1. The C/NOFS Satellite Mission and Science Plan O. de La Beaujardière, L. Jeong, B. Dichter, F. Rich, J. Retterer, W. Borer, K. Groves, W. Burke, S. Huang, T. Beach, M. Starks Air Force Research Laboratory, Space Vehicles Directorate, Hanscom AFB And C/NOFS Science Definition Team Jicamarca, May 2002

2. 2 Communication/Navigation Outage Forecasting System (C/NOFS) Outline – Introduction, C/NOFS rationale – The C/NOFS mission – Science objectives 1.Understand the physics of the equatorial ionosphere – Forecast plasma density Forecast drivers: E field, wind, etc 2.Understand physical processes that lead to bubble formation 3. Understand Spread-F waves and RF propagation through irregularities – Campaigns and coordinated/complementary observations – Conclusions

3. 3 Communication/Navigation Outage Forecasting System C/NOFS First-ever system for continuous global scintillation forecasts of communication and navigation outages “Forecasting – long denigrated as a waste of time at best and a sin at worst – became a necessity” P. Bernstein, Against the Gods, 98

4. 4 Scintillation Affects Comm & Nav Ionospheric scintillation impacts Satellite data links <2.5 GHz GPS navigation systems

5. 5 C/NOFS Program Objectives Provide scintillation nowcasts Develop capability to produce: - Short term (2-3 hrs before onset) scintillation forecasts - Medium term (4-6 hrs before onset) scintillation forecasts - Long term (24-72 hrs before onset) scintillation outlooks Develop improved understanding of equatorial ionosphere and scintillation Demonstrate operational capability during Advanced Concepts Tech Demonstration (ACTD) evaluation phase Leave behind operational capability following completion of ACTD evaluation phase Satellite System Ground Based Sensors Forecast Modeling Data Ops / ACTD Demo

6. 6 C/NOFS Mission Components Satellite – low altitude / low inclination - Inclination: 13 deg (target) - Perigee/ Apogee: 400 and 720 Km - Orbital Period: 96 min/rev Space Vehicle Design - About 300 kg (575 lbs) - Body-mounted solar panels (avoid field disruption) - TDRSS transmitter for near-real-time downlink Launch - November 03 - Dedicated Pegasus XL launch Ground-based component: - Scintillation and beacon receivers - Other Ground based instruments Space Test Program (SMC Det 12) is providing the spacecraft bus, launch service, first year of on-orbit ops

7. 7 Payload Description RAM Plasma Sensors Planar Langmuir Probe (PLP) Developed by AFRL/VS (J. Ballenthin PI) Measures: Ion Density, Ion Density Variations, Electron Temperature Ion Velocity Meter (IVM) Developed by Univ. of Texas (R. Heelis PI) Measures: Vector Ion Velocity, Ion Density, Ion Temperature Neutral Wind Meter (NWM) Developed by Univ. of Texas (R. Heelis PI) Measures: Vector Neutral Wind Velocity RF Beacon Coherent EM Radio Tomography (CERTO) Developed by NRL (P. Bernhardt PI) Measures: Remote sensing of RF scintillations and LOS TEC GPS Receiver C/NOFS Occultation Receiver for Ionospheric Sensing and Specification (CORISS) Developed by Aerospace (P. Straus PI) Measures: Remote sensing of LOS TEC Electric Field Instrument Vector Electric Field Instrument (VEFI) Developed by NASA/GSFC (R. Pfaff PI) Measures: Vector AC and DC electric fields

8. 8 Space Mission Profile Survey Mode Identify key scintillation parameters Refine / implement forecasting models Survey Mode Identify key scintillation parameters Refine / implement forecasting models LAUNCH + 1-9 MONTHS Forecast Mode Real-time downlink of sensor data Demonstrate scintillation event prediction Begin military utility assessment Forecast Mode Real-time downlink of sensor data Demonstrate scintillation event prediction Begin military utility assessment LAUNCH + 6-12 MONTHS Prototype Operational Demo Extended utility assessment Provide comm/nav outage warnings Complete ACTD objectives Prototype Operational Demo Extended utility assessment Provide comm/nav outage warnings Complete ACTD objectives LAUNCH + 12-36 MONTHS 1 2 3

