Evaluation of areal monthly average precipitation estimates from MERRA2 and ERA5 reanalysis in a colombian caribbean basin

Global reanalysis dataset estimations of climate variables constitute an alternative for overcoming data scarcity associated with sparsely and unevenly distributed hydrometeorological networks often found in developing countries. However, reanalysis datasets require detailed validation to determine...

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Autores:
Vega-Durán, Jean
Escalante-Castro, Brigitte
Canales, Fausto
Acuña Robles, Guillermo Jesús
Kaźmierczak, Bartosz
Canales, Fausto Alfredo
Tipo de recurso:
Article of journal
Fecha de publicación:
2021
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/9067
Acceso en línea:
https://hdl.handle.net/11323/9067
https://doi.org/10.3390/atmos12111430
https://repositorio.cuc.edu.co/
Palabra clave:
Rainfall
Reanalysis
ERA 5
MERRA 2
Thiessen polygons
Rights
openAccess
License
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Description
Summary:Global reanalysis dataset estimations of climate variables constitute an alternative for overcoming data scarcity associated with sparsely and unevenly distributed hydrometeorological networks often found in developing countries. However, reanalysis datasets require detailed validation to determine their accuracy and reliability. This paper evaluates the performance of MERRA2 and ERA5 regarding their monthly rainfall products, comparing their areal precipitation averages with estimates based on ground measurement records from 49 rain gauges managed by the Institute of Hydrology, Meteorology, and Environmental Studies (IDEAM) and the Thiessen polygons method in the Sinu River basin, Colombia. The performance metrics employed in this research are the correlation coefficient, the bias, the normalized root mean square error (NRMSE), and the Nash–Sutcliffe efficiency (NSE). The results show that ERA5 generally outperforms MERRA2 in the study area. However, both reanalyses consistently overestimate the monthly averages calculated from IDEAM records at all time and spatial scales. The negative NSE values indicate that historical monthly averages from IDEAM records are better predictors than both MERRA2 and ERA5 rainfall products.