Surface soil moisture (SSM) is a critical variable for understanding water and energy flux between the atmosphere and the Earth's surface. An easy to apply algorithm for deriving SSM time series that primarily uses temporal parameters derived from simulated and in situ datasets has recently been reported. This algorithm must be assessed for different biophysical and atmospheric conditions by using actual geostationary satellite images. In this study, two currently available coarse‐scale SSM datasets (microwave and reanalysis product) and aggregated in situ SSM measurements were implemented to calibrate the time‐invariable coefficients of the SSM retrieval algorithm for conditions in which conventional observations are rare. These coefficients were subsequently used to obtain SSM time series directly from Meteosat Second Generation (MSG) images over the study area of a well‐organized soil moisture network named REMEDHUS in Spain. The results show a high degree of consistency between the estimated and actual SSM time series values when using the three SSM dataset‐calibrated time‐invariable coefficients to retrieve SSM, with coefficients of determination (R2) varying from 0.304 to 0.534 and root mean square errors ranging from 0.020 m3/m3 to 0.029 m3/m3. Further evaluation with different land use types results in acceptable debiased root mean square errors between 0.021 m3/m3 and 0.048 m3/m3 when comparing the estimated MSG pixel‐scale SSM with in situ measurements. These results indicate that the investigated method is practical for deriving time‐invariable coefficients when using publicly accessed coarse‐scale SSM datasets, which is beneficial for generating continuous SSM dataset at the MSG pixel scale. 相似文献
The effects of surface flux parameterizations on tropical cyclone(TC) intensity and structure are investigated using the Advanced Research Weather Research and Forecasting(WRF-ARW) modeling system with high-resolution simulations of Typhoon Morakot(2009).Numerical experiments are designed to simulate Typhoon Morakot(2009) with different formulations of surface exchange coefficients for enthalpy(C_K) and momentum(C_D) transfers,including those from recent observational studies based on in situ aircraft data collected in Atlantic hurricanes.The results show that the simulated intensity and structure are sensitive to C_K and C_D,but the simulated track is not.Consistent with previous studies,the simulated storm intensity is found to be more sensitive to the ratio of C_K/C_D than to C_K or C_D alone.The pressure-wind relationship is also found to be influenced by the exchange coefficients,consistent with recent numerical studies.This paper emphasizes the importance of C_D and C_K on TC structure simulations.The results suggest that C_D and C_K have a large impact on surface wind and flux distributions,boundary layer heights,the warm core,and precipitation.Compared to available observations,the experiment with observed C_D and C_K generally simulated better intensity and structure than the other experiments,especially over the ocean.The reasons for the structural differences among the experiments with different C_D and C_K setups are discussed in the context of TC dynamics and thermodynamics. 相似文献
The orbital and the rational polynomial coefficients (RPC) models are the two most commonly used models to compute a three-dimensional coordinates from an image stereo-pair. But it is still confusing that with the identical user provided inputs, which one of these two models provides more accurate digital elevation model (DEM), especially for mountainous terrain. This study aimed to find out the answer by evaluating the impact of used models on the vertical accuracy of DEM extracted from Cartosat-1 stereo data. We used high-accuracy photogrammetric DEM as the reference DEM. Apart from general variations in statistics, surprisingly in a few instances, both the DEMs provided contrasting results, thus proving the significance of this study. The computed root mean square errors and linear error at 90% (LE90) were lower in case of RPC DEM for various classes of slope, aspect and land cover, thus suggesting its better relative accuracy. 相似文献