Resumo

FLORIAN-VERGARA, Carolina; SALAS, Hernán D.  e  BUILES-JARAMILLO, Alejandro. Analysis of Precipitation and Evaporation in the Colombian Orinoco According to the Regional Climate Models of the CORDEX-CORE Experiment. TecnoL. [online]. 2021, vol.24, n.52, pp.242-261.  Epub 16-Fev-2022. ISSN 0123-7799.  https://doi.org/10.22430/22565337.2144.

We evaluate the capacity of the Regional Climate Models, included in the regional scale reduction experiment (CORDEX-CORE), to represent the monthly precipitation and evaporation in a watershed of the Colombian Orinoco region. In addition, we use precipitation and evaporation data from sources such as Climate Hazards Center InfraRed Precipitation with Station data, ERA5 atmospheric reanalysis, Global Precipitation Climatology Center and Global Land Evaporation Amsterdam Model. The comparisons between the assemblies of the RCMs and the observations were done using graphical and quantitative methods, among them: box plots, percentages of bias, Nash-Sutcliffe efficiency, among others. Our results allow concluding that the average precipitation values are adequately represented, in terms of their temporality and magnitude, by the assembly of the RegCM model while the average values of total evaporation are better represented by the assembly of the REMO model in terms of temporality, but not in its magnitude. Furthermore, the long-term flow estimation shows that the total evaporation values provided by the RCMs allow an adequate estimation of the long-term average flow, but not the adequate estimation of the annual flow cycle. This work is a pioneer in the evaluation of the monthly precipitation and evaporation data provided by CORDEX-CORE in the Colombian Orinoco, sets precedents for the incorporation of regional models data for hydrological purposes in poorly instrumented areas of the country, and is the first step towards the evaluation of regional climate change scenarios.

Palavras-chave : Monthly precipitation; Monthly evaporation; Water Balance; Model Comparison; Regional Climate Models; Performance assessment.

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