PPT-MWR Roughness Correction Algorithm for the Aquarius SSS Ret

W Linwood Jones Yazan Hejazin Salem Al Nimri Central Florida Remote Sensing Lab University of Central Florida Orlando Aquarius Science Team Meting November 2014 Seattle WA USA Abstract. 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. Rain Impact . on the Aquarius . Salinity Retrievals. T. Meissner. , F. Wentz, J. Scott, K. Hilburn. Remote Sensing Systems. meissner@remss.com. 2014 Aquarius / SAC-D Science Team Meeting. November 11- 14, 2014. Debra A. Willey, Rana A. . Fine and Frank . J. Millero. Rosenstiel School, University of . Miami, . 4600 Rickenbacker Causeway, Miami, FL 33149 . USA. Introduction. The . unprecedented salinity coverage from the Aquarius satellite . Sky . Calibration. Aquarius: D. M. Le Vine. MWR: J. C. Gallo. Definition. Cold Sky Calibration: The observatory rotates 180 deg around its pitch axis from the normal Earth-viewing mode to a “sky” viewing mode. July 21, 2010. Seattle. 6. th. Aquarius/SAC-D Science Team meeting. Membership. S. Brown. R. Lang. D. . LeVine. L. Jones. D. . Vandenmark. , B. . Chapron. F. Wentz. S. . Yueh. Peter. Naoto. Carl. Liang. measurements. Wenqing Tang and Simon . Yueh. Jet Propulsion . Laboratoru. y. Drifters. N. of obs.. Pacific GYRE. 183453. MetOcean. 121940. ICM. 114784. http://www.locean-ipsl.upmc.fr/smos/. drifters. Transportation agencies devote significant resources towards collection of highly detailed and accurate pavement roughness data using profiler vans in order to support pavement maintenance decisions. Given the need of calibrated profiling equipment and specially trained personnel, they cannot afford to assess pavement roughness more frequently than once a year. . 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. by Gary Higgins. Outline. How effective have we been at correcting localized roughness at the project level?. Compare localized roughness reports from Colorado 2012 paving projects to ProVAL grinding simulation SAM using actual project data. . MWR SUTLER STORE. . This position will develop the store and merchandise for the primary purpose of serving Idaho Guardsmen and other service members training on the OCTC during the summer. This is a new addition to the Idaho MWR Program and is expected to develop into at . 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. Fournier S.. , Bingham F.M., Gonzalez-. Haro. C., Hayashi A., Carlin K.M.U., . Brodnitz. S.K., Gonzalez-. Gambau. V., and . Kuusela. M., 2023. Quantification of Aquarius, SMAP, SMOS and Argo-Based Gridded Sea Surface Salinity Product Sampling Errors. Remote Sensing. https://.