Multi-sensor Improved Sea Surface Temperatures Project
- 1. Multi-sensor Improved Sea-Surface Temperature for IOOS MISST PIs Gentemann, Cornillon, Casey and project partners: 28 scientists from Navy, JPL, NOAA, academia, and private industry. Through international cooperation, MISST is providing 12 satellite SSTs in NRT at their native sampling (L2 data) and gap-free NRT data at 1 km, daily resolution. The L2 satellite data are used to make daily high resolution gap free analyses of SST that are used operationally. NRT are available from the PO.DAAC and NOAA ERDDAP. Historical archive at NOAA NCEI (NODC). Above shows the ATN’s integration of 1 km, daily, gap-free SST with animal telemetry (cetacean, fish, pinniped, seabirds, and turtles) information to gain a better understanding of the ocean ecosystem To the left shows “Turtlewatch” which uses another MISST gap-free SST analysis to set alerts of areas to avoid loggerhead turtle interactions
- 2. http://www.camilleseaman.com/Art ist.asp? ArtistID=3258&Akey=WX679BJN &ajx=1#!P118975_I2_1543930 http://www.camilleseaman.com/Art ist.asp? ArtistID=3258&Akey=WX679BJN &ajx=1#!P118975_I2_1543930 Sea Ice Remnant Svalbard July 17, 2008 Image credit: Camille Seaman
- 3. Multi-sensor Improved Sea Surface Temperature: continuing the GHRSST partnership & improving Arctic data PI: Chelle L. Gentemann, Earth and Space Research Co-I: Peter Minnett, University of Miami Co-I: Michael Steele, University of Washington 16 partners in : Industry: Richard Jenkins (Saildrone), Jean-Francois Cayula (Vencore) Academia: Sandra Castro (U.Colorado), Peter Cornillon (U.Rhode Island), Dale Robinson (UC Santa Cruz), Andy Harris (U. Maryland) Governmental: NASA: Edward M. Armstrong (JPL/Caltech), Toshio Mike Chin (JPL/Caltech), Jorge Vazquez (JPL/Caltech), Vardis Tsontos (JPL/Caltech) Governmental: NOAA: Kenneth Casey (NCEI), Edward Cokelet (NOAA/PMEL), Eileen Maturi (NOAA/NESDIS/STAR), Gary Wick (NOAA/OAR/ESRL), Cara Wilson (NOAA/NMFS/SWFSC) Governmental: ONR: Charlie Barron (NRL/SSC) New Project 2018 - 2023
- 4. Project objectives 1) Coordinate and integrate new SST observations (e.g. GOES-R, VIIRS); improve data access; management and interoperability; and maintain and strengthen international collaboration. 2) Explore improving SST products through improved or expanded in situ SST observations in the Arctic 3) Focus on improving accuracy and uncertainty estimates of SSTs at high-latitudes 4) Explore improving SST products particularly in marginal ice zones through research into high latitude air-sea-ice interactions and regional ocean-atmosphere-ice feedbacks
- 5. Data 1) Coordinate and integrate new SST observations (e.g. GOES-R, VIIRS); improve data access; management and interoperability; and maintain and strengthen international collaboration. Coordinate with the GHRSST Project Office (GHRSST-PO) on the proposed new distributed data system with a single point of entry Images from: NOAA, LTSRF, GHRSST-PO
- 6. 2) SST algorithm development https://icdc.cen.uni- hamburg.de/fileadmin/user_upload/ icdc_Dokumente/MODIS/kilpatric ketal_AdecadeofSeaSurfaceTemper aturefromMODIS_RSE_165_27- 41_2015.pdf Image credit: IQUAM NOAA In situ SST observations 12/2017
- 7. More in situ data 2) Explore improving SST products through improved or expanded in situ SST observations in the Arctic Uptempo buoys, AXCTDs, Glider CTDs, Ship temperature data, Saildrone USVs (existing & future!) Integrate data into ICOADS & MDB
- 8. 5 Arctic Cruises Five 90-day cruises to Arctic Additional SST profile obs Improved SST skin Image credit: NOAA PMEL Image credit: Saildrone
- 9. SST algorithms 3) Focus on improving accuracy and uncertainty estimates of SSTs at high-latitudes IR -at high latitudes different algorithm formulations -very dry atmosphere. -surface emissivity more important PMW -10.7 channel not good for SST. -Wind speed and direction errors lead to larger errors. Algorithm development: -RTM – simulated TB based on environmental conditions that are not well sampled -In situ databases – not well sampled at high latitudes
- 10. SST algorithms 3) Focus on improving accuracy and uncertainty estimates of SSTs at high-latitudes IR -at high latitudes different algorithm formulations -very dry atmosphere. -surface emissivity more important PMW -10.7 channel not good for SST. -Wind speed and direction errors lead to larger errors. Algorithm development: -RTM – simulated TB based on environmental conditions that are not well sampled -In situ databases – not well sampled at high latitudes
- 11. 4) Explore improving SST products particularly in marginal ice zones through research into high latitude air-sea-ice interactions and regional ocean-atmosphere-ice feedbacks Image credit: GHRSST Project Office What is a foundation SST? How do L4 handle SST in the MIZ? How do salinity layers affect upper ocean heating? Measure turbulent heat fluxes (in situ) at high latitudes. How does upper ocean stratification affect air-sea interactions?
- 12. http://www.camilleseaman.com/Art ist.asp? ArtistID=3258&Akey=WX679BJN &ajx=1#!P118975_I2_1543930 http://www.camilleseaman.com/Art ist.asp? ArtistID=3258&Akey=WX679BJN &ajx=1#!P118975_I2_1543930 Sea Ice Remnant Svalbard July 17, 2008 Image credit: Camille Seaman -Open data policy -Encourage open source software policy (OSS) -OSS netcdf in situ to ICOADS format converter -NEW Arctic data (2015 – 2023) to be put into ICOADS -Contact me if you have Arctic research data