长江流域资源与环境 >> 2015, Vol. 24 >> Issue (11): 1850-1859.doi: 10.11870/cjlyzyyhj201511007

• 自然资源 • 上一篇    下一篇

不同再分析降水数据在洞庭湖流域的精度评估

孙葭1,2, 章新平1, 黄一民3   

  1. 1. 湖南师范大学资源与环境学院, 湖南 长沙 410081;
    2. 海南师范大学地理与旅游学院, 海南 海口 571158;
    3. 衡阳师范学院资源环境与旅游管理系, 湖南 衡阳 421008
  • 收稿日期:2015-01-28 修回日期:2015-04-09 出版日期:2015-11-20
  • 通讯作者: 章新平,E-mail:zxp@hunnu.edu.cn E-mail:zxp@hunnu.edu.cn
  • 作者简介:孙葭(1974~),女,讲师,博士研究生,主要从事全球气候变化研究.E-mail:tomsunjia@126.com
  • 基金资助:
    国家自然科学基金项目(41171035,41571021);湖南省重点学科建设项目(201101);湖南省特大干旱机理研究项目(2015001)

EVALUTION OF PRECIPITATION FROM ERA-INTERIM, CRU, GPCP AND TRMM REANALYSIS DATA IN THE DONGTING LAKE BASIN

SUN Jia1,2, ZHANG Xin-ping1, HUANG Yi-min3   

  1. 1. College of Resources and Environmental Sciences, Hunan Normal University, Changsha 410081, China;
    2. College of Geography and tourism, Hainan Normal University, Haikou 571158, China;
    3. Resource Environment and Tourism Management Department, Hengyang Normal University, Hengyang 421008, China
  • Received:2015-01-28 Revised:2015-04-09 Online:2015-11-20

摘要: 收集了4种不同数据来源的再分析降水数据:欧洲中期天气预报中心大气再分析数据(ERA-intreim)、英国East Anglia大学气候研究中心数据(CRU TS3.21)、全球降水气候学项目数据(GPCP V2.2)、TRMM多卫星降水产品——TRMM 3B43(V7)和中国气象科学数据共享服务网提供的降水实测数据(CMD),用均值、偏差和偏差百分比及标准差等统计指标对再分析降水数据在洞庭湖流域的模拟精度进行评估。结果表明:(1)4种再分析数据年、季节降水量的年际变化与CMD总体相似,其中秋冬季节与CMD的一致性好于春夏季节。(2)ERA-interim数据对年均降水量的高估比例为20%以上,对季节平均降水量的高估比例为10.13%~33.65%,年、季降水量偏差百分比变化的年际变化较大;标准差的年内变化范围为12.40%~70.13%,数据集的离散程度最大。GPCP和CRU两种数据的年季降水量偏差在 -6.19%~5.71%之间变化,均值与CMD数据最为接近;CRU数据年季降水量偏差百分比的年际变化和标准差的年内变化均较GPCP的大。TRMM数据对年季降水量的高估比例为 3.67%~ 6.52%,降水量偏差百分比的年际变化稳定;标准差的年内变化范围为4.58%~14.03%,数据集的离散程度最小。(3) ERA-interim、CRU、GPCP和TRMM数据年降水量的偏差范围分别为 1 000.21~-649.51、 333.89~-643.82、292.55~-686.85、256.20~-561.27 mm。再分析降水数据对降水的低估区域均出现在以南岳站为中心的衡阳盆地,而高估区域分布则有明显差异:ERA-interim的高估极值出现在地势较高的西部,CRU和GPCP的高估极值出现在南部山地,TRMM无明显高估区域。ERA-interim数据离散程度的空间分异明显,CRU和GPCP居中,TRMM分异较不明显。所有再分析数据在西部和南部山地区域的离散程度最大。

