地球科学进展 ›› 2011, Vol. 26 ›› Issue (11): 1162 -1172. doi: 10.11867/j.issn.1001-8166.2011.11.1162

综述与评述 上一篇    下一篇

卫星遥感反演降水研究综述
刘元波 1,傅巧妮 1,2,宋平 1,赵晓松 1,豆翠翠 1,2   
  1. 1.中国科学院南京地理与湖泊研究所湖泊与环境国家重点实验室,江苏南京210008;2.河海大学地球科学与工程学院,江苏南京210098
  • 收稿日期:2011-04-29 修回日期:2011-08-29 出版日期:2011-11-10
  • 通讯作者: 刘元波(1969-),男,山东济宁人,研究员,主要从事水文遥感研究. E-mail:ybliu@niglas.ac.cn
  • 基金资助:

    中国科学院“百人计划”择优支持项目“基于定量遥感的湖泊蓄水量变化驱动机制研究”;中国科学院知识创新工程重要方向项目“鄱阳湖流域气候—水文—物质输移过程与湖泊水安全研究”(编号:KZCX2-YW-337)资助.

Satellite Retrieval of Precipitation: An Overview

Liu Yuanbo 1, Fu Qiaoni 1,2, Song Ping 1, Zhao Xiaosong 1, Dou Cuicui 1,2   

  1. 1.State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing210008, China;
    2.School of Earth Sciences and Engineering, Hehai University, Nanjing210098, China
  • Received:2011-04-29 Revised:2011-08-29 Online:2011-11-10 Published:2011-11-10

降水是地球水循环的基本组成部分,具有重要的气象、气候和水文学意义。精准地测量降水及其区域和全球分布,长期以来一直是一个颇具挑战性的科学研究目标。经过近50年的发展,基于可见光、红外和微波等各类卫星传感器的降水反演算法也逐渐发展成熟起来。简要回顾可见光/红外、被动微波、雷达和多传感器联合反演等卫星遥感降水反演的基本原理、主要反演算法以及存在的难点和前沿性研究问题,介绍了应用降水反演算法制成的3种主要全球降水数据集,包括热带雨林观测卫星(TRMM)、全球降水卫星制图(GSMaP)和全球降水气候项目(GPCP)数据集,并结合目前存在的问题探讨卫星降水反演研究发展趋势。

Precipitation is a fundamental component of the global water cycle. It is a key hydrologic variable of the water cycle in meteorology, climatology and hydrology. Accurate observation of precipitation and its regional, global distributions has long been a challenging scientific goal. With five-decade development of space-borne sensors, the approaches to retrieving precipitation appear mature. This paper briefly describes the principles and the main types of retrieval algorithms of precipitation using visible/infrared (VIS/IR), passive-microwave (PMW), precipitation radar (PR) data, or their combinations. The VIS/IR algorithms generally had relatively low retrieval accuracy, but it could provide better long-term retrieval due to better temporal sampling of geostationary data. The PMW algorithms were more accurate but more complicated than the VIS/IR algorithms in retrieval of instantaneous precipitation, and the PMW data had low spatial and temporal resolution. Among all the PMW algorithms, the Goddard Profiling Algorithm (GPROF) is the most widely applied one. The PR algorithm enabled capture of three-dimensional precipitation structure over the ocean and land. While the PR retrievals had accuracy on the order of ground-radar data, it had limited coverage of the Earth’s surface. The deficiencies of a single sensor algorithm were alleviated with the combination use of multi-sensors. A number of algorithms have been proposed with a particular combination of VIS/IR, PMW, and/or PR data. The commonly used algorithms include the Climate Prediction Center Morphing (CMORPH) algorithm, the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) algorithm and the Global Satellite Mapping of Precipitation (GSMaP) algorithm. Currently, scientific efforts have been made to compare and evaluate the existing algorithms, for example, the Program to Evaluate High-Resolution Precipitation Products (PEHRPP). With the development of instruments and algorithms of precipitation, there are produced many regional and global data sets dedicated to precipitation monitoring. The widely spread global precipitation datasets include TRMM, GSMaP and Global Precipitation Climatology Project (GPCP). Each data set had its unique features in terms of spatial and temporal resolutions, typically in 3-hour and 0.25 degree. For future development, the launch of the Global Precipitation Measurement (GPM) mission will improve and extend the TRMM measurements to higher latitudes, with a more frequent sampling, and a higher sensitivity to light and heavy rainfalls. Furthermore, combination of observations at different wavelengths and from both low and geostationary-orbit satellites is a promising way to produce global precipitation. The International Precipitation Working Group (IPWG) is providing a focus on the study of satellite-based quantitative precipitation measurements. With the international efforts, we are approaching to a unique retrieval of a consistent global precipitation cross multi-sensors. 

