1 / 32

SPIE Defense + Security + Sensing Technology 6 May 2014, Baltimore, MD

SPIE Defense + Security + Sensing Technology 6 May 2014, Baltimore, MD. Status of JPSS SST Products Alexander Ignatov, Prasanjit Dash, Xingming Liang, Boris Petrenko, John Stroup, Yury Kihai, Irina Gladkova, Marouan Bouali, Karlis Mikelsons , John Sapper, Feng Xu, Xinjia Zhou

tonya
Download Presentation

SPIE Defense + Security + Sensing Technology 6 May 2014, Baltimore, MD

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. SPIE Defense + Security + Sensing Technology6 May 2014, Baltimore, MD Status of JPSS SST Products Alexander Ignatov, Prasanjit Dash, Xingming Liang, Boris Petrenko, John Stroup, Yury Kihai, Irina Gladkova, Marouan Bouali, KarlisMikelsons, John Sapper, Feng Xu, Xinjia Zhou NOAA; CIRA; GST Inc; CUNY Bruce Brasnett Canadian Met Centre Status of JPSS SST

  2. JPSS Program – Mitch Goldberg, Kathryn Schontz, Bill Sjoberg NASA SNPP Project Scientist – Jim Gleason NOAA NDE Team – Tom Schott, Dylan Powell, Bonnie Reed JPSS DPA – Eric Gottshall, Janna Feeley, Bruce Gunther VIIRS SDR & GSICS – Changyong Cao, Frank DeLuccia, Jack Xiong, Mark Liu, Fuzhong Weng NESDIS/STAR JPSS Team – Ivan Csiszar, Lihang Zhou, Paul DiGiacomo, many others NOAA CRTM Team – Yong Han, Yong Chen, Mark Liu Acknowledgements Status of JPSS SST

  3. JPSS SST Team Status of JPSS SST

  4. VIIRS SST Products IDPS– NOAA Interface Data Processing Segment • Official NPOESS SST EDR Product • Developed by NGAS, produced by Raytheon • Now owned by NOAA JPO ACSPO–NOAA Advanced Clear-Sky Processor for Ocean • NOAA heritage SST and clear-sky radiance system • Processes full swath and each SST pixel (no sub-sampling) • Runs CRTM with 1st guess SST and atmospheric fields. Used for cloud screening, physical SST being explored • Pattern-recognition cloud masking improvements underway NAVO–SEATEMP • Builds on NAVO AVHRR heritage • In turn builds on NOAA pre-ACSPO heritage system, transitioned from NOAA to NAVO in 1994, “Shared Processing Agreement” Status of JPSS SST

  5. Current Status of the 3 products IDPS– NOAA Interface Data Processing Segment • Produced, archived at CLASS, monitored in SQUAM • In Jan’2014, JPO recommended to “discontinue the IDPS EDR and concentrate on ACSPO development and Cal/Val” • Will be phased out once ACSPO SST is archived at JPL/NODC ACSPO– NOAA Advanced Clear-Sky Processor for Ocean • Operational with global AVHRR 4km GAC and 1km FRAC • Experimental w/Terra/Aqua MODIS Jan’2012 • Experimental w/S-NPP VIIRS Jan’2012; Operational Mar’2014 • GDS2 VIIRS SST to be archived at JPL/NODC (pending JPL) NAVO– SEATEMP • Operational with AVHRR GAC data • NAVO VIIRS SST archived at JPL since May 2013 Status of JPSS SST

  6. Objective & Methodology • Objective: Compare ACSPO and NAVO SSTs to advise users on the specifics of the two products • Methodology: Compare ACSPO/NAVO SST domain & performanceagainst two global reference SSTs • L4 SST (Canadian Met Centre CMC0.2 Analysis. Note that VIIRS data are not assimilated in CMC0.2) • in situ SST (QCed drifting buoys in iQuam www.star.nesdis.noaa.gov/sod/sst/iquam/) • Data: onerepresentative day of global data • – 23 April 2014 – in SST Quality Monitor (SQUAM) • www.star.nesdis.noaa.gov/sod/sst/squam/ Status of JPSS SST

  7. NIGHT: ACSPO L2 minus CMC L4 23 April 2014 • Delta close to zero as expected • Cold spots – Residual Cloud/Aerosol leakages Status of JPSS SST

  8. NIGHT: NAVOL2 minus OSTIA L4 23 April 2014 • Retrievals limited to VZA<54° Status of JPSS SST

  9. NIGHT: ACSPO L2 minus CMC L4 23 April 2014 • Shape close to Gaussian Status of JPSS SST

  10. NIGHT: NAVOL2 minus CMC L4 23 April 2014 • Shape close to Gaussian • Domain smaller, STD slightly better Status of JPSS SST

  11. NIGHT: ACSPO L2 minus in situ SST 23 April 2014 • Much sparser data coverage • Not fully representative of the globe Status of JPSS SST

  12. NIGHT: NAVOL2 minus in situ SST 23 April 2014 • Much sparser data coverage • Not fully representative of the globe Status of JPSS SST

  13. NIGHT: ACSPO L2 minus in situ SST 23 April 2014 • Shape close to Gaussian – small cold tail • Performance Stats well within specs (Bias<0.2K, STD<0.6K) Status of JPSS SST

