ECOSTRESS: NASA's next generation mission to measure evapotranspiration from the International Space Station

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station ECOSTRESS) was launched to the International Space Station on June 29, 2018. The primary science focus of ECOSTRESS is centered on evapotranspiration (ET), which is produced as level‐3 (L3) latent heat flux (LE) data products. These data are generated from the level‐2 land surface temperature and emissivity product (L2_LSTE), in conjunction with ancillary surface and atmospheric data. Here, we provide the first validation (Stage 1, preliminary) of the global ECOSTRESS clear‐sky ET product (L3_ET_PT‐JPL, version 6.0) against LE measurements at 82 eddy covariance sites around the world. Overall, the ECOSTRESS ET product performs well against the site measurements (clear‐sky instantaneous/time of overpass: r2 = 0.88; overall bias = 8%; normalized RMSE = 6%). ET uncertainty was generally consistent across climate zones, biome types, and times of day (ECOSTRESS samples the diurnal cycle), though temperate sites are over‐represented. The 70 m high spatial resolution of ECOSTRESS improved correlations by 85%, and RMSE by 62%, relative to 1 km pixels. This paper serves as a reference for the ECOSTRESS L3 ET accuracy and Stage 1 validation status for subsequent science that follows using these data

Développement et application du modèle SiSPAT-RS à l'échelle de la parcelle et dans le cadre de l'expérience alpilles ReSeDA

Vegetation canopy functioning can be studied combining both Soil-Vegetation-Atmosphere Transfer (SVAT) models and remote sensing data. These models describe energy and mass transfers in the soil-plant-atmosphere continuum. Remote sensing provides useful information for driving such models. The main objective of this work was to determine the contribution of multispectral remote sensing data in the functioning of a complex SVAT model. The chosen model was SiSPAT (Braud, 1995), considering coupled heat and moisture flows in the soil. It was coupled with two canopy radiative transfer models in order to simulate at field scale main surface processes and remote sensed data (bi-directional reflectance and directional brightness temperature). In the visible and the near infrared, the 2M-SAIL model (Weiss et al., 2001) was chosen for its ability to account for the development of yellow and green vegetation layers throughout the crop cycle. In the thermal infrared, the directional model proposed by François (2001) was used. In the microwaves domain (passive or active), the contribution of remote sensing data was only studied through the surface soil water content. This new developed model was called SiSPAT-RS (Simple Soil Plant Transfer and Remote Sensing) and was applied on two wheat field dataset, acquired during the ReSeDA experiment in 1997 in the South France. First, a sensitivity analysis was performed over 60 parameters and initial state variables, using a stochastic Monte Carlo sampling and a multicriteria methodology based on a Pareto ranking. Results allowed to detect the most influent parameters on the simulation of several state variables, and to reduce significantly their associated uncertainty intervals. The model calibration was performed considering different assumptions, related to the experimental knowledge of soil properties and surface variables available. This step allowed to (1) validate the model on the other wheat field and (2) propose and apply an assimilation method, based on the knowledge of thermal infrared brightness temperature and the surface soil water content. In this last context, it was possible to estimate the main surface processes with a good accuracy and to quantify the model errors associated to the parameter uncertainties.Le fonctionnement de la végétation peut être étudié à l'aide de l'utilisation combinée de modèles numériques et de données de télédétection. Les premiers décrivent les principaux Transferts d'énergie et de masse qui interagissent à l'interface Sol-Végétation-Atmosphère (modèles TSVA). Le télédétection fournit quant à elle certaines caractéristiques des couverts végétaux qui sont utiles au fonctionnement des modèles TSVA. L'objectif de ce travail est de déterminer l'apport de la télédétection multispectrale pour le fonctionnement d'un modèle TSVA. Il est basé sur le couplage du modèle TSVA SiSPAT avec deux modèles de transfert radiatif fonctionnant respectivement dans le visible-infrarouge et l'infrarouge thermique. La nouvelle version développée (SiSPAT-RS) est ainsi capable de simuler les principaux processus de surface et plusieurs variables de télédétection. Elle a été utilisée sur la base données acquises lors de la campagne expérimentale Alpilles-ReSeDA, plus particulièrement sur deux parcelles agricoles de blé. Dans un premier temps, une analyse de sensibilité a été mise en œuvre sur les 60 paramètres et variables d'initialisation du modèle couplé. Elle a reposé sur un échantillonnage de type Monte Carlo et une analyse multicritère par rangement de Pareto. Les résultats ont permis de déterminer les paramètres les plus influents sur la simulation simultanée de plusieurs variables d'état du modèle et les conditions dans lesquelles ils interviennent, et de réduire de manière efficace les gammes d'incertitude des paramètres sensibles. Dans un second temps, l'étalonnage du modèle a été réalisé sous différents contextes d'étude, liés notamment à la connaissance expérimentale des propriétés du sol et de diverses variables de surface. Ceci a finalement permis de valider le modèle et de quantifier, dans un contexte d'assimilation de données de télédétection, l'erreur du modèle liée à l'incertitude des paramètres

