Evaluation of Historical CMIP5 GCM Simulation Results Based on Detected Atmospheric Teleconnections

Atmosphere

Roland Hollós¹  Erzsébet Kristóf¹  Rita Pongrácz¹  Judit Bartholy¹  Zoltán Barcza¹ 

[1] Department of Meteorology, Eötvös Loránd University, Pázmány P. s. 1/A, H-1117 Budapest, Hungary;

关键词: teleconnection patterns;    teleconnection method;    diversity index;    CMIP5;    ERA-20C;    historical GCM outputs;   

DOI  :  10.3390/atmos11070723

来源: DOAJ

【 摘 要 】

Atmospheric teleconnections are characteristic to the climate system and exert major impacts on the global and regional climate. Accurate representation of teleconnections by general circulation models (GCMs) is indispensable given their fundamental role in the large scale circulation patterns. In this study a statistical method is introduced to evaluate historical GCM outputs of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) with respect to teleconnection patterns. The introduced method is based on the calculation of correlations between gridded time series of the 500 hPa geopotential height fields in the Northern Hemisphere. GCMs are quantified by a simple diversity index. Additionally, potential action centers of the teleconnection patterns are identified on which the local polynomial regression model is fitted. Diversity fields and regression curves obtained from the GCMs are compared against the NCEP/NCAR Reanalysis 1 and the ERA-20C reanalysis datasets. The introduced method is objective, reproducible, and reduces the number of arbitrary decisions during the analysis. We conclude that major teleconnection patterns are positioned in the GCMs and in the reanalysis datasets similarly, however, spatial differences in their intensities can be severe in some cases that could hamper the applicability of the GCM results for some regions. Based on the evaluation method, best-performing GCMs can be clearly distinguished. Evaluation of the GCMs based on the introduced method might help the modeling community to choose GCMs that are the most applicable for impact studies and for regional downscaling exercises.

【 授权许可】

Unknown