设为首页
加入收藏
A Fog Nowcast Method Based on Satellite Remote Sensing and Numerical Products from Meso-scale Atmospheric Model
-
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.
-
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: ℃)
-
[1] 柳淑萍, 高松影, 曹士民.丹东附近海域海雾产生的条件及天气学预报方法.气象与环境学报, 2006, 22(1):25-28. http://www.cnki.com.cn/Article/CJFDTOTAL-LNQX200601005.htm [2] 吴洪, 柳崇健, 邵洁, 等.北京地区大雾形成的分析和预报.应用气象学报, 2000, 11(1):123-127. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20000118&flag=1 [3] 吴滨, 施能, 李玲.福建近44年雾日趋势变化特征及可能影响因素.应用气象学报, 2007, 18(4):497-505. doi: 10.11898/1001-7313.20070410 [4] 李法然, 周之栩, 陈卫锋, 等.湖州市大雾天气的成因分析及预报研究.应用气象学报, 2005, 16(6):794-803. doi: 10.11898/1001-7313.20050604 [5] 王彦磊, 曹炳伟, 黄兵, 等.基于神经网络的单站雾预报试验.应用气象学报, 2010, 21(1):110-114. doi: 10.11898/1001-7313.20100115 [6] 董剑希, 雷恒池, 胡朝霞, 等.北京及其周边地区一次大雾的数值模拟及诊断分析.气候与环境研究, 2006, 11(12):175-184. http://www.cnki.com.cn/Article/CJFDTOTAL-QHYH200602004.htm [7] Bendix J, Frank B, Christoph R. NOAA-AVHRR and 4D GIS Towards a More Realistic View of Fog Clearance.IEEE 1999 International Geoscience and Remote Sensing Symposium (IGARSS'99), Hamburg, Germany, 1999:2235-2237. [8] Rosenfeld D, Cattani E, Melan S, et al. Considerations on daylight operation of 1.6-versus 3.7-μm channel on NOAA and Metop satellites. Bull Amer Meteor Soc, 2004, 85(6): 873-881. doi: 10.1175/BAMS-85-6-873 [9] Underwood S J, Ellrod G P, Kuhnert A L. A multiple-case analysis of nocturnal radiation-fog development in the central valley of California utilizing the GOES nighttime fog product. Appl Meteor, 2004, 43(2): 297-311. doi: 10.1175/1520-0450(2004)043<0297:AMAONR>2.0.CO;2 [10] Bendix J, Thies B, Nauss T, et al. A feasibility study of daytime fog and low stratus detection with TERRA/AQUA-MODIS over land. Meteor Appl, 2006, 13(2): 111-125. doi: 10.1017/S1350482706002180 [11] 居为民, 孙涵, 张忠义, 等.卫星遥感资料在沪宁高速公路大雾监测中的初步应用.遥感信息, 1997(3):25-27. http://www.cnki.com.cn/Article/CJFDTOTAL-YGXX199703005.htm [12] 刘健, 许健民, 方宗义.利用NOAA卫星的AVHRR资料试分析云和雾顶部粒子的尺度特征.应用气象学报, 1999, 10(1):28-33. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=19990132&flag=1 [13] 张树誉.EOS-MODIS资料在陕西大雾监测中的应用.灾害学, 2003, 18(2):23-26. http://www.cnki.com.cn/Article/CJFDTOTAL-ZHXU200302005.htm [14] 李亚春, 孙涵, 徐萌.卫星遥感在大雾生消动态监测中的应用.灾害学, 2001, 16(1):45-29. http://www.cnki.com.cn/Article/CJFDTOTAL-ZHXU200101009.htm [15] 周红妹, 谈建国, 葛伟强.NOAA卫星云雾自动检测和修复方法.自然灾害学报, 2003, 12(3):41-47. http://www.cnki.com.cn/Article/CJFDTOTAL-ZRZH200303006.htm [16] Chaudhuri B B, Nirupam S. Texture Segmentation Using Fractal Dimension. IEEE PAMI-17, No.1, 1995. [17] 许小峰, 顾建峰, 李永平.海洋气象灾害.北京:气象出版社, 2009. [18] Stunder J B. An assessment of the quality of forecast trajectories. J Appl Meteor, 1996, 35:1321-1331. doi: 10.1175/1520-0450%281996%29035<1319%3AAAOTQO>2.0.CO%3B2 -
下载:
计量
- 摘要浏览量: 3283
- HTML全文浏览量: 1019
- PDF下载量: 1775
- 被引次数: 0
