Contrasting regional and global climate simulations over South Asia

Arun Rana,Marco Kupiainen,Erik Kjellström,Michael Kolax,Gustav Strandberg,Ulf Hansson,Grigory Nikulin

doi:10.1007/s00382-020-05146-0

Abstract

Two ensembles of climate simulations, one global and one regional, are used to investigate model errors and projected climate change in seasonal mean temperature and precipitation over South Asia. The global ensemble includes ten global climate models (GCMs). In the regional ensemble all ten GCMs are downscaled by a regional climate model—RCA4 over South Asia at 50 km resolution. Our focus is on the Indian Summer Monsoon season (June–August) and we show that RCA4 can reproduce, reduce or amplify large-scale GCM biases depending on regions and GCMs. However, the RCA4 bias pattern in precipitation is similar across the simulations, regardless of forcing GCM, indicating a strong RCA4 imprint on the simulated precipitation. For climate change, the results indicate, that RCA4 can change the signal projected by the GCM ensemble and its individual members. There are a few RCA4 simulations with a substantial reduction of projected warming by RCA4 compared to the driving GCMs and with a large regional increase in precipitation absent in the GCMs. We also found that in a number of subregions warm RCA4 biases are related to stronger warming and vice versa, while there is no such dependency in the GCM ensemble. Neither the GCM nor the RCA4 ensemble shows any significant dependency between projected changes and biases for precipitation. Our results implicate that using only RCMs and excluding GCMs, a commonly established approach, can significantly change the message on future regional climate change.

Highlights

South Asia is one of the most densely populated regions in the world and, at the same time, is particular vulnerable to impacts of climate change and variability (Hijioka et al 2014)
All observation and reanalyse datasets were remapped from their native grids to the CORDEX 50 km grid by bicubic interpolations and aggregated to the common 2° global climate models (GCMs) grid by conservative remapping
The GCM ensemble shows a moderate warm bias (2–3 °C) in northern parts of India and a stronger cold bias in the Himalayas, at some grid boxes the GCM cold bias is comparable with the difference between

Summary

Introduction

South Asia is one of the most densely populated regions in the world and, at the same time, is particular vulnerable to impacts of climate change and variability (Hijioka et al 2014). The region is strongly influenced by the Asian Monsoon in boreal summer and undergoes large interannual, decadal and multi-decadal variability, expressed as extremely wet/dry and/or relatively mild/hot conditions. The largest country in South Asia, with a population of more than 1.2 billion people strongly dependent on sectors. Most of India receives much of its annual amount of rainfall in boreal summer from the Indian Summer Monsoon rainfall (ISMR). A decreasing country-scale trend in rainfall was found for the last decades and an increasing trend in extreme rainfall events and a decreasing trend in low intensity precipitation are reported (Kulkarni et al 2012; Krishnaswamy et al 2015; Roxy et al 2015). For neighbouring Bangladesh and Pakistan the frequency and intensity of extreme rainfall events have increased

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