Jean-Christophe Calvet

Centre National de Recherches Météorologiques, French National Centre for Scientific Research | CNRM · GMME

ASCAT normalized backscatter and slope contain valuable information about soil moisture and vegetation. While backscatter has been assimilated to constrain soil moisture, sometimes together with Leaf Area Index (LAI), this study is the first to assimilate ASCAT observables directly to constrain vegetation states. Here, we assimilate backscatter and...

Root zone soil moisture (RZSM) is critical for water resource management, drought monitoring and sub-seasonal flood climate prediction. While RZSM is not directly observable from space, several RZSM products are available and widely used at global and continental scales. This study conducts a comprehensive and quantitative evaluation of eight RZSM...

Clay shrinkage is the retraction of clayey soils under dry conditions, caused by the loss of adsorbed water molecules from clay minerals. This phenomenon called clay-shrinkage induced subsidence can cause permanent damage to buildings if the drying extends below the foundations. In France, soils with these characteristics are widespread, affecting...

Clay shrinkage, which consists of a reduction in the volume of clay soils during dry periods, can affect buildings and cause subsidence damage. In France, losses due to subsidence are estimated at more than EUR 16 billion for the period 1989–2021 (CCR, 2021) and are expected to increase under the effect of climate warming. This work aims to improve...

Root zone soil moisture (RZSM) is critical for water resource management, drought monitoring and sub-seasonal flood climate prediction. RZSM is not directly observable from space, but several RZSM products are available and widely used at global and continental scales. This paper presents a comprehensive quantitative evaluation of eight RZSM produc...

Observed by satellites for more than a decade, surface soil moisture (SSM) is an essential component of the Earth system. Today, with the Sentinel missions, SSM can be derived at a sub-kilometer spatial resolution. In this work, aggregated 1 km × 1 km SSM observations combining Sentinel-1 (S1) and Sentinel-2 (S2) data are assimilated for the first...

In this work, Advanced SCATterometer (ASCAT) backscatter data are directly assimilated into the interactions between soil, biosphere, and atmosphere (ISBA) land surface model using Meteo-France’s global Land Data Assimilation System (LDAS-Monde) tool in order to jointly analyse soil moisture and leaf area index (LAI). For the first time, observatio...

Clay shrinkage, which consists of a reduction in the volume of clay soils during dry periods, can affect buildings and cause subsidence damage. In France, losses due to subsidence are estimated at more than 16 billion € for the period 1989–2021 (CCR, 2021), and are expected to increase under the effect of climate warming. This work aims to improve...

Root-zone soil moisture (RZSM) is crucial for water resource management, drought monitoring and sub-seasonal flood climate forecast. RZSM is not directly observable from space but various model-derived RZSM products are available at the global scale and are widely used. In this paper, a comprehensive quantitative evaluation of eight RZSM products i...

Les données de télédétection constituent désormais les sources primordiales pour l’observation de la Terre et de l’Univers. Les techniques d’inversion et d’assimilation de données représentent les outils principaux permettant l’estimation et la prédiction des paramètres géophysiques qui caractérisent l’évolution de notre planète et de l’Univers, en...

With an increase in the number of natural processes represented, global land surface models (LSMs) have become more and more accurate in representing natural terrestrial ecosystems. However, they are still limited with respect to the impact of agriculture on land surface variables. This is particularly true for agro-hydrological processes related t...

The task of quantifying spatial and temporal variations in terrestrial water, energy, and vegetation conditions is challenging due to the significant complexity and heterogeneity of these conditions, all of which are impacted by climate change and anthropogenic activities. To address this challenge, Earth Observations (EOs) of the land and their ut...

The beginning of the 21 st century is marked by a rapid growth of land surface satellite data and model sophistication. This offers new opportunities to estimate multiple components of the water cycle via satellite-based land data assimilation (DA) across multiple scales. By resolving more processes in land surface models and by coupling the land,...

A Deep Neural Network (DNN) is used to estimate the Advanced Scatterometer (ASCAT) C-band microwave normalized backscatter (σ40o), slope (σ′) and curvature (σ″) over France. The Interactions between Soil, Biosphere and Atmosphere (ISBA) land surface model (LSM) is used to produce land surface variables (LSVs) that are input to the DNN. The DNN is t...

Backscatter measured by scatterometers and Synthetic Aperture Radars is sensitive to the dielectric properties of the soil and normally increases with increasing soil moisture content. However, when the soil is dry, the radar waves penetrate deeper into the soil, potentially sensing subsurface scatterers such as near-surface rocks and stones. In th...

The land data assimilation system, LDAS-Monde, developed by the research department of the French meteorological service (Centre National de Recherches Météorologiques – CNRM) is capable of well representing land surface variables (LSVs) from regional to global scales. It jointly assimilates satellite-derived observations of leaf area index (LAI) a...