关键词: 再分析降水数据, 洞庭湖流域, 精度, 评估

Abstract: To find a proper reanalysis dataset which could best agree with the precipitation characteristics of the Dongting lake basin (107°13'-114°18' E、24°35'-30°27' N), reanalysis precipitation data from ERA-intreim, CRU-TS3.21, GPCP V2.2 and TRMM 3B43(V7) were collected to be compared with the actual observation precipitation from CMD to assess their fitting and dispersion degree, by the analysis of mean, precipitation difference (PD), the percentage of precipitation differences (PPD) and standard deviation of PD (SD-PD) and PPD (SD-PPD). All the four reanalysis precipitation datasets were interpolated to the same 27 meteorological stations as CMD provides. The results indicated that: 1) annual and seasonal variations of the four reanalysis precipitation datasets were consistent with that of CMD, while the reanalysis precipitation data in autumn and winter fitted more closely with CMD than other seasons did;2) during 2000-2012, the average annual precipitation in Dongting lake basin of ERA-Interim, CRU, GPCP, TRMM, and CMD, are 1 648.71, 1 322.87, 1 317.76, 1 403.13 and 1 332.69 mm, respectively. Correspondingly, PPDs between four reanalysis precipitation datasets and the CMD data were 23.71%, -0.74%, -1.12% and 5.29%. In addition, spatial distribution of PD between them ranged from 1 000.21 to 649.51 mm, 333.89 to 643.82 mm, 292.55 to -686.85 mm, 256.20 to -561.27 mm, respectively, while their SD-PDs ranged from 445.89 to to 97.35 mm, 365.53 to 48.66 mm, 251.42 to 43.12 mm and 204.11 to 32.76 mm;3) of the four reanalysis precipitation datasets, ERA-interim exhibited the greatest overestimation on value and on time scale during the two periods, and its annual variation of PPD and dispersion degree were the largest. The average precipitation of CRU was more similar to CMD than that of GPCP,while the interannual variation of PPD as well as dispersion degree of GPCP were smaller than those of CRU. TRMM overestimated the precipitation slightly on time scale, and possessed stable interannual variation and minimum dispersion degree;4) precipitation in Hengyang basin, with Nanyue station as the center, were underestimated by all reanalysis datasets. The spatial distribution of overestimated value had significant difference. Overestimated extremum for ERA-interim occurred in western mountain area, however, for CRU and GPCP, in southern mountain area, and the overestimated area was not obvious for TRMM. There was distinct difference in spatial distribution of dispersion degree for ERA-interim data, followed by CRU, then GPCP, and there was no significant difference for TRMM. The maximum dispersion degree of all reanalysis data existed in western and southern mountain area of the Dongting lake basin. According to the analysis above, although TRMM data overestimated the mean value slightly, it was found that TRMM data presented the best consistency with CMD data than GPCP and CRU data did, and ERA-Interim data was the worst.

Key words: Reanalysis precipitation data, the Dongting Lake Basin, Evaluation

中图分类号: 

