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
Title: 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
Journal: Atmospheric Research, 151: 212-223
Authors: YI L.*, S. -P. Zhang, B. Thies, X. -M. Shi, K. Trachte, and J. Bendix
Abstract:An accurate cloud top retrieval from geostationary (GEO) and low earth orbit (LEO) platformsis still a pending problem. This particularly holds for low level clouds. Furthermore, cloud topheight is a crucial parameter to calculate cloud immersion of underlying terrain from GEO/LEOdata and thus, for the discrimination between low level stratus and ground fog, where thelatter is a main obstruction for air, land and sea traffic. All problems are particularly evident forocean areas such as the Yellow Sea where no ground observations are available. In this paper, anovel method is presented to retrieve low stratus/fog top heights with special reference to theYellow 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 andsplit-window bands. Two cases with very good data coverage are discussed where theretrieved low stratus/fog heights are compared to CALIPSO cloud top heights, and simulateddata using the mesoscale model WRF. The comparison of JAMI retrievals with the spatial datasources used shows an encouraging accuracy (root-mean-square error, RMSE, around 300 m) incomparison to other retrieval schemes base on IR data hitherto published. A validation of theretrievals for the position of two radiosonde stations using available sounding data of sevenfoggy days revealed an even better performance with an average deviation of 184 m (standarddeviation of 132 m). However, the validation revealed that the application of the underlyingequations to retrieve inversion strength and thickness under foggy conditions would need someadjustments because the equations taken from the work of Liu and Key (2003) were originallydeveloped for clear sky situations. Thus, the adaptation of the original scheme during future workshould especially address cloudy conditions under moderate inversion strengths which could leadto an improvement of the retrieval accuracy.