NASA Report to the GSICS Executive Panel

Transcription

1 NASA Report to the GSICS Executive Panel James J. Butler NASA Goddard Space Flight Center Greenbelt, MD USA Japan Meteorological Agency Tokyo, Japan July 15-16,

2 Agenda Instrument Updates MODIS AIRS VIIRS Instrument Intercomparisons CLARREO Status Future Missions 2

3 Instrument Updates 3

4 MODIS Terra and Aqua Instrument and Data Processing Update Both Terra MODIS (13 years) and Aqua MODIS (11 years) and their on-board calibrators continue to operate and function normally Only 1 additional noisy and inoperable detector in both Terra and Aqua MODIS over the last 3 years Collection 6 L1B reprocessing completed and data released to public Atmos. and land reprocessing to be started in early May and July 2013 Strong science applications using MODIS observations and data products Over 1000 new technical articles and 1500 new tech articles and proceedings combined Tech. and Proc. Articles: 8865 Avg. citation: 11.2/article Decade long high quality MODIS data Products have significantly contributed To a broad range of scientific studies and applications Thru 3/2013 4

5 MODIS Level 1B Collection 6 Algorithm MODIS L1B Collection 6 (C6) Plan and development started as early as Jan, 2008 Development, including all the changes to algorithms and LUTs, completed (reviewed and approved) Feb, 2012 List of algorithm changes provided in backup charts to this presentation C6 data processing started Feb, 2012 for Aqua and Aug, 2012 for Terra Products released to public July, 2012 for Aqua and Nov, 2012 for Terra 5

6 AIRS Instrument and Data Processing Status AIRS is in excellent health AIRS version 6 Level 2 science product generation software has been released AIRS Level 1B products: calibrated, geolocated radiances AIRS Level 2 products: standard T, moisture, surface, ozone, cloud and outgoing longwave radiation, CO, CH4, SO2 and dust, cloud cleared radiance, and support product (i.e. higher resolution standard product profiles, trace gas abundances, detailed QA assessments) AIRS Level 3 products: global products in 1x1 degree grid bins in 3 temporal resolutions: daily, 8-day, and monthly Changes from version 5 were confined to Level 2 and Level 3 there were no changes to the AIRS Level 1B software (radiances) Reprocessing of Level 2 for the entire mission is in progress 6

7 M8: 1240nm; M9: 1378nm; I3: 1610nm; M10: 1610nm; M11: 2250nm Suomi VIIRS Instrument and Data Processing Status The Suomi VIIRS instrument and its on-board calibrators continue to operate and function normally The VIIRS Sensor Data Record (SDR) algorithm for the reflected solar bands now accounts for time and wavelength dependent reflectance degradation of the rotating telescope assembly mirrors Curves: SD calibration gain trending Points: Lunar calibration gain trending Early in the mission, SNPP VIIRS exhibited large gain degradation in the near infrared and shortwave infrared vs time on-orbit due to WO x contamination incurred during fabrication of the telescope mirrors M1: 412nm; M2: 445nm; M3: 488nm DNB M4: 555nm; I1: 640m; M5: 672nm; M6: 746nm; M7: 865nm; I2: 865nm The physical degradation mechanism was determined thru Aerospace witness mirror sample testing The model for telescope reflectance degradation was determined using on-orbit solar diffuser/lunar data. Impact of up to 5% 7

8 Instrument Intercomparisons 8

9 NASA JPL AIRS/IASI/CrIS Comparisons At upcoming conferences, NASA JPL will present results from comparisons of AIRS, IASI, and CrIS There is excellent agreement among the instruments under clear and SNO conditions, but statistically significant disagreements under cloudy conditions Below is a plot of AIRS and CrIS brightness temperatures at 1231 cm -1 at Dome C differenced with in situ surface temperature measurements 9

10 NASA Langley MTSAT-1R and MTSAT-2 Inter-comparisons MTSAT-2 image Dec 21, 2010, 0:30 GMT MTSAT-1R minus MTSAT-2 Dec 21, 2010, 0:30 GMT Uniform radiance scenes show little difference Clear areas near bright clouds show larger differences Develop MTSAT-1 point spread function (PSF) to subtract contribution from area surrounding pixel PSF 6x10-5 4x10-5 2x x10-5 A peak=1.0-4x x pixel position Elliptical_Gauss MTSAT-1R & MODIS Aqua comparison before PSF correction MTSAT-1R & MODIS Aqua comparison after PSF correction 10 This is a GSICS success story, Arata Okuyama (JMA) provided the MTSAT-2 commissioning images, that made this PSF correction possible

