1. Neutral Atmosphere Density Interdisciplinary Research Overview of NADIR Co-Principal Investigators: Jeff Forbes - Project Manager Tim 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, A p

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. Participants 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

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

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

10. 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. Focus Area II: Internal Processes and Thermosphere-Ionosphere Coupling Fuller-Rowell, Forbes, Thayer, Codrescu, Crowley, Solomon, Richmond Relationship between  and N e - from CHAMP

11. 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, partitioning of this energy into other forms within the thermosphere and identify the neutral density and wind response 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 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. Sample Question: How are the solar flux, kinetic energy flux and Poynting flux correlated? 00 12 0618

12. 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? Focus Area IV: Wave Forcing from the Lower Atmosphere 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) Akmaev, Forbes, Fuller-Rowell

13. Focus Area V: Forecasting Geomagnetic Activity Odstrcil, 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 to achieve more realistic short-term and probabilistic long-term forecasting.

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

16. Focus Area VIII: Satellite Drag in the Re-Entry Region: Satellite Drag Brian Argrow and Jeff Forbes (CU) Motivation Accurate C D essential for drag prediction DSMC can be applied for transition flow regime Gas surface interaction models are the source of most error for current C D 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 C D 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

17. 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 -50 o to +50 o 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