No abstract

The number of weather stations that measure solar global irradiance (I g ) is scarce, and when it is available, it does not present long-time series, without gaps and high quality. When I g is unavailable, it is possible to estimate its integral over time-solar global irradiation (H g )-using empirical methods. However, for a better performance these methods need to be fitted to the local climatic conditions. The aim of this study was to assess the Hargreaves-Samani (HS) and Bristow-Campbell (BC) methods to estimate monthly average daily H g in the state of Rio de Janeiro, Southeastern Brazil, and to propose a simple approach to determine the empirical coefficients in function of the climate. The methods are based on maximum and minimum air temperature and on extraterrestrial solar irradiation. Series of air temperature extremes and H g from 15 automatic weather stations between 2000 until 2013 were used. The methods were evaluated by the statistical indexes: determination coefficient (r 2 ) of the linear regression between observed and estimated monthly H g , root mean square error (RMSE), Willmott's index (d) and performance index (c). The methods (BC-r 2 > 0.60, d > 0.85 and RMSE < 2.99 MJ m −2 d −1 and HS-r 2 > 0.55, d > 0.75 and RMSE < 3.85 MJ m −2 d −1 ) had satisfactory performance in the estimation of monthly H g for the state of Rio de Janeiro, when their coefficients were fitted to local climatic conditions. The BC presented performance classified as "optimal" (c > 0.85) in approximately 80% of the stations analyzed, while for Hargreaves-Samani, only 55% of the stations were classified as "optimal. " The highest HS coefficients (k r ) occurred in Semiarid (0.246 ± 0,023) and Dry Sub-humid (0.181 ± 0.011) climates and were associated with coastal regions (< 20 km), while the stations in Humid (0.146 ± 0.008), Sub-humid (0.1524 ± 0.003) and Dry Sub-humid (0.162 ± 0.011) climates located in interior regions presented the lowest k r . Thus, it is possible to determine the k r coefficient based only on the climatic classification of the site and distance of the coastal environment. In general, the highest atmospheric transmittance (β 0 -BC method) was observed in Semiarid and Dry Sub-humid climate regions. β 1 and β 2 coefficients did not present a distribution pattern with the local climatology and with the proximity of large water bodies. The methods presented a better performance in Dry Sub-humid and Semiarid climates, due to the lower variability of cloudiness and greater thermal amplitude.

A aplicação do método de Penman-Monteith FAO56 (PM-FAO56) para estimativa da evapotranspiração de referência (ETo) requer observações de diversos elementos meteorológicos. A maior parte das estações meteorológicas não realiza medidas de todos os elementos, o que restringe a aplicação do PM-FAO56. O objetivo foi avaliar o desempenho dos métodos empíricos de Thornthwaite, Camargo, Hargreaves-Samani, Jensen-Haise e Makkink na estimativa de ETo em função dos extremos de temperatura do ar no estado do Rio de Janeiro (RJ). Foram utilizadas séries meteorológicas entre oito e 34 anos de 10 estações convencionais pertencentes ao Instituto Nacional de Meteorologia localizadas no RJ. As estimativas decendiais e mensais de ETo pelos métodos empíricos foram comparadas com ETo determinada por PM-FAO56 (padrão) para se avaliar a exatidão (Erro Padrão de Estimativa -EPE e Índice de Willmott -d), precisão (coeficiente de determinação -R²) e o desempenho (índice c de Camargo e Sentelhas) dos métodos. Independente da escala de tempo avaliada, o método de Makkink mostrou estimativas com maior exatidão (d > 0,82 e EPE < 0,68 mm d ) e desempenhos (0,51 < índice c < 0,75) das estimativas foram proporcionadas por Jensen-Haise para todas as estações e escalas de tempo, não sendo recomendado sua aplicação no estado do RJ. Os métodos de Hargreaves-Samani, Jensen-Haise e Makkink devem ser ajustados às condições climáticas do RJ.Palavras-Chave: Penman-Monteith, radiação solar global, amplitude térmica

Monthly potential evapotranspiration (PET) using the Thornthwaite (ThW) method fed with gridded climate datasets was evaluated relative to PET by ThW and to reference evapotranspiration (ETo) estimated using the FAO56 Penman-Monteith method (PM-FAO56) with observed data, for Rio de Janeiro state, and neighboring states in southeast Brazil. The PM-FAO56 method used monthly climate series (1961–2010) on sunshine hours, air temperature, relative humidity, and wind speed, from 21 weather stations of the National Institute of Meteorology (INMET), in Rio de Janeiro (RJ), São Paulo (SP), Minas Gerais (MG), and Espírito Santo (ES) to estimate ETo. The estimated PET using the ThW method was based on observed air temperature from INMET stations and also using gridded air temperature datasets (1961–2010) from the Global Historical Climatology Network (GHCN) and the University of Delaware (UDel). The ETP estimates had an agreement (Willmott index) between 0.54 ≤ dw ≤ 0.96 – GHCN and 0.62 ≤ dw ≤ 0.96 - UDel; a precision between 0.44 ≤ r² ≤ 0.88 – GHCN and 0.53 ≤ r² ≤ 0.95 - UDel; and RMSE inferior to 1.39 mm d− 1 – GHCN and 1.13 mm d− 1 - UDel. The PET estimated with the UDel gridded series was better overall performance than using the GHCN product. Differences in altitude, latitude and longitude were the main geographic variables determining the precision and agreement of the PET estimates using GHCN and Udel. The gridded datasets are an alternative for locations without climatic series data or with low-quality non-continuous data series.

Monthly potential evapotranspiration (PET) using the Thornthwaite (ThW) method fed with gridded climate datasets was evaluated relative to PET by ThW and to reference evapotranspiration (ETo) estimated using the FAO56 Penman-Monteith method (PM-FAO56) with observed data, for Rio de Janeiro state, and neighboring states in southeast Brazil. The PM-FAO56 method used monthly climate series (1961–2010) on sunshine hours, air temperature, relative humidity, and wind speed, from 21 weather stations of the National Institute of Meteorology (INMET), in Rio de Janeiro (RJ), São Paulo (SP), Minas Gerais (MG), and Espírito Santo (ES) to estimate ETo. The estimated PET using the ThW method was based on observed air temperature from INMET stations and also using gridded air temperature datasets (1961–2010) from the Global Historical Climatology Network (GHCN) and the University of Delaware (UDel). The ETP estimates had an agreement (Willmott index) between 0.54 ≤ dw ≤ 0.96 – GHCN and 0.62 ≤ dw ≤ 0.96 - UDel; a precision between 0.44 ≤ r² ≤ 0.88 – GHCN and 0.53 ≤ r² ≤ 0.95 - UDel; and RMSE inferior to 1.39 mm d− 1 – GHCN and 1.13 mm d− 1 - UDel. The PET estimated with the UDel gridded series was better overall performance than using the GHCN product. Differences in altitude, latitude and longitude were the main geographic variables determining the precision and agreement of the PET estimates using GHCN and Udel. The gridded datasets are an alternative for locations without climatic series data or with low-quality non-continuous data series.