Fine-resolution precipitation mapping over Syria using local regression and spatial interpolation

doi:10.1016/j.atmosres.2021.105524

	Fine-resolution precipitation mapping over Syria using local regression and spatial interpolation
	Alsafadi, Karam 4,5; Mohammed, Safwan 6; Mokhtar, Ali 1,3; Sharaf, Mohammed 4,5; He, Hongming 1,2
刊名	ATMOSPHERIC RESEARCH
	2021-07-01
卷号	256 页码:16
关键词	Precipitation climatologies GIS Multi-variate regression Geostatistical analysis Syria
ISSN号	0169-8095
DOI	10.1016/j.atmosres.2021.105524
通讯作者	Alsafadi, Karam(karam.alsafadi@alexu.edu.eg)
英文摘要	Annual precipitation at 1 km2 spatial resolution have been produced over Syria for a referenced period of 1975?2010. The observations from 410 rain-gauges were interpolated over a regular grid by applying multivariate regression models (PSMRM) and local equations for sub-regions of the study area. This statistical method aims to model the influences of the essential geographical and topographical climatic factors, such as longitude, latitude, elevation, slopes, and aspects on the precipitation field in multiple local regions. The PSMRM is composed of two steps, (i) a potential surface of precipitation is calculated through multi-linear local regressions based on geographical and topographical information, then (ii) a kriging and IDW interpolation is applied to adjust the potential surface so as to better fit the station residuals (i.e. the difference between the observed values and the predicted values which are obtained from PSMRM). Ultimately, the models? accuracy was evaluated by 43 stations. The PSRMR-IDW-3 is found to be superior to all other models; the value of RMSE was 92.5 mm and the Nash-Sutcliffe efficiency NSE was 0.9187, while the Willmott index of agreement was 0.9808. In contrast, the PSMRM-OK-EXP was only superior to other models with the least mean absolute error (MEA) and the mean absolute percentage error (MAPE); the difference was 64.07 mm, i.e. 11.44%. However, all the proposed models were shown to be highly efficient compared to global models and can be considered an appropriate alternative to studying precipitation variability spatially over Syria.
WOS关键词	AIR-TEMPERATURE ; CLIMATE-CHANGE ; CLIMATOLOGICAL PRECIPITATION ; DATA SETS ; RAINFALL ; SURFACES ; MODELS ; REGION ; PROJECTIONS ; TOPOGRAPHY
WOS研究方向	Meteorology & Atmospheric Sciences
语种	英语
出版者	ELSEVIER SCIENCE INC
WOS记录号	WOS:000647566100001
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/161612]
专题	中国科学院地理科学与资源研究所
通讯作者	Alsafadi, Karam
作者单位	1.Northwest Agr & Forestry Univ, Chinese Acad Sci & Minist Water Resources, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi, Peoples R China 2.East China Normal Univ, Sch Geog Sci, Shanghai 210062, Peoples R China 3.Cairo Univ, Fac Agr, Dept Agr Engn, Giza 12613, Egypt 4.Alexandria Univ, Fac Arts, Dept Geog, Alexandria 25435, Egypt 5.Alexandria Univ, Fac Arts, GIS, Alexandria 25435, Egypt 6.Univ Debrecen, Inst Land Use Technol & Reg Dev, H-4032 Debrecen, Hungary
推荐引用方式 GB/T 7714	Alsafadi, Karam,Mohammed, Safwan,Mokhtar, Ali,et al. Fine-resolution precipitation mapping over Syria using local regression and spatial interpolation[J]. ATMOSPHERIC RESEARCH,2021,256:16.
APA	Alsafadi, Karam,Mohammed, Safwan,Mokhtar, Ali,Sharaf, Mohammed,&He, Hongming.(2021).Fine-resolution precipitation mapping over Syria using local regression and spatial interpolation.ATMOSPHERIC RESEARCH,256,16.
MLA	Alsafadi, Karam,et al."Fine-resolution precipitation mapping over Syria using local regression and spatial interpolation".ATMOSPHERIC RESEARCH 256(2021):16.