Modelling soil moisture at SMOS scale by use of a SVAT model over the Valencia Anchor Station

Juglea, Silvia Enache; Kerr, Yann H.; Mialon, Arnaud; Wigneron, Jean‐Pierre; López-Baeza, Ernesto; Cano, Antonio Rico; Bitar, Ahmad Al; Millan-Scheiding, Cristina; Antolı́n, Maria; Delwart, Steven

doi:10.5194/hess-14-831-2010

Cited by 35 publications

(19 citation statements)

References 43 publications

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“…In this study, the modelling of the heat and water transfers into the soil is based on the diffusive scheme -ISBA-DIF (Boone, 2000;Boone et al, 2000). Details on the choice of the parametrization can be found in Juglea et al (2010). The atmospheric forcing required to run the ISBA model is composed of: air temperature and humidity at screen level, atmospheric pressure, precipitation, wind speed and direction and solar and atmospheric radiation.…”

Section: Methodology -Isba Modellingmentioning

confidence: 99%

“…The increased signal attenuation by vegetation and the superficial sensing depth for higher frequencies is a limit in the soil moisture retrieval from AMSR-E data. Thus, the polarization ratio is additionally used as it provides a better agreement (than the soil moisture product from AMSR-E) with simulated soil moisture even in the vegetation growing period (Juglea et al, 2010). By means of the 6.9 GHz horizontally (h) and verticaly (v) polarized brightness temperatures we computed the polarization ratio (PR) as following:…”

Section: Amsr-e Datamentioning

confidence: 99%

“…To overcome these limitations, one issue currently under study is to use a Soil-Vegetation-Atmosphere-Transfer (SVAT) model to obtain distributed soil moisture fields. Juglea et al (2010) proved the ability of the SVAT scheme (SURFEX (Externalized Surface) -module ISBA (Interactions between SoilBiosphere-Atmosphere) (Noilhan and Planton, 1989;Noilhan and Mahfouf, 1996) to simulate the high temporal and spatial heterogeneity of soil moisture over the Valencia Anchor Station (VAS) experimental site in Spain by using in situ point measurements for model calibration and validation. VAS was selected as a key site providing in situ geophysical measurements over an area as wide as a SMOS pixel (LopezBaeza et al, 2005a;Delwart et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

“…For this purpose, the SVAT scheme SURFEX -module ISBA originally driven by sparse in situ meteorological measurements over VAS (Juglea et al, 2010) is also forced with satellite rainfall data from the PERSIANN database. First, the skill of the PERSIANN products to replicate the variability of gauge rainfall amounts and occurrence at point and areal scale is tested.…”

Section: Introductionmentioning

confidence: 99%

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Soil moisture modelling of a SMOS pixel: interest of using the PERSIANN database over the Valencia Anchor Station

Juglea

Kerr

Mialon

et al. 2010

Hydrol. Earth Syst. Sci.

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Abstract. In the framework of Soil Moisture and Ocean Salinity (SMOS) Calibration/Validation (Cal/Val) activities, this study addresses the use of the PERSIANN-CCS 1 database in hydrological applications to accurately simulate a whole SMOS pixel by representing the spatial and temporal heterogeneity of the soil moisture fields over a wide area (50×50 km 2 ). The study focuses on the Valencia Anchor Station (VAS) experimental site, in Spain, which is one of the main SMOS Cal/Val sites in Europe.A faithful representation of the soil moisture distribution at SMOS pixel scale (50×50 km 2 ) requires an accurate estimation of the amount and temporal/spatial distribution of precipitation. To quantify the gain of using the comprehensive PERSIANN database instead of sparsely distributed rain gauge measurements, comparisons between in situ observations and satellite rainfall data are done both at point and areal scale. An overestimation of the satellite rainfall amounts is observed in most of the cases (about 66%) but the precipitation occurrences are in general retrieved (about 67%).To simulate the high variability in space and time of surface soil moisture, a Soil Vegetation Atmosphere Transfer (SVAT) model -ISBA (Interactions between Soil Biosphere Atmosphere) is used. The interest of using satellite rainCorrespondence to: S. Juglea

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Section: Methodology -Isba Modellingmentioning

confidence: 99%

Section: Amsr-e Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Soil moisture modelling of a SMOS pixel: interest of using the PERSIANN database over the Valencia Anchor Station

Juglea

Kerr

Mialon

et al. 2010

Hydrol. Earth Syst. Sci.