11 NASA Langley Meteosat µm gain comparison using the MODIS Aqua 0.65µm band as reference Mean gains are within 1% MODIS Terra/Met-9 ray-match intercalibration (first inter-calibrate MODIS Terra to MODIS Aqua using SNOs over poles) Aqua-MODIS/Met-9 ray-match intercalibration Deep Convective Calibration using MODIS Aqua/Met-9 DCC reference radiance to predict MET-9 DCC radiance Libya-4 Daily Exo-atmospheric Radiance Model (DERM) (DERM built using reference GEO inter-calibrated with MODIS Aqua, then use DERM to predict target GEO) SCIAMACHY/Met-9 ray-match intercalibration (first inter-calibrate SCIAMACHY to MODIS Aqua using SNOs) 11

12 U. of Wisconsin Suomi NPP CrIS intercomparisons with EOS AIRS, Metop IASI and Suomi NPP VIIRS CrIS/AIRS brightness T (BT) intercomparisons using Simultaneous Nadir Overpasses (SNOs) over a wide range of latitude and longitude Comparison of the log scale BT distributions (i.e. left 6 plots) leads to mean BT difference distribution agreements of 0.12⁰ or better (i.e. right 6 plots) CrIS/IASI BT intercomparisons using Simultaneous Nadir Overpasses (SNOs) over northern, high latitude, nadir views Comparison of CrIS and IASI mean BTs from northern SNOs from April 2012 to November 2012 Weighted mean CrIS/IASI BT differences and uncertainties are less than a few tenths K Similar results obtained using southern SNOs 12

13 U. of Wisconsin Suomi NPP CrIS intercomparisons with EOS AIRS, Metop IASI and Suomi NPP VIIRS CrIS/VIIRS brightness T (BT) intercomparisons Time series of daily mean BT differences between VIIRS and CrIS from February 2012 to April 2013 for VIIRS bands at 4µm, 10.8µm, and 12µm Discontinuities due to adjustment to VIIRS blackbody T knowledge (March 2012) and planned VIIRS blackbody warm up/cool down linearity tests Since April 2012, the mean BT differences are less than 0.1K and are very stable Scan angle, scene T and orbit phase effects on VIIRS and CrIS BTs are being studied to fully understand instrument performance 13

14 Multi-Instrument Inter-Calibration (MIIC) Framework (C. Currey (PI NASA LaRC), A. Bartle, C. Lukashin, D. Doelling, and C. Roithmayr) 1) The MIIC Framework is a collection of software which predicts near co-incident measurements with matched viewing geometries for instruments on separate spacecraft and efficiently acquires these data from remote data servers using OPeNDAP and serverside functions. - The MIIC predictors account for the sensor operation mode (e.g. cross-track) 2) New server-side functions will complement those now in place for format translation and subset selection to minimize the computation and network demands placed on instrument teams that perform multi-instrument inter-calibration in the distributed and heterogeneous context of the NASA Earth Science infrastructure. Implemented server-side functions: - Data equal-angle gridding - Spectral convolution - Spatial convolution 3) The current MIIC project demonstrates LEO-GEO and LEO-LEO inter-calibrations use cases: - MODIS/Aqua and GOES-13; - MODIS/Aqua and SCIAMACHY/Envisat. 4) Future plans: 1) deploy MIIC web-services at the LaRC ASDC is planned; 2) collaborate with NOAA NCDC to access data from CLASS using MIIC services; 3) extend features; 4) continue to collaborate with GSICS Research and Data Working Groups 14

15 CLARREO Status 15

16 CLARREO Status: Reflected Solar (RS) Instrument (320nm to 2300nm) 1) Objective: Enabling climate benchmark using the Climate Absolute Radiance and Refractivity Observatory (CLARREO) for reference inter-calibration of existing operational sensors -climate-focused mission currently in Pre-Phase A with mission and science definition teams working to advance the science of CLARREO, explore alternative implementation strategies, and reduce technical risk 2) CLARREO Reference Inter-calibration will provide data to determine and correct operational sensors for: - Sensor offset and gain - Spectral response change on orbit - Sensitivity to Polarization - Non-linearity 3) CLARREO RS inter-calibration goal: uncertainty contribution 0.15% (k=1) over autocorrelation time period 0.8 year Wielicki & CLARREO SDT, Achieving Climate Change Absolute Accuracy in Orbit, BAMS 2013 Available online at 4) High priority inter-calibration targets: - On-orbit sensors: CERES & VIIRS/JPSS, AVHRR/Metop, GEO Imagers, TEMPO, Landsats, ESA Sentinels (optical) - Surface: Dome C, desert sites - Space: lunar irradiance 16

