Long term satellite based datasets of atmospheric ‐ ‐water vapour derived within CM SAF

Martin Stengel, Marc Schröder,Nathalie Courcoux, Karsten Fennig, Rainer Hollmann

Outline

• CM SAF overview

• CM SAF ATOVS datasets (processing, examples, validation)

• CM SAF SSM/I datasets (processing, examples, validation)

• Summary and future activities

Outline

• CM SAF overview

• CM SAF ATOVS datasets (processing, examples, validation)

• CM SAF SSM/I datasets (processing, examples, validation)

• Summary and future activities

4

CM SAF overview

• EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF)

5

CM SAF overview

• CM SAF’s role in climate monitoring and research

datasets

climate trendsand variability

processes

validation /improvement

observation

understanding

modelling

projection

mitigationadaptation

CM-SAF

CM SAF overview

• The aim of the Satellite Application Facility on Climate Monitoring is to generate, archive and distribute widely recognized high-quality satellite-derived products and services relevant for climate monitoring.

• CM SAF provides medium- and long-term term cloud, radiation, water vapour and temperature products derived from different instruments (Schulz et al., 2009).

• CM SAF water vapour products: ATOVS, SSM/I

• CM SAF data products can be distinguished in operational monitoring products and retrospectively produced data sets.

CM SAF overview

• Operational monitoring products are disseminated with high timeliness (max 8 weeks after the obs.) to support operational climate monitoring applications of national meteorological and hydrological services.

• Because of the timeliness requirement it is not possible to monitor inter-annual variability and trends. Bias error due to orbit shift and decay, as well as inter-satellite biases are not corrected for the operational products.

• For the retrospective produced data sets errors due orbit changes and inter-satellite biases are minimized.

• In general, CM SAF humidity products have to meet the service specifications that are defined for each products. The service specifications compliance is assessed on a regular basis, e.g. by validation against radiosonde observations of the GCOS Upper Air Network (GUAN).

Outline

• CM SAF overview

• CM SAF ATOVS datasets (processing, examples, validation)

• CM SAF SSM/I datasets (processing, examples, validation)

• Summary and future activities

ATOVS processing

• ATOVS instruments: HIRS/3, AMSU-A/B, MHS, HIRS/4• CM SAF ATOVS products:

• total columnar water vapour• layered columnar water vapour

(5 tropospheric layers)• Time coverage: 01/01/2004 - today• Spatial resolution: (90 km)²• Products are available as global daily and monthly means.

• Processing system: The ATOVS level l1d data generated by the ATOVS and AVHRR Processing Package (AAPP) are used as input for the IAPP (Lee at al., 2000).

• Output of the Deutscher Wetterdienst Global-Modell (GME) are used as first guess input to the retrieval.

• A Kriging routine is used to determine daily and monthly means on a global grid from the swath based retrievals, as well as uncertainties estimates. (Lindau and Schröder, 2010)

• Advantage: land and sea, day and night, clear-sky and cloudy regions

ATOVS processing

• Layer definitions:

• Satellites and AAPP/IAPP versions used:

Table: Summary of the different versions of the CM SAF ATOVS products with the correspondingdates, software and hardware updates, as well as the updates in the satellite observations used.

Product version

Date Computer AAPP version

IAPP version

Satellites used

300 01.01.04 - 29.02.08 DWD COS1 5.3 2.1 NOAA-15,-16,-18 300 01.03.08 - 31.12.08 DWD COS1 5.3 2.1 NOAA-15,-18310 01.01.09 - 31.05.09 ECMWF HPCF 5.3 2.1 NOAA-15,-18320 01.06.09 - 30.11.09 ECMWF C1A 6.10 3.0b NOAA-19, MetOp320 01.12.09 - 31.01.10 ECMWF C1A 6.10 3.0b NOAA-16, -19320 01.02.10 - now ECMWF C1A 6.10 3.0b NOAA-16, -19, MetOp

Layer 1 2 3 4 5 TCWVPressure [hPa] 300-200 500-300 700-500 850-700 Surface-850 Surface-100

Table: Layer definitions for ATOVS water vapour and temperature products.

ATOVS example

• Layered vertically integrated water vapour for the 5 layers. Monthly means for July 2005.

ATOVS example

• TCWV, number of observations, extra daily standard deviation

October 2004.

Ext

ra d

aily

sta

ndar

d de

viat

ion

kgm

-2 T

PW

kgm

-2

Obs

erva

tions

per

grid

ATOVS validation

• Comparison ATOVS TCWV vs. GUAN radiosondes

Fig: Time series of the bias and bias corrected RMSEof ATOVS TPW against GUAN radiosondes.

