Spatio-temporal detection of fog and low stratus top heights over the Yellow Sea with geostationary satellite data as a precondition for ground fog detection - A feasibility study

摘要

An accurate cloud top retrieval from geostationary (GEO) and low earth orbit (LEO) platforms is still a pending problem. This particularly holds for low level clouds. Furthermore, cloud top height is a crucial parameter to calculate cloud immersion of underlying terrain from GEO/LEO data and thus, for the discrimination between low level stratus and ground fog, where the latter is a main obstruction for air, land and sea traffic. All problems are particularly evident for ocean areas such as the Yellow Sea where no ground observations are available. In this paper, a novel method is presented to retrieve low stratus/fog top heights with special reference to the Yellow Sea and its surroundings, based on GEO data of MTSAT-1 and MTSAT-2 (JAMI sensor) and LEO data (MODIS sensor on Terra and Aqua) using the infrared (IR) water vapor and split-window bands. Two cases with very good data coverage are discussed where the retrieved low stratus/fog heights are compared to CALIPSO cloud top heights, and simulated data using the mesoscale model WRF. The comparison of JAMI retrievals with the spatial data sources used shows an encouraging accuracy (root-mean-square error, RMSE, around 300 m) in comparison to other retrieval schemes base on IR data hitherto published. A validation of the retrievals for the position of two radiosonde stations using available sounding data of seven foggy days revealed an even better performance with an average deviation of 184 m (standard deviation of 132 m). However, the validation revealed that the application of the underlying equations to retrieve inversion strength and thickness under foggy conditions would need some adjustments because the equations taken from the work of Liu and Key (2003) were originally developed for clear sky situations. Thus, the adaptation of the original scheme during future work should especially address cloudy conditions under moderate inversion strengths which could lead to an improvement of the retrieval accuracy.