Objective of NADIR

1. Neutral Atmosphere Density Interdisciplinary ResearchOverview of NADIR Co-Principal Investigators: Jeff Forbes - Project ManagerTim Fuller-Rowell - Technical Manager

2. Objective of NADIR Significantly advance understanding of drag forces on satellites, including density, winds, factors affecting the drag coefficient. Seek a level of understanding that will enable specification and prediction at the “next level”.

3. Methodology • Understand the physical process • Determine which of the processes create the structure on a scale that is important to 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

4. Jacchia/Bowman • Static • Single indices - F10.7, Ap

5. NADIR • Improve basic structure MTM Ne/ relationship Cusp heating • Time-dependent Response and recovery timescales • Spectrally-resolved EUV and UV • Magnetospheric sources Joule heating, momentum forcing, Poynting flux • Lower atmosphere forcing • Forecasting EUV, geomagnetic, and lower atmosphere forcing

6. Co-Investigators Rashid Akmaev Brian Argrow George Born Gary Bust Geoff Crowley David Falconer Juan Fontenla Delores Knipp Tomoko Matsuo Dusan Odstrcil Joachim Raeder Jeff Thayer Collaborators Eugene Avrett Jeff Anderson Christopher Bass Bruce Bowman Mihail Codrescu Doug Drob Irene Gonzalez-Hernandez Cheryl Huang Charles Lindsey Chin Lin Joseph Liu Frank Marcos Geoff McHarg Craig McLaughlin Cliff Minter Jah Moriba Steve Nerem Andrew Nicholas Vic Pizzo Eric Quemaris Stan Solomon Mark Storz Tom Woods Participants

7. Focus Areas • Scales of Density Variability, Winds, and Drag Prediction • Internal Processes and Thermosphere-Ionosphere Coupling • Energy Partitioning at High Latitudes and Density Implications • Wave Forcing from the Lower Atmosphere • Forecasting Geomagnetic Activity • Forecasting Solar EUV/UV Radiation • Driver-Response Relationships • Satellite Drag in the Transition Region

9. CHAMP Densities Focus Area I: Scales of Density Variability, Winds, and Drag Prediction Forbes, Born, McLaughlin, Thayer, Fuller-Rowell • 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. Sample Question: What spatial and temporal scales of drag variability are most relevant to in-track error? 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.

10. Focus Area II: Internal Processes and Thermosphere-Ionosphere Coupling Fuller-Rowell, Forbes, Thayer, Codrescu, Crowley, Solomon, Richmond Relationship between  and Ne - from CHAMP Science questions • What is the source of the SAV variation, the amplitude variation over the solar cycle, and the reason for the phase modulation? • How does the seasonal/latitude, solar cycle, and storm-time variation in radiative cooling impact global neutral density structure? • What is the cause of the phase lag in the neutral density response to solar UV radiation? • What is the temporal response of neutral density to flares, substorms, and storms? • What is the impact of T-I coupling on the neutral density structure? Goal • Capture the improved physical understanding in the next generation hybrid empirical/physical models.

11. 12 18 06 00 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 latitudeenergy input, partitioning of this energy into otherforms within the thermosphere and identify the neutraldensity and wind response to these high latitudeenergy inputs. • Develop driver-response relationships to improve empiricalmodel specifications. Sample Question: How are the solar flux, kinetic energy flux and Poynting flux correlated? Methodology: Numerical experiments to evaluate solar flux production of electron density and the concomitant change in the Joule heating rate. Assess this correlation and its 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 .

12. Focus Area IV: Wave Forcing from the Lower Atmosphere Akmaev, Forbes, Fuller-Rowell Temperature correction parameter (dTc) to the empirical J70 model from 4 satellite orbits in 2002 compared to solar and geomagnetic indices. Significant spectral peaks near 11, 14, and 19 days are a possible manifestation of PW effects. (Courtesy B. Bowman, 2006) Science questions • What are the observed characteristics of PW-period thermosphere density oscillations and to what extent do they correlate with similar variability in the strato-mesosphere? • To what extent are PW-period density variations produced by PW modulation of the lunar semidiurnal and solar atmospheric tides? • What is the role of gravity waves in this modulation? • How do seasonal variations of tides and other planetary-scale waves manifest in global mean thermospheric density? • To what extent can PW-period thermosphere density variations be empirically accounted for in models such as J70 and JB2006? • Can PW periodicities in density (“thermospheric weather”) be reliably predicted with whole-atmosphere models on time scales of ~one to two weeks in advance?

13. Focus Area V: Forecasting Geomagnetic ActivityOdstrcil, Pizzo, Falconer, Raeder, Fuller-Rowell Objectives: Improve existing empirical and numerical models to achieve more realistic short-term and probabilistic long-term forecasting. • 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.

14. Using previous rotation is poor Focus Area VI: Forecasting Solar EUV/UV RadiationFontenla, Woods, Avrett, Quemaris, Lindsey Images of the near-side produce daily masks of features Synoptic masks are refined by applying trends and far-side imaging: Using atmospheric models the spectrum is computed for any day AR helioseismic image Without refinement the synoptic mask features obsolescence makes it bad AR backscattered image

16. 145 km 100 km Focus Area VIII: Satellite Drag in the Re-Entry Region: Satellite Drag Brian Argrow and Jeff Forbes (CU) • Motivation • Accurate CDessential for drag prediction • DSMC can be applied for transition flow regime • Gas surface interaction models are the source of most error for current CDcomputations DSMC Simulations of a Hypersonic Waverider at 100 km and 145 km (density contours) 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 CDvalues for representative satellite geometries. Simulate aerodynamic forces for trajectory analysis

17. Reconstructed Density Diurnal Amplitudes 110 km, September 2005 Focus Area VIII: Satellite Drag in the Re-Entry Region: Tidal and Longitude Variations in Density Jeff Forbes (CU) and Jens Oberheide (Univ. of Wuppertal) • 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.