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ARL Applied Research Laboratories The University of Texas at Austin LWA Ionospherically Related Work at ARL:UT Dr. Gary S. Bust
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ARL Applied Research Laboratories The University of Texas at Austin Outline Ionospheric Calibration of LWA History and Capabilities of IDA3D Results from IDA3D IDA3D applied to LWA Future Directions at ARL:UT as they apply to LWA
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ARL Applied Research Laboratories The University of Texas at Austin Ionospheric Calibration of LWA ~ 50 stations spaced over a 300 - 400 kilometer region. Each station consists of ~256 antennas over a 100 x 100 meter region. The primary beam of a station is ~2 degrees x 2 degrees (~ 12x12 km at 300 km) Know phase to ~ 1 degree everywhere in beam.
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ARL Applied Research Laboratories The University of Texas at Austin Ionospheric Requirements 1 degree phase requirement: Know TEC to ~ 10 -4 TECU (~ 100 times greater accuracy than GPS phase measurements) At this sensitivity, need measurements every few seconds Possibly need to specify TEC on scales of 1 km or less Need to specify some kind of ionospheric map at each of 50 stations over a 300+ km baseline
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ARL Applied Research Laboratories The University of Texas at Austin Measurement Equation Simple version of visibility integral equation between two stations: Actual equation includes effects of polarization, projection,leakage,electronic gain etc. And also integration in time and bandwidth.
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ARL Applied Research Laboratories The University of Texas at Austin Issues Regarding Calibration Astronomers need the ionospheric phase calibrated for each station, and everywhere within each station primary beam. ~ 50 stations. Say we need it every 1 km in a 10 x 10 km beam Direct approach ~ 100 parameters per station ~ 5000 unknowns. But, if we have 50 stations we have 50*49/2 ~ 1,250 visibilities per calibrations source.
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ARL Applied Research Laboratories The University of Texas at Austin Issues Regarding Measurement Equation Non-linear forward integral model in the ionospheric phases Cannot necessarily bring ionospheric phases outside integral Cannot do synthesis via fourier transform of visibility Need ~ 100 sources in primary beam. Need to solve for visibilities for all 100 sources, between all stations For 50 stations ~ 125,000 visibilities
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ARL Applied Research Laboratories The University of Texas at Austin Inversion Approaches Use visibility data and measurement equation Must solve for a non-linear integral equation to estimate ionospheric phases ~ 100,000 measurements, ~ 5000 unknowns. That is good!!! Waves: If we require 2D spatial from 1-300 km we have ~ 1e5 unknowns -- not good!!! So, be more clever - wavelets? Different waves at each station? Elevation / station Pixels
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ARL Applied Research Laboratories The University of Texas at Austin VLA Calibration
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ARL Applied Research Laboratories The University of Texas at Austin Calibration Plan and Schedule FY07 Develop forward simulation of visibilities including ionospheric simulations and simulated sky map Develop initial inversion algorithm Test algorithm on simulated data FY08 Test algorithm on historical VLA data and data with Pie Town Improved forward simulation Refined inversion algorithm FY09 Test algorithm on new VLA / Pie Town experiments with LWA stations added Collaborate / Exchange results and ideas with LOFAR Good working collaboration with Jan Noordam ASTRON Netherlands
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ARL Applied Research Laboratories The University of Texas at Austin From MACE’93 to IDA3D: Ionospheric Imaging at ARL:UT Ionospheric Imaging Algorithms at AR:UT Simulations 1992 Mart 2D tomography 1992-1994 First 3D/4D algorithm (1995-1998) GPS + CIT + Ionosondes 3D First 3D algorithms in the literature Origins of IDA3D True development of IDA3D as assimilation began in 1998 3DVAR objective analysis Development continuing at present Experimental campaigns and instrumentations 12 experimental campaigns since 1992 Took over operations of Transit (now NIMS) for Navy (1996) Developed CIDR – replacement for Magnavox 1502 (2000)
