UC Irvine

An efficient method for estimating cloud top heights and correcting cloud image spatial displacements was developed. The method applies stereoscopic analysis to a pair of scan-synchronous infrared cloud images received from two GOES satellites using a piecewise linear approximation of the relationship between height and infrared brightness temperature of top of the cloud element. The algorithm solves for cloud top heights and subsequently calculates the spatial displacements of cloud images. Optimal parameterization of the piecewise linear approximation is achieved using the shuffled complex evolution (SCE) algorithm. Because the proposed method simplifies the stereoscopic analysis, it allows for an easy implementation of stereoscopic technique on desktop computers. When compared to the standard isotherm matching approaches, the proposed method yielded higher correlation between GOES 8 and GOES 9 scan- simultaneous images after the parallax adjustment. The validity of the linear approximation was tested against temperature profiles obtained from the multiple ground sounding measurements from the Tropical Rainfall Measuring Mission/Texas and Florida Underflights (TRMM/TEFLUN) experiments. The results of this comparison demonstrated good fit, particularly within the troposphere, between the optimized relationship and atmospheric sounding measurements. The data produced by this method, including cloud top temperatures and heights, atmospheric temperature profiles for cloudy sky areas, and spatial displacement-adjusted cloud images, can be useful for weather/climate and atmospheric studies. In particular, the displacement-adjusted cloud images can be critical to develop high-resolution satellite rainfall estimates, which are urgently needed by mesoscale atmospheric modeling and studies, severe weather monitoring, and heavy precipitation and flash flood forecasting. Limitations of the proposed method are also identified and discussed. Copyright 2000 by the American Geophysical Union.