In 2009, the International Soil Moisture Network (ISMN) was initiated as a community effort, funded by the European Space Agency, to serve as a centralised data hosting facility for globally available in situ soil moisture measurements . The ISMN brings together in situ soil moisture measurements collected and freely shared by a multitude of organi...

NASAs Soil Moisture Active Passive (SMAP) mission has been validating its soil moisture (SM) products since the start of data production on March 31, 2015. Prior to launch, the mission defined a set of criteria for core validation sites (CVS) that enable the testing of the key mission SM accuracy requirement (unbiased root-mean-square error <0.04 m...

With an increase in the number of natural processes represented, global land surface models (LSMs) have become more and more accurate in representing natural terrestrial ecosystems. However, they are still limited, especially in the representation of the impact of agriculture on land surface variables. This is particularly true for agro-hydrologica...

The land data assimilation system, LDAS-Monde, developed by the Research Department of the French Meteorological service (Centre National de Recherches Météorologiques – CNRM) is capable of well representing Land Surface Variables (LSVs) from regional to global scales. It jointly assimilates satellite-derived observations of leaf area index (LAI) a...

This paper presents an innovative method for observing vegetation health at a very high spatial resolution (~5 × 5 cm) and low cost by upgrading an existing Aerosol RObotic NETwork (AERONET) ground station dedicated to the observation of aerosols in the atmosphere. This study evaluates the capability of a sun/sky photometer to perform additional su...

NASA’s Soil Moisture Active Passive (SMAP) mission has been validating its soil moisture (SM) products since the start of data production on March 31, 2015. Prior to launch, the mission defined a set of criteria for core validation sites (CVS) that enable the testing of the key mission SM accuracy requirement (unbiased root-mean-square error <0.04...

NASA’s Soil Moisture Active Passive (SMAP) mission has been validating its soil moisture (SM) products since the start of data production on March 31, 2015. Prior to launch, the mission defined a set of criteria for core validation sites (CVS) that enable the testing of the key mission SM accuracy requirement (unbiased root-mean-square error <0.04...

In 2009, the International Soil Moisture Network (ISMN) was initiated as a community effort, funded by the European Space Agency, to serve as a centralised data hosting facility for globally available in situ soil moisture measurements (Dorigo et al., 2011a, b). The ISMN brings together in situ soil moisture measurements collected and freely shared...

Abstract We present the latest version of the ISBA‐CTRIP land surface system, focusing on the representation of the land carbon cycle. We review the main improvements since the year 2012, mainly added modules for wild fires, carbon leaching through soil and transport of dissolved organic carbon to the ocean, and land cover changes but also improved...

LDAS-Monde is a global offline land data assimilation system (LDAS) that jointly assimilates satellite-derived observations of surface soil moisture (SSM) and leaf area index (LAI) into the ISBA (Interaction between Soil Biosphere and Atmosphere) land surface model (LSM). This study demonstrates that LDAS-Monde is able to detect, monitor and foreca...

The high computational resources and the time-consuming IO (input/output) are major issues in offline ensemble-based high-dimensional data assimilation systems. Bearing these in mind, this study proposes a sophisticated dynamically running job scheme as well as an innovative parallel IO algorithm to reduce the time to solution of an offline framewo...

This paper presents a community effort to develop good practice guidelines for the validation of global coarse-scale satellite soil moisture products. We provide theoretical background, a review of state-of-the-art methodologies for estimating errors in soil moisture data sets, practical recommendations on data pre-processing and presentation of st...

LDAS-Monde is a global land data assimilation system (LDAS) developed by Centre National de Recherches Météorologiques (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...

The aim of this study is to estimate surface soil moisture at a spatial resolution of 500 m and a temporal resolution of at least 6 days, by combining remote sensing data from Sentinel-1 and optical data from Sentinel-2 and MODIS (Moderate-Resolution Imaging Spectroradiometer). The proposed methodology is based on the change detection technique, ap...

Cet article présente les différentes étapes des développements réalisés au CNRM des années 1990 à nos jours pour spatialiser à diverses échelles les simulations du modèle Isba des surfaces terrestres. Une attention particulière est portée sur l'intégration, dans le modèle, de données satellitaires permettant de caractériser la végétation. Deux faço...

This paper introduces an ensemble square root filter (EnSRF) in the context of jointly assimilating observations of surface soil moisture (SSM) and the leaf area index (LAI) in the Land Data Assimilation System LDAS-Monde. By ingesting those satellite-derived products, LDAS-Monde constrains the Interaction between Soil, Biosphere and Atmosphere (IS...

This chapter proposes a short review of selected recent activities on the use of Earth observation data for monitoring the hydrological, vegetation, and energy cycles of continental surfaces with a focus on the Euro-Mediterranean region. It is structured in three sections: (1) observing terrestrial variables from space; (2) integration of satellite...

