天山山区TRMM降水数据的空间降尺度研究

doi:10.11849/zrzyxb.20161384

自然资源学报 ›› 2018, Vol. 33 ›› Issue (3): 478-488.doi: 10.11849/zrzyxb.20161384

天山山区TRMM降水数据的空间降尺度研究

范雪薇¹, 刘海隆^2,*

1. 石河子大学水利建筑工程学院,新疆石河子 832003;
2. 电子科技大学资源与环境学院,成都 611731

收稿日期:2016-12-13 修回日期:2017-06-19 出版日期:2018-03-20 发布日期:2018-03-20
通讯作者: *刘海隆（1974- ）,男,四川人,教授,博士,主要从事3S技术应用研究。E-mail: liu_hai_tiger@163.com
作者简介:范雪薇（1992- ）,女,新疆昌吉人,硕士研究生,专业方向为水文及水资源。E-mail: 15009935851@163.com
基金资助:
国家自然科学基金项目（51569027）; 兵团空间信息创新团队（2016AB001）

Downscaling Method of TRMM Satellite Precipitation Data over the Tianshan Mountains

FAN Xue-wei¹, LIU Hai-long²

1. College of Water Conservancy and Architectural Engineering, Shihezi University, Shihezi 832003, China;
2. School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China

Received:2016-12-13 Revised:2017-06-19 Online:2018-03-20 Published:2018-03-20
Supported by:
National Natural Science Foundation of China, No. 51569027; XJCC Innovation Team of Geospatial Information Technology, No. 2016AB001.

摘要/Abstract

摘要： 山区降水是干旱区水资源的重要补给源,但由于山区地形复杂、监测困难造成资料缺乏,水文预报的误差较大。近年来,TRMM3B43降水数据得到了大量应用,但受其较低空间分辨率的影响,使得应用精度受到限制。论文以2001—2010年TRMM3B43数据为基础,结合提取的7个数字地形因子（经度、纬度、坡度、坡向、海拔、地形开阔度、地形起伏度）,构建了天山山区年、季的降水主成分-逐步回归降尺度模型。分析结果表明：主成分-逐步回归降尺度模型有效地将TRMM3B43数据的空间分辨率由0.25°×0.25°提高到1 km×1 km。通过站点实测降水数据对比验证,决定系数均在0.85以上,降尺度后的数据精度显著优于原始TRMM3B43数据。该方法对研究干旱区空间降水精细化具有一定参考意义。

关键词: TRMM, 地形因子, 降尺度, 降水

Abstract: The precipitation in mountains is an important supply of water resources in arid areas. The error of hydrology forecast is still high in mountain areas because of complex terrain and lack of data. In recent years, TRMM3B43 data have been widely used in precipitation estimation. However, there is limit of TRMM data in resolution (0.25°×0.25°). Based on the TRMM3B43 data during 2001-2010, a principal component-stepwise regression model for downscaling TRMM3B43 precipitation was built with seven topographic factors (longitude, latitude, altitude, slope, aspect, terrain unobstructed factor, relief degree of land surface) in this paper. The downscaling model can transform the pixel resolution from 0.25°×0.25° to 1 km×1 km effectively. The downscaled precipitation estimations were subsequently validated by observed data at 21 raingauge stations in Tianshan Mountains during 10 years. The results showed that: 1) The downscaled precipitation results have smaller errors than the original TRMM precipitation data, and the maximal improved value of annual average precipitation is 63.16 mm, suggesting the good performance of principal component-stepwise regression downscaling model. 2) The spatial distribution characteristics of precipitation in the Tianshan Mountain can be depicted by downscaled results in detail that the high precipitation values mainly appear in the Yili Valley of the western Tianshan Mountains and the low values appear in Turpan and Hami of the eastern Tianshan Mountains. 3) The downscaled results conform well with the observed data in each elevation zone in the Tianshan Mountains, but the downscaled results overestimated the actual precipitation to some extent. So the downscaling method in this article is feasible, which could provide spatial distribution of precipitation in fine resolution in arid region.

