A Fog Nowcast Method Based on Satellite Remote Sensing and Numerical Products from Meso-scale Atmospheric Model

On the basis of satellite images, the fog areas are distinguished and extracted with procedures of spectrum analysis, vein structures, shape fractals and smoothness procedures. The surface auto-weather station data in Shanghai are analyzed and diagnosed, showing that the fog moves slightly faster than the wind speed on the ground. When the relative humidity drops to lower than 91%, or the temperature difference between the sublayer and air above exceeds 3.1℃, the fog will not maintain. The wind speed thresholds for the fog to lift are 6 m/s and 11 m/s on land and sea respectively.Furthermore, a method to make fog nowcast in 2 hours is developed based on the fog coverage detected by satellite remote sensing combining with the operational meso-scale atmospheric model outputs in Shanghai Typhoon Institute. And the elements of model are modified properly based on the observations of auto-weather stations. It is proved to be efficient and accurate by case study.At last, an operational forecast platform is established and its main features include geographic information stack, satellite image editing and processing, satellite fog area identification, real-time monitoring of ground atmospheric elements, fog short-term warning product releasing, etc. Statistics with a large number of samples in foggy season of recent two years indicates that the accuracy rates of 1 and 2 hours forecast are 70% and 65%, respectively. On the other hand, this method has its limitations, e.g., the accuracy largely depends on numerical weather forecast and complexity of clouds covered. The forecast is unreliable when the atmosphere elements reach the thresholds mentioned above, and when the clouds are too thick to distinguish the fog below.