The accuracy of temporal upscaling of instantaneous evapotranspiration to daily values with seven upscaling methods

This study evaluated the accuracy of seven upscaling methods in simulating daily latent heat flux (LE) from instantaneous values using observations from 148 global sites under all sky conditions and at different times during the day. Daily atmospheric transmissivity (τ) was used to represent the sky conditions. The results showed that all seven methods could accurately simulate daily LE from instantaneous values. The mean and median of Nash–Sutcliffe efficiency were 0.80 and 0.85, respectively, and the corresponding determination coefficients were 0.87 and 0.90, respectively. The sine and Gaussian function methods simulated mean values with relatively higher accuracy, with relative errors generally within ±10 %. The evaporative fraction (EF) methods, which use potential evapotranspiration and incoming shortwave radiation, performed relatively better than the other methods in simulating daily series. Overall, the EF method using potential evapotranspiration had the highest accuracy. However, the sine function and the EF method using extraterrestrial solar irradiance are recommended in upscaling applications because of the relatively minimal data requirements of these methods and their comparable or relatively higher accuracy. The intra-day distribution of the LE showed greater consistency with the Gaussian function than the sine function. However, the accuracy of simulated daily LE series using the Gaussian function method did not improve significantly compared with the sine function method. The simulation accuracy showed a minor difference when using the same type of method, for example, the same type of mathematical function or EF method. In any upscaling scheme, the simulation accuracy from multi-time values was significantly higher than that from a single-time value. Therefore, when multi-time data are available, multi-time values should be used in evapotranspiration upscaling. The upscaling methods show the ability to accurately simulate daily LE from instantaneous values from 09:00 to 15:00, particularly for instantaneous values between 11:00 and 14:00. However, outside of this time range the upscaling methods performed poorly. These methods can simulate daily LE series with high accuracy at τ > 0.6; when τ < 0.6, simulation accuracy is significantly affected by sky conditions and is generally positively related to daily atmospheric transmissivity. Although every upscaling scheme can accurately simulate daily LE from instantaneous values at most sites, this ability is lost at tropical rainforest and tropical monsoon sites.

PARAMETERIZATION OF SHORT-WAVE SOLAR IRRADIANCE FOR GLACIOLOGICAL APPLICATIONS

Solar irradiance is the most important factor which determines the thermal conditions of mountain glaciers. We use trigonometric formulae to calculate direct solar radiation incoming on any arbitrary oriented surface under the condition of absence of the atmosphere. Shading effect from the surrounding relief can also be evaluated rather precisely. Nevertheless, in order to obtain correct results, it is necessary to take into account atmospheric transmissivity, diffuse radiation, and influence of cloudiness. The paper presents a model for calculation of shortwave radiation, utilizing up-to-date data on the atmospheric composition and schemes for parameterization of the atmospheric transmissivity, which have never been implemented in glaciological applications before. Validation of the model was carried out using observational data on the global radiation on two weather stations established on Karabatkak glacier (Inner Tien Shan).

Global Analysis of Atmospheric Transmissivity Using Cloud Cover, Aridity and Flux Network Datasets

Atmospheric transmissivity (τ) is a critical factor in climatology, which affects surface energy balance, measured at a limited number of meteorological stations worldwide. With the limited availability of meteorological datasets in remote areas across different climatic regions, estimation of τ is becoming a challenging task for adequate hydrological, climatic, and crop modeling studies. The availability of solar radiation data is comparatively less accessible on a global scale than the temperature and precipitation datasets, which makes it necessary to develop methods to estimate τ. Most of the previous studies provided region specific datasets of τ, which usually provide local assessments. Hence, there is a necessity to give the empirical models for τ estimation on a global scale that can be easily assessed. This study presents the analysis of the τ relationship with varying geographic features and climatic factors like latitude, aridity index, cloud cover, precipitation, temperature, diurnal temperature range, and elevation. In addition to these factors, the applicability of these relationships was evaluated for different climate types. Thus, empirical models have been proposed for each climate type to estimate τ by using the most effective factors such as cloud cover and aridity index. The cloud cover is an important yet often overlooked factor that can be used to determine the global atmospheric transmissivity. The empirical relationship and statistical indicator provided the best performance in equatorial climates as the coefficient of determination (r2) was 0.88 relatively higher than the warm temperate (r2 = 0.74) and arid regions (r2 = 0.46). According to the results, it is believed that the analysis presented in this work is applicable for estimating the τ in different ecosystems across the globe.