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“…In situ measurements for satellite validation are usually collected in field campaigns over extended areas and during short periods of time or over longer time spans at few selected measuring locations. In addition to other remotesensing datasets, the outputs of spatially distributed environmental process models can make a valuable contribution to the validation of remotely sensed soil moisture products (Crow et al, 2005;Albergel et al, 2010;Juglea et al, 2010;dall'Amico et al, 2012a). These datasets can help to extend long-term validation activities to larger areas.…”

Section: F Schlenz Et Al: Analysis Of Smos Brightness Temperature Amentioning

confidence: 99%

Analysis of SMOS brightness temperature and vegetation optical depth data with coupled land surface and radiative transfer models in Southern Germany

Schlenz¹,

Dall'Amico²,

Mauser³

et al. 2012

Hydrol. Earth Syst. Sci.

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Abstract. Soil Moisture and Ocean Salinity (SMOS) L1c brightness temperature and L2 optical depth data are analysed with a coupled land surface (PROMET) and radiative transfer model (L-MEB). The coupled models are validated with ground and airborne measurements under contrasting soil moisture, vegetation and land surface temperature conditions during the SMOS Validation Campaign in May and June 2010 in the SMOS test site Upper Danube Catchment in southern Germany. The brightness temperature root-meansquared errors are between 6 K and 9 K. The L-MEB parameterisation is considered appropriate under local conditions even though it might possibly be further optimised. SMOS L1c brightness temperature data are processed and analysed in the Upper Danube Catchment using the coupled models in 2011 and during the SMOS Validation Campaign 2010 together with airborne L-band brightness temperature data. Only low to fair correlations are found for this comparison (R between 0.1-0.41). SMOS L1c brightness temperature data do not show the expected seasonal behaviour and are positively biased. It is concluded that RFI is responsible for a considerable part of the observed problems in the SMOS data products in the Upper Danube Catchment. This is consistent with the observed dry bias in the SMOS L2 soil moisture products which can also be related to RFI. It is confirmed that the brightness temperature data from the lower SMOS look angles and the horizontal polarisation are less reliable. This information could be used to improve the brightness temperature data filtering before the soil moisture retrieval. SMOS L2 optical depth values have been compared to modelled data and are not considered a reliable source of information about vegetation due to missing seasonal behaviour and a very high mean value. A fairly strong correlation between SMOS L2 soil moisture and optical depth was found (R = 0.65) even though the two variables are considered independent in the study area. The value of coupled models as a tool for the analysis of passive microwave remote-sensing data is demonstrated by extending this SMOS data analysis from a few days during a field campaign to a longer term comparison.

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Evaluating the patterns of spatiotemporal trends of root zone soil moisture in major climate regions in East Asia

2017

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Root zone soil moisture (RZSM) is a crucial variable in land‐atmosphere interactions. Evaluating the spatiotemporal trends and variability patterns of RZSM are essential for discerning the anthropogenic and climate change effects on the regional and global hydrological cycles. In this study, the trends of RZSM, computed by the exponential filter from the European Space Agency's Climate Change Initiative soil moisture, were evaluated in major climate regions of East Asia from 1982 to 2014. Moreover, the trends of RZSM were compared to the trends of precipitation (P), skin temperature (Tskin), and actual evapotranspiration (AET) to investigate how they influence the RZSM trends in each climate region. Drying trends were predominant in arid and continental regions, whereas wetting trends were found in the tropical and temperate regions. The increasing trends of Tskin and AET cause drying in arid and continental regions, whereas in tropical regions, these cause wetting trends, which might be due to convective P. In temperate regions, despite decreasing P and increasing Tskin, the RZSM trend was increasing, attributed to the intensive irrigation activities in these regions. This is probably the first time to analyze the long‐term trends of RZSM in different climate regions. Hence, the results of this study will improve our understanding of the regional and global hydrological cycles. Despite certain limitations, the results of this study may be useful for improving and developing climate models and predicting long‐term vast scale natural disasters such as drought, dust outbreaks, floods, and heat waves.

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Modelling soil moisture at SMOS scale by use of a SVAT model over the Valencia Anchor Station

Cited by 35 publications

References 43 publications

Soil moisture modelling of a SMOS pixel: interest of using the PERSIANN database over the Valencia Anchor Station

Soil moisture modelling of a SMOS pixel: interest of using the PERSIANN database over the Valencia Anchor Station

Analysis of SMOS brightness temperature and vegetation optical depth data with coupled land surface and radiative transfer models in Southern Germany

Evaluating the patterns of spatiotemporal trends of root zone soil moisture in major climate regions in East Asia

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