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Authors’ reply: Station data and modelled climate data in Africa

机译:作者的回复:非洲的台站数据和模拟气候数据

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We thank Dr Shaman for his valuable comments [1] on our article [2]. We agree that it is challenging to study environmental determinants of diseases in locations where data are scarce. There are certainly weaknesses in the University of East Anglia Climate Research Unit (CRU) TS 3.21 dataset that could have affected our con- clusions. This dataset was based on large climate data- sets gathered by the World Meteorological Organization and the United States National Oceanographic and Atmospheric Administration. To maximise the use of available climate data, particularly in regions with imperfect station coverage, historical data, distant sta- tion data and station data of related climatic variables were processed and interpolated to provide modelled climatic data at a global scale. Technical details are available in an article written by Harris et al. [3].
机译:感谢Shaman博士对我们的文章[2]提出的宝贵意见[1]。我们同意在缺乏数据的地方研究疾病的环境决定因素具有挑战性。东英吉利大学气候研究小组(CRU)TS 3.21数据集中肯定存在一些弱点,可能会影响我们的结论。该数据集基于世界气象组织和美国国家海洋与大气管理局收集的大型气候数据集。为了最大程度地利用可用的气候数据,特别是在站覆盖范围不完善的地区,对历史数据,远距离站数据和相关气候变量的站数据进行了处理和插值,以提供全球范围内的模拟气候数据。技术细节可在Harris等人撰写的文章中找到。 [3]。

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