中图分类号: 

[1]Michaelides S, Levizzani V, Anagnostou E, et al. Precipitation: Measurement, remote sensing, climatology and modeling[J].Atmospheric Research, 2009, 94(4):512-533.
[2]Kummerow C, Barnes W. The Tropical Rainfall Measuring Mission (TRMM) sensor package[J]. Journal of Atmospheric and Oceanic Technology, 1998, 15(3):809-817.
[3]Kidd C. Satellite rainfall climatology: A review[J]. International Journal of Climatology, 2001, 21(9):1 041-1 066.
[4]Ebert E E, Manton M J. Performance of satellite rainfall estimation algorithms during TOGA COARE[J].Journal of the Atmospheric Sciences,1998, 55(9):1 537-1 557.
[5]Levizzani V, Bauer P, Turk F J. Measuring Precipitation from Space: EURAINSAT and the Future[M]. Berlin: Springer, 2007.
[6]Kubota T, Ushio T, Shige S, et al. Verification of high-resolution satellite—Based rainfall estimates around Japan using a gauge-calibrated ground-radar dataset[J].Journal of the Meteorological Society of Japan, 2009, 87A:203-222.
[7]Prigent C. Precipitation retrieval from space: An overview[J].Comptes Rendus Geoscience, 2010, 342(4/5):380-389.
[8]Arkin P A, Meisner B N. The relationship between large-scale convective rainfall and cold cloud over the Western Hemisphere during 1982-84[J]. Monthly Weather Review, 1987, 115(1):51-74.
[9]Ba M B, Gruber A. GOES Multispectral Rainfall Algorithm (GMSRA)[J]. Journal of Applied Meteorology, 2001, 40(8):1 500-1 514.
[10]Griffith C G, Woodley W L, Grube P G, et al. Rain estimates from geosynchronous satellite imagery: Visible and infrared studies[J]. Monthly Weather Review, 1978, 106:1 153-1 171.
[11]Xie P, Arkin P A. Global precipitation: A 17 year monthly analysis based on gauge observations, satellite estimates, and predictions[J]. Journal of Climate, 1997, 78(11):840-858.
[12]Wilheit T T, Change A T C, Rao M S V, et al. A satellite technique for quantitatively mapping rainfall rates over oceans[J]. Journal of Applied Meteorology, 1977, 16(5):551-560.
[13]Ferraro R R. Special sensor microwave imager derived global rainfall estimates for climatological applications[J]. Journal of Geophysical Research, 1997, 102(D14):715-735.
[14]Kummerow C D, Hong Y, Olson W S, et al. The evolution of the Goddard Profiling Algorithm (GPROF) for rainfall estimation from passive microwave sensors[J]. Journal of Applied Meteorology, 2001, 40(11):1 801-1 820.
[15]Iguchi T, Kozu T, Meneghini R, et al. Rain-profiling algorithm for the TRMM precipitation radar[J]. Advances in Space Research, 2000, 25(5):973-976.
[16]Joyce R J, Janowiak J E, Arkin P A, et al. CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution[J].Journal of Hydrometeorology, 2004, 5(3):487-503.
[17]Huffman G J, Alder R, Bolvin D T, et al. The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales[J]. Journal of Hydrometeorology, 2007, 8:38-55.
[18]Okamoto K, Iguchi T, Takahashi N, et al. The Global Satellite Mapping of Precipitation (GSMaP) project[C]Geoscience and Remote Sensing Symposium, IGARSS Proceedings, 2005 IEEE International,2005:3 414-3 416.
