Ionospheric Imaging of E-Region Densities Gary S. Bust and Fabiano Rodrigues Atmospheric Space Technology & Research Associates (ASTRA) Mike Nicolls SRI International

Outline Introduction Description of IDA4D Concept for improved E-region imaging –Data sources, new measurements Current NSF project to image E-region densities –Description –Initial results Using bi-static oblique HF to image E-region –Concept –Example low-vhf transionospheric results with Forte Summary

Introduction Many science topics leverage requirements to obtain improved 3D imaging of ionospheric E-region –Equatorial spread-F –High latitude conductances – AMIE –Global current system –Lightning-ionosphere coupling Traditional data assimilation sources are not sensitive to E-region –GPS TEC –In-situ Satellite measurements –Beacon TEC To accurately estimate E-region densities we need: –New data sources –Customized data assimilation algorithms for E-region imaging

Ionospheric Data Assimilation Four- Dimensional: IDA4D 4D global ionospheric electron density imaging algorithm Based on more than 15 years experience in data analysis, and ionospheric tomographic research and development Mathematical formulation follows closely the meteorological 3DVAR methodology found in Daley and Barker Can be considered a maximum likelihood solution, or Gauss Markov Kalman Filter At each time step, previous best estimate for electron density is used as initial guess and then data are used to improve global solution Typically 5-15 minute temporal cadence Non-linear estimator of log density –Solving for the log of the density rather than density guarantees positivity –However to do so requires a non-linear estimation process –IDA4D methodology: » non-linear methodology in Daley and Barker » Combined with a Levenberg-Marquardt type iteration process. August 16, 2015

IDA4D as Data Assimilative Test Bed Simple forward model being added –Electron density continuity equation –Use data as much as can – AMIE ExB, ExB from Anderson magnetometers NSF Reverse Engineering project –Estimate drivers directly from IDA4D density outputs New Data Sources –Easily tested –HF –6300 Optical –Others

Standard: IDA4D Data Sources Ground Based –GPS TEC (~1400 sites) –DORIS TEC (~57 sites, 4 LEO satellites) –Digisonde virtual height vs frequency (~40) Space Based –GPS Occultations » CHAMP, SACC, GRACE, COSMIC (9 satellites) –GPS SST topside TEC » Same 9 satellites –Insitu Electron Denisities » DMSP, CHAMP

IDA4D: Data Sources sensitive to Bottom-side F- and E-region Space-based GPS Occultations –9 satellites -> ~ occultations over New Mexico / day New Data Sources –Bistatic oblique HF time-delay versus frequency » N transceivers -> N(N-1)/2 link paths » Range over frequency – height information as well as horizontal – lower frequencies sensitive to E region » Use 3D ray-tracer Tracker inside IDA4D non-linear iteration to get densities along path –6300 ground optical imaging data » Measurements ~ integral Ne*F(neutrals) » Estimate F(neutrals) from ASPEN/TIMEGCM Perhaps scalar correction » Ingest in IDA4D – imaging of bottom-side altitudes IDA4D can calibrate counts to Raylieghs

IDA4D: New Methods Model and Data Error Covariance Matrix –Size of estimated variance error on model predictions (TIMEGCM, SAMI2 etc), compared to data error, dictates how strongly solution is weighted by data –Over estimation of data errors reduces influence on solution » Very important in E-region –Vertical error correlations dictate over what altitudes measurements can influence profile –Horizontal error correlations dictate over what horizontal ranges data can influence densities –Mis-specification of any of these parameters can lead to large errors – particularly in E-region Grid –High resolution km horizontal resolution –High resolution ~ 1 km vertical resolution in E-region Run IDA4D in Global Background Mode (w/o occultations) –Use results as background model input to high resolution regional IDA4D run

Lightning E Region Imaging GPS Occultations –Currently 9 satellites –Occultations extend down to bottom of E-region –Issue is errors due to mis-specification of F-region bleeding into E-region Deploy 6 HF transceivers around New Mexico –Links optimized for E-region measurements –30 independent horizontal links –Time-delay versus frequency measurements (~ few micro- second accuracy) Deploy 6300 optical imager (2??) Ingest all data into IDA4D along with normal data sources Use methods being developed in other NSF grant to optimize E-region imaging

Synergy NSF: Investigation of Global E-region Conductivities Relevant to the Seeding and Variability of Equatorial Spread F Using Measurements from COSMIC 3 year project to developed optimized algorithms to accurately estimate E-region densities at off equatorial latitudes All methods being investigated –IDA4D “assistance” to Abel or Maximum Entropy inversions (M. Nicolls) –Full IDA4D estimation of E-region First year complete Initial comparison with daytime Jicamarca E-region densities very promising

