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Wade T. Crow, Concepcion Arroyo Gomez, Joaquín Muñoz Sabater, Thomas Holmes, Christopher R. Hain, Fangni Lei, Jianzhi Dong, Joseph G. Alfieri, and Martha C. Anderson

). This approach combines best-possible estimates of land surface states based on available observations and short-range atmospheric forecasts provided by the NWP system. In this regard, the European Space Agency (ESA) Soil Moisture Ocean Salinity (SMOS) mission ( Kerr et al. 2012 ), specifically designed to measure surface SM and ocean salinity from space, provides a unique opportunity to assimilate L-band microwave brightness temperature (Tb) observations that are highly sensitive to surface SM

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Anne Felsberg, Gabriëlle J. M. De Lannoy, Manuela Girotto, Jean Poesen, Rolf H. Reichle, and Thomas Stanley

. Here, we will investigate the potential of two L-band (1.4 GHz) microwave satellite missions that are dedicated to soil moisture monitoring, i.e., the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions ( Kerr et al. 2012 ; Entekhabi et al. 2010 ). We further use data from the Gravity Recovery and Climate Experiment (GRACE) mission, which provides anomalies in the vertically integrated terrestrial water storage (TWS), including groundwater, soil moisture, snow

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David A. Lavers, Shaun Harrigan, and Christel Prudhomme

modeled freshwater flux from the land to the ocean. The resulting reduced ocean salinity then in turn could affect the ocean circulation and degrade ocean–atmosphere interactions. It has been previously found in a project—named the Benefits of dynamically modeled river discharge input for ocean and coupled atmosphere–land–ocean systems ( Mercator Ocean 2020 )—that when coupling the land and the ocean with the GloFAS-ERA5 river discharge reanalysis, a large degradation was seen in ocean modeling skill

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Trent W. Ford, Steven M. Quiring, Chen Zhao, Zachary T. Leasor, and Christian Landry

.25° horizontal resolution. We use the ESA-CCI dataset in this study instead of an individual platform such as Soil Moisture Active Passive (SMAP; Entekhabi et al. 2010 ) or Soil Moisture and Ocean Salinity (SMOS L3; Kerr et al. 2010 ) because of their relatively short data records (~5 years and ~11 years, respectively). ESA-CCI provides daily soil moisture observations in units of volumetric water content (m 3 m −3 ). The Noah soil moisture dataset, which is part of the National Land Data Assimilation

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Nina Raoult, Catherine Ottlé, Philippe Peylin, Vladislav Bastrikov, and Pascal Maugis

soil moisture observational products available with which to confront the models and possibly improve their representation of soil moisture. These range from local in situ measurements making up the ISMN (International Soil Moisture Network; Dorigo et al. 2011 , 2013 ) to remotely sensed global products using active or passive microwave sensors, such as SMOS (Soil Moisture Ocean Salinity; Kerr et al. 2010 ), SMAP (Soil Moisture Active Passive; Entekhabi et al. 2010b ), or the ESA CCI SM

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Junxia Li, Xueping Bai, Yuting Jin, Fangbo Song, Zhenju Chen, Lixin Cai, Fenghua Zou, Mengzhu Jiang, Ruixin Yun, and Zhaoyang Lv

.4236/jwarp.2010.211111 . 10.4236/jwarp.2010.211111 Durack , P. J. , S. E. Wijffels , and R. J. Matear , 2012 : Ocean salinities reveal strong global water cycle intensification during 1950 to 2000 . Science , 336 , 455 – 458 , . 10.1126/science.1212222 Easterling , D. R. , J. L. Evans , P. Ya. Groisman , T. R. Karl , K. E. Kunkel , and P. Ambenje , 2000 : Observed variability and trends in extreme climate events: A brief review

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Peter J. Shellito, Sujay V. Kumar, Joseph A. Santanello Jr., Patricia Lawston-Parker, John D. Bolten, Michael H. Cosh, David D. Bosch, Chandra D. Holifield Collins, Stan Livingston, John Prueger, Mark Seyfried, and Patrick J. Starks

Jackson , T. J. , T. J. Schmugge , and J. R. Wang , 1982 : Passive microwave sensing of soil moisture under vegetation canopies . Water Resour. Res. , 18 , 1137 – 1142 , . 10.1029/WR018i004p01137 Jackson , T. J. , and Coauthors , 2012 : Validation of Soil Moisture and Ocean Salinity (SMOS) soil moisture over watershed networks in the U.S . IEEE Trans. Geosci. Remote Sens. , 50 , 1530 – 1543 , . 10

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Edgar L. Andreas, Rachel E. Jordan, and Aleksandr P. Makshtas

seawater that infiltrates the snowpack. Jordan et al. (2001) report our preliminary adaptations to SNTHERM. Here we summarize them more fully. All units in what follows are SI. Following Maykut and Untersteiner (1971) , we parameterize the thermal properties of sea ice in terms of its temperature depression T D below 0°C and its bulk salinity S (in psu). The thermal conductivity k si and apparent heat capacity c si of sea ice are thus, In these, k i is the thermal conductivity and c

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Bert G. Heusinkveld, Simon M. Berkowicz, Adrie F. G. Jacobs, Albert A. M. Holtslag, and Willy C. A. M. Hillen

manual microlysimeters was 8%, with an individual high of 14%. This is consistent with data obtained from a previous field campaign in 1997 on the same slope ( Jacobs et al. 2000a ). To explain the large difference between the playa and dune slope dew yields, we suggest that it can be attributed to the playa’s characteristic high silt, clay, and salinity levels. The dune slope surfaces, in contrast, have grain size distribution medians of 90 μ m for the 2–4-mm-thick crust and 230 μ m for the coarse

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Catherine Champagne, Andrew Davidson, Patrick Cherneski, Jessika L’Heureux, and Trevor Hadwen

-real-time measurements of soil moisture conditions at the surface. The Soil Moisture Ocean Salinity (SMOS) mission was launched in November 2009 with goals that included the direct measurement of soil moisture at the earth’s surface and the integration of these measurements into land surface models to estimate root zone soil moisture conditions ( Kerr et al. 2001 ). Beginning with the 2010 growing season and continuing to the end of the 2013 growing season, Agriculture and Agri-Food Canada (AAFC) piloted the use of

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