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DOI	10.1016/j.atmosres.2019.104632
	Symmetrical uncertainty and random forest for the evaluation of gridded precipitation and temperature data
	Nashwan M.S.; Shahid S.
发表日期	2019
ISSN	0169-8095
卷号	230
英文摘要	Selection of appropriate gridded rainfall and temperature data is a key problem for hydro-climatic studies, particularly in regions where long-term reliable and dense observations are not available. The ability of two intelligent algorithms, symmetrical uncertainty (SU) and random forest (RF), to assess the degree of similarity or the distance between two time series was utilized in this study for the evaluation of gridded climate data. In this study, the performances of seven widely used gridded rainfall datasets and five temperature datasets were evaluated against the available station data in Egypt. Monthly rainfall and mean temperature data recorded at 57 locations for the period 1979–2014 were used for this purpose. The results revealed the better performance of Global Precipitation Climatology Centre (GPCC) gridded rainfall and University of Delaware (Udel) gridded temperature data in replicating observed rainfall and mean temperature, respectively, in most of the locations in Egypt. Validation of the results using conventional statistical metrics revealed the better performance of different datasets in term of different metrics at different locations. However, the mean values of all the metrics support the results obtained using SU and RF. The study indicates that SU and RF can be used for the selection of appropriate gridded rainfall and temperature data by avoiding confusion arise from contradictory results obtained using various statistical metrics. © 2019 Elsevier B.V.
英文关键词	Egypt; Gridded climate data; Performance evaluation; Rainfall; Random forest; Symmetrical uncertainty; Temperature
语种	英语
scopus关键词	Decision trees; Location; Temperature; Uncertainty analysis; Climate data; Egypt; Performance evaluation; Random forests; Symmetrical uncertainty; Rain; algorithm; climate modeling; numerical model; performance assessment; precipitation (climatology); precipitation intensity; regional climate; temperature profile; uncertainty analysis; Egypt
来源期刊	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/162177
作者单位	Construction and Building Engineering Department, College of Engineering and Technology, Arab Academy for Science, Technology and Maritime Transport (AASTMT), 2033 Elhorria, Cairo, Egypt; Department of Hydraulics and Hydrology, School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), Skudia, Johor 81310, Malaysia
推荐引用方式 GB/T 7714	Nashwan M.S.,Shahid S.. Symmetrical uncertainty and random forest for the evaluation of gridded precipitation and temperature data[J],2019,230.
APA	Nashwan M.S.,&Shahid S..(2019).Symmetrical uncertainty and random forest for the evaluation of gridded precipitation and temperature data.Atmospheric Research,230.
MLA	Nashwan M.S.,et al."Symmetrical uncertainty and random forest for the evaluation of gridded precipitation and temperature data".Atmospheric Research 230(2019).