Upscaling of evapotranspiration fluxes from instantaneous to daytime scales for thermal remote sensing applications

Abstract

Abstract. Four upscaling methods for estimating daytime actual evapotranspiration (ET) from single time-of-day snapshots, as commonly retrieved using remote sensing, were compared. These methods assume self-preservation of the ratio between ET and a given reference variable over the daytime hours. The analysis was performed using eddy covariance data collected at 12 AmeriFlux towers, sampling a fairly wide range in climatic and land cover conditions. The choice of energy budget closure method significantly impacted performance using different scaling methodologies. Therefore, a statistical evaluation approach was adopted to better account for the inherent uncertainty in ET fluxes using eddy covariance technique. Overall, this approach suggested that at-surface solar radiation was the most robust reference variable amongst those tested, due to high accuracy of upscaled fluxes and absence of systematic biases. Top-of-atmosphere irradiance was also tested and proved to be reliable under near clear-sky conditions, but tended to overestimate the observed daytime ET during cloudy days. Use of reference ET as a scaling flux yielded higher bias than the solar radiation method, although resulting errors showed similar lack of seasonal dependence. Finally, the commonly used evaporative fraction method yielded satisfactory results only in summer months, July and August, and tended to underestimate the observations in the fall/winter seasons from November to January at the flux sites studied. In general, the proposed methodology clearly showed the added value of an intercomparison of different upscaling methods under scenarios that account for the uncertainty in eddy covariance flux measurements due to closure errors.

Mapping evapotranspiration with high-resolution aircraft imagery over vineyards using one- and two-source modeling schemes

“…The reference variables typically used include A , standardized reference ET (Allen et al, 2007), solar radiation (Zhang and Lemeur, 1995), top-of-atmosphere irradiance (Ryu et al, 2012). Cammalleri et al (2014) compared the performances of the scale factors derived by these four reference valuables in ET upscaling at 12 AmeriFlux towers, drawing a conclusion that solar radiation was the most robust reference variable for operational applications, particularly in areas where the modeled G component of A may have high uncertainties. However, the applicability of the various reference variables may differ within areas, since the energy budget is significantly influenced by surface characteristics such as soil moisture, vegetation condition (Crago, 1996).…”

“…In this study, EF (defined as the ratio of LE to A or H + LE) is assumed constant during the daytime period when solar radiation is larger than 0. The extrapolation to daytime ET using a constant EF is reasonable to apply during the main growing season period (Cammalleri et al, 2014). The ratio of instantaneous to daytime A at the flux tower site is used to obtain daytime A for each pixel within the study area by assuming that the A ratio between pixel and flux tower is constant during the daytime.…”

Remotely sensed land-surface energy fluxes at sub-field scale in heterogeneous agricultural landscape and coniferous plantation

“…Some recent studies suggest that EF remains stable, especially around noon hours in cloud-free condition, in a wide range of ecosystems (Peng et al, 2013) while others have proposed the replacement of EF with the ratio of LE to incoming solar radiation at ground level (Cammalleri et al, 2014). Therefore in this study we evaluate three approaches to estimate what we term the constant ratio (CR): EF, ratio of LE to incoming solar radiation, LE/R s, in , and the ratio of H to incoming solar radiation, H /R s, in .…”

Effect of the revisit interval and temporal upscaling methods on the accuracy of remotely sensed evapotranspiration estimates

“…Similarly, Lhomme and Elguero (1999) and later Van Niel et al (2012) showed that the degree of self-preservation can be influenced by cloud cover. As such, the assumption of clear-sky conditions is a significant potential source of error in the ET estimates that must be considered when utilizing or evaluating temporally upscaled moisture flux data (Van Niel et al, 2012;Peng et al, 2013;Cammalleri et al, 2014). Other studies have focused on using a quantity derived from the local meteorological conditions as χ because it would consider many of the meteorological factors that influence the moisture flux.…”

“…Chief among these is the infrequent acquisition of the medium to high-resolution imagery needed as input for remote sensing-based models to determine ET. This infrequent acquisition of imagery is due to both lengthy return intervals and the presence of cloud cover (Ryu et al, 2012;Van Niel et al, 2012;Cammalleri et al, 2013). To provide temporally continuous ET estimates, the moisture flux during the period between data acquisitions is often estimated using an interpolation technique commonly referred to as temporal upscaling.…”