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Article

Optimization Assessment of Projection Methods of Climate Change for Discrepancies between North and South China

by 1, 1,2,*, 1 and 1,2,3
1
College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China
2
Center for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China
3
Chinese-Israeli International Center for Research and Training in Agriculture, China Agricultural University, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Water 2020, 12(11), 3106; https://doi.org/10.3390/w12113106
Received: 2 September 2020 / Revised: 22 October 2020 / Accepted: 2 November 2020 / Published: 5 November 2020
(This article belongs to the Special Issue Past and Future Trends and Variability in Hydro-Climatic Processes)
Downscaling methods have been widely used due to the coarse and biased outputs of general circulation models (GCMs), which cannot be applied directly in regional climate change projection. Hence, appropriate selection of GCMs and downscaling methods is important for assessing the impacts of climate change. To explicitly explore the influences of multi-GCMs and different downscaling methods on climate change projection in various climate zones, the Heihe River Basin (HRB) and the Zhanghe River Basin (ZRB) were selected in this study to represent the north arid region and the south humid region in China, respectively. We first evaluated the performance of multi-GCMs derived from Coupled Model Inter-comparison Project Phase 5 (CMIP5) in the two regions based on in-situ measurements and the 40 year European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) data. Subsequently, to construct appropriate climate change projection techniques, comparative analysis using two statistical downscaling methods was performed with consideration of the significant north–south meteorological discrepancies. Consequently, specific projections of future climate change for 2021–2050 under three representative concentration pathway (RCP) scenarios (RCP2.6, RCP4.5, and RCP8.5) were completed for the HRB and ZRB, including daily precipitation, maximum air temperature, and minimum air temperature. The results demonstrated that the score-based method with multiple criteria for performance evaluation of multiple GCMs more accurately captured the spatio-temporal characteristics of the regional climate. The two statistical downscaling methods showed respective advantages in arid and humid regions. The statistical downscaling model (SDSM) showed more accurate prediction capacities for air temperature in the arid-climate HRB, whereas model output statistics (MOS) better captured the probability distribution of precipitation in the ZRB, which is characterized by a humid climate. According to the results obtained in this study, the selection of appropriate GCMs and downscaling methods for specific climate zones with different meteorological features significantly impact regional climate change projection. The statistical downscaling models developed and recommended for the north and south of China in this study provide scientific reference for sustainable water resource management subject to climate change. View Full-Text
Keywords: climate change; downscaling; GCM; CMIP; ensemble; uncertainty climate change; downscaling; GCM; CMIP; ensemble; uncertainty
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MDPI and ACS Style

Lun, Y.; Liu, L.; Wang, R.; Huang, G. Optimization Assessment of Projection Methods of Climate Change for Discrepancies between North and South China. Water 2020, 12, 3106. https://doi.org/10.3390/w12113106

AMA Style

Lun Y, Liu L, Wang R, Huang G. Optimization Assessment of Projection Methods of Climate Change for Discrepancies between North and South China. Water. 2020; 12(11):3106. https://doi.org/10.3390/w12113106

Chicago/Turabian Style

Lun, Yurui; Liu, Liu; Wang, Ruotong; Huang, Guanhua. 2020. "Optimization Assessment of Projection Methods of Climate Change for Discrepancies between North and South China" Water 12, no. 11: 3106. https://doi.org/10.3390/w12113106

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