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

2021 ◽  
Vol 25 (8) ◽  
pp. 4417-4433
Author(s):  
Zhaofei Liu

Abstract. 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.

2021 ◽  
Author(s):  
Zhaofei Liu

Abstract. 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.


2008 ◽  
Vol 8 (18) ◽  
pp. 5615-5626 ◽  
Author(s):  
P. Weihs ◽  
M. Blumthaler ◽  
H. E. Rieder ◽  
A. Kreuter ◽  
S. Simic ◽  
...  

Abstract. A measurement campaign was performed in the region of Vienna and its surroundings from May to July 2007. Within the scope of this campaign erythemal UV was measured at six ground stations within a radius of 30 km. First, the homogeneity of the UV levels within the area of one satellite pixel was studied. Second, the ground UV was compared to ground UV retrieved by the ozone monitoring instrument (OMI) onboard the NASA EOS Aura Spacecraft. During clear-sky conditions the mean bias between erythemal UV measured by the different stations was within the measurement uncertainty of ±5%. Short term fluctuations of UV between the stations were below 3% within a radius of 20 km. For partly cloudy conditions and overcast conditions the discrepancy of instantaneous values between the stations is up to 200% or even higher. If averages of the UV index over longer time periods are compared the difference between the stations decreases strongly. The agreement is better than 20% within a distance of 10 km between the stations for 3 h averages. The comparison with OMI UV showed for clear-sky conditions higher satellite retrieved UV values by, on the average, approximately 15%. The ratio of OMI to ground measured UV lies between 0.9 and 1.5. and strongly depends on the aerosol optical depth. For partly cloudy and overcast conditions the OMI derived surface UV estimates show larger deviation from the ground-based reference data, and even bigger systematic positive bias. Here the ratio OMI to ground data lies between 0.5 and 4.5. The average difference between OMI and ground measurements is +24 to +37% for partly cloudy conditions and more than +50% for overcast conditions.


PeerJ ◽  
2019 ◽  
Vol 6 ◽  
pp. e6240 ◽  
Author(s):  
Chuang Liu ◽  
Yi Liu ◽  
Yanhong Lu ◽  
Yulin Liao ◽  
Jun Nie ◽  
...  

Improving the accuracy of predicting plant productivity is a key element in planning nutrient management strategies to ensure a balance between nutrient supply and demand under climate change. A calculation based on intercepted photosynthetically active radiation is an effective and relatively reliable way to determine the climate impact on a crop above-ground biomass (AGB). This research shows that using variations in a chlorophyll content index (CCI) in a mathematical function could effectively obtain good statistical diagnostic results between simulated and observed crop biomass. In this study, the leaf CCI, which is used as a biochemical photosynthetic component and calibration parameter, increased simulation accuracy across the growing stages during 2016–2017. This calculation improves the accuracy of prediction and modelling of crops under specific agroecosystems, and it may also improve projections of AGB for a variety of other crops.


2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Suhua Liu ◽  
Hongbo Su ◽  
Renhua Zhang ◽  
Jing Tian ◽  
Shaohui Chen ◽  
...  

Evapotranspiration (ET) is a significant component in the water cycle, and the estimation of it is imperative in water resource management. Regional ET can be derived by using remote sensing technology which combines remote sensing inputs with ground-based measurements. However, instantaneous ET values estimated through remote sensing directly need to be converted into daily totals. In this study, we attempted to retrieve daily ET from remotely sensed instantaneous ET. The study found that the Gaussian fitting curve closely followed the ET measurements during the daytime and hence put forward the Gaussian fitting method to convert the remotely sensed instantaneous ET into daily ETs. The method was applied to the middle reaches of Heihe River in China. Daily ETs on four days were derived and evaluated with ET measurements from the eddy covariance (EC) system. The correlation between daily ET estimates and measurements showed high accuracy, with a coefficient of determination (R2) of 0.82, a mean average error (MAE) of 0.41 mm, and a root mean square error (RMSE) of 0.46 mm. To make more scientific assessments, percent errors were calculated on the estimation accuracy, which ranged from 0% to 18%, with more than 80% of locations having the percent errors within 10%. Analyses on the relationship between daily ET estimates and land use status were also made to assess the Gaussian fitting method, and the results showed that the spatial distribution of daily ET estimates well demonstrated ET differences caused by land use types and was intimately linked with the vegetation pattern. The comparison between the Gaussian fitting method and the sine function method and the ETrF method indicated that results derived through the Gaussian fitting method had higher precision than that obtained by the sine function method and the ETrF method.


