Abstract
Abstract The use of multisensor, multifrequency satellite data to specify initial conditions for numerical weather prediction (NWP) models offers a unique opportunity to improve the depiction of small-scale processes in the atmosphere through a myriad of data assimilation approaches. The authors previously developed an algorithm to retrieve temperature and dewpoint profiles from a combination of infrared [high-resolution infrared radiation sounder (HIRS), 18–20-km resolution] and microwave [Advanced Microwave Sounding Unit-A (AMSU-A), 48-km resolution] data, using collocated radiosondes. Besides (and separately from) the estimation problem, one key question in the context of model initialization is how to blend multiresolution data to generate fields at the spatial resolution of the NWP model of interest. In this paper, a fractal downscaling technique is proposed to blend multiresolution satellite data and generate brightness temperature fields at 1-km resolution. The downscaled HIRS and AMSU-A data subse...
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