...
首页> 外文期刊>Theoretical and applied climatology >Spatial downscaling algorithm of TRMM precipitation based on multiple high-resolution satellite data for Inner Mongolia, China
【24h】

Spatial downscaling algorithm of TRMM precipitation based on multiple high-resolution satellite data for Inner Mongolia, China

机译:基于多个高分辨率卫星数据的TRMM降水的空间缩减算法

获取原文
获取原文并翻译 | 示例
           

摘要

Daily precipitation data from 42 stations in Inner Mongolia, China for the 10 years period from 1 January 2001 to 31 December 2010 was utilized along with downscaled data from the Tropical Rainfall Measuring Mission (TRMM) with a spatial resolution of 0.25 degrees x 0.25 degrees for the same period based on the statistical relationships between the normalized difference vegetation index (NDVI), meteorological variables, and digital elevation models (DEM) using the leave-one-out (LOO) cross validation method and multivariate step regression. The results indicate that (1) TRMM data can indeed be used to estimate annual precipitation in Inner Mongolia and there is a linear relationship between annual TRMM and observed precipitation; (2) there is a significant relationship between TRMM-based precipitation and predicted precipitation, with a spatial resolution of 0.50 degrees x 0.50 degrees; (3) NDVI and temperature are important factors influencing the downscaling of TRMM precipitation data for DEM and the slope is not the most significant factor affecting the downscaled TRMM data; and (4) the downscaled TRMM data reflects spatial patterns in annual precipitation reasonably well, showing less precipitation falling in west Inner Mongolia and more in the south and southeast. The new approach proposed here provides a useful alternative for evaluating spatial patterns in precipitation and can thus be applied to generate a more accurate precipitation dataset to support both irrigation management and the conservation of this fragile grassland ecosystem.
机译:利用了2001年1月1日至2010年12月31日这10年中来自中国内蒙古的42个气象站的每日降水数据,以及来自热带降雨测量团(TRMM)的降尺度数据,其空间分辨率为0.25度x 0.25度。基于标准化差异植被指数(NDVI),气象变量和数字高程模型(DEM)之间的统计关系,采用了留一法(LOO)交叉验证方法和多元逐步回归。结果表明:(1)TRMM数据的确可以用于估算内蒙古的年降水量,年TRMM值与观测降水量之间存在线性关系; (2)基于TRMM的降水与预测降水之间存在显着关系,空间分辨率为0.50度x 0.50度; (3)NDVI和温度是影响DEM TRMM降水量数据降尺度的重要因素,而坡度不是影响TRMM降尺度数据的最重要因素; (4)缩小的TRMM数据较好地反映了年降水量的空间格局,内蒙古西部降水减少,而南部和东南部降水增加。本文提出的新方法为评估降水的空间格局提供了一种有用的替代方法,因此可用于生成更准确的降水数据集,以支持灌溉管理和该脆弱草地生态系统的保护。

著录项

  • 来源
    《Theoretical and applied climatology》 |2019年第2期|45-59|共15页
  • 作者单位

    Inner Mongolia Agr Univ, Coll Water Conservancy & Civil Engn, Hohhot 010018, Peoples R China;

    Beijing Normal Univ, Minist Educ, Key Lab Environm Change & Nat Disaster, Beijing 100875, Peoples R China|Beijing Normal Univ, State Key Lab Earth Surface Proc& Resource Ecol, Beijing 100875, Peoples R China|Beijing Normal Univ, Acad Disaster Reduct & Emergency Management, Beijing 100875, Peoples R China;

    Inner Mongolia Agr Univ, Coll Water Conservancy & Civil Engn, Hohhot 010018, Peoples R China|Fraunhofer IOSB, Applicat Ctr Syst Technol, D-98693 Ilmenau, Germany;

    Inner Mongolia Agr Univ, Coll Water Conservancy & Civil Engn, Hohhot 010018, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号