Phenology and associated canopy development exert a strong control over seasonal energy and mass exchanges between the earth's surface and the atmosphere. Satellite measurements are used to assess main phenological stages of the vegetation at the global scale. The authors propose a method to derive the start, the maximum, the end, and the length of the vegetation cycle, based on the analysis of temporal series of weekly vegetation index, at a resolution of 1Њ lat ϫ 1Њ long for year 1986. Global maps of these characteristics of the vegetation are presented, and their zonal distribution is discussed. The start of the vegetation cycle has been related to temperature sums in the case of temperate deciduous forest and to precipitation in the case of savannahs. It is concluded that satellite measurements offer interesting perspectives for global-scale quantitative phenology modeling.
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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...
Models simulating the seasonal growth of vegetation have been recently coupled to soil-vegetation-atmosphere transfer schemes (SVATS). Such coupled vegetation-SVATS models (V-S) account for changes of the vegetation leaf area index (LAI) over time. One problem faced by V-S models is the high number of parameters that are required to simulate different sites or large areas. Therefore, efficient calibration procedures are needed. This study describes an attempt to calibrate a V-S model with satellite [Advanced Very High Resolution Radiometer (AVHRR)] data in the shortwave and longwave domains. A V-S model is described using ground data collected over three semiarid grassland sites during the Hydrological Atmospheric Pilot Experiment (HAPEX)-Sahel experiment. The effect of calibrating model parameters with time series of normalized difference vegetation index (NDVI) and thermal infrared (TIR) data is assessed by examining the simulated latent heat flux (LE) and LAI for a suite of calibration experiments. A sensitivity analysis showed that the parameters related to plant growth vigor and to soil evaporative resistance were the best candidates for calibration. The NDVI and TIR time series were used to calibrate these parameters, both independently and simultaneously, to assess their synergy. Ground-based, airborne, and satellite sensor (AVHRR) data were successively investigated. Both airborne and AVHRR NDVI data could be used to constrain the vegetation growth vigor. These calibrations significantly improved the simulation of the LAI and LE (rmse decreased by 21% for LE), and the site-to-site variability was greatly enhanced. The soil resistance could also be calibrated with ground-based TIR data, but the effect on the simulated variables was small. Although both NDVI and ground-based TIR data were suitable to constrain the V-S model, the synergy between the two wavelengths was not clearly established. Last, satellite TIR data from the AVHRR proved unsuitable for model calibration. Indeed, the AVHRR surface temperature values were systematically lower than both ground-based data and model outputs. The authors conclude that the calibration of a vegetation-SVAT model with shortwave AVHRR time series can be used to scale the energy and water fluxes up to the regional scale.
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