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The use of weather forecasting models in energy applications has proven to be an effective tool in the management of renewable energy sources in power distribution networks which requires precise predictions and high-resolution of solar radiation and wind speed data. Therefore, the use of data from meteorological satellites such as Meteosat second Generation (MSG) can produce improvements in weather forecasting results. The integration of satellite data in weather prediction models is a developing field, because the assimilated data for these types of models mainly proceed from in-situ data at multiple stations, with low spatial resolution. The objective of this work has been the integration of data from the MSG satellite in the assimilation of meteorological model Weather Research and Forecasting (WRF-ARW), trying to improve results in meteorology predictions used in renewable power applications. [ABSTRACT FROM PUBLISHER]

Focusing on Asian dust aerosols, the Community Radiative Transfer Model (CRTM) developed at JCSDA under NOAA/NESDIS is used to simulate the effects of dust on the observations from 10–12µm split-window channels of the Visible and InfraRed Radiometor(VIRR) on Chinese FengYun-3A (FY-3A) satellite. Based on the simulation, an infrared dust retrieving algorithm is developed with VIRR data, in which the effective radius of Asian dust is defined with the ground measurements from SKYNET. The optical thickness and height of the dust layer are retrieved simultaneously with this algorithm. The results show the optical thickness of dust layer is reliable comparing with the height. The errors in the calibration of sensors and surface temperature may have large effect on the retrieving. [ABSTRACT FROM PUBLISHER]