A Time Downscaling Scheme of Pr ecipitation by Using Geostationary Meteorological Satellite Data
Received date: 2008-04-01
Revised date: 2008-06-01
Online published: 2008-07-25
Precipitation estimation with high quality and highresolution in time and space is significant for land model simulation, land data assimilation, and the weather, climate and environment research. To estimate precipitation distribution from rain gauge, the traditional methods interpolate the precipitation in space and time without considering the function of the cloud and discontinuity of precipitation incident in time and space. The paper develops a highresolution precipitation estimation scheme by using geostationary satellite data, which estimates six- hour resolution precipitation by using multi- channel satellite data and gauge data, and then interpolates the six- hour resolution precipitation into one- hour resolution precipitation by using cloud precipitation probability as weight. The newly developed method is applied to FY2C satellite data and its 6- hour resolution precipitation data to get one- hour resolution precipitation, and is validated again precipitation observation, which shows that the scheme is reasonable.
SHI Chunxiang, XIE Zhenghui . A Time Downscaling Scheme of Pr ecipitation by Using Geostationary Meteorological Satellite Data[J]. PROGRESS IN GEOGRAPHY, 2008 , 27(4) : 15 -22 . DOI: 10.11820/dlkxjz.2008.04.003
[1] Qian T, A Dai, K E. Trenberth, et al. Simulation of global land surface conditions from 1948 - 2004. Part I: Forcing data and evaluation. J. Hydrometeorology,2006,7,953~975.
[2] Chen M, P Xie, J E Janowiak, et al. Global land precipitation: A 50- yr monthly analysis based on gauge observations. J. Hydrometeorol., 2002, 3, 249~266.
[3] Janowiak J E, A Gruber, C R Kondragunta, et al. Huffman. A comparison of the NCEP–NCAR reanalysis precipitation and the GPCP rain gauge – satellite combined dataset with observational error considerations. J. Climate, 1998, 11, 2960~2979.
[4] Ngo- Duc T, J Polcher and K Laval. A 53- year forcing data set for land surface models. J. Geophys. Res., 110, D06116, doi:10.1029/2004JD005434, 2005.
[5] Ruiz - Barradas A and S Nigam. Warm- season rainfall variability over the US Great Plains in observations, NCEP and ERA- 40 reanalyses, and NCAR and NASA AMIP simulations: Intercomparisons for NAME. J. Climate, 2005, 18: 1808~1830.
[6] Sheffield J, A D Ziegler, E F Wood, et al. Correction of the high - latitude rain day anomaly in the NCEP/NCAR reanalysis for land surface hydrological modeling, J. Climate, 2004, 17: 3814~3828.
[7] Cosgrove B A. Real Time and Retrospective Forcing in the North American Land Data Assimilation System (NLDAS) Project. Journal of Geophysics Research, 2003, 108 (D22): 8842.
[8] Luo L. Validation of the North American Land Data Assimilation System (NLDAS) Retrospective Forcing Over the Southern Great Plains. Journal of Geophysics Research, 2003, 108 (D22).
[9] Development of a European Land Data Assimilation System to Predict Floods and Droughts. Description of Work http: //www. knmi. nl/ samenw/eldas/
[10] 卢乃锰, 吴蓉璋. 强对流降水云团的云图特征分析. 应用 气象学报, 1997, 8(3): 269~275.
[11] 师春香, 卢乃锰. 卫星面降水估计人工神经网络方法. 气 候与环境研究, 2001, 6(4): 467~472.
[12] 游然, 卢乃锰. FY- 2C 卫星降水估计产品，http://satellite. cma.gov.cn/jsp/basic/onlinehelp.jsp#.
[13] 刘建，云检测. http://satellite.cma.gov.cn/jsp/basic/onlinehelp. jsp#
[14] 师春香. 高云检测，http://satellite.cma.gov.cn/jsp/basic/onlinehelp. jsp#
[15] 罗敬宁. 云分类，http://satellite.cma.gov.cn/jsp/basic/onlinehelp. jsp#
/
| 〈 |
|
〉 |