Because space-borne radiometers do not measure the Earth’s outgoing fluxes directly, angular distribution models (ADMs) are required to relate actual radiance measurement to flux at given solar angle, satellite-viewing geometries, surface, and atmospheric conditions. The conversion of one footprint broad-band radiance into the corresponding flux requires therefore one to first characterize each footprint in terms of surface type and cloud cover properties to properly select the adequate ADM.
A snow (and sea-ice) retrieval technique based on spectral measurements from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat 8 is presented. It has been developed to improve the scene identification and thus the ADM selection in the near-real time processing of the Geostationary Earth Radiation Budget (GERB) data at the Royal Meteorological Institute of Belgium. The improvement in the GERB short wave flux estimations over snow covered scene types resulting from angular conversion using dedicated snow ADMs (e.g., empirical snow ADMs and/or pre-computed theoretical snow ADM) instead of empirical snow-free ADMs is discussed. 相似文献
Drought is an important natural disaster that causes devastating impacts on the ecosystem, livestock, environment, and society. So far, various remote-sensing methods have been developed to estimate drought conditions, each of which has advantages and restrictions. This study aims to monitor the real-time drought indices at the field scales via the integration of various earth observations. Our proposed method consists of two steps. In the first step, the relationships between long-term standardized precipitation indices (SPI) derived from PERSIANN-CDR rainfall data and two drought-dependent parameters derived from MODIS products, including normalized NDVI and soil-air temperature gradient, are obtained at the spatial resolution of PERSIANN-CDR grid (approximately 25 km). As the next step, the corresponding relationships are applied to estimate the drought index maps at the spatial resolution of MODIS products (1 km). Numerous analyses are carried out to evaluate the proposed method. The results revealed that, from various drought indices, including SPIs of different timescales (1, 3, 6, and 12-months), SPI-3 and SPI-6 are more appropriate to the proposed method in terms of correlation with temperature and vegetation parameters. The findings also demonstrate the competency of the proposed method in estimating SPI indices with average RMSE 0.67 and the average correlation coefficient of 0.74. 相似文献