干旱区研究

干旱区研究 >

2025 , Vol. 42 >Issue 1: 51 - 62

DOI: https://doi.org/10.13866/j.azr.2025.01.05

水土资源

多源降水产品在高寒内陆河流域的适用性和误差组分

  • 徐柳昕 ,
  • 王文雨 ,
  • 王晓燕 ,
  • 王雪莹 ,
  • 谷黄河
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  • 1.河海大学水灾害防御全国重点实验室，江苏 南京 210098
    2.河海大学水文水资源学院，江苏 南京 210098
徐柳昕（2001-），女，硕士研究生，主要从事水文与水资源研究. E-mail: 231601010127@hhu.edu.cn
王晓燕. E-mail: xywang@hhu.edu.cn

收稿日期: 2024-09-24

  修回日期: 2024-12-01

  网络出版日期: 2025-01-17

基金资助

中央高校基本科研业务费(B240201075);国家自然科学基金项目(42277074);水利部重大科技项目“智慧化流域产汇流及洪水预报模型研究”(SKR-2022074)

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Evaluation and Error decomposition of multisource precipitation data in an alpine and endorheic river watershed

  • XU Liuxin ,
  • WANG Wenyu ,
  • WANG Xiaoyan ,
  • WANG Xueying ,
  • GU Huanghe
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  • 1. The National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing 210098, Jiangsu, China
    2. College of Hydrology and Water Resources, Hohai University, Nanjing 210098, Jiangsu, China

Received date: 2024-09-24

  Revised date: 2024-12-01

  Online published: 2025-01-17

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摘要

降水资料的质量是高寒山区径流模拟精度的重要影响因素，对水资源管理及生态安全等至关重要。本文结合多种统计指标和误差分解模型，对比分析4套降水产品（卫星降水数据GPM、亚洲地区高质量高时空分辨率降水数据集AIMERG、再分析数据CMFD和ERA5）在叶尔羌河上游流域的降水时空分布特征，评估不同产品的精度，解析不同产品的误差特征。结果表明：（1） CMFD和AIMERG的年降水呈现了南高北低的空间特征，与基于中国地面台站的插值格点数据集CN05.1的特征一致，但ERA5和GPM呈现了相反的空间分布。高分辨率的AIMERG和CMFD可以捕捉到西南部冰川区降水高的特征。（2） 不同降水产品的年际变化特征差异显著且多数产品夏秋季节降水占比超过60%。对比发现，仅有AIMERG产品可以较好地呈现研究区降水年内变化的峰型和峰现时间，对站点月降水量的捕捉能力最强，呈现较高的相关系数（>0.6）和较小的均方根误差（8.45~11.57 mm），而ERA5产品最差。（3） 日尺度的不同降水产品精度均呈现出多雨期（5—10月）高于少雨期（11月—次年4月）的特征，AIMERG在不同时期均呈现较高的日降水关键成功指数。（4） 不同降水产品夏季的主导误差均为命中误差，而冬季的主导误差随降水产品而变化。研究成果可为高寒区径流模拟和降水产品的算法改进提供一定的参考价值。

关键词： 再分析数据; 卫星降水; AIMERG; 误差分解模型; 叶尔羌河上游

本文引用格式

徐柳昕 , 王文雨 , 王晓燕 , 王雪莹 , 谷黄河 . 多源降水产品在高寒内陆河流域的适用性和误差组分[J]. 干旱区研究, 2025 , 42(1) : 51 -62 . DOI: 10.13866/j.azr.2025.01.05

Abstract

The quality of precipitation data are critical factor influencing the accuracy of runoff simulation in high-cold mountainous districts as it plays an important role in the ecological environmental protection and water resource management. The spatiotemporal characteristics of precipitation are analyzed in the headwater catchment of the Yarkant River Basin on the basis of GPM (Global Precipitation Measurement), AIMERG (the Asian precipitation dataset by calibrating the GPM-era IMERG), CMFD (China Meteorological Forcing Dataset) and ERA5 (The fifth-generation atmospheric reanalysis of the European Center for Medium-Range Weather Forecasts). Subsequently, the accuracy of the multisource precipitation data are evaluated against the observed precipitation. The error characteristics of various precipitation products was analyzed by means of the error decomposition model. The main findings were as follows: (1) The spatial pattern for CMFD and AIMERG was characterized by the increase from the north to south, which was consistent with the spatial pattern for the grid observation data set CN05.1 (the National Climate Center of China Meteorological Administration precipitation dataset). An opposite pattern was detected for ERA5 and GPM. Additionally, AIMERG and CMFD displayed higher precipitation in the glacier area. (2)The inter-annual variation characteristics of various precipitation products were significantly different, and the ratio of summer and autumn precipitation to annual precipitation for most precipitation products was more than 60%. Among all the precipitation products, only AIMERG reproduced the seasonal patterns, such as the time when the maximum monthly precipitation occurred and the peak shape for the monthly precipitation at all stations. AIMERG had the greatest ability to reproduce gauged monthly precipitation, with a higher correlation coefficient (>0.6) and lower root mean square error (8.45-11.57 mm), whereas ERA5 show the poorest ability. (3) All precipitation products showed a higher performance in reproducing daily precipitation during the wet period (from May to October) than during the dry period (from November to April). AIMERG had a greater critical success index in both wet period and dry period than for other precipitation products. (4) The dominant error of the various precipitation products in summer was the hit error, whereas the dominant error in winter varied with the precipitation product. These findings provide some reference for the runoff simulation and algorithm improvement of precipitation products in the high-cold region, where meteorological data are limited.

Key words： reanalysis data; satellite precipitation; AIMERG; error decomposition model; upper Yarkant River

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