afosr muri: neutral atmosphere interdisciplinary research (nadir) space weather workshop, 2008 1...

AFOSR MURI: Neutral Atmosphere Interdisciplinary Research (NADIR) • Space Weather Workshop, 2008 1

Neutral Atmosphere Density Interdisciplinary Research: (NADIR)

A Multidisciplinary University Research Initiative (MURI)Sponsored by the Air Force Office of Scientific Research

The objective of NADIR is to significantly advance understanding of drag forces on satellites, including density, winds, and factors affecting the drag coefficient.

We seek a level of understanding that will enable specification and prediction at the “next level” of performance.

Actual Position

Predicted Position

Co-Principal Investigators: Jeff Forbes and Tim Fuller-RowellUniversity of Colorado at Boulder

Aug 2007 - Aug 2012 $7.2 M

http://ccar.colorado.edu/muri/


NADIR Participants

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Co-Investigators• Rashid Akmaev,• Brian Argrow,• George Born,• Geoff Crowley,• David Falconer,• Delores Knipp, USAFA• Juan Fontenla,• Tomoko Matsuo,• Dusan Odstrcil,• Joachim Raeder, • Jeff Thayer,

DoD Oversight

Kent Miller, AFOSR; Joseph Liu, AFSPC; Robert McCoy, ONR

Collaborators

• Jeffrey Anderson, NCAR• Eugene Avrett, Harvard-SAO• Christopher Bass, AFSPC• Bruce Bowman, AFSPC• Gary Bust, UTSA• Mihail Codrescu, SEC, NOAA• Doug Drob, NRL• Irene Gonzalez-Hernandez, NSO• Cheryl Huang, AFRL• Chin Lin, AFRL• Charles Lindsey, Co-RA• Frank Marcos, AFRL• Matthew McHarg, USAFA• Craig McLaughlin, U Kansas• Cliff Minter, NGA• Steve Nerem, CU• Andrew Nicholas, NRL• Jens Oberheide, U Wuppertal• Vic Pizzo, SEC, NOAA• Eric Quemaris, CNRS• Arthur Richmond, NCAR• Stan Solomon, NCAR• Thomas Woods, CU

AdministrationSarah Melssen, CU


1000 km


NADIR Methodology

• Better understand the physical processes

• Determine which of the processes create structure on a scale that is importantto satellite drag.

• Determine the driver-response relationships - internal and external.

• Improve forecasts of the drivers.• Determine the most valuable datasets required

to specify the system state and forecast the drivers


Eight Focus AreasI. Scales of Density Variability, Winds, and Drag

Prediction:

What spatial and temporal scales of drag variability are most relevant to in-track error?

II. Internal Processes and Thermosphere-Ionosphere Coupling:

CHAMP Densities

How do cooling processes regulate the response and recovery of magnetic storms?

What is the impact of T-I coupling on the neutral density structure?

What is the source of the semiannual variation and its solar cycle dependence?


Eight Focus AreasIII. Energy Partitioning at High Latitudes and Density

Implications

How is magnetospheric energy input partitioned (Joule heating, momentum transfer, etc.) and what are the implications for density and density-driver-relationships?

IV. Wave Forcing from the Lower Atmosphere

What are the meteorological influences on thermosphere density, and can a predictive capability be developed?

-- Joule Heating

-- Density

(Geoff Crowley - Numerical Experiments Using TIMEGCM Model)

4 hr delay


Eight Focus AreasV. Forecasting

Geomagnetic Activity

Objective: Use observations in the

photosphere, corona, at L1 and

numerical models of the heliosphere and magnetosphere to:

(1) Improve existing empirical and numerical models of the heliosphere and geospace; and

(2) Achieve more realistic short-term and

probabilistic long-term forecasting.

• Forecasting Solar EUV/UV Radiation

Objective: Develop EUV & UV solar flux forecastsup to a few weeks using:

• near-side solar observations and • far-side helio-seismological and L-scattering observations






Eight Focus AreasVII. Driver-Response

Relationships

What are the dominant modes of density variability, and how do they relate to the drivers?

