Semi-automatic detection of fog in the Persian Gulf and Oman Sea using MSG Images

Fog is one of the most important meteorological phenomena in the oceans and seas, which is important for maritime transport and navigation of ships. The lack of automatic meteorological stations and buoy-weather s in the oceans and seas have made it necessary to use modern technologies such as remote sensing to monitor and predict sea fog phenomena in the oceans and seas. In this study, we used a method for fog and low stratus detection based on Meteosat 8 SEVIRI data due to its excellent spatial, spectral and temporal resolutions. Fog and low stratus areidentified by a number of experiments which explicitly and implicitly address fog/low stratus spectral, spatial and microphysical properties. Validation of the results was carried out using data from meteorological stations located in the north of the Persian Gulf and Oman Sea, whichconfirmed the accuracy of the method used and the results. The algorithm is found to detect low clouds very accurately, with good probabilities of detection (POD), and false alarm ratios (FAR) which indicate the high capability of MSG images for use in operational forecasting andmonitoring systems in the Persian Gulf and the Sea Oman. The retrieval of sub-pixel and temporal effects remain issues for further investigation.

کلیدواژه ها:

Fog ، SEVIRI ، MSG ، Persian Gulf ، Gulf of Oman ، Remote Sensing