JAFOE Next Generation Environmental Sensors
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1 JAFOE Next Generation Environmental Sensors David Kunkee The Aerospace Corporation 19 November 2008
2 Agenda Environmental Measurements Most Recent Configurations DMSP and NPOESS Environmental Data Records Calibration and Validation of New Sensors Next Generation Operational Microwave Imager (MIS) MIS Sensor Description and Key Capabilities Environmental Sensor Data Perspectives Summary 2
3 Current Polar Orbiting Systems
4 NPOESS - Certified 2 EMD Satellites plus 2 Optional (2010 decision) Bus sized to carry all sensors VIIRS, CrIS, ATMS, CERES, OMPS-N, SEM, ADCS, SARSAT remain APS, TSIS, OMPS-L, ERBS, Alt, SuS, SESS de-manifested from C1 & C2 [accommodation remains] CMIS deleted from C1 & C2 [MIS planned for C2] Ground architecture essentially unchanged Continuity, Flexibility, Advanced Capability
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7 Soil Moisture Soil Moisture Determined from AMSR Following Passage of Major Late Winter Storm Front (S. Chan, JPL) and precipitation map developed by NOAA Climatic Data Center.
8 Sea Surface Wind Direction WindSat Data Comparison with NCEP Forecast Model Showing Detection (Analysis by R. Atlas, NOAA AMOL, Ocean Sciences Conference, February 2006). NCEP analysis January 6 WindSat Surface Wind retrievals in the North Atlantic show the presence of paired cyclonic vortices not captured until the following day by the National Center for Environmental Prediction (NCEP) forecast analysis. NCEP analysis January 7
9 Sea Surface Temperature [LEFT] A cold wake (blue region near the white circles) was produced by Hurricane Bonnie on 24 to 26 August 1998, as seen by the TRMM Microwave Imager (TMI) [RIGHT] The cold wake was not seen by the visible/ infrared AVHRR imager (right) due to areas of persistent rain and cloud cover (white patches) over the 3-day period. White dots: Hurricane Bonnie s daily position as it moved northwest from 24 through 26 August. Gray dots: Hurricane Danielle as it moved northwest from 27 August through 1 September. Danielle crossed Bonnie s cold wake on 29 August and its intensity dropped. Cloud cover prevented AVHRR from observing this sequence, however, TMI was able to measure characteristics of the surface.
10 Cloud Liquid Water and Precipitable Water AMSR-E Cloud Liquid Water: 3-days ending Atmospheric Water Vapor: 3-days ending Liquid Water: mm Water Vapor: mm Global maps of total Precipitable Water and Cloud Liquid Water are produced from AMSR data on the Aqua satellite and from SSM/I and SSMIS on DMSP These datasets have value for weather forecasts and models of the energy and water cycles. Precipitable Water Vapor is considered critical for data continuity for GEOSS. Only microwave sensors can provide estimates of Cloud Liquid Water.
11 Precipitation Rate Rain rate (mm/h) at 2 km height from TMI. Squall line south of Japan. (From Aonashi and Liu, JAM, 2000). Rain Rate (mm/hour) Measurements of precipitation rate are valuable for tactical maneuvers, maritime navigation and fisheries dynamics. TMI provides rain rate measurements over the tropics. The addition of 166- and 183-GHz channels adds capability to measure snow and small ice.