VIII. Satellite Drag in the Transition Region





Utilize Direct Simulation Monte Carlo (DSMC) methods to simulate andunderstand drag coefficient changesIn the re-entry regime (ca. 150-90 km).

Use tidal theory, wind and temperatureObservations to model density variability in the re-entry regime.


Research Highlight:Rotating Solar Coronal Holes and Periodic

Modulation of the Upper Atmosphere

Lei, J., Thayer, J.P., Forbes, J.M., Sutton, E.K., and R.S. Nerem, Rotating Solar Coronal Holes and Periodic Modulation of the Upper Atmosphere, Geophys. Res. Lett., in press, 2008.

Thayer, J.P., Lei, J., Forbes, J.M., Sutton, E.K., and R.S. Nerem, Thermospheric Density Oscillations due to Periodic Solar Wind Fast Streams, J. Geophys. Res., in press, 2008.

Lei, J., Thayer, J.P., Forbes, J.M., Sutton, E.K.,Nerem, R.S., Temmer, M., and A.M. Veronig, Periodic oscillations in thermospheric density measured by the CHAMP satellite during the declining phase of solar cycle 23, J. Geophys. Res., submitted, 2008.


During declining and low solar activity, multiple rotating coronal holes produce periodic high-speed solar wind streams.

At Earth, these high-speed streams modulate geomagnetic activity in the geospace environment with the same periodicity.




Thermosphere Density - 400 km

F10.7

Solar Wind Speed

Kp






TIMED/SEE


F10.7

Solar Wind Speed

Kp

Spectra for all of 2005

A triad of coronal holes during 2005 leads to a27d/3 = 9d periodicity inthermosphere density




Density at 400 km

An element of predictability is inherent in this phenomenon!

Latitude Structure of Density ResponseA: Actual Data B: Band-Pass Filtered Data

Percent density change




27d/3 = 9.0

27d


F10.7

Solar Wind Speed

Kp


27d/4 = 6.8

27d/2 = 13.5


google: ‘asen-5335’








Additional SlidesMore Details of Focus Areas


Focus Area I: Scales of Density Variability, Winds, and Drag Prediction

Forbes, Born, McLaughlin, Thayer, Fuller-Rowell

Methodology: A test bed of satellites will be used to perform satellite orbit predictions, and to evaluate predicted versus actual in-track satellite positions (“in-track errors”) in terms of characteristics of density variability (e.g., scale size).

Anticipated Outcome: Understand what spatial and temporal resolutions that both empirical and first-principles models should seek to achieve, as well as the required temporal resolution of geophysical indices or data that drive the models.

Sample Question: What spatial and temporal scales of drag variability are most relevant to in-track error?

Objectives

• Gain quantitative knowledge and a deeper understanding of how prediction error depends on the various facets of density variability.

• Connect our scientific research activities to the actual prediction of satellite ephemerides.

CHAMP Densities


Sample Questions:

• What is the impact of T-I coupling on the neutral density structure?

• What is the source of the semiannual variation and its solar cycle dependence?

• How do cooling processes regulate the response and recovery of magnetic storms?

Focus Area II: Internal Processes and Thermosphere-Ionosphere Coupling

Fuller-Rowell, Forbes, Thayer, Codrescu, Crowley, Solomon, Richmond

Relationship between and Ne - from CHAMP

Objective: Attain improved understanding of internal processes, and capture this understanding in the next generation of hybrid empirical/physical models.


Focus Area III: Energy Partitioning at High Latitudes and Density Implications

Thayer, Fuller-Rowell, Codrescu, Crowley, Knipp, Forbes, Richmond

Objectives

• Improve scientific understanding of the high latitude energy input; energy partitioning into other forms; neutral density and wind responses to these high latitude energy inputs.

• Develop driver-response relationships to improve empirical model specifications.

Methodology: Numerical experiments to evaluate solar flux production of electron density and the concomitant change in the Joule heating rate; assess impact on global temperatures and density. Perform similar numerical experiments using empirical relations with kinetic energy flux and Poynting flux.

