Analysis of the NASA-POWER system for estimating reference evapotranspiration in the Comarca Lagunera, Mexico

Abstract

Introduction: The FAO-56 Penman-Monteith (PM) is one of the most solid and commonly used methods for estimating reference evapotranspiration (ETo); however, it requires meteorological data that are not always available, so an alternative is the use of reanalysis data. Objective: To estimate the error that the NASA-POWER (NP) system data can generate in the ETo of the Comarca Lagunera, Mexico. Methodology: Daily and decadal average ETo were estimated in five different ways. In each case, a different method was used to estimate ETo (FAO-56 PM or Hargreaves and Samani [HS]) and a different meteorological data source (measured, NP data or combination of both). Results: NP data can be used to provide temperature, solar radiation and relative humidity variables, but not wind speed. The NP data overestimate the measured ETo, an RMSE of 1.15 and 0.89 mm∙d-1 was found for daily and decadal periods, respectively. Limitations of the study: A grid error analysis could not be carried out because the number of stations is limited. Originality: The use of reanalysis data to estimate ETo has not been analyzed locally. Conclusion: When measured data are not available, NP data and the HS equation can be used. When using the FAO-56 PM method and NP data, the in situ wind speed must be available.

Estimation of Reference Evapotranspiration in a Semi-Arid Region of Mexico

“…This low radiation was due to atypical conditions: high cloudiness (rainfall of 7.6 mm recorded) and high relative humidity (84.5%). Some authors mention that wind speed and solar radiation are the climatic variables with the most significant influence on ET0 estimates in the study area [27]. Other authors reach the same conclusion when performing a sensitivity analysis in other regions [68][69][70].…”

Estimation of Reference Evapotranspiration in a Semi-Arid Region of Mexico

“…However, this method requires various meteorological input variables (temperature, solar radiation, relative humidity, and wind speed), which restrains its widespread use [ 25 ]. Therefore, its usefulness is limited in regions with no meteorological stations or a shortage of input data [ 26 ], which are usually unavailable with the required frequency and quality [ 27 ]. The other equations can be used in regions with very little climatological information, such as the case of Hargreaves–Samani (HS) and Blaney–Criddle (BC) equations, which are the most common ones [ 28 , 29 , 30 ] and only require temperature as an input variable [ 31 ].…”

“…Reanalysis data or gridded meteorological data are an alternate source of information that can be used to estimate ET 0 [ 42 , 43 , 44 ]. It is available on different platforms: National Aeronautics and Space Administration—Prediction of Worldwide Energy Resource (NASA-POWER) [ 27 , 45 ], Global Land Data Assimilation System (GLDAS) [ 46 ], Climate Forecast System ver. 2 (CFSv2) [ 47 ], North American Land Data Assimilation System (NLDAS) [ 48 ], and National Digital Forecast Database (NDFD) [ 49 ].…”

“…2 (CFSv2) [ 47 ], North American Land Data Assimilation System (NLDAS) [ 48 ], and National Digital Forecast Database (NDFD) [ 49 ]. These global or regional platforms provide data with higher spatial and temporal resolution [ 27 ]. However, it should be noted that higher spatial resolution does not necessarily imply higher precision [ 50 ].…”

Implementación de datos meteorológicos modelados en el norte patagónico argentino (1982-2017)

“…El repositorio de datos meteorológicos de reanálisis POWER NASA está habilitado para su uso en un entorno SIG (Sistema de Información Geográfica) con observaciones meteorológicas diarias desde 1982 hasta 2021 (Stackhouse et al, 2015;POWER NASA, 2020). Los datos de POWER NASA fueron útiles en el cálculo de la evapotranspiración en Lagunera, México (Jiménez-Jiménez et al, 2021). Rodríguez & Braga (2021) demostraron, también, que los datos de temperaturas máximas y mínimas y radiación solar de NASA POWER, poseen una alta correlación con mediciones meteorológicas in situ en el sur de Portugal.…”