Towards understanding multi-model precipitation predictions from CMIP5 based on China hourly merged precipitation analysis data-Reference-Cited by-同舟云学术

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Towards understanding multi-model precipitation predictions from CMIP5 based on China hourly merged precipitation analysis data

Published:2020-01 Issue: Volume:231 Page:104671
ISSN:0169-8095
Container-title:Atmospheric Research
language:en
Short-container-title:Atmospheric Research

Author:

Lv Yanmin,Guo Jianping,Yim Steve Hung-Lam,Yun Yuxing,Yin Jinfang,Liu Lin,Zhang Yong,Yang Yuanjian,Yan Yan,Chen Dandan

Funder

National Meteorological Information Center of China Meteorological Administration

Ministry of Science and Technology of China

National Natural Science Foundation of China

Chinese Academy of Meteorological Sciences

Publisher

Elsevier BV

Subject

Atmospheric Science

Reference95 articles.

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2. Global observed changes in daily climate extremes of temperature and precipitation;Alexander;J. Geophys. Res.-Atmos.,2006

3. Statistical bias correction for creating coherent total ozone record from OMI and OMPS observations;Bai;Remote Sens. Environ.,2016

4. Stochastic downscaling of climate model precipitation outputs in orographically complex regions: 2. Downscaling methodology;Bordoy;Water Resour. Res.,2014

5. Bias adjustment of satellite precipitation estimation using ground-based measurement: a case study evaluation over the Southwestern United States;Boushaki;J. Hydrometeorol.,2009

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