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OUTLINE

Ionospheric Research at USU R.W. Schunk, L. Scherliess, J.J. Sojka, D.C. Thompson & L. Zhu Center for Atmospheric & Space Sciences Utah State University Logan, Utah 84322 Presented at: University of New Mexico May 16, 2006. OUTLINE. Current Ionosphere Data Assimilation Models

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OUTLINE

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  1. Ionospheric Research at USUR.W. Schunk, L. Scherliess, J.J. Sojka, D.C. Thompson & L. ZhuCenter for Atmospheric & Space SciencesUtah State UniversityLogan, Utah 84322Presented at:University of New MexicoMay 16, 2006

  2. OUTLINE Current Ionosphere Data Assimilation Models Thermosphere Modeling Tracking a TID

  3. 1. Current Ionosphere Data Assimilation Models • Gauss-Markov Kalman Filter Model of the Ionosphere • Full Physics Kalman Filter Model of the Ionosphere • Ensemble Kalman Filter Model of High-Latitude Electrodynamics

  4. GAIM Basic Approach We use a physics-based ionosphere-plasmasphere-polar wind model and a Kalman Filter as a basis for assimilating a diverse set of real-time (or near real-time) measurements. GAIM provides both specifications and forecasts on a global, regional, or local grid. Regional Local Global

  5. GAIM Assimilates Multiple Data Sources • Data Assimilated Exactly as They Are Measured • Bottomside Ne Profiles from Digisondes (20) • Slant TEC from up to 1000 Ground GPS Receivers • Ne Along Satellite Tracks (4 DMSP satellites) • Integrated UV Emissions • Occultation Data (CHAMP, SAC-C, IOX)

  6. Gauss-Markov Kalman Filter Model Specification of the Global Ionosphere

  7. Provides background ionosphere Global physics-based model 90 - 1400 km 15 - minute output cadence O+, H+, NO+, N2+, O2+, Te, Ti Only use Ne Kalman solves for deviations from background Ionosphere Forecast Model (IFM)

  8. Gauss-Markov Kalman Filter Model • Operational Version Delivered July 15, 2004. • NRL • AFWA • Northrop Grumman • AFRL • CCMC • CISM, BEI, UCAR-ESMF • NOAA

  9. Full Physics Kalman Filter Model Ionosphere Specification with Middle & Low Latitude Drivers

  10. Global Ionosphere-Plasmasphere-Polar Wind Model • 3-D Time-Dependent Parameters • NO+, O2+, N2+, O+, H+,He+ • Te, Ti • u||,u • Auxiliary Parameters • NmF2 • hmF2 • NmE • hmE • TEC • Grid System • Global • Regional • Localized • 90-30,000 km • Realistic Magnetic Field (IGRF) • Spatial Resolution Along B • 0.9 km in E-Region • 1.3 km in F-Region • 3.8 km in Topside • 240 km at 17,000 km

  11. Full Physics GAIM Output • Continuous Reconstruction of Global NeDistribution • Ionosphere-Plasmasphere-Polar Wind • 90-30,000 km • Quantitative Estimates of the Accuracy of Reconstruction • Auxiliary Parameters • NmF2, hmF2, NmE, hmE • Slant and vertical TEC • Model Drivers • High-Latitude Convection and Precipitation • Low-Latitude Electric Fields • Global Neutral Winds • Global Neutral Composition

  12. Ensemble Kalman Filter for High-Latitude Electrodynamics High-Resolution Specification of Convection & Precipitation Drivers

  13. Physics-Based Model of High-Latitude Electrodynamics Time-Dependent Ionosphere Model • 3-D Density Distributions (NO+,O2+,N2+,O+,H+,He+) • 3-D Te and Ti Distributions • Ion Drifts Parallel & Perpendicular to B • Hall & Pedersen Conductances M-I Electrodynamics Model • MHD Transport Equations & Ohm’s Law • Alfven Wave Propagation • Active Ionosphere • 10 km & 5 sec Resolutions • Potential, E-field, Currents, Joule Heating Magnetic Induction Model • Calculates B Perturbations in Space & on Ground • Includes Earth’s Induction Effect

  14. Data Assimilated • Ground Magnetic Data from 100 Sites • Cross-Track Velocities from 4 DMSP Satellites • Line-of-Sight Velocities from the SuperDARN Radars • In-situ Magnetic Perturbations from the 66 IRIDIUM Satellites

  15. Output of the Electrodynamics Model(High Resolution) • Electric Potential • Convection Electric Field • Energy Flux and Average Energy of Precipitation • Field-Aligned and Horizontal Currents • Hall and Pedersen Conductances • Joule Heating Rates • 3-D Electron and Ion Densities • 3-D Electron and Ion Temperatures • TEC • Ground and Space Magnetic Disturbances