[19]Wang Jiankang. Review on the techniques for estimation of precipitation with satellite data[J].Meteorology, 1993, 19(5):3-8. [王健康. 用卫星资料估计降水方法的评述[J]. 气象, 1993,19(5):3-8.]
[20]Liu Wen, Zhao Yujin, Zhang Shanjun. Heavy rain detecting technique by GMS satellite data[J].Meteorology, 2003, 29(3):49-52.[刘文,赵玉金,张善君. GMS卫星遥感资料监测暴雨技术[J]. 气象,2003,29(3):49-52.]
[21]Li Peijun, Guo Hongtao, Huang Jianguo, et al. Rainfall estimates by GMS satellite data of severe convective cloud[J].Journal of PLA University of Science and Technology,2004, 5(1):88-92.[李培军,郭洪涛,黄建国,等. 利用GMS卫星资料进行强对流降水估计[J]. 解放军理工大学学报:自然科学版,2004,5(1):88-92.]
[22]Liu Xiaoyang, Diallo T D, Mao Jietai, et al. Monthly precipitation estimation over Western China using GMS satellite data[J]. Chinese Journal of Atmospheric Science, 2005, 29(4):518-525.[刘晓阳,Diallo T D,毛节泰,等. GMS-5卫星估计中国西部地区月降水[J]. 大气科学,2005, 29(4):518-525.]
[23]Xu Jing, Bi Baogui. Optimization and zoning test of satellite rainfall estimation product in China[J].Meteorology,2005, 31(2):27-31.[徐晶,毕宝贵. 卫星估计降水量产品的优化处理及分区检验[J]. 气象,2005,31(2):27-31.]
[24]Chen Liqun, Liu Changming, Yang Shengtian, et al. Reproduction of precipitation in the source regions of Yellow River with remote sensing[J].China Environmental Science, 2006,26(Suppl.):87-91. [陈利群,刘昌明,杨胜天,等. 黄河源区降水遥感反演[J]. 中国环境科学,2006,26(增刊):87-91.]
[25]EOS/AMSR Rainfall:Algorithm theoretical basis document[EB/OL]. NASA AMSR Joint Science Team. 1999[2011-04-25]. http:eospso.gsfc.nasa.gov/eos_homepage/for_scientists/atbd/docs/AMSR/atbd-amsr-rainfall.pdf.
[26]Savage R C, Weinman J A. Preliminary calculations of the upwelling radiance from rain clouds at 37.0 and 19.35 GHz[J].Bulletin of the American Meteorological Society, 1975, 56(12):1 272-1 274.
[27]Alishouse J C. Total precipitable water and rainfall determinations from the Seasat scanning multichannel microwave radiometer[J].Journal of Geophysical Research,1983, 88(C3):1 929-1 935.
[28]Li Xiaoqing. Review of algorithms for retrieving rainfall from spaceborne passive microwave measurements[J].Meteorological Science and Technology,2004, 32(3):149-154.[李小青. 星载被动微波遥感反演降水算法回顾[J]. 气象科技,2004,32(3):149-154.]
[29]Smith E A, Mugnai A, Cooper H J, et al. Foundations for statistical-physical precipitation retrieval from passive microwave satellite measurements. Part I: Brightness-temperature properties of a time-dependent cloud-radiation model[J].Journal of Applied Meteorology, 1992, 31(6):506-531.
[30]Mugnai A, Smith E A, Triopli G J. Foundations for statistical-physical precipitation retrieval from passive microwave satellite measurements. Part II: Emission-source and generalized weighting-function properties of a time-dependent cloud-radiation model[J]. Journal of Applied Meteorology, 1993, 32(1):17-39.
[31]Kummerow C D, Masunaga H, Bauer P. A next-generation microwave rainfall retrieval algorithm for use by TRMM and GPM[M]Levizzani V, Bauer P, Turk F J, eds. Measuring Precipitation from Space: EURAINSAT and the Future. Berlin: Springer-Verlag,2007.
[32]Iguchi T. Space-borne radar algorithms[M]∥Levizzani V, Bauer P, Turk F J, eds. Measuring Precipitation from Space: EURAINSAT and the Future. Berlin: Springer-Verlag, 2007:199-212.