Key words: downscaling, precipitation, topographic factors, TRMM

中图分类号:

P468.0⁺24

范雪薇, 刘海隆. 天山山区TRMM降水数据的空间降尺度研究[J]. 自然资源学报, 2018, 33(3): 478-488.

FAN Xue-wei, LIU Hai-long. Downscaling Method of TRMM Satellite Precipitation Data over the Tianshan Mountains[J]. JOURNAL OF NATURAL RESOURCES, 2018, 33(3): 478-488.

参考文献

[1] VIVIROLI D, DÜRR H H, MESSERLI B, et al. Mountains of the world, water towers for humanity: Typology, mapping, and global significance[J]. Water Resources Research, 2007, 43(7): W07447. doi: 10.1029/2006WR005653.
[2] ZHANG K X, PAN S M, CAO L G, et al.Spatial distribution and temporal trends in precipitation extremes over the Hengduan Mountains region, China, from 1961 to 2012[J]. Quaternary International, 2014, 349: 346-356.
[3] CHEVAL S, BIRSAN M V, DUMITRESCU A.Climate variability in the Carpathian Mountains region over 1961-2010[J]. Global and Planetary Change, 2014, 118: 85-96.
[4] DALY C, NEILSON R P, PHILLIPS D L.A statistical topographic model for mapping climatological precipitation over mountainous terrain[J]. Journal of Applied Meteorology, 1994, 33(2): 140-158.
[5] PARDO-IGUZQUIZA E.Comparison of geostatistical methods for estimating the areal average climatological rainfall mean using data on precipitation and topography[J]. International Journal of Climatology, 1998, 18: 1031-1047.
[6] GOOVAERTS P.Using elevation to aid the geostatistical mapping of rainfall erosivity[J]. Catena, 1999, 34(3/4): 227-242.
[7] KYRIAKIDIS P C, MILLER N L, KIM J.A spatial time series framework for simulating daily precipitation atregional scales[J]. Journal of Hydrology, 2004, 297(1/4): 236-255.
[8] 傅抱璞. 地形和海拔高度对降水的影响[J]. 地理学报, 1992, 47(4): 302-314.
[FU B P.The effects of topography and elevation on precipitation. Acta Geographica Sinica, 1992, 47(4): 302-314. ]
[9] 舒守娟, 王元, 熊安元. 中国区域地理、地形因子对降水分布影响的估算和分析[J]. 地球物理学报, 2007, 50(6): 1703-1712.
[SHU S J, WANG Y, XIONG A Y.Estimation and analysis for geographic and orographic influences on precipitation distribution in China. Chinese Journal of Geophysics, 2007, 50(6): 1703-1712. ]
[10] 穆振侠, 姜卉芳. 基于TRMM/TMI的天山西部山区降水垂直分布规律的研究[J]. 干旱区资源与环境, 2010, 24(10): 66-71.
[MU Z X, JIANG H F.The vertical distribution law of precipitation in the western Tianshan Mountain based on TRMM/TMI. Journal of Arid Land Resources and Environment, 2010, 24(10): 66-71. ]
[11] 张正勇, 何新林, 刘琳, 等. 中国天山山区降水空间分布模拟及成因分析[J]. 水科学进展, 2015, 26(4): 500-508.
[ZHANG Z Y, HE X L, LIU L, et al.Spatial distribution of rainfall simulation and the cause analysis in China’s Tianshan Mountains area. Advances in Water Science, 2015, 26(4): 500-508. ]
[12] 穆振侠, 姜卉芳, 党建新, 等. 不同地形对山区降水垂直分布规律的影响[J]. 新疆农业大学学报, 2010, 33(1): 66-71.
[MU Z X, JIANG H F, DANG J X, et al.Effects of different topographies on vertical distribution law of precipitation in mountain region. Journal of Xingjiang Agricultural University, 2010, 33(1): 66-71. ]
[13] MICHAELIDES S C, TYMVIOS F S, MICHAELIDOU T.Spatial and temporal characteristics of the annual rainfall frequency distribution in Cyprus[J]. Atmospheric Research, 2009, 94(4): 606-615.
[14] IMMERZEEL W W, RUTTEN M M, DROOGERS P.Spatial downscaling of TRMM precipitation using vegetative response on the Iberian Peninsula[J]. Remote Sensing of Environment, 2009, 113(2): 362-370.
