研究论文

地形因子对华东地区降水影响的尺度效应研究

  • 曾礼 ,
  • 高艳红 ,
  • 蒋盈沙 ,
  • 刘朝阳 ,
  • 李锁锁
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  • 1.中国科学院西北生态环境资源研究院陆面过程与气候变化重点实验室,甘肃 兰州 730000
    2.复旦大学大气与海洋科学系/大气科学研究院,上海 200438
    3.上海市海洋—大气相互作用 前沿科学研究基地,上海 200438
    4.上海长江河口湿地生态系统国家野外科学 观测研究站,上海 200438
    5.中国科学院大学,北京 100049
曾礼(1996-),男,四川自贡人,硕士研究生,主要从事地形降水研究. E-mail: zengli19@mails.ucas.ac.cn
高艳红(1973-),女,山西太谷人,教授,主要从事陆面过程与区域气候变化的数值模拟研究. E-mail: gaoyh@fudan.edu.cn

收稿日期: 2021-11-03

  修回日期: 2022-01-26

  网络出版日期: 2022-05-31

基金资助

国家重点研发计划项目“副热带地区区域模式关键技术及其应用”(2017YFC1502101)

Scale Effects of Terrain Factors on Precipitation in East China

  • Li ZENG ,
  • Yanhong GAO ,
  • Yingsha JIANG ,
  • Chaoyang LIU ,
  • Suosuo LI
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  • 1.Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions,Northwest Institute of Ecology and Environmental Resources,Chinese Academy of Sciences,Lanzhou 730000,China
    2.Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences,Fudan University,Shanghai 200438,China
    3.Shanghai Frontiers Science Center of Atmosphere-Ocean Interaction,Shanghai 200438,China
    4.National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary,Shanghai 200438,China
    5.University of Chinese Academy of Sciences,Beijing 100049,China
ZENG Li (1996-), male, Zigong City, Sichuan Province, Master student. Research areas include terrain precipitation. E-mail: zengli19@mail.ucas.ac.cn
GAO Yanhong (1973-), female, Taigu County, Shanxi Province, Professor. Research areas include land-atmosphere interaction and its regional climate effect over the Tibetan Plateau. E-mail: gaoyh@fudan.edu.cn

Received date: 2021-11-03

  Revised date: 2022-01-26

  Online published: 2022-05-31

Supported by

the National Key Research and Development Program of China “Key technologies and applications in the subtropical regional model”(2017YFC1502101)

摘要

降水是地表淡水资源的主要来源,降水分布强烈的时空异质性给陆地水循环研究带来了较大不确定性,因此降水的空间异质性及其影响因子研究一直是水循环研究的重点。选取观测资料丰富的华东地区,采用351个气象台站降水观测数据,通过一般线性回归模型、地理加权回归模型和多尺度地理加权回归模型的拟合结果,研究了典型地形因子对降水空间分布的影响及其影响尺度。结果表明,传统的一般线性回归模型不能表征降水分布的空间异质性,而地理加权回归模型和多尺度地理加权回归模型均较好地拟合出了降水在空间上的非均匀分布(R2>0.7)。此外,多尺度地理加权回归模型的带宽数还反映了各地形因子对降水空间分布的影响尺度。一般说来,带宽数较小的局地影响因子对降水的空间异质性影响较强。对于年降水量,地形高程和地形起伏度是影响降水空间异质性的主要地形因子,而地形坡度和主风向系数对降水的影响不显著。在不同季节,各地形因子对降水空间分布的影响程度不同。地形高程对夏季降水影响较大;离海岸线距离对春、秋季南部山区降水影响较大;地形起伏度对冬季降水有重要影响。厘清我国不同季节降水与地形因子间的关系,有助于理解各季节复杂地形因子对降水的贡献,为地形复杂地区的模式模拟及改进提供支撑。

本文引用格式

曾礼 , 高艳红 , 蒋盈沙 , 刘朝阳 , 李锁锁 . 地形因子对华东地区降水影响的尺度效应研究[J]. 地球科学进展, 2022 , 37(5) : 535 -548 . DOI: 10.11867/j.issn.1001-8166.2022.020

Abstract

Precipitation is the main source of surface freshwater. The temporal and spatial heterogeneity of precipitation distribution brings great uncertainty to the study of the surface water cycle. The study of spatial heterogeneity and the factors influencing precipitation has always been the focus of water cycle research. To explore the relationship between the spatial distribution of precipitation and terrain factors, 351 precipitation observation stations in eastern China with abundant observational data were used according to the Ordinary Least Squares regression (OLS), Geographically Weighted Regression model (GWR), and Multi-scale Geographically Weighted Regression model (MGWR). The results show that OLS cannot show the influence of terrain factors on the spatial heterogeneity of precipitation distribution, while GWR and MGWR achieved a better goodness of fit and stronger interpretability (Goodness of fit R2>0.7). Furthermore, the MGWR can reflect the scale effects of terrain factors on the spatial distribution of precipitation based on bandwidths, and local influencing factors with smaller bandwidths have a stronger influence on the spatial heterogeneity of precipitation. For the annual average precipitation, the terrain elevation and terrain relief are the main terrain factors that affect the spatial heterogeneity of precipitation, while the terrain slope and Prevailing Wind-direction Effect Index (PWEI) have no significant impact on precipitation. However, seasonally, the influence of different terrain factors on the spatial distribution of precipitation is different. Specifically, in summer, terrain elevation is more important than other factors; in spring and autumn, the distance from the coast plays an important role in the mountain regions, and in winter local influencing factors such as terrain relief mainly affect the spatial distribution of precipitation. Clarifying the relationship between precipitation and terrain factors can help us understand the contribution of complex terrain factors (in all seasons) to precipitation and provide support for model simulation and improvement in regions with a complex topography.

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