  16. We obtain the entire High Latitude Electrodynamic Environment Kalman Filter ‘Truth’ Climate (No Data)

  17. 2. Thermosphere General Circulation Model • Numerical Solution of Neutral Gas Continuity, Momentum, and Energy Equations • Time-Dependent, High-Resolution, Global Model • 25 Non-Uniform Altitude Layers from 97-500 km • 0.5 deg in latitude, 3 deg in longitude • 50 km resolution in polar region • Flux-Corrected-Transport (FCT) Numerical Method • Rotating Coordinate System fixed to Earth • Ma and Schunk (1995)

  18. Thermosphere Model Inputs • Global Ionosphere • Densities • Velocities • Temperatures • Tidal and Gravity Wave Forcing from Below

  19. Global Thermosphere Response to Ionospheric Structures • Propagating Plasma Patches • Ma & Schunk (1995, 1997a, 1997b, 2001) • Sun-Aligned Polar Cap Arcs • Ma & Schunk (1997) • Theta Aurora • Demars & Schunk (2005) • Equatorial Plasma Bubbles • Schunk & Demars (2003, 2005) • Cusp Neutral Gas Upwelling • Demars & Schunk (2006) • Supersonic Neutral Winds • Schunk & Demars (2006)

  20. Qaanaaq, Greenland, October 29, 1989 All-Sky Images (630 nm) 2 - Minute Interval

  21. Equatorial Spread-F and Bubbles JULIA Coherent Scatter Radar Hysell and Burcham (1998)

  22. 3. Tracking a TID

  23. A Model TID • In this “test,” the following are variables • TID Equatorward Speed • TID Width in Latitude • TID Amplitude History • In this “test,” the assumptions are • TID is a perturbation on the background ionosphere. • TID perturbed densities are very noisy • TID moves along a meridian. • Observations lie along the meridian. • Propagation with simple advective model

  24. 1-D TID/TAD • 1-D Propagation • Propagation along meridian • Density Perturbations • Network of ~10 observatories

  25. 1-D TID/TAD • 1-D Propagation • Propagation along meridian • Density Perturbations • Network of ~10 observatories

  26. 1-D TID/TAD • 1-D Propagation • Propagation along meridian • Density Perturbations • Network of ~10 observatories

  27. 1-D TID/TAD • 1-D Propagation • Propagation along meridian • Density Perturbations • Network of ~10 observatories

  28. The Observations • 10 Stations • Density Perturbations • 100% Noise

  29. Kalman Filter Reconstruction • Reconstruction of TID Density Perturbations • # of Stations = 10 • 100% Noise • True Velocity = 2 T=1

  30. Kalman Filter Reconstruction • Reconstruction of TID Density Perturbations • # of Stations = 10 • 100% Noise • True Velocity = 2 T=2

  31. Kalman Filter Reconstruction • Reconstruction of TID Density Perturbations • # of Stations = 10 • 100% Noise • True Velocity = 2 T=3

  32. Kalman Filter Reconstruction • Reconstruction of TID Density Perturbations • # of Stations = 10 • 100% Noise • True Velocity = 2 T=4

  33. Kalman Filter Reconstruction • Reconstruction of TID Density Perturbations • # of Stations = 10 • 100% Noise • True Velocity = 2 T=5

  34. Kalman Filter Reconstruction • Reconstruction of TID Density Perturbations • # of Stations = 10 • 100% Noise • True Velocity = 2 T=6

  35. Kalman Filter Reconstruction • Reconstruction of TID Density Perturbations • # of Stations = 10 • 100% Noise • True Velocity = 2 T=10

  36. Kalman Filter Reconstruction • Reconstruction of TID Density Perturbations • # of Stations = 10 • 100% Noise • True Velocity = 2 T=15

  37. Kalman Filter Reconstruction • Reconstruction of TID Density Perturbations • # of Stations = 10 • 100% Noise • True Velocity = 2 T=20

  38. Kalman Filter Reconstruction • Reconstruction of TID Density Perturbations • # of Stations = 10 • 100% Noise • True Velocity = 2 • Guessed Velocity • 50% Off

  39. Kalman Filter Reconstruction • Reconstruction of TID Density Perturbations • # of Stations = 10 • 100% Noise • True Velocity = 2 • Guessed Velocity • 50% Off

  40. Kalman Filter Reconstruction T=150 • Reconstruction of TID Density • Perturbations • Determination of TID Velocity • # of Stations = 10 • 100% Noise • True Velocity = 2

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