Comparison of GCM and RCM simulated precipitation and temperature over Central America and the Caribbean
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ORIGINAL PAPER
Comparison of GCM and RCM simulated precipitation and temperature over Central America and the Caribbean Alejandro Vichot-Llano 1 Abel Centella-Artola 1
&
Daniel Martinez-Castro 1,2 & Filippo Giorgi 3 & Arnoldo Bezanilla-Morlot 1 &
Received: 24 May 2019 / Accepted: 17 September 2020 # Springer-Verlag GmbH Austria, part of Springer Nature 2020
Abstract The climate features over Central America and the Caribbean are simulated with the regional climate model RegCM4 to analyze the performance of the model in reproducing precipitation and temperature patterns over the region. Results from RegCM4 and the driving global climate model (GCM) HadGEM2-ES (HadG) are compared against gridded observations for a period from January 1980 to December 2004 using a perturbed physics ensemble formed by four configurations of the RegCM4 using different combinations of four convection schemes run over land and ocean areas: Kain Fritsch (Kf), Emanuel (Em), Grell (Ge), and Tiedtke (Tk). The added value of RegCM4 relative to the GCM simulation is also estimated, with focus over four subregions, using several metrics calculated on the RegCM4 as well as the GCM grids. The RegCM4 downscaling, expressed by the ensemble mean ENS, adds significant details to the HadG simulation of the temperature field patterns, showing smaller biases of up to ± 1.6 °C at the RCM resolution. Regarding the spatial patterns of precipitation, the HadG has overall higher correlation values with observations than ENS. However, the regional model provides more detailed spatial distributions, decreasing the bias by more than 1 mm/day over some of the islands. It also captures extreme precipitation events that are underestimated in the HadG simulation, even after upscaling to the GCM resolution grid. Concerning the performance of the different RegCM4 convection scheme combinations, KfEm and EmEm show the highest skill values for precipitation, while for temperature TkEm and GeEm are the best performing. This highlights that no individual scheme outperforms the others in all respects, while the application of the averaged ensemble technique provides the best results.
1 Introduction The use of regional climate models (RCMs) driven by global climate models (GCMs) to produce climate simulations or projections at a higher scale than that of the GCM has become a common practice in the last decades (Giorgi 2019). The advantages and disadvantages of RCMs have been discussed in many papers (Anthes et al. 1989; Centella-Artola et al. 2015; Feser 2006; Giorgi and Gutowski 2015; Giorgi and Mearns 1991; Castro et al. 2005; Martínez-Castro et al. 2006, 2016, 2018; Prömmel et al. 2010; Rockel et al. 2008; * Alejandro Vichot-Llano [email protected]; [email protected] 1
Instituto de Meteorología, Loma de Casablanca S/N, Havana, Cuba
2
Instituto Geofísico del Perú, Lima, Perú
3
Earth Physics Section, International Centre for Theoretical Physics, Trieste, Italy
Vichot-Llano et al. 2014; Winterfeldt and Weisse 2009). One of the most debated
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