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文件名称: 34种cmip5中国全国统计降尺度数据RCP45、RCP85(百度网盘资源).txt
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  文件大小: 78byte
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  上传时间: 2020-04-21
  提 供 者: zhao*****
 详细说明:Use of NWAI-WG data   So far, NWAI-WG data have been used on a collaborative basis in publications (see the attached file). The major reasons are the data were not widely distributed. They were only used in our group and our collaborative networks. There were some cases with requests of the data made after people read Liu and Zou's (2012) paper. You have two options for using the data. Option 1: Collaboration with us. In this case, we will help you to describe the downscaling method and contribute to other parts of the paper such as comments/suggestions on the papers, if the fields are within our expertise. Option 2: Use of the data on your own. While option 1 for collaboration with us is welcome, option 2 is also highly encouraged, particularly, when the data are used for these research disciplines, rather than agricultural related. Thanks to Professor Yu who provides us with his group's web site (www.agrivy.com) as a media for distribution of the data.   Acknowledgment for option 1  “We acknowledge the modelling groups, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP’s Working Group on Coupled Modelling (WGCM) for their roles in making available the WCRP CMIP5 multi-model dataset. Support of this dataset is provided by the Office of Science, US Department of Energy. Dr. Ian Macadam of the University of New South Wales downloaded the raw GCM monthly data. ”   Acknowledgment for option 2  “We acknowledge the modelling groups, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP’s Working Group on Coupled Modelling (WGCM) for their roles in making available the WCRP CMIP5 multi-model dataset. Support of this dataset is provided by the Office of Science, US Department of Energy. Dr. Ian Macadam of the University of New South Wales downloaded the raw GCM monthly data. Dr. De Li Liu of the NSW Department of Primary Industries used NWAI-WG to downscale downscaled daily data. Also, thanks to AGRIVY (www.agrivy.c
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