How Does a Regional Climate Model Modify the Projected Climate Change Signal of the Driving GCM: A Study over Different CORDEX Regions Using REMO

Claas Teichmann,Christopher Moseley,Alberto Elizalde,Kevin Sieck,Daniela Jacob,Andreas Haensler,Armelle Remedio,Thomas Raub,Hinnerk Ries,Juliane Petersen,Diana Rechid,Bastian Eggert,Torsten Weber,Fahad Saeed,Swantje Preuschmann,Susanne Pfeifer,Pankaj Kumar

doi:10.3390/atmos4020214

Abstract

Global and regional climate model simulations are frequently used for regional climate change assessments and in climate impact modeling studies. To reflect the inherent and methodological uncertainties in climate modeling, the assessment of regional climate change requires ensemble simulations from different global and regional climate model combinations. To interpret the spread of simulated results, it is useful to understand how the climate change signal is modified in the GCM-RCM modelmodelgeneral circulation model-regional climate model (GCM-RCM) chain. This kind of information can also be useful for impact modelers; for the process of experiment design and when interpreting model results. In this study, we investigate how the simulated historical and future climate of the Max-Planck-Institute earth system model (MPI-ESM) is modified by dynamic downscaling with the regional model REMO in different world regions. The historical climate simulations for 1950–2005 are driven by observed anthropogenic forcing. The climate projections are driven by projected anthropogenic forcing according to different Representative Concentration Pathways (RCPs). The global simulations are downscaled with REMO over the Coordinated Regional Climate Downscaling Experiment (CORDEX) domains Africa, Europe, South America and West Asia from 2006–2100. This unique set of simulations allows for climate type specific analysis across multiple world regions and for multi-scenarios. We used a classification of climate types by Köppen-Trewartha to define evaluation regions with certain climate conditions. A systematic comparison of near-surface temperature and precipitation simulated by the regional and the global model is done. In general, the historical time period is well represented by the GCM and the RCM. Some different biases occur in the RCM compared to the GCM as in the Amazon Basin, northern Africa and the West Asian domain. Both models project similar warming, although somewhat less so by the RCM for certain regions and climate types. A common feature in regions of tropical climate types is that REMO shows dryer climate conditions than forMax Planck Institute for Meteorology-Earth System Model (MPI-ESM) for RCP 4.5 and RCP 8.5, leading to an opposing sign in the climate change signal. With an increase in radiative forcing from RCP 2.6 to RCP 8.5 and towards the end of the 21st century, some of the detected differences between GCM and RCM are more pronounced.

Highlights

General circulation models (GCMs) are commonly used to assess present-day climate and possible future climate changes at the global scale at rather coarse resolutions [1,2,3,4,5,6]
In which the Max-Planck-Institute earth system model (MPI-ESM) simulated sea surface temperature (SST) was replaced by the SST of ERA-Interim, the results indicate that the monsoon precipitation is better simulated with the corrected SST
The global and regional model processes leading to the opposite precipitation signals of the regional and the global simulations in the projected climate over central Africa are presently investigated by Saeed et al [68]

Summary

Introduction

General circulation models (GCMs) are commonly used to assess present-day climate and possible future climate changes at the global scale at rather coarse resolutions (mostly 300 to 100 km) [1,2,3,4,5,6]. In order to investigate regional impacts of different climate conditions, spatially higher resolved information about the state of the regional climate system is needed [7,8,9,10,11]. To reflect the inherent and methodological uncertainties in climate modeling, the assessment of regional climate change requires ensemble simulations by different global and regional climate model combinations as is done in several past and present international projects, e.g., PRUDENCE [19], ENSEMBLES [20] and the COordinated. In order to help interpret the spread of the simulated results, it is useful to know how the climate change signal is modified within the individual modeling chains of global to regional models. We want to answer the question, how does the RCM REMO modifiesmodify the simulated historical climate and the global climate change signal of the driving GCM Max Planck

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Conclusion