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The aim of this study is to analyze the influence of the soil moisture sampling depth in the parameterization of soil emission in microwave radiometry at L-band. The analysis is based on brightness temperature, soil moisture and temperature measurements acquired over a bare soil during the SMOSREX experiment. A more detailed profile of surface soil moisture was obtained with a soil heat and water flows mechanistic model. It was found that (1) the soil moisture sampling depth depends on soil moisture conditions, (2) the effective soil moisture sampling depth is shallower than provided by widely used field moisture sensors, and (3) the soil moisture sampling depth has an impact on the calibration of soil roughness model parameters. These conclusions are crucial for the calibration and validation of remote sensing data at L-band

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International audienceA meta-analysis data-driven approach is developed to represent the soil evaporative efficiency (SEE) defined as the ratio of actual to potential soil evaporation. The new model is tested across a bare soil database composed of more than 30 sites around the world, a clay fraction range of 0.02-0.56, a sand fraction range of 0.05-0.92, and about 30,000 acquisition times. SEE is modeled using a soil resistance ($r_{ss}$) formulation based on surface soil moisture ($\theta$) and two resistance parameters $r_{ss,ref}$ and $\theta_{efolding}$. The data-driven approach aims to express both parameters as a function of observable data including meteorological forcing, cut-off soil moisture value $\theta_{1/2}$ at which SEE=0.5, and first derivative of SEE at $\theta_{1/2}$, named $\Delta\theta_{1/2}^{-1}$. An analytical relationship between $(r_{ss,ref};\theta_{efolding})$ and $(\theta_{1/2};\Delta\theta_{1/2}^{-1})$ is first built by running a soil energy balance model for two extreme conditions with $r_{ss} = 0$ and $r_{ss}\sim\infty$ using meteorological forcing solely, and by approaching the middle point from the two (wet and dry) reference points. Two different methods are then investigated to estimate the pair $(\theta_{1/2} ; \Delta\theta_{1/2}^{-1})$ either from the time series of SEE and $\theta$ observations for a given site, or using the soil texture information for all sites. The first method is based on an algorithm specifically designed to accomodate for strongly nonlinear $\text{SEE}(\theta)$ relationships and potentially large random deviations of observed SEE from the mean observed $\text{SEE}(\theta)$. The second method parameterizes $\theta_{1/2}$ as a multi-linear regression of clay and sand percentages, and sets $\Delta\theta_{1/2}^{-1}$ to a constant mean value for all sites. The new model significantly outperformed the evaporation modules of ISBA (Interaction Sol-Biosph\`{e}re-Atmosph\`{e}re), H-TESSEL (Hydrology-Tiled ECMWF Scheme for Surface Exchange over Land), and CLM (Community Land Model). It has potential for integration in various land-surface schemes, and real calibration capabilities using combined thermal and microwave remote sensing data

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Abstract. Evapotranspiration has been recognized as one of the most uncertain terms in the surface water balance simulated by land surface models. In this study, the SURFEX/ISBA-A-gs (Interaction Sol-BiosphereAtmosphere) simulations of evapotranspiration are assessed at the field scale over a 12-year Mediterranean crop succession. The model is evaluated in its standard implementation which relies on the use of the ISBA pedotransfer estimates of the soil properties. The originality of this work consists in explicitly representing the succession of crop cycles and inter-crop bare soil periods in the simulations and assessing its impact on the dynamics of simulated and measured evapotranspiration over a long period of time. The analysis focuses on key parameters which drive the simulation of ET, namely the rooting depth, the soil moisture at saturation, the soil moisture at field capacity and the soil moisture at wilting point. A sensitivity analysis is first conducted to quantify the relative contribution of each parameter on ET simulation over 12 years. The impact of the estimation method used to retrieve the soil parameters (pedotransfer function, laboratory and field methods) on ET is then analysed. The benefit of representing the variations in time of the rooting depth and wilting point is evaluated. Finally, the propagation of uncertainties in the soil parameters on ET simulations is quantified through a Monte Carlo analysis and compared with the uncertainties triggered by the mesophyll conductance which is a key above-ground driver of the stomatal conductance.This work shows that evapotranspiration mainly results from the soil evaporation when it is continuously simulated over a Mediterranean crop succession. This results in a high sensitivity of simulated evapotranspiration to uncertainties in the soil moisture at field capacity and the soil moisture at saturation, both of which drive the simulation of soil evaporation. Field capacity was proved to be the most influencing parameter on the simulation of evapotranspiration over the crop succession. The evapotranspiration simulated with the standard surface and soil parameters of the model is largely underestimated. The deficit in cumulative evapotranspiration amounts to 24 % over 12 years. The bias in daily daytime evapotranspiration is −0.24 mm day −1 . The ISBA pedotransfer estimates of the soil moisture at saturation and at wilting point are overestimated, which explains most of the evapotranspiration underestimation. The use of field capacity values retrieved from laboratory methods leads to inaccurate simulation of ET due to the lack of representativeness of the soil structure variability at the field scale. The most accurate simulation is achieved with the average values of the soil properties derived from the analysis of field measurements of soil moisture vertical profiles over each crop cycle. The representation of the variations in time of the wilting point and the maximum rooting depth over the crop succession has litPublished by Copernicus Publica...

The significance of the soil surface moisture (0s) with respect to daily bare soil evaporation (Ea) is analyzed using data from numerical simulations. This was performed by running a mechanistic model of heat and water flows in the soil. The mechanistic model was calibrated and validated on three different soils with contrasted hydraulic properties. Results show that Os does not allow an accurate estimate of the ratio of Ea to the daily potential evaporation (EPa). Added variables such as Epa and the wind velocity are necessary to improve the prediction of the Ea/Epa ratio. In a second attempt, a simple model of E a is proposed. It is based on three empirical parameters and required the measurement of Os obtained at midday, Epa, and the daily wind velocity. For a given soil, a single set of the three parameters allows an accurate estimate of Ea under soil moisture and climatic conditions encountered through the year in temperate areas.