Anticipated Outcome: Understand the correlations amongst the fluxes to develop driver-response relationships that may depend on multiple energy sources .

Sample Question: In what ways are the solar flux, kinetic energy flux and Poynting flux related?

00

12

0618


Sample questions

• What are the observed characteristics?

• How are they connected to dynamical variations in the strato-mesosphere?

• Can PW-period density variations be empirically accounted for in models such as J70 and JB2006?

• Can PW periodicities in density be reliably predicted with whole-atmosphere models on time scales of ~one to two weeks in advance?

Focus Area IV: Wave Forcing from the Lower Atmosphere

Akmaev, Forbes, Fuller-Rowell

Objectives

• Delineate density variations at planetary-wave (PW) periods (2-20 days) and understand their origin.

• Develop driver - response relationships to enable predictive capability.

AFOSR MURI: Neutral Atmosphere Interdisciplinary Research (NADIR) • Space Weather Workshop, 2008

Focus Area V: Forecasting Geomagnetic ActivityOdstrcil, Pizzo, Falconer, Raeder, Fuller-Rowell

Methodology: Use observations in the photosphere (left-top), corona (left-bottom), at L1 (bottom-center), and numerical models of the heliosphere (top-center) and magnetosphere (right).

Anticipated Outcome: Improved forecasting ability with the lead times: 30-60 min: driving magnetospheric models by L1 observations; 1-3 days: driving heliospheric models by coronal observations; 3-5 days: using probability of solar magnetic eruptions.

Objectives: Improve existing empirical and numerical models of the heliosphere and geospace to achieve more realistic short-term and probabilistic long-term forecasting.


Focus Area VI: Forecasting Solar EUV/UV Radiation

Fontenla, Woods, Avrett, Quemaris, Lindsey



Objective

• Develop forecasts of EUV and UV solar flux variability up to a few weeks in advance.

Methodology

• Using various measurements of solar properties on the near-side (Earth-facing) part of the Sun, models of the solar atmosphere, and existing empirical relationships, construct solar spectra or “masks”for 10 positions on the solar disk each day.

• Validate against SORCE and other measurements.



• Use helio-seismological and L scattering observations of the far-side of the Sun to apply corrections to the “obsolete”parts of the mask. (Active regions change since the last time they were seen on the near-side)




Focus Area VIII: Satellite Drag in the Re-Entry Region:Satellite Drag

Brian Argrow and Jeff Forbes

Motivation

• Accurate CD essential for drag prediction

• DSMC can be applied for transition flow regime

• Gas surface interaction models are the source of most error for current CD computations

Methodology: Application of the Direct Simulation Monte Carlo (DSMC) for vehicle simulations from free-molecular flow to slip-flow regimes with emphasis on the gas-surface interaction model.

Anticipated Outcome: Data base of altitude-dependent CD values for representative satellite geometries. Simulate aerodynamic forces for trajectory analysis

DSMC Simulations of a Hypersonic Waverider at 100 km and 145 km (density contours)

100 km 145 km


Focus Area VIII: Satellite Drag in the Re-Entry Region:Tidal and Longitude Variations in Density

Jeff Forbes and Jens Oberheide

Motivation

• Re-entry prediction an important problem.

• Few density measurements exist at re- entry altitudes (ca. 80-200 km)

• Strong longitude variations in tides known to exist in temperature and wind measurements

Methodology: A fitting scheme using “Hough Mode Extensions” will be applied to TIMED/SABER and TIMED/TIDI measurements of temperatures and winds over 80-120 km and -50o to +50o latitude during 2002-2006.

Anticipated Outcome: global specifications of longitude-dependent tidal variations in density, winds, and temperature over the 80-200 km height region.

Reconstructed Density Diurnal Amplitudes 110 km, September 2005

afosr muri: neutral atmosphere interdisciplinary research (nadir) space weather workshop, 2008 1...

Documents

thermosphere density

density implicationshow

model density variability

neutral density structure

solar observations

drag coefficient

rotating solar coronal

solar euvuv radiationobjective