Joint assimilation of surface soil moisture and LAI observations into a land surface model

International audienceLand Surface Models (LSM) offer a description of land surface processes and set the lower boundary conditions for meteorological models. In particular, the accurate description of those surface variables which display a slow response in time, like root-zone soil moisture or vegetation biomass, is of great importance. Errors in their estimation yield significant inaccuracies in the estimation of heat and water fluxes in Numerical Weather Prediction (NWP) models. In the present study, the ISBA-A-gs LSM is used decoupled from the atmosphere. In this configuration, the model is able to simulate the vegetation growth, and consequently LAI. A simplified 1D-VAR assimilation method is applied to observed surface soil moisture and LAI observations of the SMOSREX site near Toulouse, in south-western France, from 2001 to 2004. This period includes severe droughts in 2003 and 2004. The data are jointly assimilated into ISBA-A-gs in order to analyse the root-zone soil moisture and the vegetation biomass. It is shown that the 1D-VAR improves the model results. The efficiency score of the model (Nash criterion) is increased from 0.79 to 0.86 for root-zone soil moisture and from 0.17 to 0.23 for vegetation biomass

From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations

International audienceA long term data acquisition effort of profile soil moisture is under way in southwestern France at 13 automated weather stations. This ground network was developed in order to validate remote sensing and model soil moisture estimates. In this paper, both those in situ observations and a synthetic data set covering continental France are used to test a simple method to retrieve root zone soil moisture from a time series of surface soil moisture information. A recursive exponential filter equation using a time constant, T , is used to compute a soil water index. The Nash and Sutcliff coefficient is used as a criterion to optimise the T parameter for each ground station and for each model pixel of the synthetic data set. In general, the soil water indices derived from the surface soil moisture observations and simulations agree well with the reference root-zone soil moisture. Overall, the results show the potential of the exponential filter equation and of its recursive formulation to derive a soil water index from surface soil moisture estimates. This paper further investigates the correlation of the time scale parameter T with soil properties and climate conditions. While no significant relationship could be determined between T and the main soil properties (clay and sand fractions, bulk density and organic matter content), the modelled spatial variability and the observed inter-annual variability of T suggest that a weak climate effect may exist

Utilisation de données satellitaires en hydro-météorologie : la recherche à Météo-France

La modélisation des processus de surface en relation avec le cycle du carbone et l’hydrologie superficielle, requiert l’utilisation de la télédétection pour spatialiser et piloter les modèles, et l’assimilation de données de télédétection dans différents domaines de longueur d’onde. L’utilisation des produits de télédétection spatiale sur les surfaces continentales pour des applications de recherche et pré-opérationnelles est développée à Météo-France dans le cadre de la plate-forme de modélisation SURFEX, incluant une représentation du système sol-plante (ISBA), des zones urbaines (TEB) et des lacs (FLAKE). La spatialisation des paramètres du modèles est réalisée dans SURFEX grâce à la base de données ECOCLIMAP, et sur l’Europe et l’Afrique, une version plus récente (ECOCLIMAP2). Le rayonnement incident et l’albédo (produits par le SAF-Land d’EUMETSAT en particulier) permettent de contraindre le modèle. Humidité superficielle du sol et LAI peuvent être assimilés dans le modèle, pour corriger sa « trajectoire ». Température de surface, et une indication du gel/dégel du sol permettent de vérifier les simulations. Enfin, étant donné la disponibilité de séries satellitaires de plus en plus longues (AVHRR, micro-ondes actives ou passives), la télédétection est susceptible d’être utilisée dans la production ou la vérification de réanalyses climatiques. Un développements important de l’utilisation de données de télédétection pour les surfaces continentales est à attendre dans le cadre de GMES (Global Monitoring for Environment and Security) et des SAF d’EUMETSAT. En parallèle, il est important de développer des sites de mesure pour la validation croisée satellite / modèle / in-situ

Assimilation of EO data in land surface models: interactions between water and carbon cycles

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Verification and Assimilation of SMOS Data

International audienceIntensive airborne and in situ observations were performed in southern France for the SMOS CAL/VAL, from April to July 2010. The modelling tools, the experimental set-up and first results are described

Verification and Assimilation of SMOS Data

International audienceIntensive airborne and in situ observations were performed in southern France for the SMOS CAL/VAL, from April to July 2010. The modelling tools, the experimental set-up and first results are described

Verification and Assimilation of SMOS Data

International audienceIntensive airborne and in situ observations were performed in southern France for the SMOS CAL/VAL, from April to July 2010. The modelling tools, the experimental set-up and first results are described

Review of soil salinity assessment for agriculture across multiple scales using proximal and/or remote sensors

Mapping and monitoring soil spatial variability is particularly problematic for temporally and spatially dynamic properties such as soil salinity. The tools necessary to address this classic problem only reached maturity within the past 2 decades to enable field- to regional-scale salinity assessment of the root zone, including GPS, GIS, geophysical techniques involving proximal and remote sensors, and a greater understanding of apparent soil electrical conductivity (ECa) and multi- and hyperspectral imagery. The concurrent development and application of these tools have made it possible to map soil salinity across multiple scales, which back in the 1980s was prohibitively expensive and impractical even at field scale. The combination of ECa-directed soil sampling and remote imagery has played a key role in mapping and monitoring soil salinity at large spatial extents with accuracy sufficient for applications ranging from field-scale site-specific management to statewide water allocation management to control salinity within irrigation districts. The objective of this paper is: (i) to present a review of the geophysical and remote imagery techniques used to assess soil salinity variability within the root zone from field to regional scales; (ii) to elucidate gaps in our knowledge and understanding of mapping soil salinity; and (iii) to synthesize existing knowledge to give new insight into the direction soil salinity mapping is heading to benefit policy makers, land resource managers, producers, agriculture consultants, extension specialists, and resource conservation field staff. The review covers the need and justification for mapping and monitoring salinity, basic concepts of soil salinity and its measurement, past geophysical and remote imagery research critical to salinity assessment, current approaches for mapping salinity at different scales, milestones in multi-scale salinity assessment, and future direction of field- to regional-scale salinity assessment