17 CLARREO RS Instrument On-Orbit Pointing Operations Matching requirements: - Within +/- 5 min of the JPSS passing; - VZA match within 1.4 ; - RAZ match within 0.5 o ; - SZA < 75 o ; - At least 10 km effective width of swath. Inter-calibration sampling studies: - CLARREO in polar 90 o inclination orbit - The ISS orbit - Sampling for both, LEO and GEO targets Figure: CLARREO RSS boresight locations, which matched JPSS cross-track data over one year time period. CLARREO in P90 orbit. 2-D pointing on-orbit is required. Time/space/angle matching to obtain ensemble of samples with data matching noise 1% 17

18 CLARREO Reflected Solar (RS) Calibration Demonstration System (CDS) Solar/Lunar for Absolute Reflectance Imaging Spectrometer (SOLARIS) Spectral range: nm Spectral sampling: 4 nm Spectral resolution: 8 nm Swath width at nadir from 600 km orbit: >100 km GIFOV < km Spatial resolution per sample: 70% of energy from within a 0.5 km x 0.5 km area 95% within a 1.0 km x 1.0 km area SNR > 33 for λ < 900 nm SNR > 25 for λ > 900 nm Polarization sensitivity for 100% polarized input: <0.50% (TBD) below 1000 nm and <0.75% (TBD) at other wavelengths Radiometric calibration accuracy: 0.3% of albedo (integration of reflectance across all wavelengths) and within individual bands 18

19 CLARREO RS CDS (a.k.a. SOLARIS) Detector-based Calibration using Tunable Laser Source Traceability flow from NIST to the CLARREO calibration demonstration system (called SOLARIS) POWR Primary optical Watt Radiometer Full-field spectral and radiometric characterization On March 23, 2013, SOLARIS participated in a field intercalibration campaign at Red Lake Playa, Arizona, with ground based spectrometers and the NASA G-LiHT aircraft instrument coupled 19 with Landsat-7 and Landsat-8 overflights

20 CLARREO InfraRed (IR) Calibration Demonstration System (CDS) Compact, Demonstration, Four-Port, Fourier Transform Spectrometer operating from the mid to far-ir (5-50mm) with resolution 0.5cm -1 Goal is to measure brightness temperatures accurate to 0.1K (k=3), for K scenes (CLARREO IR Req.) Vac. Chamber Housing CDS LN 2 Cold Cal. Source Characterize systematic radiance measurement uncertainty & refine instrument performance model Variable Scene Temperature Blackbody (VTBB) Scene Select Housing Pyroelectric Detector (not visible) Bolometer Detector Develop a cost-effective instrument Design Create a flexible and modular instrument design testbed operating in a controlled thermal and acoustic environment 20

21 CLARREO IR CDS Brightness Temperature Results 2 hrs. data at each temperature Bolometer: 10pt., 5cm -1 bins Pyroelectric: 50pt., 25cm -1 bins 21

22 CLARREO IR CDS Status Radiometric Accuracy Assessment w/ Current Design Complete: For the tested range of 200K to 320K scene temperature, over the spectral range cm -1 where responsivity for both detector channels is high: Radiance bias is generally less than W/m 2 sr cm -1 ; Brightness temperature bias is generally less than 0.2K; Bolometer bias is dominated by uncorrected nonlinearity; There may still be a source of bias in the pyroelectric channel that is not yet accounted for. Full Measurement Uncertainty Report: July 24,