[33]Morin E, Krajewski W F, Goodrich D C, et al. Estimating rainfall intensities from weather radar data: The scale-dependency problem[J].Journal of Hydrometeorology, 2003, 4(5):782-797.
[34]Shelton M L. Hydroclimatology[M]. Cambridge: Cambridge University Press, 2008.
[35]Villarini G, Krajewski W F. Review of the different sources of uncertainty in single polarization radar-based estimates of rainfall[J].Survey in Geophysics, 2010, 31(1):107-129.
[36]Iguchi T. Uncertainties in the rain profiling algorithm for the TRMM precipitation radar[J].Journal of the Meteorological Society of Japan, 2009, 87A:1-30.
[37]Bauer P, Schanz L. Outlook for combined TMI-VIRS algorithms for TRMM: Lessons from the PIP and AIP projects[J].Journal of the Atmospheric Sciences,1998, 55(9):1 714-1 729.
[38]Kubota T, Shige S, Hashizume H, et al. Global precipitation map using satellite-borne microwave radiometers by the GSMaP project: Production and validation[J]. IEEE Transactions on Geoscience and Remote Sensing,2007, 45(7):2 259-2 275.
[39]Aonashi K, Awaka J, Hirose M, et al. GSMaP passive microwave precipitation retrieval algorithm: Algorithm description and validation[J].Journal of the Meteorological Society of Japan, 2009, 87A:119-136.
[40]Ushio T, Sasashige K, Kubata T, et al. A Kalman filter approach to the Global Satellite Mapping of Precipitation (GSMaP) from combined passive microwave and infrared radiometric data[J].Journal of the Meteorological Society of Japan, 2009, 87A:137-151.
[41]Turk F J, Arkin P, Ebert E E, et al. Evaluating high-resolution precipitation products[J].Bulletin of the American Meteorological Society, 2008, 89:1 911-1 916.
[42]Sapiano M R P, Arkin P A. An intercomparison and validation of high-resolution satellite precipitation estimates with 3-hourly gauge data[J].Journal of Hydrometeorology, 2009, 10(1):149-166.
[43]Chiu L S, Liu Z, Rui H, et al. Tropical Rainfall Measuring Mission data and access tools[M]Qu J J, Gao W, Kafatos M, et al, eds. Earth Science Satellite Remote Sensing. Berlin: Springer-Verlag, 2006. 
[44]TRMM: Tropical Rainfall Measuring Mission[EB/OL]. The National Aeronautics and Space Administration. 2006 [2011-04-25]. http:trmm.gsfc.nasa.gov/data_dir/data.html.
[45]Negri A J, Bell T L, Xu L. Sampling of the diurnal cycle of precipitation using TRMM[J].Journal of Atmospheric and Oceanic Technology,2002, 19(9):1 333-1 344. 
[46]L’Ecuyer T S, McGarragh G. A 10-year climatology of tropical radiative heating and its vertical structure from TRMM observations[J].Journal of Climate,2010, 23(3):519-541.
[47]Wu Qingmei. Study of microwave characteristics of rainfall over south China and Yangtze River Basin using TRMM data[J].Journal of Applied Meteorological Science, 2003,14(2):206-214. [吴庆梅.利用TRMM卫星资料研究我国的降水的微波特征[J].应用气象学报,2003,14(2):206-214.]
[48]Bai Aijuan, Fang Jiangang, Zhang Kexiang. Summer rainfall in Shaanxi and its neighborhood regions observed by TRMM Satellite[J].Journal of Catastrophology, 2008,23(2):41-45.[白爱娟,方建刚,张科翔. TRMM卫星资料对陕西及周边地区夏季降水的探测[J]. 灾害学, 2008, 23(2):41-45.]
