Abstract

OCAMPO, Dora  and  RIVAS, Raúl. Estimating daily net radiation from multiple linear regression models. Rev. Chapingo ser. cienc. for. ambient [online]. 2013, vol.19, n.2, pp.263-272. ISSN 2007-4018.  https://doi.org/10.5154/r.rchscfa.2012.04.031.

Knowledge of daily net radiation (Rn) is basic to quantifying energy used in various processes occurring at the surface level such, as evapotranspiration. This study applies a Multiple Linear Regression Model (MRLM) for the estimation of Rn in a subhumid-humid zone of Argentina. In the model we used weather data of solar radiation, temperature and relative humidity, Rn (measured with a Kipp & Zonen net radiometer) and inverse relative distance earth-sun. As a result, eight estimation equations of Rn were obtained. The MRLM models were evaluated using the statistics Mean Bias Error (MBE) and Root Mean Square Error (RMSE). The results showed good adjustment and low error at daily scale, highlighting those equations involving solar radiation, temperature, relative humidity and inverse distance earth-sun, allowing calculation of Rn with errors less than 19 W·m^-2.

Keywords : Meteorological variables; evapotranspiration; net radiation; subhumid-humid zone.

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