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Integrating Ascat Surface Soil Moisture and Geov1 Leaf Area Index Into the Surfex Modelling Platform: a Land Data Assimilation Application Over France : Volume 10, Issue 7 (11/07/2013)

By Barbu, A. L.

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Book Id: WPLBN0004011859
Format Type: PDF Article :
File Size: Pages 47
Reproduction Date: 2015

Title: Integrating Ascat Surface Soil Moisture and Geov1 Leaf Area Index Into the Surfex Modelling Platform: a Land Data Assimilation Application Over France : Volume 10, Issue 7 (11/07/2013)  
Author: Barbu, A. L.
Volume: Vol. 10, Issue 7
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2013
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Calvet, J., Lafont, S., Mahfouf, J., & Barbu, A. L. (2013). Integrating Ascat Surface Soil Moisture and Geov1 Leaf Area Index Into the Surfex Modelling Platform: a Land Data Assimilation Application Over France : Volume 10, Issue 7 (11/07/2013). Retrieved from http://hawaiilibrary.net/


Description
Description: CNRM-GAME, UMR3589, Météo France, CNRS, Toulouse, France. The land monitoring service of the European Copernicus programme has developed a set of satellite-based biogeophysical products, including surface soil moisture (SSM) and leaf area index (LAI). This study investigates the impact of joint assimilation of remotely sensed SSM derived from ASCAT backscatter data and the GEOV1 satellite-based LAI into the ISBA-A-gs land surface model within the SURFEX modelling platform of Meteo-France. The ASCAT data were bias corrected with respect to the model climatology by using a seasonal-based CDF (Cumulative Distribution Function) matching technique. A multivariate multi-scale land data assimilation system (LDAS) based on the Extended Kalman Filter (EKF) is used for monitoring the soil moisture, terrestrial vegetation, surface carbon and energy fluxes across the France domain at a spatial resolution of 8 km. Each model grid box is divided in a number of land covers, each having its own set of prognostic variables. The filter algorithm is designed to provide a distinct analysis for each land cover while using one observation per grid box. The updated values are aggregated by computing a weighted average.

In this study, it is demonstrated that the assimilation scheme works effectively within the ISBA-A-gs model over a four-year period (2008–2011). The EKF is able to extract useful information from the data signal at the grid scale and to distribute the root-zone soil moisture and LAI increments among the mosaic structure of the model. The impact of the assimilation on the vegetation phenology and on the water and carbon fluxes varies from one season to another. The spring drought of 2011 is an interesting case study showing the potential of the assimilation to improve drought monitoring. A comparison between simulated and in situ soil moisture gathered at the twelve SMOSMANIA stations shows improved anomaly correlations for eight stations.


Summary
Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: a land data assimilation application over France

Excerpt
Barbu, A. L., Calvet, J.-C., Mahfouf, J.-F., Albergel, C., and Lafont, S.: Assimilation of Soil Wetness Index and Leaf Area Index into the ISBA-A-gs land surface model: grassland case study, Biogeosciences, 8, 1971–1986, doi:10.5194/bg-8-1971-2011, 2011.; Baret, F., Hagolle, O., Geiger, B., Bicheron, P., Miras, B., Huc, M., Berthelot, B., Weiss, M., Samain, O., Roujean, J. L., and Leroy, M.: LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION. Part 1: Principles of the algorithm, Remote Sens. Environ., 110, 275–286, 2007.; Baret, F., Weiss, M., Lacaze, R., Camacho, F., Makhmarad, H., Pacholczyk, P., and Smetse, B.: GEOV1: LAI, FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part 1: Principles of development and production, Remote Sens. Environ., doi:10.1016/j.rse.2012.12.027, in press, 2013.; Bartalis, Z., Wagner, W., Naeimi, V., Hasenauer, S., Scipal, K., Bonekamp, H., Figa, J., and Anderson, C.: Initial soil moisture retrievals from the METOP-A advanced Scatterometer (ASCAT), Geophys. Res. Lett., 34, L20401, doi:10.1029/2007GL031088, 2007.; Bolten, J. D. and Crow, W. T.: Improved prediction of quasi-global vegetation conditions using remotely-sensed surface soil moisture, Geophys. Res. Lett., 39, L19406, doi:10.1029/2012GL053470, 2012.; Boone, A., Calvet, J.-C., and Noilhan, J.: Inclusion of a third soi layer in a land surface scheme using the force-restore method, J. Appl. Meteor., 38, 1611–1630, 1999.; Brut, A., Rüdiger, C., Lafont, S., Roujean, J.-L., Calvet, J.-C., Jarlan, L., Gibelin, A.-L., Albergel, C., Le Moigne, P., Soussana, J.-F., Klumpp, K., Guyon, D., Wigneron, J.-P., and Ceschia, E.: Modelling LAI at a regional scale with ISBA-A-gs: comparison with satellite-derived LAI over southwestern France, Biogeosciences, 6, 1389–1404, doi:10.5194/bg-6-1389-2009, 2009.; Calvet, J.-C.: Investigating soil and atmospheric plant water stress using physiological and micrometeorological data sets, Agr. Forest Meteorol., 103, 229–247, 2000.; Albergel, C., Rüdiger, C., Pellarin, T., Calvet, J.-C., Fritz, N., Froissard, F., Suquia, D., Petitpa, A., Piguet, B., and Martin, E.: 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, Hydrol. Earth Syst. Sci., 12, 1323–1337, doi:10.5194/hess-12-1323-2008, 2008.; Albergel, C., Calvet, J.-C., Gibelin, A.-L., Lafont, S., Roujean, J.-L., Berne, C., Traullé, O., and Fritz, N.: Observed and modelled ecosystem respiration and gross primary production of a grassland in southwestern France, Biogeosciences, 7, 1657–1668, doi:10.5194/bg-7-1657-2010, 2010.; Calvet, J.-C., Noilhan, J., Roujean, J.-L., Bessemoulin, P., Cabelguenne, M., Olioso, A., and Wigneron, J.-P.: An interactive vegetation SVAT model tested against data from six contrasting sites, Agr. Forest Meteorol., 92, 73–95, 1998.; Calvet, J.-C., Rivalland, V., Picon-Cochard, C., and Guelh, J.-M.: Modelling forest transpiration and CO2 fluxes-response to soil moisture stress, Agr. Forest Meteorol., 124, 143–156, doi:10.1016/j.agrformet.2004.01.007, 2004.; Calvet, J.-C., Fritz, N., Froissard, F., Sequia, D., Petitpa, A., and Piguet, B.: In situ soil moisture observations for the CAL/VAL of SMOS: the SMOSMANIA network, International Geoscience and Remote Sensing Symposium, IGARSS, Barcelona, Spain, 23–28 July 2007, 1196–1199, &l

 

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