基于TRMM卫星降水的太行山区降水时空分布格局

杜军凯; 贾仰文; 李晓星; 牛存稳; 刘欢; 仇亚琴

doi:10.14042/j.cnki.32.1309.2019.01.001

高级搜索

全国中文核心期刊
中国科技核心期刊
美国工程索引（EI）收录期刊

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于TRMM卫星降水的太行山区降水时空分布格局

杜军凯, 贾仰文, 李晓星, 牛存稳, 刘欢, 仇亚琴

文章导航 > 水科学进展 > 2019 > 30(1): 1-13

杜军凯, 贾仰文, 李晓星, 牛存稳, 刘欢, 仇亚琴. 基于TRMM卫星降水的太行山区降水时空分布格局[J]. 水科学进展, 2019, 30(1): 1-13. doi: 10.14042/j.cnki.32.1309.2019.01.001

引用本文:

DU Junkai, JIA Yangwen, LI Xiaoxing, NIU Cunwen, LIU Huan, QIU Yaqin. Study on the spatial-temporal distribution pattern of precipitation in the Taihang Mountain region using TRMM data[J]. Advances in Water Science, 2019, 30(1): 1-13. doi: 10.14042/j.cnki.32.1309.2019.01.001

Citation:

DU Junkai, JIA Yangwen, LI Xiaoxing, NIU Cunwen, LIU Huan, QIU Yaqin. Study on the spatial-temporal distribution pattern of precipitation in the Taihang Mountain region using TRMM data[J]. Advances in Water Science, 2019, 30(1): 1-13. doi: 10.14042/j.cnki.32.1309.2019.01.001

基于TRMM卫星降水的太行山区降水时空分布格局

doi: 10.14042/j.cnki.32.1309.2019.01.001

1.
中国水利水电科学研究院流域水循环模拟与调控国家重点实验室, 北京 100038;
2.
中国环境科学研究院, 北京 100012

基金项目: 国家重点研发计划资助项目（2016YFC0401301）；国家重点基础研究发展计划（973计划）资助项目（2015CB452701）

详细信息

作者简介:
杜军凯(1987-),男,河南禹州人,工程师,博士研究生,主要从事流域水循环及其伴生过程模拟研究。E-mail:du_djk@163.com

通讯作者:
贾仰文,E-mail:Jiayw@iwhr.com

中图分类号: P339

Study on the spatial-temporal distribution pattern of precipitation in the Taihang Mountain region using TRMM data

1.
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China;
2.
Chinese Research Academy of Environmental Sciences, Beijing 100012, China

摘要: 基于TRMM 3B42V7数据，综合采用多元线性回归、偏最小二乘回归和地理加权回归3种方法，建立了太行山区卫星降水产品的降尺度校正模型，将遥感降水信息从0.25°×0.25°降尺度到0.05°×0.05°。在结果评估和优选的基础上，分析了"像元-集水区-全区"年、月降水的多时空尺度干湿季节分布和垂向分布特征，并从机理方面论证了研究的合理性。结果表明：①地理加权回归校正效果最优，可明显降低校正降水与实测降水系列的均方根误差和平均相对偏差且提高决定系数；偏最小二乘回归可降低两项误差，但对决定系数无提升；多元线性回归最差，各项指标均无改善。②处于夏季风迎风侧的东坡和南坡降水量普遍高于500 mm，背风侧的西坡和北坡降水量较低，最大年降水量位于东南坡海拔1 300~1 500 m的地带。③研究区7-9月降水量占全年的58.7%，干湿季节降水量之比为1：18，各集水区的变化范围为1：13~1：25。④季风风向影响降水中心的移动路径，各月降水量沿高程变化梯度区间为-5.2~6.7 mm/hm，且迎风坡降水的垂向分布更复杂。
- 热带降雨测量任务 /
- 降尺度 /
- 干湿季节 /
- 垂直地带性
Abstract: A comprehensive understanding of the spatial and temporal distribution of precipitation in mountain areas is of great significance for improving the simulation accuracy of regional water cycle processes,as well as the level of water management. In view of the fact that there is a severe lack of ground monitoring in high altitude areas,as well as the disadvantage of downscaling of satellite precipitation products by a single method,this study selects the Taihang Mountain as the research region and establishes a downscaling correction model. The model consists of the validation module and the downscaling module,which includes the multiple linear regression,the partial least squares regression,and the geographically weighted regression. Using the model,the original TRMM data is scaled from 0.25° to 0.05°. The distribution of the wet and dry seasons and the vertical distribution of the annual and monthly precipitation of the "pixel-catchment-region" are analyzed on the basis of the evaluation and optimization of the downscaling results. The research results are as follows: ① The geographically weighted regression is the most effective,reducing the root mean square error and average relative deviation of the corrected and gauged precipitation series,as well as improving the coefficient of determination. The partial least squares regression can reduce the two errors,but it cannot improve the determination coefficient. The multiple linear regression cannot improve any of the three indicators. ② The precipitation on the east and south slopes on the windward side of the summer monsoon is generally higher than 500 mm,while that on the west and north slopes on the leeward side is lower. The zones of the maximum annual precipitation are located in the southeast slope at an altitude of 1 300—1 500 m. ③ The precipitation from July to September accounts for 58.7% of the entire year;the ratio of precipitation in the dry and wet season is 1∶18;and the ratio in each catchment ranges from 1∶13 to 1∶25. ④ The variations of wind direction of the monsoon affect the moving track of the precipitation center,and the vertical zonality is more complicated in the windward than in the leeward.
- Tropical Rainfall Measuring Mission /
- downscaling /
- dry and wet season /
- vertical zonality