Radiação global e difusa diária na região de transição Cerrado-Amazônia brasileira

This study aimed to analyze the seasonal variations in atmospheric transmissivity and solar radiation (global and diffuse) on the horizontal surface in Sinop, Mato Grosso (MT) (11.865°S, 55.485°W, and altitude of 371 m) from 06/02/2011 to 12/31/2014. The values of diffuse radiation were measured using the Melo-Escobedo-Oliveira (MEO) shadow ring, with application of astronomical, geometric, and anisotropic correction factors. The analysis of atmospheric transmissivity was based on the classification of sky cover as cloudy, partly cloudy, partially clear, or clear. The diffuse radiation showed similar behavior to the radiation at the top of the atmosphere, reaching a maximum between October and April (rainy season), while the global radiation displayed higher levels during the dry season (May to September). The average daily global radiation ranged from 22.75±0.61 MJ m−2 d−1 in August to 16.44±1.45 MJ m−2 d−1 in January. In Sinop, cloudy and partly cloudy skies occurred on 45.6% of days and atmospheric transmissivity of global radiation was greater than 55% on 54.6% of days. The variations in diffuse radiation in the region were influenced by cloudiness and the concentration of biomass burning aerosol particles. The diffuse radiation can represent 8.02%–99.12% of the global radiation and 5.33%–29.01% of solar energy incident at the top of the atmosphere.

Accuracy of temporal upscaling instantaneous evapotranspiration insimulating daily values in remote sensing applications

This study evaluated the accuracy of seven upscaling methods in simulating daily latent heat flux (LE) from instantaneous values using observations from 148 global sites under all sky conditions, and at different times during the day. Daily atmospheric transmissivity (τ) was used to represent the sky conditions. The results showed that all seven methods could accurately simulate daily LE from instantaneous values. The mean and median of Nash–Sutcliffe efficiency were 0.80 and 0.85, respectively, and the corresponding determination coefficients were 0.87 and 0.90, respectively. The sine and Gaussian function methods simulated mean values with relatively higher accuracy, with relative errors generally within ±10 %. The evaporative fraction (EF) methods, which use potential evapotranspiration and incoming shortwave radiation, performed relatively better than the other methods in simulating daily series. Overall, the EF method using potential evapotranspiration had the highest accuracy. However, the sine function and the EF method using extraterrestrial solar irradiance are recommended in upscaling applications because of the relatively minimal data requirements of these methods and their comparable or relatively higher accuracy. The intra-day distribution of the LE showed greater consistency with the Gaussian function than the sine function. However, the accuracy of simulated daily LE series using the Gaussian function method did not improve significantly compared with the sine function method. The simulation accuracy showed minor difference when using the same type of methods, for example, the same type of mathematical function or EF method. In any upscaling scheme, the simulation accuracy from multi-time values was significantly higher than that from a single time value. Therefore, when multi-time data are available, multi-time values should be used in evapotranspiration upscaling. The upscaling methods show the ability to accurately simulate daily LE from instantaneous values from 9:00–15:00, particularly for instantaneous values between 11:00 and 14:00. However, outside of this time range the upscaling methods performed poorly. These methods can simulate daily LE series with high accuracy at τ > 0.6; when τ < 0.6, simulation accuracy is significantly affected by sky conditions, and is generally positively related to daily atmospheric transmissivity. Although every upscaling scheme can accurately simulate daily LE from instantaneous values at most sites, this ability is lost at tropical rainforest and tropical monsoon sites.

Métodos baseados em temperatura do ar para estimativa de radiação solar incidente diária no Estado do Rio de Janeiro

