Affiliation:
1. National Research Institute for Rural Engineering, Water and Forestry, University of Carthage, BPN 10, Ariana 2080, Tunisia
2. Water Technological Center, CETAQUA, Ctra. d’Esplugues, 75, Cornellà de Llobregat, 08940 Barcelona, Spain
Abstract
Systematic biases in general circulation models (GCM) and regional climate models (RCM) impede their direct use in climate change impact research. Hence, the bias correction of GCM-RCMs outputs is a primary step in such studies. This study compares the potential of two bias correction methods (the method from the third phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3) and Detrended Quantile Matching (DQM)) applied to the raw outputs of daily data of minimum and maximum air temperatures and precipitation, in the Cap-Bon region, from eight GCM-RCM combinations. The outputs of GCM/RCM combinations were acquired from the European branch of the coordinated regional climate downscaling experiment (EURO-CORDEX) dataset for historical periods and under two representative concentration pathway (RCP4.5 and RCP8.5) scenarios. Furthermore, the best combination of bias correction/GCM-RCM was used to assess the impact of climate change on reference evapotranspiration (ET0). Numerous statistical indicators were considered to evaluate the performance of the bias correction/historical GCM-RCMs compared to the observed data. Trends of the Hargreaves–Samani_ET0 model during the historical and projected periods were determined using the TFPMK method. A comparison of the bias correction methods revealed that, for all the studied model combinations, ISIMIP3 performs better in reducing biases in monthly precipitation. However, for Tmax and Tmin, the biases are greatly removed when the DQM bias correction method is applied. In general, better results were obtained when the HadCCLM model was used. Before applying bias correction, the set of used GCM-RCMs projected reductions in precipitation for most of the months compared to the reference period (1982–2006). However, Tmin and Tmax are expected to increase in all months and for the three studied periods. Hargreaves–Samani ET0 values obtained from the best combination (DQM/ HadCCLM) show that RCP8.5 (2075–2098) will exhibit the highest annual ET0 increase compared to the RCP4.5 scenario and the other periods, with a change rate equal to 11.85% compared to the historical period. Regarding spring and summer seasons, the change rates of ET0 are expected to reach 10.44 and 18.07%, respectively, under RCP8.5 (2075–2098). This study shows that the model can be used to determine long-term trends in ET0 patterns for diverse purposes, such as water resources planning, agricultural crop management and irrigation scheduling in the Cap-Bon region.
Funder
MAGO project through PRIMA program supported by the European Union
PROJET MAGO/INRGREF
Reference47 articles.
1. A toolkit for climate change analysis and pattern recognition for extreme weather conditions e Case study: California-Baja California Peninsula;Vaghefi;Environ. Model. Softw.,2017
2. Investigating the variability of GCMs’ simulations using time series analysis;Sarzaeim;J. Water Clim. Change,2018
3. Climate extremes indices in the CMIP5 multimodel ensemble: Part 1. Model evaluation in the present climate;Sillmann;J. Geophys. Res. Atmos.,2013
4. Hostetler, S.W., Alder, J.R., and Allan, A.M. (2011). Dynamically Downscaled Climate Simulations over North America: Methods, Evaluation and Supporting Documentation for Users, U.S. Geological Survey. U.S. Geological Survey Open-File Report 2011-1238.
5. Hydrologic impact of climate change in the Saguenay watershed: Comparison of downscaling methods and hydrologic models;Dibike;J. Hydrol.,2005
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献