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一个天气功能数据集用于预测乌干达短期降雨量
Andrew Gahwera Tumusiime1, Odongo Steven Eyobu1, Isaac Mugume2
1College of Computing and IS, Makerere University, P.O Box, 7062, Kampala, Uganda.
Data in brief
|October 9, 2023
概括
乌干达的研究人员开发了2020-2022年的清洁天气数据集,以改善降雨预测模型. 这些数据弥合了由稀疏的气象站和不一致的记录造成的差距,有助于短期降雨预报.
科学领域:
- 气象学和气候学
- 数据科学和机器学习
背景情况:
- 天气数据对于开发准确的天气预测模型至关重要.
- 数据的可用性和质量是全球面临的重大挑战,特别是在乌干达,由于气象站稀疏和记录不一致.
- 这些数据缺口阻碍了乌干达开发高效的天气预报模型.
研究的目的:
- 为了应对乌干达天气数据有限的挑战.
- 为短期降雨预测创建一个准备好和清理的数据集.
- 为了弥合乌干达研究人员的数据可用性差距.
主要方法:
- 从2020-2022年获得的国家特定时间序列每小时的观测天气数据.
- 使用"气候"R包访问来自Ogimet存储库的数据.
- 在R中使用自动化程序来下载和清理数据,处理重复和非统一的条目.
主要成果:
- 在2020-2022年期间从乌干达各地的11个站点获得每小时的观测天气数据.
- 成功清理原始数据,删除重复和不一致.
- 制作了一个可用的数据集,适合用于降雨模式分析和预测.
结论:
- 准备好的数据集有效地弥合了乌干达气象研究的数据缺口.
- 这一清理的数据集对于开发和改进短期降雨预测模型非常有价值.
- 促进进一步研究乌干达的天气模式和气候动态.
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