12 First Year and Multi-year Sea Ice Concentration
13 Upper Atmospheric Temperature
14 SSMIS and MIS Radiometers CMIS (similar to MIS) on NPOESS Special Sensor Microwave Imager Sounder (SSMIS) on DMSP F-16
15 Sensor Scan Geometry
16 Zenith Opacity at Microwave Frequencies
17 Vertical Temperature Weighting Functions
18 Sensor Cal/Val Calibration Absolute Accuracy Polarization Purity Geolocation Accuracy Instrument Stability Doppler Correction Antenna Pattern Correction Validation Ocean Wind Speed Water Vapor Cloud Water Rain Rate Sea Ice Soil Moisture Snow water Land Temp Lower Air Profiles Upper Air Ensure Mission Meet Specification Operational production of synoptic maps and profiles of critical atmospheric, oceanographic and land parameters Quality Control Users NWP Real-time tactical Non-tactical JTWC NHC NIC Others
19 Sensor System Errors Observation Vector Antenna - spillover -xpol - emission -polrotation - FOV intrusion - beam pointing Receiver - Freq set/stab - Passband set/stab -Sq. Law -NEDT - ΔG/G - Quantization -RFI Cal Targets -warm-load unif/stab - Sun-intrusion - emissivity - cold-space FOV (moon, S/C) CAL/VAL Ground Data Processing Ground Truth - Raobs/Lidar/dropsondes -Surface Obs. - Space/Time Coincidence - Accuracy - Research Field Campaigns - Magnetic Storms -Match-ups - Stratifications - Performance/QC - Anomalies ECTBP TDRP - Geo-location -EIA/Az SDRP - slope/offset -APC - RFI Detection - Resampling - Foot print Match TDR SDR NWP - Background Fields - C oincidence - Interpolations - Data Bases RTM -Antenna model - Receiver - Atmosphere O 2, H 2 O vapor, clouds, rain - Surface emissivity EDRP -Inversion Problem -Uniqueness/stability - Foot print Match - RFI Detection. -Mapping EDR
20 SSMIS Sensor Gain / rev
21 Solar Heating of Calibration Standard
22 Sensor Calibration Anomalies
23 Reflector Emission
24 Priorities for MIS Maintaining continuity of environmental information even at the sacrifice of performance above today s capabilities is the key factor in managing MIS Senior User Advisory Group (SUAG) Letter Prioritized capabilities 1. KPPs: Core Radiometry channels (10-89 GHz) 2. AVMP/AVTP Sounding Channels (50-60, 166 & 183 GHz) 3. Soil Moisture/Sea Surface Temp 6 GHz 4. Wind Direction: (10-37 GHz polarimetric channels) 5. Upper Atmospheric Sounding (60-63 GHz) Acquisition Decision Memorandum (ADM) directs NPOESS not to fall below heritage on its Key Performance Parameters (KPP) MIS provides NPOESS Soil Moisture and Wind Speed Key parameters ATMS and CrIS provides AVMP and AVTP; VIIRS provides SST and Imagery Upper Atmospheric Sounding not included Exist in a low operational readiness state and not proven to be operationally useful (yet) Next DMSP launch should address sensor data shortfalls Expecting maturation of requirements between now and F2 Most straightforward incremental capability to add with incremental development 2 4
25 Heritage Microwave Sensors SSM/I (DMSP) SSMIS (DMSP) AMSR (ADEOS) AMSR-E (NASA Aqua) WindSat (NRL) AMSU (NOAA) ATMS (NPOESS) Conical Scanners (Imagers/Sounders) Cross-Track Scanners (Sounders)
26 MIS Design Trade Space W/R/T IORD-II No Capability Useful Data/Marginal Min IORD Capability IORD or Better Unknown A: 1.2 meter Antenna B: 1.8 meter Ant. + 6 GHz x1: Core Imaging + Polarimetry x2: Core + Polarimetry + Sounding B8: Upper Air Sounding 26
27 MIS System Spec Baseline W/R/T IORD-II No Capability Useful Data/Marginal Min IORD Capability IORD or Better Unknown A, A-1, A-2 Provides Inadequate Spatial Resolution for IORD-II A: 1.2 meter Antenna B: 1.8 meter Ant. + 6 GHz B-2 Equals or Surpasses Legacy Performance (no UAS) x1: Core Imaging + Polarimetry x2: Core + Polarimetry + Sounding B8: Upper Air Sounding 27
28 Why This Sensor Concept? SSMIS Frequencies from ~18 GHz to 89 GHz Not capable of NPOESS Soil Moisture as defined in IORD 0.6 meter dish (Small and obsolescent design) 10 GHz considered necessary core capability (minimum based on current technology/needs) Wind Speed KPP met with 10 GHz Climate and Weather communities argued for 6 GHz on MIS to continue data continuity at NAS Decadal Survey 6 GHz not considered best value on < 1.8 meter reflector Soil Moisture KPP and SST very close to IORD with 6 GHz Sounding desired to support legacy requirements Wind Direction desired over UAS (SUAG documented prioritization of capabilities) Drop ~40 channels with no UAS CMIS: ~100 Channels; 2.2 meter reflector MIS: ~40 Channels; 1.8 meter reflector (less redundant channels) UAS simplest capability to incrementally upgrade for C3 28