[15] JIA S F, ZHU W B, LÜ A F, et al.A statistical spatial downscaling algorithm of TRMM precipitation based on NDVI and DEM in the Qaidam Basin of China[J]. Remote Sensing of Environment, 2011, 115(12): 3069-3079.
[16] DUAN Z, BASTIAANSSEN W G M. First results from Version 7 TRMM 3B43 precipitation product in combination with a new downscaling-calibration procedure[J]. Remote Sensing of Environment, 2013, 131: 1-13.
[17] 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.
[WANG C, ZHAO C Y.A study of the spatio-temporal distribution of precipitation in upper reaches of Heihe River of China using TRMM data. Journal of Natural Resources, 2013, 28(5): 862-872.
[18] 李净, 张晓. TRMM降水数据的空间降尺度方法研究[J]. 地理科学, 2015, 35(9): 1164-1169.
[LI J, ZHANG X.Downscaling method of TRMM satellite precipitation data. Scientia Geographica Sinica, 2015, 35(9): 1164-1169. ]
[19] 中国科学院新疆综合考察队. 新疆地貌 [M]. 北京: 科学出版社, 1978.
[Xingjiang Comprehensive Investigation Team of Chinese Academy of Sciences. Xinjiang Landform. Beijing: Science Press, 1978. ]
[20] 胡汝骥. 中国天山自然地理 [M]. 北京: 中国环境科学出版社, 2004.
[HU R J.Natural Geography of Tianshan Mountains in China. Beijing: China Environmental Science Press, 2004. ]
[21] 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.
[LIU J F, CHEN R S, QING W W, et al.Study on the vertical distribution of precipitation in mountainous regions using TRMM data. Advances in Water Science, 2011, 22(4): 447-454. ]
[22] 廖菲, 洪延超, 郑国光. 地形对降水的影响研究概述[J]. 气象科技, 2007, 35(3): 309-316.
[LIAO F, HONG Y C, ZHENG G G.Review of orographic influences on surface precipitation. Meteorological Science and Technology, 2007, 35(3): 309-316. ]
[23] 魏文寿, 胡汝骥. 中国天山的降水与气候效应[J]. 干旱区地理, 1990, 13(1): 29-36.
[WEI W S, HU R J.Precipitation and climate conditions of Tianshan Mountains. Arid Land Geography, 1990, 13(1): 29-36. ]
[24] 吴诚鸥, 秦伟良. 近代实用多元统计分析 [M]. 北京: 气象出版社, 2007.
[WU C O, QIN W L. Multivariate Statistical Analysis.Beijing: Meteorological Press, 2007. ]
[25] 贺江舟, 龚明福, 范君华, 等. 逐步回归及通径分析在主成分分析中的应用[J]. 新疆农业科学, 2010, 47(3): 431-437.
[HE J Z, GONG M F, FAN J H, et al.Application of stepwise regression and path analysis in principal component. Xinjiang Agricultural Sciences, 2010, 47(3): 431-437. ]
[26] PROPASTIN P, KAPPAS M, ERASMI S.Application of geographically weighted regression to investigate the impact of scale on prediction uncertainty by modelling relationship between vegetation and climate[J]. International Journal of Spatial Data Infrastructures Research, 2008, 3: 73-94.
[27] FOTHERINGHAM A S, CHARLTON M E, BRUNSDON C.Geographically weighted regression: A natural evolution of the expansion method for spatial data analysis[J]. Environment and Planning A, 1998, 30: 1905-1927.
[28] 刘小婵, 张洪岩, 赵建军, 等. 东北地区TRMM数据降尺度的GWR模型分析[J]. 地球信息科学学报, 2015, 17(9): 1055-1062.
[LIU X C, ZHANG H Y, ZHAO J J, et al.Spatial downscaling of TRMM precipitation data based on GWR model in Northeast China. Journal of Geo-Information Science, 2015, 17(9): 1055-1062. ]
[29] LÜ A F, LEI Z.A rainfall model based on a geographically weighted regression algorithm for rainfall estimations over the arid Qaidam Basin in China[J]. Remote Sensing, 2016, 8(4): 311. doi: 10.3390/rs8040311.
[30] CAI Y C, JIN C J, WANG A Z, et al.Comprehensive precipitation evaluation of TRMM 3B42 with dense rain gauge networks in a mid-latitude basin, northeast, China[J]. Theoretical & Applied Climatology, 2016, 126(3/4): 659-671.

