after space qualification, volume/mass/power optimization, etc.) in a Low Earth Orbit satellite platform environment. The technical components and technologies shall also be selected with the clear view in mind that the satellite instrument is required to operate over a lifetime of at least 3 years (section 2.1, Table 1), in a typical mode as follows (cf. section 3.2 and ACCURATE, 2005): Receive the LIO laser signals for one to two hundred occultation events (= measurement sequences) per day, each occultation event consisting of ~30 sec measurement time at required perform-ance. In the several minutes between such events the Rx system can be switched off (power-off, hibernation time). The breadboard shall allow repeated power-on/power-off and demon-strate warm-up times of the Rx system of < 15 sec. The total power-on time per event for real occultation events (warming-up plus measurement time) is < 45 sec.



Preliminary offer by industry to implement such a LIO Rx breadboard

Specifications similar to the above (complemented by meanwhile obsolete specifications for a separate option using CO2 lines in the 1500–1600 nm range), have been forwarded, after a company screening for (Austrian) industry expertise, to Austrian Aerospace (LIO-IBS, 2005b). The company prepared, together with partners, a technical response proposing an implementation and including a preliminary cost estimation. Since that time (end 2005) sig-nificant further refinement of the Rx demo breadboard concept has taken place so that before the start of implementing the breadboard a fresh industry offer based on the specifications in this section is needed to be prepared. The company information of end 2005 and the results since then, in line with the specifica-tions above, show that there are no critical obstacles regarding the feasibility and that the technology is basically available for the Rx breadboarding to start immediately. The optical filtering/de-multiplexing unit for the four Rx channels, for separating the total received signal into the up to three individual laser signals received simultaneously, is considered the most challenging part. The cost for a suitable breadboard implementation according to specifications (given without telescope cost), which can be estimated based on Austrian Aerospace cost information of end 2005 and more recent knowledge, is expected to be ~400 kEUR, including optical Rx tests and Tx-Rx characterization based on the complete LIO Tx and Rx system. The estimated du-ration of a respective breadboard development and testing was eight to nine months.



6 Summary, Conclusions, and Outlook

This report has described an initial assessment of the novel LEO-LEO infrared laser occulta-tion (LIO) approach, which is combined with and used in synergy with LEO-LEO radio oc-cultation (LRO), as proposed in the ACCURATE (2005) climate and chemistry satellite mis-sion concept. The report, after introducing the context and scientific utility of ACCURATE, first summa-rized the LIO observational and system requirements. This was followed by a description of the concepts and characteristics of the ACCURATE LIO payload. A scientific performance analysis complemented this more payload-oriented assessment in form of an initial perform-ance estimation determining LIO retrieval errors for trace species and wind profiles based on a reasonably realistic modeling of simulated transmissions of all target species and of their expected retrieval accuracy under different atmospheric conditions from tropical to sub-arctic winter. Based on the results of these assessments, specifications for a representative LIO dem-onstration breadboard system were provided. Regarding the payload, no critical areas were detected in the assessment which would pose a feasibility issue, i.e., a significant difficulty to fulfill the LIO system requirements. The fairly preliminary assessments of ACCURATE (2005) were thus confirmed in a considerably more consolidated manner: all technical sub-systems and components are basically available, both at LIO Tx and LIO Rx side, to start implementation of the payload, for example, in form of a demo breadboard system. The study derived and suggested detailed specifications for such a demo breadboarding, which it found feasible at an attractive cost-benefit ratio when using a small region near 2.1 μm to probe CO2 (incl. isotope species) and H2O lines, and wind sensitivity. Demo bread-boarding could start immediately as all required technical components and scientific-technical understanding are available by end of this assessment study. The scientific performance analysis found that all target species profiles, including isotope species, are generally retrieved within the UTLS outside clouds to an accuracy of < 1-5% at 1-2 km vertical resolution, and line-of-sight wind profiles to < 2 m/s (individual profiles accu-racy). Regarding monthly-mean species profiles, these are found generally accurate to < 0.25 to 0.5%, and UTLS GHG columns to < 0.25%. These accuracy estimates indicate that ACCURATE, when fulfilling the system requirements laid out for it, can deliver its atmos-pheric profiles well within observational requirements, in almost all cases/height ranges within target requirements. In the broader context of Earth observation from space, these encouraging results underline the potential of the ACCURATE technique to provide benchmark measurements of unprece-dented quality for future monitoring of climate, GHGs, and chemistry variability and change in the global atmosphere.



In more practical terms, these encouraging results suggest to undertake the following next steps: 1. Advance this initial assessment by a complete and detailed LRO+LIO scientific per-formance analysis for all parameters, thermodynamic, wind, greenhouse gases and isotopes; as well as for the complementary aerosol, cloud, and turbulence information. 2. Produce a breadboard of the LIO transmitter-receiver system, for CO2, H2O, and Wind near 2.1 μm as representative system, as recommended in this study, and 3. Start implementation of ACCURATE as space mission, e.g., first as an “ACCUDEMO” proof-of-concept mission, then followed by a full-fledged four-to-six satellite LEO constellation. Acknowledgments. The authors gratefully acknowledge all colleagues and their institutions who, in various ways, have supported the preparation of the ACCURATE mission and of this ACCURAID report. M. Gorbunov, V. Sofieva, F. Dalaudier, P. Bernath, R. Hughes, R. Kursinski, and A. Dudhia are particularly acknowledged for their advice. J. Fritzer, J. Ramsauer, M. Schwaerz, F. Ladstaedter, and H. Krenn (Univ. of Graz) are particularly acknowledged for various support issues in course of this initial LIO performance assessment. Furthermore, the following companies, and colleagues, are particularly acknowledged for advice on technical aspects during this ACCURAID study: TOPTICA Photonics AG (www.toptica.com, primary advisor A. Deninger, advice on SWIR laser technology and LIO Tx system), Laser Components GmbH (www.lasercomponents.com, primary advisor J. Kunsch, advice on SWIR detector technology and LIO Rx system), and Swedish Space Corporation (www.ssc.se, primary advisor S. Veldman, advice on preliminary ACCURATE system analysis). S. Schweitzer was funded for this work by the ACCURAID Project of the FFG-ALR.



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