  • P9
[1] PRIGENT C. Precipitation retrieval from space: An overview[J]. Comptes Rendus Geoscience, 2010, 342(4/5): 380-389.
[2] 胡庆芳.基于多源信息的降水空间估计及其水文应用研究[D].北京:清华大学博士学位论文,2013.
[3] 阚宝云,苏凤阁,童 凯,等.四套降水资料在喀喇昆仑山叶尔羌河上游流域的适用性分析[J].冰川冻土,2013,35(3):710-722.
[4] 闻新宇,王绍武,朱锦红.英国CRU高分辨率格点资料揭示的20世纪中国气候变化[J].大气科学,2006,30(5):894-904.
[5] 罗 健,荣艳淑.利用英国CRU资料重建华北地区百年蒸发量及变化分析[C].第三届全国水力学与水利信息学大会.南京:中国水利学会,2007:1-6.
[6] CHEN L, FRAUENFELD O W. A comprehensive evaluation of precipitation simulations over China based on CMIP5 multimodel ensemble projections[J]. Journal of Geophysical Research: Atmospheres, 2014, 119(10): 5767-5786.
[7] DELWORTH T L, ZENG F R. Regional rainfall decline in Australia attributed to anthropogenic greenhouse gases and ozone levels[J]. Nature Geoscience, 2014, 7(8): 583-587.
[8] BERRISFORD P, KÅLLBERG P, KOBAYASHI S, et al. Atmospheric conservation properties in ERA-Interim[J]. Quarterly Journal of the Royal Meteorological Society, 2011, 137(659): 1381-1399.
[9] 许建玉,王艳杰.基于ERA Interim资料的2003年淮河流域梅雨期水汽收支分析[J].暴雨灾害,2013,32(4):324-329.
[10] 吕少宁,文 军,刘 蓉.中国大陆地区不同降水资料的适用性及其应用潜力[J].高原气象,2011,30(3):628-640.
[11] 王 芬,曹 杰,李腹广,等.多套格点降水资料在云南及周边地区的对比[J].应用气象学报,2013,24(4):472-483.
[12] 成晓裕,王艳华,李国春,等.三套再分析降水资料在中国区域的对比评估[J].气候变化研究进展,2013,9(4):258-265.
[13] ZHAO T B, FU C B. Comparison of products from ERA-40, NCEP-2, and CRU with station data for summer precipitation over China[J]. Advances in Atmospheric Sciences, 2006, 23(4): 593-604.
[14] 胡增运,倪勇勇,邵 华,等.CFSR、ERA-Interim和MERRA降水资料在中亚地区的适用性[J].干旱区地理,2013,36(4):700-708.
[15] 范彬彬,罗格平,张 弛,等.新疆夏季降水时空分布的适用性评估[J].地理研究,2013,32(9):1602-1612.
[16] ADLER 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): 1147-1167.
[17] 自 勇,许吟隆,傅云飞.GPCP与中国台站观测降水的气候特征比较[J].气象学报,2007,65(1):63-74.
[18] 白建锋,赵红莉,蒋云钟,等.全球共享GPCP数据在长江中下游地区的适用性分析[J].南水北调与水利科技,2011,9(6):33-38.
[19] 王红丽,刘 健,况雪源.四种再分析资料与长江中下游地区降水观测资料的对比研究[J].长江流域资源与环境,2008,17(5):703-711.
[20] 刘向培,王汉杰,刘金波.区域气候模式分辨率对夏季降水模拟的影响[J].水科学进展,2011,22(5):615-623.
[21] 况雪源,刘 健,王红丽,等.近千年来中国区域降水模拟与重建资料的对比分析[J].地球科学进展,2009,24(2):159-171.
[22] 刘俊峰,陈仁升,卿文武,等.基于TRMM降水数据的山区降水垂直分布特征[J].水科学进展,2011,22(4):447-454.
[23] CHENG M H, HE H Z, MAO D Y, et al. Study of 1998 heavy rainfall over the Yangtze river basin using TRMM data[J]. Advances in Atmospheric Sciences, 2001, 18(3): 387-396.
[24] 曾红伟,李丽娟.澜沧江及周边流域TRMM 3B43数据精度检验[J].地理学报,2011,66(7):994-1004.
[25] 王 超,赵传燕.TRMM多卫星资料在黑河上游降水时空特征研究中的应用[J].自然资源学报,2013,28(5):862-872.
[26] ZHANG T, HE Y Q, MA J, et al. Spatial and temporal distribution of precipitation based on corrected TRMM data around the Hexi Corridor, China[J]. Sciences in Cold and Arid Regions, 2014, 6(2): 159-167.
[27] 王国杰,姜 彤,王艳君,等.洞庭湖流域气候变化特征(1961-2003年)[J].湖泊科学,2006,18(5):470-475.
[28] 黄菊梅,邹用昌,彭嘉栋,等.1960—2011年洞庭湖区年降水量变化特征[J].气象与环境学报,2013,29(6):81-86.
[29] 李景刚,黄诗峰,李纪人,等.1960-2008年间洞庭湖流域降水变化时空特征分析[J].中国水利水电科学研究院学报,2010,8(4):275-280.
[30] 李景刚,李纪人,黄诗峰,等.基于TRMM数据和区域综合Z指数的洞庭湖流域近10年旱涝特征分析[J].资源科学,2010,32(6):1103-1110.
[31] 李景刚,黄诗峰,李纪人.TRMM数据在区域同期降水趋势特征分析中的应用[J].中国水利水电科学研究院学报,2012,10(2):98-104.
[32] 刘 晗.基于地理格网的洞庭湖流域降水变化分析[D].湘潭:湖南科技大学,2012.
[33] 张剑明,黎祖贤,章新平,等.湖南省近46年来降水时空分布特征及趋势分析[J].水文,2009,29(4):73-78.
[34] 中国气象局. 中国地面气候资料月值数据集[DB/OL].http://cdc.cma.gov.cn/ dataSetDetailed.do#.2014.
[35] DEED P, UPPALA S M, SIMMONS A J, et al. The ERA-Interim reanalysis: Configuration and performance of the data assimilation system[J]. Quarterly Journal of the Royal Meteorological Society, 2011, 137(656): 553-597.
[36] ECMWF. ERA-Interim[DB/OL].http://data-portal.ecmwf.int/data/d/interim_full_mnth/. 2014.
[37] JONES P D, HARRIS I. CRU TS3.21: Climatic Research Unit (CRU) Time-Series (TS) Version 3.21 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901-Dec. 2012). NCAS British Atmospheric Data Centre, 2013.
[38] NASA . GPCP Version 2.2 Combined Precipitation Data Set (Final)[DB/OL].http://www.esrl.noaa.gov/ psd/data/gridded/data.gpcp.html.2014.
[39] NASA.3B43: Monthly 0.25 x 0.25 degree merged TRMM and other sources estimates[DB/OL].http://mirador.gsfc.nasa.gov/, 2014.
[40] 左德鹏, 徐宗学, 程 磊, 等. 渭河流域潜在蒸散量时空变化及其突变特征[J].资源科学, 2011,33(5): 975-982.
[41] 阎 洪. 气候时空数据的样条插值与应用[J].地理与地理信息科学, 2003, 19(5): 27-31.
[42] 刘劲松, 陈 辉, 杨彬云, 等. 河北省年均降水量插值方法比较[J].生态学报, 2009, 29(7): 3493-3500.
[43] 祝青林, 张留柱, 于贵瑞, 等. 近 30 年黄河流域降水量的时空演变特征[J].然资源学报, 2005, 20(4): 477-482.
[44] MA L, ZHANG T, FRAUENFELD O W, et al. Evaluation of precipitation from the ERA-0, NCEP-1, and NCEP-2 Reanalyses and CMAP-1, CMAP-2, and GPCP-2 with ground-based measurements in China[J]. Journal of Geophysical Research: Atmospheres (1984-2012), 2009, 114(D9).
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