Abstract
Net radiation is a key component of the energy balance, whose estimation accuracy has an impact on energy flux estimates from satellite data. In typical remote sensing evapotranspiration (ET) algorithms, the outgoing shortwave and longwave components of net radiation are obtained from remote sensing data, while the incoming shortwave (RS) and longwave (RL) components are typically estimated from weather data using empirical equations. This study evaluates the accuracy of empirical equations commonly used in remote sensing ET algorithms for estimating RS and RL radiation. Evaluation is carried out through comparison of estimates and observations at five sites that represent different climatic regions from humid to arid. Results reveal (1) both RS and RL estimates from all evaluated equations well correlate with observations (R2 ≥ 0.92), (2) RS estimating equations tend to overestimate, especially at higher values, (3) RL estimating equations tend to give more biased values in arid and semi-arid regions, (4) a model that parameterizes the diffuse component of radiation using two clearness indices and a simple model that assumes a linear increase of atmospheric transmissivity with elevation give better RS estimates, and (5) mean relative absolute errors in the net radiation (Rn) estimates caused by the use of RS and RL estimating equations varies from 10% to 22%. This study suggests that Rn estimates using recommended incoming radiation estimating equations could improve ET estimates.
Highlights
Net radiation (Rn) is a key component of the energy balance, whose estimation accuracy has an impact on energy flux estimates from remotely sensed data
The diffuse component is parameterized in SW6 using two clearness indices KBo and KDo, with the clearness index for the diffuse component that depends on the clearness index for the direct component and the latter is computed from an empirical turbidity coefficient which is assigned a constant value for clear sky conditions
SW7 is more complex, and it is based on a number of relations that rely on two aerosol optical parameters related to the turbidity coefficient which is assigned a constant value for clear sky conditions
Summary
Net radiation (Rn) is a key component of the energy balance, whose estimation accuracy has an impact on energy flux estimates from remotely sensed data. In typical algorithms that handle remote sensing data, evapotranspiration (ET) is estimated as a residual of Rn after accounting for sensible heat flux (H) and soil heat flux (G) [1,2,3,4]; G is estimated from empirical equations that relate G/Rn to vegetation index, and H is estimated such that the maximum value of H over a “hot” surface does not exceed Rn. Llasat and Snyder reported that 65%–85% of the error in Rn estimation directly propagates to crop-reference ET in the Catalonia region of Spain [5]. The outgoing components ( S and L ) could be directly estimated from remote sensing optical and thermal information of land surface
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