9. 9 Understand, characterize and forecast equatorial spread F and associated scintillation Local Time (hr) Altitude (km) C/NOFS Science Main Objective Disturbance “Plumes” Jicamarca, Sept 26, 94

10. 10 C/NOFS Science Objectives Understand the physics of the ionospheric plasma – Forecast N e Forecast E, wind, etc Understand processes that lead to plasma irregularity formation – Calculate instability growth rate – Model plasma bubble to predict scintillation index – Determine triggering mechanisms Understand Spread-F waves and model RF propagation through irregularities

11. 11 Forecast Ne Assimilation Models Ionospheric models – ITFM (Ionosphere Thermosphere Forecast Model) – GAIM ( MURI, other assimilative) – Other (Huba et al, …) Challenges: – Large and disparate and data to assimilate – Estimate error bars – What ‘sub-models’ to include – Correlations from orbit to orbit, spatial correlations – Can E be forecast from wind and magnetospheric effects? TEC output from PRISM, driven with GPS data

12. 12 Need to specify and forecast ion and neutral densities, E field, wind, conductivities … Plasma moves easily along field lines Eastward Electric Field supports plasma against gravity  unstable configuration E-region “shorts out” electrodynamic instability during the day Physics of equatorial ionosphere Magnetic (Dip) Equator Magnetic Field Lines Unstable Plasma Earth E Region Daytime “Shorting” F Region

13. 13 Forecast Winds Zonal Wind -- How Accurately Can It Be Specified and Forecast from in situ Observations? TFM of Fuller-Rowell et al.

14. 14 Data Assimilation Methods Constraining model output Developing statistical interpolation techniques (using knowledge of correlation distances gained with CNOFS experience) Adjusting model drivers – Kalman filter – Adjoint methods Forecast N e The satellite provides only a one-dimensional sampling of the parameters. Will we be able to specify the ionosphere in 3-D?

15. 15 Jicamarca Modeling – Ambient Ionosphere From Retterer et al., 2000 Data Assimilation and Linear Growth Rate Ambient model (on right) reproduces the features of ionosphere very accurately. In example, calculated growth rate accurately reproduces regions of intense irregularities Can we reliably derive growth rate from ambient model?

16. 16 During daytime E field is eastward – upward velocity At sunset eastward field increases (PRE) Around 19 LT E reverses to westward Forecast E Field Pre-Reversal Enhancement What drives PRE? Which parameters control its magnitude?

17. 17 DMSP Typical Data – Low Latitude M-0 M-1 M-2 M-3 South EQ North How can we integrate DMSP data to C/NOFS algorithms? Examples of Equatorial Plasma Bubbles observed on DMSP Plots show ion density (cm -3 ) as a function of latitude at 20 MLT

18. 18 Magnetospheric Effects Probability to encounter equatorial plasma bubble increases with magnetic activity, when Kp >5 Bubbles form during storm main phase Will we be able to forecast bubble formation during periods of high activity? DMSP BUBBLE OBSERVATIONS From Huang et al. 2000

19. 19 Forecast E Field and Winds How much of the unpredictability of the equatorial scintillation phenomenon is due to the variability of the winds and electric fields in the region? Can high-latitude phenomena, which are the most variable drivers of these fields, be estimated and predicted? Can the models reproduce all the timescales for propagation of high latitudes effects to the equator: – From almost immediate (penetration fields) – To tens of hours (disturbance dynamo effects)

20. 20 Understand Physical Processes that Lead to Bubble Formation Heavy Fluid Light Fluid View along bottomside of ionosphere (looking north from equator) Fluid Mechanics analogy (a) Steep bottomside density gradient during / after sunset (b) Fluid instability analog (Rayleigh-Taylor instability) Perturbation starts at large scales (100s km) Cascades to smaller scales (200 km to 30 cm) (b) (a)

