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dc.contributor.authorPolcher, Jan
dc.contributor.authorPiles Guillem, Maria
dc.contributor.authorGelati, Emiliano
dc.contributor.authorBarella Ortiz, Anais
dc.contributor.authorTello Alonso, Marivi
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2017-04-18T08:42:57Z
dc.date.available2017-04-18T08:42:57Z
dc.date.issued2016-03-01
dc.identifier.citationPolcher, J., Piles, M., Gelati, E., Barella, A., Tello, M. Comparing surface-soil moisture from the SMOS mission and the ORCHIDEE land-surface model over the Iberian Peninsula. "Remote sensing of environment", 1 Març 2016, vol. 174, p. 69-81.
dc.identifier.issn0034-4257
dc.identifier.urihttp://hdl.handle.net/2117/103499
dc.description.abstractThe aim of this study is to compare the surface soil moisture (SSM) retrieved from ESA's Soil Moisture and Ocean Salinity mission (SMOS) with the output of the ORCHIDEE (ORganising Carbon and Hydrology In Dynamic EcosystEm) land surface model forced with two distinct atmospheric data sets for the period 2010 to 2012. The comparison methodology is first established over the REMEDHUS (Red de Estaciones de MEDición de la Humedad def Suelo) soil moisture measurement network, a 30 by 40. km catchment located in the central part of the Duero basin, then extended to the whole Iberian Peninsula (IP). The temporal correlation between the in-situ, remotely sensed and modelled SSM are satisfactory (r. >. 0.8). The correlation between remotely sensed and modelled SSM also holds when computed over the IP. Still, by using spectral analysis techniques, important disagreements in the effective inertia of the corresponding moisture reservoir are found. This is reflected in the spatial correlation over the IP between SMOS and ORCHIDEE SSM estimates, which is poor (¿. ~. 0.3). A single value decomposition (SVD) analysis of rainfall and SSM shows that the co-varying patterns of these variables are in reasonable agreement between both products. Moreover the first three SVD soil moisture patterns explain over 80% of the SSM variance simulated by the model while the explained fraction is only 52% of the remotely sensed values. These results suggest that the rainfall-driven soil moisture variability may not account for the poor spatial correlation between SMOS and ORCHIDEE products.
dc.format.extent13 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Teledetecció
dc.subject.lcshRemote sensing
dc.subject.lcshSoil moisture--Measurement
dc.subject.otherLand-surface modelling
dc.subject.otherORCHIDEE
dc.subject.otherRemote sensing
dc.subject.otherSMOS
dc.subject.otherSoil moisture
dc.titleComparing surface-soil moisture from the SMOS mission and the ORCHIDEE land-surface model over the Iberian Peninsula
dc.typeArticle
dc.subject.lemacTeledetecció
dc.subject.lemacSòls -- Humitat -- Mesurament
dc.contributor.groupUniversitat Politècnica de Catalunya. CTE-CRAE - Grup de Recerca en Ciències i Tecnologies de l'Espai
dc.identifier.doi10.1016/j.rse.2015.12.004
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S003442571530225X
dc.rights.accessOpen Access
local.identifier.drac17546865
dc.description.versionPostprint (published version)
local.citation.authorPolcher, J.; Piles, M.; Gelati, E.; Barella, A.; Tello, M.
local.citation.publicationNameRemote sensing of environment
local.citation.volume174
local.citation.startingPage69
local.citation.endingPage81


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