Evaluating the effects of climate change on precipitation and temperature for Iran using RCP scenarios

Shahab Doulabian,Conor Murphy,Amirhossein Shadmehri Toosi,Saeed Golian

doi:10.2166/wcc.2020.114

Abstract

AbstractClimate change has caused many changes in hydrologic processes and climatic conditions globally, while extreme events are likely to occur more frequently at a global scale with continued warming. Given the importance of general circulation models (GCMs) as an essential tool for climate studies at global/regional scales, together with the wide range of GCMs available, selecting appropriate models is of great importance. In this study, six synoptic weather stations were selected as representative of different climatic zones over Iran. Utilizing monthly data for 20 years (1981–2000), the outputs of 25 GCMs for surface air temperature (SAT) and precipitation were evaluated for the historical period. The root-mean-square error and skill score were chosen to evaluate the performance of GCMs in capturing observed seasonal climate. Finally, the outputs of selected GCMs for the three Representative Concentration Pathways emission scenarios (RCPs), namely RCP2.6, RCP4.5, and RCP8.5, were downscaled using the change factor method for each station for the period 2046–2065. Results indicate that SAT in all months is likely to increase for each region, while for precipitation, large uncertainties emerge, despite the selection of climate models that best capture the observed seasonal cycle. These results highlight the importance of selecting a representative ensemble of GCMs for assessing future hydro-climatic changes for Iran.

Highlights

Climate change (CC), driven by increases in greenhouse gases concentrations in the atmosphere, as a consequence of anthropogenic activities, has led to an increase in the global temperature of approximately 1 C since the preindustrial period (Dibike & Coulibaly ; Feng et al ; Bekele et al )
In this study, utilizing monthly data for 20 years (1981– 2000), the outputs of 25 general circulation models (GCMs) for surface air temperature (SAT) and precipitation were evaluated using observations for six synoptic stations over Iran. The performance of these models was evaluated using root-mean-square error (RMSE) and skill score (SS), and the best models were selected at seasonal time scale and the future data were generated
Evaluation of the results of the present study illustrates that models generally perform better in simulating SAT compared to precipitation

Summary

Introduction

Climate change (CC), driven by increases in greenhouse gases concentrations in the atmosphere, as a consequence of anthropogenic activities, has led to an increase in the global temperature of approximately 1 C since the preindustrial period (Dibike & Coulibaly ; Feng et al ; Bekele et al ). CC can alter local climatic conditions and accelerate hydrological processes (Kim et al ; Thomas et al ; Bekele et al ). The integration of likely changes in hydrology is.

Results

Discussion

Conclusion