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ARL Applied Research Laboratories The University of Texas at Austin ARL:UT Tomography Data Assimilation Experiments Mace: Days 181-349 19939 receivers ICMT1: Days 24-4619952 5 receiver arrays ICMT2:Days 80-11019963 5 receiver arrays RadWhite: Days 267-3551996(ICMT1 Config) Traits:Days 183-3651997(Caribbean) Days 28-351998 PR Heater Days 21-281998 (8 receivers @ PR) CIC1Days 173-1821998(Caribbean) PrairieDog Days 190-2781998 (West and East Cst) CIC2Days 250-2731999 (Caribbean) AlaskaDay 285 - ?2000 - Current Greenland Day 278 - ? 2000 - Current NECADay 325 - ?2002 - Current
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ARL Applied Research Laboratories The University of Texas at Austin Overview of IDA3D Solves spatial 3D tomographic inverse problem - maximum likelihood solution Equivalent to 3DVAR in meteorology Solution also known as Kalman gain Important inverse imaging math and development is in the choice of background model, model error covariance and data error covariance Solution updated at user selected intervals (typically 5-15 minutes) Verified and validated many times IDA3D has validated against altitude distribution of plasma density in addition to TEC validation
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ARL Applied Research Laboratories The University of Texas at Austin Capabilities of IDA3D Flexible User can input customized irregular grid User can input any model empirical or physical Flexible error covariance data base inputs Entire program designed to be customized by user Global globally and regionally Storms and quiet times Data types Accepts large number of different data types currently Designed modularly to make easy to add new data sets.
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ARL Applied Research Laboratories The University of Texas at Austin IDA3D Current Status of Development Data Sources Ground Based GPS TEC Tomography: Greenland, Alaska, NECA, Equatorial CIDR arrays EISCAT, Sondrestrom, Millstone Hill ISR’s Space Based In-situ DMSP, CHAMP, ROCSAT Occultations: Champ, SACC, GRACE, IOX OSEC: Champ, SACC, GRACE TOPEX TEC Models IRI, PIM, TIMEGCM, RIBG Recent Improvements Now solve for state vector log 10 (Ne) Assimilate ionosonde virtual heights versus frequency Run in parallel on 24 processor cluster
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ARL Applied Research Laboratories The University of Texas at Austin Validation of Tomography and IDA3D Mid-America Computerized Ionospheric Tomography Experiment (MACE): 1993 Comparisons with ionosonde virtual heights Virtual height error ~ 6% f o F 2 error 1.9-3.2 % Single Sight Location (SSL) experiments On 1650 km path, range error ~ 9% compared to 15% using classical SSL methods
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ARL Applied Research Laboratories The University of Texas at Austin Ionosonde Virtual Height Comparisons MACE Papers: 1) “Application of ionospheric tomography to single-site location range estimation” Bust et al., 1994, J. Imaging Sys. and Tech. 2) “Mid-America computerized ionospheric tomography experiment (MACE ‘93)”, Kronschnabl et al., 1995, Radio Science
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ARL Applied Research Laboratories The University of Texas at Austin Traits Campaign 1997 “Verification of ionospheric sensors”, C. Coker et al., 2001, Radio Science.
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ARL Applied Research Laboratories The University of Texas at Austin ISR Comparisons to IDA3D Sondrestrom Sept 30, 2000 Oct 30, 2003 EISCAT Dec 12, 2001 Patches Millstone Hill Nov 20, 2003 uplifts
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ARL Applied Research Laboratories The University of Texas at Austin IDA3D Sept. 30, 2000 compare to Sondestrom Watermann et al., “Mapping plasma structures in the high- latitude ionosphere using beacon satellite, incoherent scatter radar and ground-based magnetometer observations”, Annals of Geophysics, 45, 2002
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ARL Applied Research Laboratories The University of Texas at Austin IDA3D Dec 12, 2001 compare to EISCAT Bust, G.S. and G. Crowley, “Tracking of polar cap ionospheric patches”, submitted to J. Geophys. Res., 2006
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ARL Applied Research Laboratories The University of Texas at Austin IDA3D Oct. 30, 2003 compare to Sondestrom
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ARL Applied Research Laboratories The University of Texas at Austin IDA3D Nov. 20, 2003 compare to Millstone Hill IDA3D sees extreme uplift in plasma 17-18 UT, as does Millstone Hill. Also notice the double E-F layers in IDA3D and Millstone Hill later.