29 Initial MIS Sensor Configuration NPOESS C2 Sensor (2016) 1.8m main reflector Core Imaging Channels: 10 VH; 23 V, 18 VH; 37 VH; 89 VH Atmospheric Sounding: GHz; 150/166 & GHz Low Frequency: 6.8 VH (with RFI mitigation) Polarimetric Channels: 10 PM or LR; 18 PMLR; 37 PM Upper Air Sounding: GHz [C3 Increment] ~CMIS channels Key EDRS: Soil Moisture, Sea Surface Winds, Sea Surface Wind Direction, Sea Surface Temperature Swath Width: ~1,700km Calibration: 2-point calibration Deployable structure 29
30 EDR Examples SSMIS Soil Moisture Capability Wind Vectors MIS Soil Moisture Capability 30
31 Impact to NWP From Loss of Data by Type (ECMWF) Global degradation Analysis No Satellite Losing all microwave sounders Losing all infrared sounder Losing all radiosonde T, q and u Losing all radiosonde T and q Ten years ago? TOVS NESDIS retrievals, AMV, more but lower quality radiosondes Impact of Microwave Data on NWP Has Significantly Increased After Saunders, R., et. al., Exploitation of Satellite Data at the UK Met Office,
32 ECMWF: SSMIS Assimilation Trials Southern Hemisphere Anomaly Correlation 500hPa height NO SAT NO SAT + SSMIS NO SAT + N15 AMSU SSMIS Pre-processed data: 40% flagged limited coverage tuning ongoing T sounding channels only 0.5K obs errors Graeme Kelly Days NH AC 500hPa height After Saunders, R., et. al., Exploitation of Satellite Data at the UK Met Office, Microrad 06, San Juan Puerto Rico.
33 Long Term Snow Cover Data Set National Snow and Ice Data Center (NSIDC) global monthly EASE-Grid snow water equivalent climatology for the Northern Hemisphere, December The overall data set comprises monthly satellite-derived snow water equivalent (SWE) climatologies from November 1978 through June The global data are gridded to the Northern and Southern 25 kilometer Equal-Area Scalable Earth Grids (EASE-Grids).[1] SOURCE: NASA. [1] Located at URL
34 No Frequency allocation for EESS in the C-band region RFI at 6- and 10-GHz
35 10 GHz RFI over Ocean
36 Summary Extensive investments in space-based passive microwave radiometry span three generations providing ever increasing capability NPOESS MIS development continues to represent the latest most capable operational microwave radiometer MIS is responsible for 18 EDRs (includes 2 NPOESS KPPs) MIS offers improvements to nearly all heritage EDRs: DMSP SSMIS: Better Horizontal Spatial Resolution NASA AMSR-E: RFI Mitigation for 6-GHz NRL WindSat: Similar Capability Improvements to weather forecasts will be realized with MIS atmospheric sounding, wind direction and all weather sea surface temperature capability Impact and mitigation of RFI must be considered in the current RF environment
37 Back-Up Slides
38 NPOESS VIIRS (Visible/Infrared Imager Radiometer Suite) Imagery Spatial Resolution: / EOS Dimensions: 134 x 141 x 85 cm Mass: 275 kg Power: 240 W Data Rate: 10.5 peak/8 avg Mbps Spectral Bands: 22 (Visible/ Near IR: 9 Day/Night Band:1 Mid - Wave IR: 8 Long - Wave IR: 4)
39 VIIRS Produces Data for 23 EDRs from 0.4 to 12 microns Visible Imagery Sea Surface Temperature
40 Passive Radiometry Missions Current and Past Missions At least 34 successful space-based missions either carry or have carried passive radiometers
41 Passive Radiometry Missions Future and Proposed Missions At least 19 different space-based radiometer designs have flown and least 7 more are in development
42 Imaging (SSM/I) Microwave Imager/Sounder Atmospheric Water / Clouds *Sea Surface Wind Speed Sea Ice Rain/Precipitation Design Drivers Sea Surface Wind Direction (WindSat) Temperature and Moisture Profiles / NWP (SSMIS) 50/60-GHz and 166/183-GHz measurements using conical-scan geometry Sea Surface Temperature and *Soil Moisture (AMSR + WindSat) * EDRs with KPP attributes 6- and 10-GHz V- and H-pol channels
43 Comparison of SSM/I and SSMIS SDRS
44 Retrieved Water Vapor Comparison
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