PPT-Quantification of Aquarius, SMAP, SMOS and Argo-Based Gridded Sea Surface Salinity Product

Fournier S Bingham FM Gonzalez Haro C Hayashi A Carlin KMU Brodnitz SK Gonzalez Gambau V and Kuusela M 2023 Quantification of Aquarius SMAP SMOS and ArgoBased Gridded Sea Surface Salinity Product Sampling Errors Remote Sensing https. alongshiptracksattheexpenseofaworsesynopticcover-age.Shipsalinityisalsomeasuredatafewmetersdepth.PriortoSMOSlaunch,H R. Bindlish, T. Jackson, M. Cosh. November 2014. Overview. Soil moisture algorithm. Soil moisture product. Validation. Linkage between Soil Moisture and SSS. Aquarius Soil Moisture Algorithm. The baseline soil moisture algorithm uses the . D. Vandemark, H. . Feng. Univ. of New Hampshire/EOS. N. . Reul. , F. . . Ardhuin. , B. . Chapron. . IFREMER/Centre de Brest. within . Aq. Cal/Val team efforts. OSST Meeting 2012. 2. OSST 2012. Overview. J. Boutin. 1. , N. Martin. 1. , G. Reverdin. 1. ,S. Morisset. 1. , X. Yin. 1. , L. Centurioni. 2 . and N. Reul. 3. . 1. LOCEAN, Sorbone Universités, UPMC/CNRS/IRD/MNHN, Paris, France. 2. SIO, La Jolla, CA, USA. Maximum as . Observed by . Aquarius. Frederick . Bingham (1. ), Julius Busecke, Arnold Gordon, Claudia Giulivi (2) and Zhijin Li (3). . (. 1) Center for Marine Science,. . University of North Carolina Wilmington, . J. Boutin. 1. , N. Martin. 1. , G. Reverdin. 1. ,S. Morisset. 1. , X. Yin. 1. , L. Centurioni. 2 . and N. Reul. 3. . 1. LOCEAN, Sorbone Universités, UPMC/CNRS/IRD/MNHN, Paris, France. 2. SIO, La Jolla, CA, USA. Algorithm. Frank . J. . Wentz and . Thomas . Meissner, . Remote Sensing Systems . Gary . S. . Lagerloef. , . Earth and Space Research. . David M. Le . Vine, . NASA Goddard. Presented at . 7. th. Aquarius/SAC-D Science Meeting. we compare measured . salinity across . metric distributions. . In . addition to traditional comparisons . between mean or median . values, the . 1%, 10%, 25%, 50%, 75%, 90% and 99% . quantiles of . the statistical . Seung-bum . Kim (JPL). Jae-hak . Lee (Korean Institute of Ocean Science and . Technology). Paolo de Matthaeis. . (GSFC). D. ata provision by I.C. Pang, Jeju Natl. Univ., S. Korea. Funded by OSST. Results available in JGR 2014 special issue.. Salinity. E. P. Dinnat. 1,2. , D. M. Le Vine. 1. , J. Boutin. 3. , X. Yin. 3. , . 1. Cryospheric Sciences Lab., NASA GSFC, Greenbelt, MD, U.S.A. 2. Chapman University, Orange, CA, U.S.A.. 3. LOCEAN, Paris, France. Rajat Bindlish. 1. , Thomas Jackson. 1. , Tianjie Zhao. 1. , Michael Cosh. 1. , Steven Chan. 2. , Peggy O'Neill. 3. , Eni Njoku. 2. , Andreas Colliander. 2. , Yann H. Kerr. 4. , Jiancheng Shi. 5. 1. USDA ARS Hydrology and Remote Sensing Lab, Beltsville, MD. E. Hackert, S. Akella, R. Kovach, K. Nakada, A. Borovikov, A. Molod, K. Drushka, and M. Jacob. Problem. : Satellite observes the top centimeter of the ocean. In rainy conditions, the vertical salinity gradient between SSS and first model layer (i.e., where these data are assimilated - S. Scientific Co-lead: J. Boutin (LOCEAN),N. Reul (IFREMER). Climate Research Group: D. Stammer and J. Khoeler (UHAM) . Project Manager: Rafael Catany (ARGANS). CCI CMUG Integration Meeting. Exeter 2018. . Thomas Meissner. 1. , Lucrezia Ricciardulli. 1. , Frank Wentz. 1. , . Andrew Manaster. 1. , Charles Sampson. 2. 1. Remote Sensing Systems, Santa Rosa, CA, USA. 2. NRL, Monterey, CA, USA. IOVWST Meeting, April 24 – 26, 2018.