Comparación de series mensuales de precipitación y temperaturas de los Modelos CMIP6 para Guatemala

Paris Rivera; Eduardo Herrera; Werner Ochoa

doi:10.36829/63CTS.v9i2.1285

Authors

Paris Rivera Instituto de Investigaciones de Ingeniera, Matemática y Ciencias Físicas, Universidad Mariano Gálvez de Guatemala https://orcid.org/0000-0001-7259-5152
Eduardo Herrera Facultad de Instrumentación Electrónica, Universidad Veracruzana, México
Werner Ochoa Escuela de Estudios de Postgrado, Facultad de Ingeniería, Universidad de San Carlos de Guatemala https://orcid.org/0000-0003-4984-2877

DOI:

https://doi.org/10.36829/63CTS.v9i2.1285

Keywords:

Climatic model, precipitation, temperature

Abstract

Metrics from 37 global climate models (GCMs) from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) with the purpose of simulating the climate of Guatemalan from 1971 to 2014. Monthly temperature and precipitation were compared with data from observation of the Climatic Research Unit of the University of East Anglia (CRU). A ranking of models was generated based on the shortest distance between three resignations based on three metrics; Pearson's Correlation Coefficient (PCC), Root Mean Square Error (RMSE), and Standard Deviation (SD). This ordering coincides with the best values of Nash-Sutcliffe efficiency (NSE) for temperature and Kling-Gupta efficiency (KGE) for precipitation; other metrics are calculated; Spearman's correlation coefficient (CCS), mean bias errors (MBE), and mean absolute error (MAE). For precipitation, the first 5 models present KGE values between 0.5 and 0.7, the CCP and CCS between 0.7 and 0.8 compared to CRU. For temperature, the first 5 models present NSE values between 0.5 to 0.6, CCP, and CCS of 0.8. The models slightly overestimate temperature and underestimate precipitation. The models with the best ability were CIESM for temperature and the IPSL-CM6A-LR model for precipitation. Additionally, the average of 66 local stations is compared with CRU, presenting a KGE of 0.51, CCP of 0.77 for precipitation, and NSE of -0.,17, and a CCP of 0.20 for temperature. Finally, a table is presented with the first 10 models for each variable.

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Author Biography

Paris Rivera, Instituto de Investigaciones de Ingeniera, Matemática y Ciencias Físicas, Universidad Mariano Gálvez de Guatemala

Researcher
Research Institute of Engineering, Mathematics and Physical Sciences of the Mariano Gálvez University of Guatemala

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