This paper investigates to what extent soil moisture and vegetation density information can be extracted from the Advanced Scatterometer (ASCAT) satellite-derived radar backscatter (σ •) in a data assimilation context. The impact of independent estimates of the surface soil moisture (SSM) and leaf area index (LAI) of diverse vegetation types on ASC...

Monitoring crop status at plot scale in agricultural areas is essential for crop and irrigation management and yield optimization. The Vegetation Optical Depth (VOD) of canopy is directly related to the canopy water content, and thus, it represents an effective tool for crop health monitoring. Currently, VOD is provided at low spatial resolution wh...

This study demonstrates that LDAS-Monde, a global and offline Land Data Assimilation System (LDAS), that integrates satellite Earth observations into the ISBA (Interaction between Soil Biosphere and Atmosphere) Land Surface Model (LSM), is able to detect, monitor and forecast the impact of extreme weather on land surface states. LDAS-Monde jointly...

The mission geosynchronous – continental land atmosphere sensing system (G-CLASS) is designed to study the diurnal water cycle, using geosynchronous radar. Although the water cycle is vital to human society, processes on timescales less than a day are very poorly observed from space. G-CLASS, using C-band geosynchronous radar, could transform this....

This Special Issue is a collection of papers reporting research on various aspects of coupled data assimilation in Earth system models. It includes contributions presenting recent progress in ocean–atmosphere, land–atmosphere, and soil–vegetation data assimilation.

This paper introduces an Ensemble Square Root Filter (EnSRF), a deterministic Ensemble Kalman Filter, to the context of assimilating jointly observations of surface soil moisture (SSM) and leaf area index (LAI) in the Land Data Assimilation System LDAS-Monde. By ingesting those satellite-derived products, LDAS-Monde constrains the Interaction betwe...

This study demonstrates LDAS-Monde, global and offline integration of satellite Earth observations in the ISBA (Interaction between Soil Biosphere and Atmosphere) Land Surface Model (LSM), great potential to detect, monitor and forecast the impact of extremes weather on land surface conditions. LDAS-Monde jointly assimilates Earth observations of s...

The high computational resources and the time-consuming IO (Input/Output) are major issues in offline ensemble- based high-dimentional data assimilation systems. Bearing these in mind, this study proposes a sophisticated dynamically running job scheme as well as an innovative parallel IO algorithm to reduce the time-to-solution of an offline framew...

In this study, the frequency and intensity of soil-cooling rains is assessed using in situ observations of atmospheric and soil profile variables in southern France. Rainfall, soil temperature, and topsoil volumetric soil moisture (VSM) observations, measured every 12 min at 21 stations of the SMOSMANIA (Soil Moisture Observing System – Meteorologi...

This paper investigates the impact of leaf area index (LAI) and surface soil moisture (SSM) on satellite-derived radar backscatter (sigma0 (σ°)) observations over southwestern France. Observations from the Advanced Scatterometer (ASCAT) are compared to simulated sigma0 values produced by the Water Cloud Model (WCM) coupled to the Interactions betwe...

This study focuses on the ability of the global Land Data Assimilation System, LDAS-Monde, to improve the representation of land surface variables (LSVs) over Burkina-Faso through the joint assimilation of satellite derived surface soil moisture (SSM) and leaf area index (LAI) from January 2001 to June 2018. The LDAS-Monde offline system is forced...

This study aims to assess the potential of the LDAS-Monde platform, a land data assimilation system developed by Météo-France, to monitor the impact on vegetation state of the 2018 summer heatwave over Western Europe. The LDAS-Monde is driven by ECMWF's (i) ERA5 reanalysis, and (ii) the Integrated Forecasting System High Resolution operational anal...

This study focuses on the ability of the global land data assimilation system LDAS-Monde to improve the representation of land surface variables (LSVs) over Burkina Faso through the joint assimilation of satellite derived Surface Soil Moisture (SSM) and Leaf Area Index (LAI) from January 2001 to June 2018. The LDAS-Monde offline system is forced by...

We present the application of a generic, semi-empirical first-order radiative transfer modelling approach for the retrieval of soil-and vegetation related parameters from coarse-resolution space-borne scatterometer measurements (σ 0). It is shown that both angular-and temporal variabilities of ASCAT σ 0 measurements can be sufficiently represented...

This study aims to assess the potential of the LDAS-Monde a land data assimilation system developed by Météo-France to monitor the impact of the 2018 summer heatwave over western Europe vegetation state. The LDAS-Monde is forced by the ECMWF's (i) ERA5 10 reanalysis, and (ii) the Integrated Forecasting System High Resolution operational analysis (I...

In this study, the frequency and intensity of soil-cooling rains is assessed using in situ observations of atmospheric and soil profile variables in southern France. Rainfall, soil temperature and topsoil volumetric soil moisture (VSM) observations, measured every 12 minutes at 21 stations of the SMOSMANIA (Soil Moisture Observing System – Meteorol...