2013 ◽  
Vol 32 ◽  
pp. 55-60 ◽  
Author(s):  
M Abdur Rab ◽  
Jasmin Akhter

In this paper we establish a traveling wave solution for nonlinear partial differential equations using sine-function method. The method is used to obtain the exact solutions for three different types of nonlinear partial differential equations like general equal width wave equation (GEWE), general regularized long wave equation (GRLW), general Korteweg-de Vries equation(GKDV) which are the important soliton equations DOI: http://dx.doi.org/10.3329/ganit.v32i0.13647 GANIT J. Bangladesh Math. Soc. (ISSN 1606-3694) 32 (2012) 55-60


2019 ◽  
Vol 20 (11) ◽  
pp. 2185-2201 ◽  
Author(s):  
Yaqin Wang ◽  
Yi Luo ◽  
Muhammad Shafeeque

Abstract Seasonal variations in precipitation (P) and potential evapotranspiration (ET0) are critical for regional hydrometeorological studies and water resource management. The sinusoidal function is widely used to describe the seasonal pattern of P and ET0. However, high errors occur either in the arid places or in places with hyperseasonal precipitation. These limitations are intrinsic properties of the sinusoidal climate descriptor and remain a barrier to provide insight into regional water–energy partitions and hydrologic similarity and predictability. In this study, we used a Gaussian framework as an alternative to describe seasonal variations in P and ET0 regimes in the Yellow River basin (YRB). The results show that the Gaussian framework provides a good approximation to the seasonal pattern of P and has a strong regional applicability for reproducing the monthly P and ET0. This allows us to assess the climate seasonality characterizing the regional balance between water supply and energy availability using δP, δET0, and aridity index. The climate seasonality indicates that the balance between water supply and energy availability has a switch in about 32% of the grid cells during the seasonal cycle from 1982 to 2015. These grid cells are mostly located in regions with average annual precipitation above 550 mm. In the northwest region of the YRB, which has a dry climate, the amount of potential evapotranspiration always exceeds the precipitation. We argue that the Gaussian function provides a quantitative conceptual framework for accurate assessment of regional water supply and energy availability and offers a penetrating insight into hydrometeorology.


2010 ◽  
Vol 146-147 ◽  
pp. 495-498
Author(s):  
Shou Hui Chen ◽  
Hong Qin Yu

The tensile performance of the woven membrane materials shows three characters: nonlinear, anisotropic and non-elastic. Besides, when suffering from the bi-axial loads, the tensile property of the woven membrane material is more complicated. These features make the analysis of the tensile performance of woven membrane materials more difficult. The analysis methods including the elastic matrix method, the mathematical function method, and the mechanical model method have been discussed in details.


1989 ◽  
Vol 32 (3) ◽  
pp. 681-687 ◽  
Author(s):  
C. Formby ◽  
B. Albritton ◽  
I. M. Rivera

We describe preliminary attempts to fit a mathematical function to the slow-component eye velocity (SCV) over the time course of caloric-induced nystagmus. Initially, we consider a Weibull equation with three parameters. These parameters are estimated by a least-squares procedure to fit digitized SCV data. We present examples of SCV data and fitted curves to show how adjustments in the parameters of the model affect the fitted curve. The best fitting parameters are presented for curves fit to 120 warm caloric responses. The fitting parameters and the efficacy of the fitted curves are compared before and after the SCV data were smoothed to reduce response variability. We also consider a more flexible four-parameter Weibull equation that, for 98% of the smoothed caloric responses, yields fits that describe the data more precisely than a line through the mean. Finally, we consider advantages and problems in fitting the Weibull function to caloric data.


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