PPT-H SAF Soil Moisture Data Services

Wolfgang Wagner Department of Geodesy and Geoinformation GEO Vienna University of Technology TU Wien httpwwwgeotuwienacat Active and Passive Microwave Remote Sensing Passive microwave sensors record . 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 . Colin Pettinati. Winter Ecology . Mountain Research Station 2014. University of Colorado, Boulder. Factors Controlling soil pH. Parent Material. Precipitation (moisture). Native Vegetation. Crops grown. Wade T. Crow. USDA Hydrology and Remote Sensing Laboratory, Beltsville, MD, USA . John D. Bolten. NASA Goddard Space Flight Center, Greenbelt, MD, USA . Research funded by a grant from the NASA Applied Sciences Program (W.T. Crow PI, Bradley Doorn, program manager). Soil . Moisture Active Passive (SMAP) Mission. SMAP-GPM Joint Mission . Teacher Workshop. GSFC Visitor’s Center. June 26, 2013. Peggy O’Neill, NASA GSFC. SMAP Deputy Project Scientist. Water is Vital for Life. PI: Cecilia Hidalgo (UBA) . . proyectoiai.serv.climaticos@gmail.com. http://serviciosclimaticos.blogspot.com.ar. /. Presentation. . made. . by. Hugo Berbery and . Julian. . Baez. 1. C. limate. . Merge . Precipitation Products for . Land . Surface Modeling. Abheera. . Hazra. Department of Civil, Infrastructure and Environmental Engineering. Viviana Maggioni. Department of Civil. , . Environmental . John Bolten. NASA Goddard Space Flight Center . Thanks:. . Xiwu Zhan . (NOAA NESDIS), . Curt Reynolds . (USDA FAS), . Christa Peters-Lidard . (NASA GSFC), . John . Eylander. . (AFWA) and . Sujay Kumar . John Bolten. NASA Goddard Space Flight Center . Thanks:. . Xiwu Zhan . (NOAA NESDIS), . Curt Reynolds . (USDA FAS), . Christa Peters-Lidard . (NASA GSFC), . John . Eylander. . (AFWA) and . Sujay Kumar . Long Term Pavement Performance Computed Parameter Moisture ContentO FHW-HRT-08-035 2008The ability to accurately monitor subsurface soil parameters on a continuous basis is extremely beneficial in pav Jacopo . Dari. . (1). , Pere Quintana-. Seguí. . (2). , Maria José . Escorihuela. . (3). , Luca Brocca . (4). , Renato Morbidelli . (1. ). , and Vivien Stefan . (3). (1) . University. . of Perugia, . Sponsored by the NASA Climate Indicators and Data Products for Future Climate Assessment Program. Kenneth Tobin (TAMIU). Wade Crow . and Jianzhi Dong (USDA ARS). William Teng (NASA GSFC/ADNET Systems Inc.. Rolf Reichle. 1. , Gabrielle DeLannoy. 1,2. , and . Wade Crow. 3. 1. NASA Goddard Space Flight Center Global Model and Assimilation Office. 2 . University of Louvain, Louvain, Belgium. 3. USDA ARS Hydrology and Remote Sensing Lab. Land Surface Data . Assimilation – Part 2 . Patricia de Rosnay. Outline. Part I (Monday 7. . March). . Introduction. Snow analysis. Screen level parameters analysis. ‏. Part II (Tuesday 8. . from . combined LST, SM, precipitation observations. Y. Zhao. , . F. . Cheruy. LMD/IPSL. . LST_cci. User Workshop . 2020.  . 24-26 . June 2020  . Can we use combined LST, SM, PRECIP data to detect the contribution of soil thermal inertia which is strongly dependent on soil moisture to daily variations in nighttime minimum temperature?.