23 Future Missions 23

24 Upcoming Missions Mission Instruments Projected Launch Date TCTE TIM 10/2013 GPM Core GMI; DPR (Japan) 2/2014 ESSP/OCO-2 3 grating spectrometers 7/2014 SMAP L-band radiometer & radar 10/2014 SAGE-III (ISS) SAGE-III 12/2014 GOES-R ABI, GLM 10/2015 GRACE-FO (US/Germany) GPS; HAIRS; USO; SCA (Denmark); SSA (France) 8/2016 PFF-1 TSIS 8/2016 ICESat-2 ATLAS; GPS 12/2016 CYGNSS (EV-2) 8 GPS µ-satellites JPSS-1 ATMS; CERES; CrIS; OMPS-N; VIIRS 2017 TEMPO (EV-1) UV & Vis Offner grating spectrometer 2017 ESSP/OCO-3 3 grating spectrometers 2017 SWOT Ka band radar interferometer 2020 PACE Ocean color spectrometer; polarimeter (TBD) 2020 JPSS-2 ATMS; RBI; CrIS; OMPS-N & L; VIIRS 2021 ASCENDS LIDAR >2021 ACE Spectrometer; polarimeter; LIDAR; Cloud Radar >2021 GEO-CAPE UV-Vis-NIR IR imagers >2021 HyspIRI Hyperspectral & TIR imagers >2021 L-band SAR InSAR >2021 CLARREO IR &/or VisNiRSwir spectrometers; GNSS-RO 2022 Spacecraft provided by NASA Spacecraft not provided by NASA 24

25 Acknowledgements The material presented in this talk was provided by the colleagues listed below MODIS: Jack Xiong (NASA) and the MODIS Characterization Support Team AIRS & AIRS/IASI/CrIS comparisons: Denis Elliott (JPL) VIIRS: Jack Xiong (NASA) and the VIIRS Characterization Support Team MTSAT-1R and MTSAT-2 comparisons & Meteosat µm gain comparisons: Dave Doelling (NASA) CrIS/AIRS/IASI/VIIRS comparisons: Dave Tobin (U. of Wisconsin) Multi-Instrument Inter-Calibration Framework & CLARREO RSB: Costy Lukashin (NASA) CLARREO RSB CDS: Joel McCorkel (NASA) CLARREO IR CDS: Marty Mlynczak (NASA), Dave Johnson (NASA), & Rich Cageao (NASA) 25

26 NASA Earth Science Division Operating Missions Questions? 26

27 Backup Slides 27

28 MODIS L1B C6 Product Changes Reflective Solar Bands (RSB) SD degradation at 936 nm included (previous degradation normalized at 936 nm) Time dependent RVS for all VIS/NIR bands, including bands Detector bias corrections (derived from EV data) and detector dependent RVS applied to Terra bands 3, 8-12 and Aqua bands 8-12 EV response trending used to correct calibration drifts noticeable in recent years at different AOIs (including SD AOI) for Terra bands 1-4, 8, 9, 10 (proposed) and Aqua 8-9 SD to provide radiometric calibration reference Lunar trending to track on-orbit radiometric change EV trending at different AOIs to track on-orbit changes in RVS Thermal Emissive Bands (TEB) Others Use BB cool-down data to compute TEB nonlinear calibration coefficients Use a0=0 for Terra PV bands mirror side 1 (mirror side 2 a0 is adjusted to minimize the mirror side difference) and a0=0 for Terra/Aqua b31-32 Aqua pre-launch a2 (used in L1B) are adjusted to capture on-orbit changes using on-board BB calibration, while keeping the small initial difference Add FPA temperature dependence to the fixed b1 for Aqua bands 33, 35, and 36 when the BB is operated above their saturation temperatures Fill-value for inoperable detectors and QA flag for inoperable or noisy detectors at sub-frame level Improved implementation of calibration uncertainty algorithm (based on actual on-orbit calibration/retrieval with time, AOI, and scene dependence) 28 L1B code fix for sector rotation data anomaly (during lunar roll)

29 MODIS References Journal Papers Xiong et. al, Multi-year On-orbit Calibration and Performance of Terra MODIS Reflective Solar Bands, IEEE TGRS, Vol. 45, No. 4, , 2007 Xiong et. al, Multiyear On-orbit Calibration and Performance of Terra MODIS Thermal Emissive Bands, IEEE TGRS, 46 (6), , 2008 Xiong et. al Aqua MODIS Thermal Emissive Bands On-orbit Calibration, Characterization, and Performance, IEEE TGRS, 47(3), , 2009 Xiong et. al, On-Orbit Calibration and Performance of Aqua MODIS Reflective Solar Bands, IEEE TGRS 48(1), , 2010 Toller et. al, Terra and Aqua Moderate-resolution Imaging Spectroradiometer Collection 6 Level 1B Algorithm, to be published, J. Appl. Remote Sensing, 2013 SPIE Papers Xiong et. al, Terra and Aqua MODIS calibration algorithms and uncertainty analysis, Proc. SPIE 5978, no V (2005) Sun et. al MODIS RSB calibration improvements in Collection 6 Proc. SPIE 8528, no N (2012) Wenny et. al MODIS TEB calibration approach in collection 6 Proc. SPIE 8533, no M (2012) 29

