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A Fog Nowcast Method Based on Satellite Remote Sensing and Numerical Products from Meso-scale Atmospheric Model
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摘要: 以气象卫星云图为基础, 应用云雾光谱特征和结构特征进行雾区的动态检测和提取；并利用地面自动气象站资料，采用诊断分析方法探讨雾区变化与多气象要素的关系。分析表明：雾区移动速度与地面风速有关，一定的相对湿度、地气温差和风速大小等要素阈值可以作为雾的排空条件。利用经修正的中尺度数值天气预报模式输出的气象要素产品，对卫星遥感雾区进行0~2 h的外延预报，进而建立了一个大雾短时临近预报业务平台，对2009年和2010年多雾季节的1—4月大雾过程应用统计结果表明，该方法对大雾短时临近预报具有一定的效果。Abstract: 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.
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图 1 2009年1—4月上海地区能见度与相对湿度的关系
Fig. 1 Relationship between visibility and humidity in Shanghai from Jan to Apr in 2009
图 2 2009年4月10日卫星云图和经云雾分离后的雾区 (蓝色区域) 图
Fig. 2 Satellite images and the fog area (blue areas) after identification on 10 Apr 2009
图 3 WRF中尺度数值预报模式输出的2009年4月10日地面要素
(a)03:00风场 (矢量) 和04:00相对湿度 (等值线，单位：%)，(b)04:00风场 (矢量) 和05:00相对湿度 (等值线，单位：%)
Fig. 3 Output of surface elements from WRF model
(a) wind (vectors) at 0300 BT and humidity (contours, unit:%) at 0400 BT on 10 Apr 2009, (b) wind (vectors) at 0400 BT and humidity (contours, unit:%) at 0500 BT on 10 Apr 2009
图 4 WRF中尺度数值预报模式输出的2009年4月10日地气温差要素场 (单位：℃)
Fig. 4 Temperature difference between surface and air on 10 Apr 2009 from WRF model (unit: ℃)
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