Direct Comparisons to Jicamarca E-region Ne ASPEN - Solid IDA 4D - + Jicamarca - *

F-region Gradients from IDA-4D - Run global IDA runs, incorporating datasets from 4/5/2007: no occultations - Evaluate IDA TEC along occultation geometry above 150 km - Subtract from measurement to estimate E-region TEC - apply inverse transform - Including F region gradients produces more reasonable low altitude profiles (go to 0 at low alts) - Quite good agreement with Jicamarca - Substantially different from direct Abel results

Using Bi-static HF Links to Imge E- Region Bistatic HF links over ~ 300 – 1000 km or so Range over frequency (~1-2 MHz – 15 MHz) Data is time-delay versus frequency along oblique paths Thus for a given link, we get a range of measurements that probe different altitudes between the E- and F-region peak The propagation path through the ionosphere can be modeled by a full 3D ray-trace algorithm that uses the Appleton-Hartree (AH) equation for the complex refraction. AH depends on the 3D electron density and magnetic field. Therefore, HF data can be used with 3D ray-trace model to non-linearly iteratively adjust electron densities along the path (and adjust the path!!!!) until the model matches the data We have implemented the full 3D ray-tracer “tracker” in IDA4D along with a non-linear estimation method to be able to use HF oblique data to improve estimation of densities in the bottom- side F and E region. Improved bottom-side imaging due to inclusion of HF links can provide accurate ionospheric specification to HF applications

Possible Configuration of 6 HF Transceivers in New Mexico

Second Possible Configuration

IDA4D Results using Broadband Low VHF Forte Data As an example of how Oblique HF would be ingested into IDA4D – use Actual low VHF data from Forte Satellite MHz 800 Km altitude near-polar orbit LANL Pulsar provides broadband transmission April 10, 2001 (storm) 18 UT 6 separate sets of data at 6 different Forte satellite positions (28 – 42 degrees latitude) Each set of data ~ 20 frequencies versus (relative) time delays Ingest in IDA4D use Tracker, and non-linear iteration method

IDA4D Forte: Post-IDA4D fit to Forte Data Fit to time delay versus frequency Blue is ASPEN model Red IDA4D post-fit to data 28.4 Satellite Latitude 38.2 Satellite Latitude

IDA4D Forte: Model versus IDA4D April 10, 2001 (storm day) 18 UT 6 Forte paths over New Mexico All other data available also ASPEN IDA4D

HF/Forte Example using actual low VHF broadband data demonstrates cabability of IDA4D to fit the data and to adjust densities, providing an improved estimation of density Same thing can be done for range of frequencies for ground-based HF links Multiple HF links will provide crossing paths in the bottom-side, and therefore provides the cabability of actually imaging the 3D bottom-side F and E region ionosphere Example configuration above provides 15 independent links.

AM/HF Absorption Measurements Low cost MF/HF receivers designed to measure changes in received signal strength Use transmitters of opportunity – frequencies that monitor E/D region of ionosphere Monitor changes in signal strength versus time Sensitive to solar flares etc –Sensitive to lightning strikes??? Deploy on same links as HF transceivers –Get electron density from HF/ IDA4D –Use absorption to then estimate electron collision frequencies » Temperature changes » Neutral composition changes

Uses a commercial shortwave radio receiver (NRD-535)‏ PC-controlled / unattended operation Initial observations made to detect particle precipitation in the SAMA region Used AM broadcast stations in Brazil Effects of solar flares detected Low-cost monitoring of the lower ionosphere Rodrigues et al., 2004; Contreira et al., 2005

Examples of observations: Daily variation of signal strength (daytime absorption)‏ Low-cost monitoring of the lower ionosphere Rodrigues et al., 2004

Low-cost monitoring of the lower ionosphere Examples of observations: Effects of solar flares Contreira et al., 2005

Summary Imaging E-region and bottom-side F-region is difficult since easily available data sets consist of integrated TEC which is not very sensitive to E-region Data sources that are sensitive to bottomside F and E- region include –GPS Occultations –Ground based bi-static HF links –Ground based optical data ASTRA and SRI have a joint NSF project to improve imaging of E-region densities at low latitudes that is synergistic with this project IDA4D can ingest all the above data sets – particularly ground based HF data that can be used to provide improved 3D imaging of regional E-region densities