[49]Liu Peng. Comparison of Precipation between Rain Gauge Observations and TRMM PR Measurements[D]. Hefei:University of Science and Technology of China, 2009.[刘鹏.星载测雨雷达探测结果与地面雨量计观测结果之比较[D].合肥:中国科学技术大学,2009.]
[50]Mu Zhenxia, Jiang Huifang. Research of precipitation in the western Tianshan Mountain based on TRMM/TMI[J].Journal of Arid Land Resources and Environment,2010, 24(7):115-119.[穆振侠,姜卉芳. 基于TRMM/TM的天山西部山区降水研究[J]. 干旱区资源与环境,2010,24(7):115-119.]
[51]Janowiak J, Joyce R J, Yahosh Y. A real-time global half-hourly pixel-resolution IR dataset and its applications[J].Bulletin of American Meteorological Society,2001, 82(2):205-217.
[52]GSMaP:Global Satellite Mapping of precipitation[EB/OL]. Japan:Earth Observation Research Center, Japan Aerospace Exploration Agency, 2009[2011-04-25].http:∥sharaku.eorc.jaxa.jp/GSMaP_crest/index.html.
[53]JAXA global rainfall watch[EB/OL]. Japan:Earth Observation Research Center, Japan Aerospace Exploration Agency, 2011 [2011-04-25].http:sharaku.eorc.jaxa.jp/GSMaP/index.html.
[54]Global Precipitaion Climatology Project(GPCP). World data center for meteorology, Asheville. Global analyses of monthly precipitation derived from satellite and surface measurements. 2009 [2011-04-25]. http:∥lwf.ncdc.noaa.gov/oa/wmo/wdcamet-ncdc.html.
[55]Huffman G J, Adler R F, Morrissey M, et al. Global precipitation at one-degree daily resolution from multi-satellite observations[J].Journal of Hydrometeorology,2001, 2(1):36-50.
[56]Aldle R F, Huffman G J, Chang A, et al. The version 2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979-present)[J].Journal of Hydrometeorology, 2003, 4(6): 1 147-1 167.
[57]Xie P, Janowiak J E, Arkin P A, et al. GPCP pentad precipitation analyses: An experimental dataset based on gauge observations and satellite estimates[J].Journal of Climate, 2003, 16(13):2 197-2 214. 
[58]Assessment of global precipitation products: A project of the World Climate Research Programme Global Energy and Water Cycle Experiment (GEWEX) radiation panel[EB/OL]. Gruber A, Levizzani V.2008[2011-04-25].http:www.gewex.org/reports/2008AssessmentGlobalPrecipReport.pdf.
[59]PERSIANN  0.25°product access tools[EB/OL]. Center for Hydrometeorology and Remote Sensing. 2011 [2011-08-20]. http:chrs.web.uci.edu/persiann/data.html.
[60]Global precipitation  monitoring: CMORPH  precipitation [EB/OL]. National Weather Service Climate Precipation Center. 2005 [2011-08-20]. http:www.cpc.ncep.noaa.gov/products/janowiak/cmorph.shtml.
[61]NRL-Blended[EB/OL]. U.S.Naval Research Lab. 2010 [2011-08-20]. ftp:cics.umd.edu/pub/PEHRPP/NRL-Blended/.
[62]Hou A Y, Skofronick-Jackson G, Kummerow C D, et al. Global precipitation measurement[M]Michaelides S ed. Precipitation: Advances in Measurement, Estimation and Prediction. Berlin: Springer-Verlag, 2008.
[63]Lu Naimeng, You Ran, Zhang Wenjian. A fusing technique with satellite precipitation estimate and raingauge data [J].Acta Meteorologica Sinica, 2004, 18(2):141-146.

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