[1]	易小波, 贾小旭, 邵明安, 赵春雷. 黄土高原区域尺度土壤干燥化的空间和季节分布特征 . 水科学进展, 2017, 28(3): 373-381. doi: 10.14042/j.cnki.32.1309.2017.03.007
[2]	黄文峰, 韩红卫, 牛富俊, 李志军. 季节性冰封热融浅湖水温原位观测及其分层特征 . 水科学进展, 2016, 27(2): 280-289. doi: 10.14042/j.cnki.32.1309.2016.02.013
[3]	张光辉, 田言亮, 王电龙, 严明疆, 王金哲. 冀中山前农业区地下水位强降弱升特征与机制 . 水科学进展, 2015, 26(2): 227-232. doi: 10.14042/j.cnki.32.1309.2015.02.010
[4]	章诞武, 丛振涛, 倪广恒. 1956—2010年中国水热季节性特征分析 . 水科学进展, 2015, 26(4): 466-472. doi: 10.14042/j.cnki.32.1309.2015.04.002
[5]	陶辉, 毛炜峄, 黄金龙, 翟建青. 塔里木河流域干湿变化与大气环流关系 . 水科学进展, 2014, 25(1): 45-52.
[6]	杨云川, 程根伟, 范继辉, 孙建, 李卫朋. 卫星降雨数据在高山峡谷地区的代表性与可靠性 . 水科学进展, 2013, 24(1): 24-33.
[7]	陈子燊, 黄强, 刘曾美. 1962-2007年广东干湿时空变化特征分析 . 水科学进展, 2013, 24(4): 469-476.
[8]	刘昌明, 刘文彬, 傅国斌, 欧阳如琳. 气候影响评价中统计降尺度若干问题的探讨 . 水科学进展, 2012, 23(3): 427-437. doi: CNKI: 32.1309.P.20120501.1616.002
[9]	刘向培, 王汉杰, 何明元. 应用统计降尺度方法预估江淮流域未来降水 . 水科学进展, 2012, 23(1): 29-37. doi: CNKI:32.1309.P.20120104.2012.005
[10]	陆桂华, 吴娟, 吴志勇. 水文集合预报试验及其研究进展 . 水科学进展, 2012, 23(5): 728-734. doi: CNKI: 32.1309.P.20120824.1606.016
[11]	孙正宝, 陈治谏, 廖晓勇, 王海明. 侵蚀性降雨识别的模糊隶属度模型建立及应用 . 水科学进展, 2011, 22(6): 801-806.
[12]	黄小燕, 张明军, 贾文雄, 王圣杰, 张宁. 中国西北地区地表干湿变化及影响因素 . 水科学进展, 2011, 22(2): 151-159.
[13]	陈皓锐, 黄介生, 伍靖伟, 杨金忠. 灌溉用水效率尺度效应研究评述 . 水科学进展, 2011, 22(6): 872-880.
[14]	周辉, 吴时强, 陈惠玲. 泄洪雾化降雨模型相似性探讨 . 水科学进展, 2009, 20(1): 58-62.
[15]	孙立群, 胡成, 陈刚. TOPMODEL模型中的DEM尺度效应 . 水科学进展, 2008, 19(5): 699-706.
[16]	刘吉峰, 李世杰, 丁裕国. 基于气候模式统计降尺度技术的未来青海湖水位变化预估 . 水科学进展, 2008, 19(2): 184-191.
[17]	董斌, 崔远来, 李远华. 水稻灌区节水灌溉的尺度效应 . 水科学进展, 2005, 16(6): 833-839.
[18]	王家祁, 顾文燕, 姚惠明. 中国降水与暴雨的季节变化 . 水科学进展, 1997, 8(2): 108-116.
[19]	罗毅, 雷志栋, 杨诗秀. 潜在腾发量的季节性变化趋势及概率分布特性研究 . 水科学进展, 1997, 8(4): 308-312.
[20]	杨大庆, 张志忠, 康尔泗, 张寅生, Kelly Elder, Richard Kattelmann. 地面积雪测量与雨量器量测降雪量一致性实验研究 . 水科学进展, 1992, 3(2): 136-141.