天山山区TRMM降水数据的空间降尺度研究

Downscaling Method of TRMM Satellite Precipitation Data over the Tianshan Mountains

RichHTML

PDF (PC)

赞

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	何振芳, 郭庆春, 刘加珍, 张莹莹, 刘杰, 丁航. 河北省大气污染时空变化特征及其影响因素[J]. 自然资源学报, 2021, 36(2): 411-419.
[2]	薛海, 张帆. 降水量与城市大气环境关系——以113个环保重点城市为例[J]. 自然资源学报, 2020, 35(4): 937-949.
[3]	马伟东, 刘峰贵, 周强, 陈琼, 刘飞, 陈永萍. 1961—2017年青藏高原极端降水特征分析[J]. 自然资源学报, 2020, 35(12): 3039-3050.
[4]	费龙, 邓国荣, 张洪岩, 郭笑怡, 王晓东. 基于降水Z指数的朝鲜降水及旱涝时空特征[J]. 自然资源学报, 2020, 35(12): 3051-3065.
[5]	余灏哲, 李丽娟, 李九一. 基于TRMM降尺度和MODIS数据的综合干旱监测模型构建[J]. 自然资源学报, 2020, 35(10): 2553-2568.
[6]	石育中, 杨新军, 赵雪雁. 气象干旱对甘肃省榆中县乡村社会—生态系统的影响[J]. 自然资源学报, 2019, 34(9): 1987-2000.
[7]	李明, 王贵文, 柴旭荣, 胡炜霞, 张莲芝. 基于空间聚类的中国东北气候分区及其气象干旱时间变化特征[J]. 自然资源学报, 2019, 34(8): 1682-1693.
[8]	汪成博, 李双双, 延军平, 武亚群. 1970-2015年汉江流域多尺度极端降水时空变化特征[J]. 自然资源学报, 2019, 34(6): 1209-1222.
[9]	陈琦, 郭锦荣, 李超, 王翰琨, 吴春生, 邓文平, 刘苑秋, 叶清, 李晓东. 庐山地区大气降水中稳定同位素变化特征[J]. 自然资源学报, 2019, 34(6): 1306-1316.
[10]	孙美平, 张海瑜, 巩宁刚, 闫露霞, 赵琳林. 基于TRMM降水订正数据的祁连山地区最大降水高度带研究[J]. 自然资源学报, 2019, 34(3): 646-657.
[11]	李明, 柴旭荣, 王贵文, 胡炜霞, 张莲芝. 长江中下游地区气象干旱特征[J]. 自然资源学报, 2019, 34(2): 374-384.
[12]	陈洁, 刘玉洁, 潘韬, 吴绍洪, 谭清华, 葛全胜, 刘燕华. 1961-2010年中国降水时空变化特征及对地表干湿状况影响[J]. 自然资源学报, 2019, 34(11): 2440-2453.
[13]	李沛, 黄生志, 黄强, 马岚, 吴洪石, 栾金凯. 大通河流域降水结构的演变特征及其驱动力探究[J]. 自然资源学报, 2018, 33(9): 1588-1598.
[14]	张钦弟, 卫伟, 陈利顶, 杨磊. 黄土高原草地土壤水分和物种多样性沿降水梯度的分布格局[J]. 自然资源学报, 2018, 33(8): 1351-1362.
[15]	张扬, 李宝富, 陈亚宁. 1970—2013年西北干旱区空中水汽含量时空变化与降水量的关系[J]. 自然资源学报, 2018, 33(6): 1043-1055.