21. 21 Understand Physical Processes that Lead to Bubble Formation How realistic will the planned scintillation model architecture be? 1. Forecast ambient ionosphere 2. Derive linear growth rate 3. Calculate non-linear bubble evolution 4. Calculate irregularities spectral index 5. Derive scintillation statistics Prototype Models Developed Ionospheric Forecast Model (IFM) Dynamo model IFM-Dynamo coupling Thermospheric Forecast Model (TFM) TFM-IFM coupling Mesoscale bubble model Plasma instability model

22. 22 Forecast Product Goal: 6 to 72 hours forecast Global Maps of Instability Regions and Strength of Scintillation, 1 hr interval

23. 23 Forecast Scintillation Strength Local Map of Strength of Fluctuations Leads to Scintillation index estimates With what level of confidence can we forecast ambient ionosphere, bubble evolution and associated scintillation index?

24. 24 Spread-F Waves E and delta n measurements: can they provide the different wave contribution? Can they elucidate cross-scale coupling processes, energy transfer between scale lengths? (R. Pfaff)

25. 25 SCINDA = Scintillation Network Decision Aid (AFRL-developed system) SEVEREMODERATEWEAK Scintillation Strength DayNight Terminator Satellite Links How accurately can we specify and forecast Scintillation? Model radio waves propagation through ionosphere Presently, specification based on ground based scintillation receivers

26. 26 Phase Screen Development: Algorithm Concept Satellite-measures density perturbations Estimate irregularity power spectrum Construct a geometry-based equivalent zenith phase screen Step 1Step 2Step 3 Generate a frequency- dependent scintillating waveform Step 4 Step 5 Compute statistics (M Starks)

27. 27 Phase Screen Development: Discretized Irregularity Model The discretized irregularity model creates a 3-D representation of plasma density perturbations. Arbitrary propagation geometries are converted to equivalent zenith problems. Altitude Longitude Latitude SATCOM link geometry Equivalent phase screen Longitude Altitude (M Starks)

28. 28 C/NOFS Collaborations National and international collaborations essential Discussions in progress with other US agencies to coordinate guest-investigator type program Ground and satellite coordinated observations will be planned Specific campaigns to validate satellite products and pursue science topics will be planned Jicamarca site and observations from the Latin American sector are essential

29. 29 Existing and Planned Equatorial Ground Stations AF ground stations C/NOFS Support Ancon, Antofagasta, San Jose, Ascension, Bahrain, Diego G, Singapore, Indonesia (2), Malaysia, Manila, New Guinea, Guam, Kwaj Proposed SiteReal-TimeGPS Data Logging 30N 0 30S 60S 210E 240E 270E 300E330E 0 30E 60E90E120E 150E

30. 30 Summary C/NOFS Mission Developing first-ever system for continuous global scintillation forecasts Major advance in new technologies for real-time global monitoring, and forecasting of equatorial ionospheric scintillation Unique opportunity for equatorial aeronomy community for both basic and applied research Campaigns, ground and satellite support, are essential Satellite System Ground-Based Sensors Forecast Modeling Prototype Operational Demo Communication/Navigation Outage Forecasting System (C/NOFS)

31. 31 Summary C/NOFS Science Objectives Understand the physics of the ionosphere plasma – Forecast N e, E, wind, etc – Forecast bubbles during mag storms Understand plasma irregularity formation processes – Calculate instability growth rate – Determine triggering mechanisms – Model plasma bubble to predict scintillation index Understand Spread-F waves and RF propagation through irregularities Coordinated observations with ground-based instruments and other satellites Forecasting – long denigrated as a waste of time at best and a sin at worst – is a necessity Will we be up to the challenge? We hope we will neither sin nor waist our time.

32. 32 Back up slides Scintillation Prediction (6 to 72 hrs)

33. 33 After Fig. 7 from Farley et al., J. Geophys. Res., 91, 13,723,1986; modifications from Eccles, J. Geophys. Res.,, 103, 26,709,1998. F Region E Region WestEast Wind U + + + + – – – – B V – – – – – EfEf EE EE (a) (b) DayNight