点击查看大图

计量

文章访问数: 201
HTML全文浏览量: 34
PDF下载量: 388
被引次数: 0

基于TRMM卫星降水的太行山区降水时空分布格局

doi: 10.14042/j.cnki.32.1309.2019.01.001

1. 中国水利水电科学研究院流域水循环模拟与调控国家重点实验室, 北京 100038;

2. 中国环境科学研究院, 北京 100012

基金项目: 国家重点研发计划资助项目（2016YFC0401301）；国家重点基础研究发展计划（973计划）资助项目（2015CB452701）

作者简介:
杜军凯(1987-),男,河南禹州人,工程师,博士研究生,主要从事流域水循环及其伴生过程模拟研究。E-mail:du_djk@163.com

通讯作者: 贾仰文,E-mail:Jiayw@iwhr.com

收稿日期: 2018-08-21
刊出日期: 2019-02-25

中图分类号: P339

关键词:

热带降雨测量任务 /

降尺度 /

干湿季节 /

垂直地带性

摘要: 基于TRMM 3B42V7数据，综合采用多元线性回归、偏最小二乘回归和地理加权回归3种方法，建立了太行山区卫星降水产品的降尺度校正模型，将遥感降水信息从0.25°×0.25°降尺度到0.05°×0.05°。在结果评估和优选的基础上，分析了"像元-集水区-全区"年、月降水的多时空尺度干湿季节分布和垂向分布特征，并从机理方面论证了研究的合理性。结果表明：①地理加权回归校正效果最优，可明显降低校正降水与实测降水系列的均方根误差和平均相对偏差且提高决定系数；偏最小二乘回归可降低两项误差，但对决定系数无提升；多元线性回归最差，各项指标均无改善。②处于夏季风迎风侧的东坡和南坡降水量普遍高于500 mm，背风侧的西坡和北坡降水量较低，最大年降水量位于东南坡海拔1 300~1 500 m的地带。③研究区7-9月降水量占全年的58.7%，干湿季节降水量之比为1：18，各集水区的变化范围为1：13~1：25。④季风风向影响降水中心的移动路径，各月降水量沿高程变化梯度区间为-5.2~6.7 mm/hm，且迎风坡降水的垂向分布更复杂。

English Abstract

Study on the spatial-temporal distribution pattern of precipitation in the Taihang Mountain region using TRMM data

1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China;

2. Chinese Research Academy of Environmental Sciences, Beijing 100012, China

Received Date: 2018-08-21
Publish Date: 2019-02-25

Keywords:

