An Extended Triple Collocation Method With Maximized Correlation for Near Global‐Land Precipitation Fusion

Author:

Wei Linyong12,Jiang Shanhu12ORCID,Ren Liliang13ORCID,Yuan Shanshui4ORCID,Liu Yi2ORCID,Yang Xiaoli2ORCID,Wang Menghao2,Zhang Linqi2ORCID,Yu Huafei5ORCID,Duan Zheng6ORCID

Affiliation:

1. The National Key Laboratory of Water Disaster Prevention Hohai University Nanjing China

2. College of Hydrology and Water Resources Hohai University Nanjing China

3. Cooperative Innovation Center for Water Safety and Hydro‐Science Hohai University Nanjing China

4. Yangtze Institute for Conservation and Development Hohai University Nanjing China

5. School of Resource and Environmental Sciences Wuhan University Wuhan China

6. Department of Physical Geography and Ecosystem Science Lund University Lund Sweden

Abstract

AbstractAn Extended Triple Collocation for maximized Correlation (ETCC) method was proposed with a unique correlation function, the purpose of which is to maximize the correlation between the merged product and unknown truth. The method was tested over quasi‐global land by combining three independent precipitation products. The performance of the ETCC‐merged product was then evaluated against three reference data sets and compared with the existing Triple Collocation (TC) merging. The merged product was found to be generally superior to each contributor. Moreover, the ETCC method is better able to improve the correlation of merged product compared with the TC approach. Other improvements are also shown in the absolute difference of the ETCC‐merged product, such as regional validation for central North America and mainland China. These demonstrate the effectiveness of the ETCC method, and accordingly, it can provide a promising solution for maximizing the correlation of merged product without the truth.

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Geophysics

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3