Développement et application du modèle SiSPAT-RS à l'échelle de la parcelle dans le cadre de l'expérience Alpilles ReSeDA

PARIS7-Bibliothèque centrale (751132105) / SudocSudocFranceF

Modélisation des cycles couplés de l'eau, de l'énergie et de la végétation sur les surfaces continentales

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SCOPE model: a tool to simulate the surface temperature directional anisotropy

National audienceThermal infrared (TIR) measurements are prone to directional effects. A lot of experimental studies of the TIR anisotropy, which is defined as the difference between oblique and nadir surface temperatures measurements, have been performed since the 60’s and reported in literature. They reveal important hotspot effect and possible significant errors - up to 10°C - on surface temperature measurements. Directional effects have to be characterized to correct or to normalize satellite data, particularly large swath satellites data such as MODIS or AATSR for which scan angles reach ± 55° and ± 47° from nadir, respectively. They also have to be considered for defining the mission specifications of future TIR systems. Finally they can help to improve the estimation of surface fluxes by making possible discriminating the contributions of soil and canopy. In this idea a better characterization of TIR directional anisotropy is expected to improve the assimilation of thermal satellite data in vegetation models. A large range of approaches have been developed to simulate the anisotropy (geometric models, radiative transfer, 3D models, parametric kernels...). Nevertheless, deterministic radiative transfer modelization remains essential to generalize experimental measurements and to assess the sensitivity of surface features (vegetation structure, LAI, water status etc.) and the impact of the Sun-observer geometry impact on directional radiative temperature measurements. Moreover, new methods (such as kernel approaches or neural networks) have to be developed to correct for directional anisotropy, simple enough to be integrated in ground segments for operational satellite data processing. For this purpose another use of a deterministic model of TIR anisotropy could be the simulation of data sets from which derive operational simpler algorithms could be derived. The deterministic SCOPE (Soil Canopy Observation, photochemistry and Energy fluxes) model, developed by Van der Tol et al. (2009) at the ITC (Nederland), is a good candidate to address the problem of the temperature anisotropy. It is a one-dimensional multilayer model coupling a radiative transfer model based on the 4SAIL (Scattering by Arbitrary Inclined Leaves designed by Verhoef et al. 2007) algorithm and an energy balance module. It has been designed to simulate radiance spectra, energy and CO 2 fluxes but it also simulates directional brightness temperatures. After a brief description of the model, we present a validation exercise of SCOPE for fluxes and directional brightness temperatures over two original experimental data sets obtained on wheat and pine stands recorded during different years; they offer a large range of surface conditions (vegetation structure, LAI, water status). Directional radiative temperatures were measured with several radiothermometers positioned in different zenithal and azimuthal viewing configurations (18° towards South, 55° towards North and 27° towards West). During a few months, a GV2M: Global Vegetation Monitoring and Modeling (18° towards South, 55° towards North and 27° towards West). During a few months, a radiothermometer was also mounted on a motorized platform piloted to follow the sun course during the day, so providing the temperature at the hotspot. The sites belonging to different international networks, (CarboEurope, Fluxnet) the energy (sensible and latent heat) and CO 2 fluxes were also continuously monitored. SCOPE was calibrated using several inversion strategies which are described. The biochemical input parameters (maximal carboxylation capacity and the marginal cost of assimilation which strongly govern photosynthesis and transpiration processes) revealed to have most sensitivity on simulations and were retained to calibrate the model. The validation of SCOPE was made on cloudless days and for diurnal conditions only. Satisfactory results have been obtained on fluxes with a root mean square error (RMSE) on convective fluxes estimation of about 40 W.m- 2. The simulation of directional brightness surface temperatures revealed excellent with a 1°C RMSE over both wheat and pine data sets, and for all viewing geometries. The use of SCOPE for generating polar plots of temperature anisotropy is finally illustrated by a qualitative comparison exercise. Simulations revealed directional anisotropy structure quite consistent with measurements available at the laboratory. The applications to evaluate the possible effects of different variables such as vegetation structure (leaf angles, LAI, etc.) and micrometeorological conditions (wind speed for instance) are discussed