  14. NIGHT: NAVOL2 minus in situ SST 23 April 2014 • Shape close to Gaussian – small cold tail • Performance Stats well within specs (Bias<0.2K, STD<0.6K ) Status of JPSS SST

  15. NIGHT – Summary ΔT = “VIIRS minus CMC” SST (expected ~0) • IDPS: SST domain is +1% larger than ACSPO, All stats degraded • NAVO: SST domain is factor of ×3 smaller than ACSPO, stats improved ΔT = “VIIRS minus in situ” SST (expected ~0) • IDPS: SST domain is +13% larger than ACSPO, All stats degraded • NAVO: SST domain is factor of ×3 smaller than ACSPO, stats comparable Status of JPSS SST

  16. DAY – Summary ΔT = “VIIRS minus CMC” SST (expected ~0) • IDPS: SST domain is comparable with ACSPO, All stats degraded • NAVO: SST domain is factor of ×3 smaller than ACSPO, stats comparable ΔT = “VIIRS minus in situ” SST (expected ~0) • IDPS: SST domain is +5% larger than ACSPO, All stats degraded • NAVO: SST domain is factor of ×3 smaller than ACSPO, stats improved Status of JPSS SST

  17. ACSPO_V2.30b01_NPP_VIIRS_2014-01-18_1440-1450_20140314.174252_NAVOACSPO_V2.30b01_NPP_VIIRS_2014-01-18_1440-1450_20140314.174252_NAVO Africa Missed lines? SEATEMP Status of JPSS SST Rectangular shapes?

  18. Africa ACSPO Status of JPSS SST

  19. ACSPO_V2.30b01_NPP_VIIRS_2014-01-18_1810-1819_20140314.184153_NAVOACSPO_V2.30b01_NPP_VIIRS_2014-01-18_1810-1819_20140314.184153_NAVO Florida Tri-angular shape? SEATEMP Status of JPSS SST

  20. Florida ACSPO Status of JPSS SST

  21. ACSPO_V2.30b01_NPP_VIIRS_2014-01-18_2030-2039_20140314.192134_NAVOACSPO_V2.30b01_NPP_VIIRS_2014-01-18_2030-2039_20140314.192134_NAVO India Too-Regular shapes? SEATEMP Status of JPSS SST

  22. India ACSPO Status of JPSS SST

  23. ACSPO_V2.30b01_NPP_VIIRS_2014-01-18_0440-0450_20140314.145310_NAVOACSPO_V2.30b01_NPP_VIIRS_2014-01-18_0440-0450_20140314.145310_NAVO Missed lines? Tri-angular shape? China Korea SEATEMP Status of JPSS SST

  24. China Korea ACSPO Status of JPSS SST

  25. Users’ Feedback Status of JPSS SST

  26. Some Early Results Assimilating ACSPO VIIRS L2P Datasets Bruce Brasnett Canadian Meteorological Centre May, 2014

  27. ACSPO VIIRS L2P Datasets • Received courtesy of colleagues at STAR • Two periods: 1 Jan – 31 Mar 2014 & 15 Aug – 9 Sep 2013 • Daily coverage is excellent with this product • Experiments carried out assimilating VIIRS data only and VIIRS data in combination with other satellite products • Rely on independent data from Argo floats to verify results • Argo floats do not sample coastal regions or marginal seas Status of JPSS SST

  28. Assessing relative value of 2 VIIRS datasets: NAVO vs. ACSPO Using ACSPO instead of NAVO improves assimilation Status of JPSS SST

  29. Coverage for 2014/02/01 • Text NAVO AVHRR19 ACSPO VIIRS

  30. Coverage for 2013/09/01 ACSPO VIIRS NAVO AVHRR18 & 19 and Metop-A combined

  31. Summary • ACSPO VIIRS L2P is an excellent product • Based on the Jan – Mar 2014 sample, VIIRS contains more information than either the OSI-SAF MetOP-A or the RSS AMSR2 datasets • L2P ancillary information: quality level flags and wind speeds are useful but experiment with SSES bias estimates was inconclusive • Current plan at CMC is to assimilate ACSPO VIIRS L2P dataset when it becomes available Status of JPSS SST

  32. Conclusion and Near-Future Work • ACSPO and NAVO are two viable VIIRS SST choices for users • Both are available in GDS2 (or shortly will be) via JPL/NODC • ACSPO retrieval domain is larger than NAVO, by a factor of ~3. (NAVO: swath VZA<54°, more conservative cloud mask) • NAVO STDs are smaller than ACSPO by a narrow margin • Initial assimilation in CMC L4 analysis suggests that ACSPO adds information to the currently used L2 SSTs (AMSR2, OSI SAF and NAVO AVHRR, NAVO VIIRS), mainly due to coverage • ACSPO has a warm bias in the North latitudes, and SSES bias does not improve assimilation Near-Future ACSPO tasks • Implement destriping operationally (M. Bouali’spresentation) • Pattern recognition mask improvement (I. Gladkova’spresentation) • Improve performance in high-latitudes • Establish reprocessing and back-fill ACSPO VIIRS to Jan’2012 Status of JPSS SST

More Related