Abstract: A comprehensive understanding of the spatial and temporal distribution of precipitation in mountain areas is of great significance for improving the simulation accuracy of regional water cycle processes,as well as the level of water management. In view of the fact that there is a severe lack of ground monitoring in high altitude areas,as well as the disadvantage of downscaling of satellite precipitation products by a single method,this study selects the Taihang Mountain as the research region and establishes a downscaling correction model. The model consists of the validation module and the downscaling module,which includes the multiple linear regression,the partial least squares regression,and the geographically weighted regression. Using the model,the original TRMM data is scaled from 0.25° to 0.05°. The distribution of the wet and dry seasons and the vertical distribution of the annual and monthly precipitation of the "pixel-catchment-region" are analyzed on the basis of the evaluation and optimization of the downscaling results. The research results are as follows: ① The geographically weighted regression is the most effective,reducing the root mean square error and average relative deviation of the corrected and gauged precipitation series,as well as improving the coefficient of determination. The partial least squares regression can reduce the two errors,but it cannot improve the determination coefficient. The multiple linear regression cannot improve any of the three indicators. ② The precipitation on the east and south slopes on the windward side of the summer monsoon is generally higher than 500 mm,while that on the west and north slopes on the leeward side is lower. The zones of the maximum annual precipitation are located in the southeast slope at an altitude of 1 300—1 500 m. ③ The precipitation from July to September accounts for 58.7% of the entire year;the ratio of precipitation in the dry and wet season is 1∶18;and the ratio in each catchment ranges from 1∶13 to 1∶25. ④ The variations of wind direction of the monsoon affect the moving track of the precipitation center,and the vertical zonality is more complicated in the windward than in the leeward.

引用本文:

Citation:

DU Junkai, JIA Yangwen, LI Xiaoxing, NIU Cunwen, LIU Huan, QIU Yaqin. Study on the spatial-temporal distribution pattern of precipitation in the Taihang Mountain region using TRMM data[J]. Advances in Water Science, 2019, 30(1): 1-13. doi: 10.14042/j.cnki.32.1309.2019.01.001

全文HTML

下载: 全尺寸图片幻灯片

返回文章

用微信扫码二维码

分享至好友和朋友圈

留言板

基于TRMM卫星降水的太行山区降水时空分布格局

doi: 10.14042/j.cnki.32.1309.2019.01.001

作者简介: 杜军凯(1987-),男,河南禹州人,工程师,博士研究生,主要从事流域水循环及其伴生过程模拟研究。E-mail:du_djk@163.com

通讯作者: 贾仰文,E-mail:Jiayw@iwhr.com

Study on the spatial-temporal distribution pattern of precipitation in the Taihang Mountain region using TRMM data

计量

出版历程

基于TRMM卫星降水的太行山区降水时空分布格局

doi: 10.14042/j.cnki.32.1309.2019.01.001

1. 中国水利水电科学研究院流域水循环模拟与调控国家重点实验室, 北京 100038; 2. 中国环境科学研究院, 北京 100012

作者简介: 杜军凯(1987-),男,河南禹州人,工程师,博士研究生,主要从事流域水循环及其伴生过程模拟研究。E-mail:du_djk@163.com

通讯作者: 贾仰文,E-mail:Jiayw@iwhr.com

English Abstract

Study on the spatial-temporal distribution pattern of precipitation in the Taihang Mountain region using TRMM data

1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China; 2. Chinese Research Academy of Environmental Sciences, Beijing 100012, China

全文HTML

目录

作者简介:
杜军凯(1987-),男,河南禹州人,工程师,博士研究生,主要从事流域水循环及其伴生过程模拟研究。E-mail:du_djk@163.com

通讯作者:
贾仰文,E-mail:Jiayw@iwhr.com

1. 中国水利水电科学研究院流域水循环模拟与调控国家重点实验室, 北京 100038;

2. 中国环境科学研究院, 北京 100012

作者简介:
杜军凯(1987-),男,河南禹州人,工程师,博士研究生,主要从事流域水循环及其伴生过程模拟研究。E-mail:du_djk@163.com

1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China;

2. Chinese Research Academy of Environmental Sciences, Beijing 100012, China