Evaluation of Multiple Methods for the Production of Continuous Evapotranspiration Estimates from TIR Remote Sensing

International audienceContinuous daily estimates of evapotranspiration (ET) spatially distributed at plot scale are required to monitor the water loss and manage crop irrigation needs. Remote sensing approaches in the thermal infrared (TIR) domain are relevant to assess actual ET and soil moisture status but due to lengthy return intervals and cloud cover, data acquisition is not continuous over time. This study aims to assess the performances of 6 commonly used as well as two new reference quantities including rainfall as an index of soil moisture availability to reconstruct seasonal ET from sparse estimates and as a function of the revisit frequency. In a first step, instantaneous in situ eddy-covariance flux tower data collected over multiple ecosystems and climatic areas were used as a proxy for perfect retrievals on satellite overpass dates. In a second step, instantaneous estimations at the time of satellite overpass were produced using the Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) energy balance model in order to evaluate the errors concurrent to the use of an energy balance model simulating the instantaneous IRT products from the local surface temperature. Significant variability in the performances from site to site was observed particularly for long revisit frequencies over 8 days, suggesting that the revisit frequency necessary to achieve accurate estimates of ET via temporal upscaling needs to be fewer than 8 days whatever the reference quantity used. For shorter return interval, small differences among the interpolation techniques and reference quantities were found. At the seasonal scale, very simple methods using reference quantities such as the global radiation or clear sky radiation appeared relevant and robust against long revisit frequencies. For infra-seasonal studies targeting stress detection and irrigation management, taking the amount of precipitation into account seemed necessary, especially to avoid the underestimation of ET over cloudy days during a long period without data acquisitions

A new reflectivity index for the retrieval of surface soil moisture from radar data

International audienceA new approach based on the change detection technique is proposed for the estimation of surface soil moisture (SSM) from a time series of radar measurements. A new index of reflectivity (IR) is defined that uses radar signals and Fresnel coefficients. This index is equal to 0 in the case of the smallest value of the Fresnel coefficient, corresponding to the driest conditions and the weakest radar signal, and is equal to 1 for the highest value of the Fresnel coefficient, corresponding to the wettest soil conditions and the strongest radar signal. The Integrated Equation Model (IEM) is used to simulate the behavior of radar signals as a function of soil moisture and roughness. This approach validates the greater usefulness of the IR compared with that of the commonly used index of SSM (ISSM), which assumes that the SSM varies linearly as a function of radar signal strength. The IR-based approach was tested using Sentinel-1 radar data recorded over three regions: Banizombou (Niger), Merguellil (Tunisia), and Occitania (France). The IR approach was found to perform better for the estimation of SSM than the ISSM approach based on comparisons with ground measurements over bare soils

The sensitivity of nocturnal low-level jets and near-surface winds over the Sahel to model resolution, initial conditions and boundary-layer set-up

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