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ARL Applied Research Laboratories The University of Texas at Austin Statistical Validation of IDA3D with ISRs 4 days in 2003. Two closer to Equinox (2003, Oct 28, Oct 30) Two closer to Solstice (2003, Nov 19, Nov 20) Two magnetically quiet days (Oct 28, Nov 19) Two disturbed days (Oct 30, Nov 20) Days need to have ISR coverage, and good data coverage Results Quiet Times Standard deviations of 1.0E11 and 1.5E11 el/m 3 in the F-region Mean offsets of -0.3E11 and -0.5E11 el/m 3 Active Times Standard deviations: 2.2E11 and 3.8E11 el/m 3 Mean: 0.08E11 and -0.91E11 el/m 3
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ARL Applied Research Laboratories The University of Texas at Austin IDA3D Movies of Scientific Results Oct 30, 2003 polar VTEC movie November 20, 3003 slice along 290 longitude Oct 30, 2003 VTEC Movie over the USA Oct 30, 2003 slice movie over the USA
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ARL Applied Research Laboratories The University of Texas at Austin Oct 30, 2003 Polar Movie
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ARL Applied Research Laboratories The University of Texas at Austin Oct 30, 2003 VTEC over the USA with data coverage
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ARL Applied Research Laboratories The University of Texas at Austin Oct 30, 2003 slice at 260 longitude. Log Density.
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ARL Applied Research Laboratories The University of Texas at Austin IDA3D and LWA Large scale imaging 300+ km horizontal ~ 10-25 km resolution ~ 100 look directions (maybe more) every 10 seconds, 50 stations -> ~ 5000 data points. Ingest into IDA3D and do high-resolution regional imaging every few seconds Japan GPS network is similar in many ways ~ 1000 receivers separated by ~ 10 km. Currently see 6-10 satellites ~ 6000 data points Same amount of data, roughly same coverage area (somewhat larger) IDA3D has already been successfully used to image results from Japan network. This gives us great confidence in using it with LWA
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ARL Applied Research Laboratories The University of Texas at Austin Japan 2003, Nov. 4 Altitude-latitude slice at 138 Long. over Japan. 1040 UT Nov. 4, 2003 Re-integrated VTEC from IDA3D over Japan. 1040 UT Nov. 4 2003
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ARL Applied Research Laboratories The University of Texas at Austin Future Directions: Mesoscale and LWA Within a primary beam ~ 1 km resolution over 12-15 km regions By crossing beams possibly look at 3D + time variations in delta Ne Ionospheric Regional Assimilative Model (IRAM) 2nd of two year development funded by ONR Numerical data assimilation on regional scales Expand continuity equation, electron, ion momentum, divergence of current in perturbations of background Keep non-linear terms Assume temperature perturbations are not drivers Transform to Fourier wave-vector/frequency space Iteratively solve non-linear terms Transform back into real space-time
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ARL Applied Research Laboratories The University of Texas at Austin Future Directions: Connecting LWA to Broader Community GPS Workshop at ARL:UT (Sept. 30-Oct. 1) Introduce LWA to GPS TEC Community - closest to LWA, experience, ideas, algorithms Third Meeting Last one had one member of modeling / DA community Tim Fuller Rowell Univ. of Colorado This time invite other modelers / DA groups Get them more involved in GPS TEC community Share expertise of GPS group
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