干旱区生态环境知识资源中心(Arid): Comparing the Performance of Dynamical and Statistical Downscaling on Historical Run Precipitation Data over a Semi-Arid Region

Arid

DOI	10.1007/s13143-019-00112-1
	Comparing the Performance of Dynamical and Statistical Downscaling on Historical Run Precipitation Data over a Semi-Arid Region
	Salehnia, Nasrin 1,2; Hosseini, Fateme 2; Farid, Ali 2; Kolsoumi, Sohrab 1; Zarrin, Azar 3; Hasheminia, Majid 2
通讯作者	Farid, Ali
来源期刊	ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES
ISSN	1976-7633
EISSN	1976-7951
出版年	2019
卷号	55 期号:4 页码:737-749
英文摘要	Precise evaluations of climate model precipitation outputs are valuable for making decisions regarding agriculture, water resource, and ecosystem management. Many downscaling techniques have been developed in the past few years for projection of weather variables. We need to apply dynamical and statistical downscaling (DD and SD) to bridge the gap between the coarse resolution general circulation model (GCM) outputs and the need for high-resolution climate information over a semi-arid region. We compare the requirements of DD (RegCM4) and SD (Delta) approaches, evaluate the historical run of NNRP1 data in comparison with station data, and analyze the changes in wet days and precipitation values through both methods during 1990-2010. In this study, we did not want to use prediction data under different scenarios of climate change, and we have just applied observed data to assess the amount of precise of NNRP1 data, over the observed period. SD method requires less time and computing power than DD. The DD approach performs better over the evaluation period according to efficiency criteria. In general, the Pearson correlation in DD with observation data in evaluation period was higher than (r > 0.72 and R-2 > 0.52) SD (r > 0.65 and R-2 > 0.41) over three study stations. Similarly, MAE and NSE show better results from DD relative to SD. SD underestimates the number annual mean wet-days for all three stations examined. DD overestimates a number of annual mean wet-days, but with less deviation from the observed mean.
英文关键词	Delta method RegCM4 NNRP1 Bias correction Resolution Wet-day
类型	Article
语种	英语
国家	Iran
收录类别	SCI-E
WOS记录号	WOS:000491562300014
WOS关键词	CLIMATE MODEL REGCM2 ; BIAS-CORRECTION ; WINTER PRECIPITATION ; CHANGE SCENARIOS ; FUTURE CHANGES ; RAINFALL ; SIMULATIONS ; TEMPERATURE ; INDICATORS ; FRAMEWORK
WOS类目	Meteorology & Atmospheric Sciences
WOS研究方向	Meteorology & Atmospheric Sciences
EI主题词	2019-11-01
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/310410
作者单位	1.Ferdowsi Univ Mashhad, Agrimetsoft, Roshd Ctr, Mashhad 9177949207, Razavi Khorasan, Iran; 2.Ferdowsi Univ Mashhad, Fac Agr, Mashhad 9177948944, Razavi Khorasan, Iran; 3.Ferdowsi Univ Mashhad, Dept Geog, Mashhad 9177948974, Razavi Khorasan, Iran
推荐引用方式 GB/T 7714	Salehnia, Nasrin,Hosseini, Fateme,Farid, Ali,et al. Comparing the Performance of Dynamical and Statistical Downscaling on Historical Run Precipitation Data over a Semi-Arid Region[J],2019,55(4):737-749.
APA	Salehnia, Nasrin,Hosseini, Fateme,Farid, Ali,Kolsoumi, Sohrab,Zarrin, Azar,&Hasheminia, Majid.(2019).Comparing the Performance of Dynamical and Statistical Downscaling on Historical Run Precipitation Data over a Semi-Arid Region.ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES,55(4),737-749.
MLA	Salehnia, Nasrin,et al."Comparing the Performance of Dynamical and Statistical Downscaling on Historical Run Precipitation Data over a Semi-Arid Region".ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES 55.4(2019):737-749.