ATOVS validation

• Comparison ATOVS LCWV vs. GUAN radiosondes

Fig: Time series of the bias (left) and bias corrected RMSE (right) of ATOVS LPW 1-5 fromATOVS and GUAN radiosondes.

ATOVS validation

• Work done in the frame of a federate activity by Claudia Stubenrauch, LMD

Open symbols: July

Plain symbols: January

ocean land

TOVS-B 1987-1995 AIRS-L2 2003-2009AIRS-L2 2008/2009 ATOVS 2008/2009

(IAPP)

Outline

• CM SAF overview

• CM SAF ATOVS datasets (processing, examples, validation)

• CM SAF SSM/I datasets (processing, examples, validation)

• Summary and future activities

CM SAF SSM/I processing

• Transition of HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite data; http://www.hoaps.org/) into CM-SAF

• CM SAF SSM/I product: 20-year Thematic Climate Data Record (TCDR) of total column integrated water vapour derived from SSM/I

• Satellites used: F08, F10, F11, F13, F14, F15• Radiance homogenization, reference sensor F11

• Statistical retrieval (Schlüssel, P. and Emery W.J., 1990)• A Kriging routine is used to determine daily and monthly means on a

global grid from the swath based retrievals, as well as uncertainties estimates. (Lindau and Schröder, 2010)

• Advantages: day and night, clear-sky and cloudy regions• Disadvantage: over ocean only

CM SAF SSM/I example

• Example

Fig. EUMETSAT CM SAF SSM/I derived total column water vapour (top) and associated variability (bottom), averaged over the time series from 1987-2006.

CM SAF SSM/I evaluation

• Evaluation against Wentz (RSS) results

(Sohn and Smith, 2003)

CM SAF SSM/I evaluation

• Evaluation against Wentz (RSS) results:

CM SAF SSM/I evaluation

• Evaluation against ATOVS results

CM SAF SSM/I application

• Comparison to NWP

CM SAF SSM/I application

• Trend analysis

Fig. Trends in total column water vapour over the ice-free ocean

determined from CM SAF SSM/I derived TCWV.

Outline

• CM SAF overview

• CM SAF ATOVS datasets (processing, examples, validation)

• CM SAF SSM/I datasets (processing, examples, validation)

• Summary and future activities

Summary and Outlook

• CM SAF ATOVS:• The ATOVS humidity products exhibit high quality (comparisons against

GUAN stations). Comparison against other data sets are also promising.• Reprocessing from 1998 to now is ongoing work.

• Updated, constant retrieval system• Time period will be extended with 1998 today• Switch from GME to ERA-Interim• SNO to be used for homogenization of L1 radiances

• CM SAF SSM/I:• Provides a highly accurate dataset enabling long-term monitoring of

TCWV over ocean• Reprocessing will be done using improved SSM/I FCDR

• Improved satellite sensor calibration and intercalibration• FCDR is also used in other projects, e.g. ESA DUE GlobVapour

• Possibly 1D-Var system used in the future (retrieval error estimates)*• Extension of time period covered by including SSMIS sensors*

• Li, J., W. Wolf, W. P. Menzel, W. Zhang, H.-L. Huang, and T. H. Achtor, 2000: Global soundings of the atmosphere from ATOVS measurements: The algorithm and validation. J. Appl. Meteo., 39, 1248-1268.

• Lindau R., M. Schröder, 2010, Algorithm Theoretical Basis Document: Objective analysis (Kriging) for water vapour. CM SAF ATBD, Ref Nr. SAF/CM/DWD/ATBD/KRIGING, version 1.1, 25 June 2010.

• Schulz, J. and P. Albert, H.D. Behr. D. Caprion,, H. Deneke, S. Dewitte, B. Dürr, P. Fuchs, A. Gratzki, P. Hechler, P. et al., 2009: Operational climate monitoring from space: the EUMETSAT Satellite Application Facility on Climate Monitoring (CM-SAF), Atmos. Chem. Phys., 9, 1-23.

• Schluessel, P. and Emery W.J., 1990: Atmospheric water-vapor over oceans from SSM/I measurements, International Journal of Remote Sensing 11/5, 753-766.

• Sohn, B.J. and E.A. Smith 2003: Explaining sources of discrepancy in SSM/I water vapour algorithms. Journal of climate, 16, 3229-3255.

Thank you

www.cmsaf.eu