{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T13:52:55Z","timestamp":1770817975757,"version":"3.50.1"},"reference-count":73,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2020,6,24]],"date-time":"2020-06-24T00:00:00Z","timestamp":1592956800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"POMME-V project","award":["CDT-R056-L00-T00"],"award-info":[{"award-number":["CDT-R056-L00-T00"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>LDAS-Monde is a global land data assimilation system (LDAS) developed by Centre National de Recherches M\u00e9t\u00e9orologiques (CNRM) to monitor land surface variables (LSV) at various scales, from regional to global. With LDAS-Monde, it is possible to jointly assimilate satellite-derived observations of surface soil moisture (SSM) and leaf area index (LAI) into the interactions between soil biosphere and atmosphere (ISBA) land surface model (LSM) in order to analyze the soil moisture profile together with vegetation biomass. In this study, we investigate LDAS-Monde\u2019s ability to predict LSV states up to two weeks in the future using atmospheric forecasts. In particular, the impact of the initialization, and the evolution of the forecasted variables in the LSM are addressed. LDAS-Monde is an offline system normally driven by atmospheric reanalysis, but in this study is forced by atmospheric forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) for the 2017\u20132018 period over the contiguous United States (CONUS) at a 0.2\u00b0 \u00d7 0.2\u00b0 spatial resolution. These LSV forecasts are initialized either by the model alone (LDAS-Monde open-loop, without assimilation) or by the analysis (assimilation of SSM and LAI). These two forecasts are then evaluated using satellite-derived observations of SSM and LAI, evapotranspiration (ET) estimates, as well as in situ measurements of soil moisture from the U.S. Climate Reference Network (USCRN). Results indicate that for the three evaluation variables (SSM, LAI, and ET), LDAS-Monde provides reasonably accurate and consistent predictions two weeks in advance. Additionally, the initial conditions after assimilation are shown to make a positive impact with respect to LAI and ET. This impact persists in time for these two vegetation-related variables. Many model variables, such as SSM, root zone soil moisture (RZSM), LAI, ET, and drainage, remain relatively consistent as the forecast lead time increases, while runoff is highly variable.<\/jats:p>","DOI":"10.3390\/rs12122020","type":"journal-article","created":{"date-parts":[[2020,6,24]],"date-time":"2020-06-24T08:54:50Z","timestamp":1592988890000},"page":"2020","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["From Monitoring to Forecasting Land Surface Conditions Using a Land Data Assimilation System: Application over the Contiguous United States"],"prefix":"10.3390","volume":"12","author":[{"given":"Anthony","family":"Mucia","sequence":"first","affiliation":[{"name":"CNRM, Universit\u00e9 de Toulouse, M\u00e9t\u00e9o-France, CNRS, 31057 Toulouse, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8808-2201","authenticated-orcid":false,"given":"Bertrand","family":"Bonan","sequence":"additional","affiliation":[{"name":"CNRM, Universit\u00e9 de Toulouse, M\u00e9t\u00e9o-France, CNRS, 31057 Toulouse, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongjun","family":"Zheng","sequence":"additional","affiliation":[{"name":"CNRM, Universit\u00e9 de Toulouse, M\u00e9t\u00e9o-France, CNRS, 31057 Toulouse, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1095-2702","authenticated-orcid":false,"given":"Cl\u00e9ment","family":"Albergel","sequence":"additional","affiliation":[{"name":"CNRM, Universit\u00e9 de Toulouse, M\u00e9t\u00e9o-France, CNRS, 31057 Toulouse, France"},{"name":"Now at European Space Agency Climate Office, ECSAT, Harwell Campus, Oxfordshire, Didcot OX11 0FD, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6425-6492","authenticated-orcid":false,"given":"Jean-Christophe","family":"Calvet","sequence":"additional","affiliation":[{"name":"CNRM, Universit\u00e9 de Toulouse, M\u00e9t\u00e9o-France, CNRS, 31057 Toulouse, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,24]]},"reference":[{"key":"ref_1","unstructured":"Pachauri, R.K., Allen, M.R., Barros, V.R., Broome, J., Cramer, W., Christ, R., Church, J.A., Clarke, L., Dahe, Q., and Dasgupta, P. 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