30 Recent References on CLARREO Inter-calibration in the RS C.M. Roithmayr, and P.W. Speth, Chap. 13, Analysis of Opportunities for Intercalibration between Two Spacecraft," Advances in Engineering Research, Vol. 1, edited by V. M. Petrova, Nova Science Publishers, Hauppauge, NY, 2012, pp C.M. Roithmayr, C. Lukashin, P.W. Speth, K. Thome, B.A. Wielicki, D.F. Young, CLARREO Approach for On-Orbit Reference Inter-Calibration of Reflected Solar Radiance Sensors, submitted to IEEE Tran. Geo. Rem. Sensing, February, C.M. Roithmayr, C. Lukashin, P.W. Speth, K. Thome, D.F. Young, B.A. Wielicki, Opportunities to Intercalibrate Radiometric Sensors from International Space Station, in preparation for submission to JTECH, July, C. Lukashin, B.A. Wielicki, D.F. Young, K. Thome, Z. Jin, and W. Sun, Uncertainty Estimates for Imager Reference Inter-Calibration With CLARREO Reflected Solar Spectrometer, IEEE TGRS, Special Issue on Instrument Inter-calibration, DOI: /TGRS , Wenbo Sun and C. Lukashin, Modeling polarized solar radiation from ocean-atmosphere system for CLARREO inter-calibration applications, Atmos. Chem. Phys. Discuss., 13, 1 58, C. Lukashin, Z. Jin, D.G. Macdonnell, K. Thome, W. Sun, B.A. Wielicki, D.F. Young, Requirement for Instrument Sensitivity to Polarization for Climate Observing System in Reflected Solar, in preparation for submission to Journal of Geophysical Research, Wielicki & CLARREO SDT, Achieving Climate Change Absolute Accuracy in Orbit, BAMS 2013 Available online at 30

31 Acronyms ABI Advanced Baseline Imager ICESat Ice, Cloud, and land Elevation Satellite ACE ASCENDS Aerosol-Clouds-Ecosystems Active Sensing of CO2 Emissions over Nights, Days, and Seasons InSAR JPSS Interferometric Synthetic Aperture Radar Joint Polar Satellite System ATMS ATLAS CLARREO CERES CrIS CYGNSS DPR ESSP EV GLM Advanced Technology Microwave Sounder Advanced Topographic Laser Altimeter System Climate Absolute Radiance and Refractivity Observatory Clouds and the Earth s Radiant Energy System Crosstrack Infrared Sounder Cyclone Global Navigation Satellite System Dual frequency Precipitation Radar Earth System Science Pathfinder Earth Venture Geostationary Lightning Mapper LIDAR OCO OMPS PACE RBI SAGE SCA SIRCUS SMAP SOLARIS LIght Detection And Ranging Orbiting Carbon Observatory Ozone Mapping and Profiler Suite Pre-Aerosol, Clouds, and ocean Ecosystem Radiation Budget Instrument Stratospheric Aerosol and Gas Experiment Star Camera Assembly Spectral Irradiance and Radiance responsivity Calibrations using Uniform Sources Soil Moisture Active Passive Solar/Lunar for Absolute Reflectance Imaging Spectrometer GEO-CAPE GMI GNSS-RO GPM GEOstationary Coastal and Air Pollution Events GPM Microwave Imager Global Navigation Satellite Systems- Radio Occultation Global Precipitation Measurement SSA SWOT TCTE TEMPO SuperStar Accelerometer Suface Water Ocean Topography Total solar irradiance Calibration Transfer Experiment Tropospheric Emissions: Monitoring of Pollution GPS Global Positioning System TIM Total Irradiance Monitor GRACE-FO HyspIRI Gravity Recovery And Climate Experiment-Follow On Hyperspectral InfraRed Imager TSIS VIIRS Total Solar Irradiance Sensor Visible Infrared Imager Radiometer 31 Suite