设为首页
加入收藏
The Application of Multi-source Data to Three-dimensional Cloud Amount Analysis in LAPS
-
摘要: 该文将我国FY-2C气象卫星通道数据、地面观测数据、雷达数据融合进入LAPS (Local Analysis Prediction System) 三维数据分析系统中，获得了三维云量场分布，并采用北京地区2009年11月9日08：00(北京时，下同) 和华南地区2008年6月12日14：00个例，设计了5种试验对LAPS融合的云量场进行分析。结果表明：LAPS云分析中，地面观测对云底结构起主要订正作用，雷达观测对云中、低部信息起主要订正作用，而卫星云图数据对云顶分布订正效果显著，卫星资料是获得客观三维云量场不可或缺的数据。Abstract: The quantitative three-dimensional cloud data is important in nowcasting and the modeling of weather and climate. Therefore, 5 schemes are designed to construct three-dimensional cloud amount data from FY-2C satellite data, radar data, ground observation data using LAPS (Local Analysis Prediction System) developed by NOAA ERSL. The roles of each data in LAPS system are also analyzed. Scheme 1 uses background data only, and Scheme 2 adds ground observation data. Scheme 3 employs background data and FY-2C satellite data, Scheme 4 uses background data and radar data, and Scheme 5 takes background data, ground observation data, radar data and FY-2C satellite data into consideration.The analysis indicates that every data is important in order to get more objective three-dimensional cloud distribution. Ground observation data gives information of cloud base and cloud amount for the lower atmosphere. Satellite infrared brightness temperature and visible reflectance provide cloud top height and cloud amount in the upper atmosphere. Radar data can help to construct three-dimensional cloud field in the middle and lower level. Combining all these data can provide more objective information of three-dimensional cloud amount.Comparing column cloud amount deduced by LAPS with satellite visible and infrared image shows that the cloud distribution when assimilating all these data is more consistent with real situation. Moreover, the satellite data is one of the most important data in cloud analysis in LAPS.
-
Key words:
- three-dimensional cloud amount;
- LAPS;
- multi-source data
-
图 1 北京地区2009年11月9日08:00云分析5种试验获得的沿39.8°N的三维云量场剖面图
Fig. 1 Cross section of three-dimensional cloud amount along 39.8°N at 08:00 9 November 2008 in Beijing by 5 schemes
图 2 北京地区2009年11月9日08:00云分析5种试验分析得到的柱总云量
Fig. 2 Distribution of column cloud amount at 08:00 9 November 2008 in Beijing by 5 schemes
图 3 北京地区2009年11月9日08:00 FY-2C气象卫星可见光云图 (a) 和红外云图 (b)
Fig. 3 FY-2C visible image (a) and infrared image (b) at 08:00 9 November 2008 in Beijing
-
[1] Albers S C, McGinley J A, Birkenheuer D L, et al. The Local Analysis and Prediction System (LAPS): Analyses of clouds, precipitation, and temperature. Wea Forecasting, 1996, 11:273-287. doi: 10.1175/1520-0434(1996)011<0273:TLAAPS>2.0.CO;2 [2] Zhang J. Moisture and Diabatic Initialization Based on Radar and Satellite Observation. Oklahoma:University of Oklahoma, 1999. [3] Benjamin S G, Devenyi D, Weygandt S S, et al. An hourly assimilation forecast cycle: The RUC. Mon Wea Rev, 2004, 132: 495-518. doi: 10.1175/1520-0493(2004)132<0495:AHACTR>2.0.CO;2 [4] Xue M, Droegemeier K K, Wong V, et al. The Advanced Regional Prediction System (ARPS)—A multi-scale nonhydrostatic atmospheric simulation and prediction tool. Part Ⅱ: Model physics and applications. Meteor Atmos Phys, 2001, 76:143-166. doi: 10.1007/s007030170027 [5] Hu M, Xue M. Initializing convection using cloud analysis and radar data in grid-point statistical interpolation (GSI) system and impact on the forecast of advanced research WRF. Geophy Res Letters, 2007, 34, L07808, doi: 10.1029/2006GL028847. [6] Shaw B L, Thaler E R, Szoke E J. Operational Evaluation of the LAPS-MM5 "Hot Start" Local Forecast Model.18th Conference on Weather Analysis and Forecasting, Amer Meteor Soc, 2001: 160-164. https://ams.confex.com/ams/WAF-NWP-MESO/webprogram/Paper23440.html [7] Alberoni P P, Levizzani V, Mezzasalma P, et al. Impact of Meteorological Radar and Satellite Data onto Mesoscale Analyses. Mediterranean Storms-EGS Plinius Conf 99, 2000: 545-556. https://www.researchgate.net/publication/257118791_Impact_of_meteorological_radar_and_satellite_data_onto_mesoscale_analyses [8] Shaw B L, Birkenheuer D, Albers S, et al. LAPS Diabatically Initialized MM5 for the IHOP_2002 Campaign.13th PSU/NCAR Mesoscale Model User's Workshop, 2003: 113-115. http://box.mmm.ucar.edu/mm5/workshop/ws03/session7/Shaw.pdf [9] Christopher A H. Comparing Local Analysis and Prediction System (LAPS) assimilations with independent observations. Wea Forecasting, 2006, 21: 1024-1040. doi: 10.1175/WAF961.1 [10] 鄢俊一, 王洪庆, 张焱, 等.卫星资料在中尺度模式ARPS中的应用.北京大学学报, 2006, 42: 791-795. doi: 10.3321/j.issn:0479-8023.2006.06.017 [11] 李永平, 袁招洪, 王晓峰.用多普勒雷达反射率调整模式大气的云微物理变量.应用气象学报, 2004, 15(6): 658-664. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20040679&flag=1 [12] 管成功, 陈起英, 王娟, 等.初值中云变量对T213预报性能的影响.应用气象学报, 2007, 18(5): 594-600. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20070592&flag=1 [13] 施丽娟, 许小峰, 李柏, 等.雷达资料在登陆台风"桑美"模拟中的应用.应用气象学报, 2009, 20(3): 257-266. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20090301&flag=1 [14] 李红莉, 张兵, 陈波.局地分析和预报系统 (LAPS) 及其应用.气象科技, 2008, 36(1): 20-24. http://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ200801005.htm [15] 李红莉, 崔春光, 王志斌. LAPS的设计原理、模块功能及产品应用.暴雨灾害, 2009, 28: 64-70. doi: 10.3969/j.issn.1004-9045.2009.01.010 -
下载:
点击查看大图
图(4)
计量
- 摘要浏览量: 4170
- HTML全文浏览量: 841
- PDF下载量: 1984
- 被引次数: 0