A radiação solar global (Rs) é um parâmetro de entrada necessária para estimativa da evapotranspiração e em modelos de crescimento, desenvolvimento e simulação do rendimento das culturas. Em locais com ausência de dados de Rs, podem ser utilizados métodos empíricos em função dos extremos de temperatura do ar para sua estimativa. No estado do Rio de Janeiro, estudos sobre Rs com base em métodos empíricos são escassos. Portanto, o objetivo foi estimar Rs diária com base no método de Hargreaves-Samani (HS) por meio de dados da amplitude térmica diária de 11 estações meteorológicas automáticas na escala bianual (2013-2014). O desempenho do método HS com o coeficiente proposto por Hargreaves (1994) e calibrado por Allen (1995) foi avaliado com indicadores estatísticos. O coeficiente R² variou entre 0,30 a 0,85, seguido do índice d entre 0,58 a 0,95 e do índice c entre 0,32 a 0,87, classificados como “Péssimo” a “Ótimo”. O erro absoluto variou de -6,23 a 7,09 MJ m-2 d-1 e o RQME 2,98 entre 8,69 MJ m-2 d-1. Baseado nos resultados o coeficiente proposto por Hargreaves (1994) resulta em estimativas precisas em comparação ao calibrado por Allen (1995), com ressalva das estações costeiras. Methods based on air temperature to estimate daily incident solar radiation in Rio de Janeiro State A B S T R A C TGlobal solar radiation (Rs) is a necessary input parameter for estimating evapotranspiration and in crop growth, development and simulation models. In places with no data of Rs, empirical methods may be used as a function of the extremes of air temperature for their estimation. In the state of Rio de Janeiro, studies on Rs based on empirical methods are scarce. Therefore, the objective was to estimate daily Rs based on the Hargreaves-Samani (HS) method using data from the daily thermal amplitude of 11 automatic meteorological stations on a biannual scale (2013-2014). The performance of the HS method with the coefficient proposed by Hargreaves (1994) and calibrated by Allen (1995) was evaluated with statistical indicators. The R² coefficient ranged from 0.3 to 0.85, followed by the d index between 0.58 to 0.95 and the c index between 0.32 to 0.87, classified as "Poor" to "Great." The médium erro ranged from -6.23 to 7.09 MJ m-2 d-1 and RMSE 2.98 to 8.69 MJ m-2 d-1. Based on the results, the coefficient proposed by Hargreaves (1994) results in more accurate estimates compared to the one calibrated by Allen (1995), with the exception of the coastal stations.Keywords: meteorological parameters, atmospheric transmissivity, thermal amplitude.

Albedo Trend Analyses in Atlantic Forest Biome Areas

The albedo is an important variable that controls the balance of radiation and energy of the atmosphere, so changes in land cover cause alterations in albedo values, influencing changes in climate behavior at different scales. The goal in this work was to investigate the possible occurrence and causes associated with surface albedo trends within the Atlantic Forest biome (S&atilde;o Francisco de Paula, state of Rio Grande do Sul, Brazil), during the last thirty years (1987-2017), evaluating the impacts of the forest cover structure on albedo trends. The study included images of the TM/Landsat 5 and OLI/Landsat 8 sensors over the period 1987 to 2017. The surface albedo was obtained from the SEBAL algorithm, which includes in its variables the reflectance values of each band, reflected solar radiation and atmospheric transmissivity. The trend analysis was performed by the Mann-Kendall test verifying the existence of significant trends over 30 years. Subsequently, the influence of vegetation greenness on the trend presented by the albedo surface was evaluated. Approximately 92% of the pixels with significant tendency are associated with the decreasing tendency of the albedo. The downward trend was observed with the change from the field to the forest cover, while increasing trends were influenced by the change in forest cover, such as the suppression of individuals from the upper forest canopy. The forest populations in areas of the Mata Atl&acirc;ntica biome had a large participation in the energy balance, which exposed a reduction of approximately 60% of the surface albedo with its implantation, showing its importance for reducing the emission of energy to the atmosphere. The spatial pattern of the trend distribution of the surface albedo is related to the concentration and vigor of the arboreal vegetation.

Estimation of the Daily Global Solar Radiation using RadEst 3.00 Software at Nepalgunj, Nepal

The RadEst 3.00 version software estimates daily total solar radiation at low land area using meteorological parameters such as precipitation, temperatures and solar radiation of Nepalgunj (Lat.28.05°N, Lon.81.62°E, and Alt.150m). Radiation is calculated as the product of the atmospheric transmissivity of radiation and radiation outside earth atmosphere. The model parameters are fitted in two years data. An accurate knowledge of solar radiation distribution in each particular geographical location is crucial for the promotion of solar active and passive energy technology. The values estimated by the models are compared with measured solar radiation data. The performance of the model was evaluated using root mean square error (RMSE), mean bias error (MBE), Coefficient of Residual Mass (CRM) and coefficient of determination (R2). The RadEst 3.0 software which showed the better results using BC, CD, DB and DCBB, among them the DCBB model is the best model for this site. The values of RMSE, MBE, CRM and R2are 5.20, 3.98, 0.00 and 0.47 respectively. The finding coefficients of different models can be utilized for the estimation of solar radiation at the similar meteorological sites of Nepal.Journal of the Institute of Engineering, 2016, 12(1): 199-209