Upscaling latent heat flux for thermal remote sensing studies: Comparison of alternative approaches and correction of bias

Niel, Tom Van; McVicar, Tim R.; Roderick, Michael L.; Dijk, Albert I. J. M. van; Beringer, Jason; Hutley, Lindsay B.; Gorsel, Eva van

doi:10.1016/j.jhydrol.2012.08.005

Cited by 71 publications

(76 citation statements)

References 36 publications

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“…For example, both Gentine et al (2007) and Hoedjes et al (2008) showed that the self-preservation of evaporative fraction is sensitive to soil moisture conditions and fractional vegetation cover. 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).…”

Section: Introductionmentioning

confidence: 91%

“…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.…”

Section: Introductionmentioning

confidence: 91%

“…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.…”

Section: Introductionmentioning

confidence: 99%

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

Alfieri

Anderson

Kustas

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. Accurate spatially distributed estimates of actual evapotranspiration (ET) derived from remotely sensed data are critical to a broad range of practical and operational applications. However, due to lengthy return intervals and cloud cover, data acquisition is not continuous over time, particularly for satellite sensors operating at medium ( ∼ 100 m) or finer resolutions. To fill the data gaps between clear-sky data acquisitions, interpolation methods that take advantage of the relationship between ET and other environmental properties that can be continuously monitored are often used. This study sought to evaluate the accuracy of this approach, which is commonly referred to as temporal upscaling, as a function of satellite revisit interval. Using data collected at 20 Ameriflux sites distributed throughout the contiguous United States and representing four distinct land cover types (cropland, grassland, forest, and open-canopy) as a proxy for perfect retrievals on satellite overpass dates, this study assesses daily ET estimates derived using five different reference quantities (incident solar radiation, net radiation, available energy, reference ET, and equilibrium latent heat flux) and three different interpolation methods (linear, cubic spline, and Hermite spline). Not only did the analyses find that the temporal autocorrelation, i.e., persistence, of all of the reference quantities was short, it also found that those land cover types with the greatest ET exhibited the least persistence. This carries over to the error associated with both the various scaled quantities and flux estimates. In terms of both the root mean square error (RMSE) and mean absolute error (MAE), the errors increased rapidly with increasing return interval following a logarithmic relationship. Again, those land cover types with the greatest ET showed the largest errors. Moreover, using a threshold of 20 % relative error, this study indicates that a return interval of no more than 5 days is necessary for accurate daily ET estimates. It also found that the spline interpolation methods performed erratically for long return intervals and should be avoided.

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Section: Introductionmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Alfieri

Anderson

Kustas

et al. 2017

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…However, as pointed out by Van Niel et al (2012), the assumption of clearsky conditions during the whole day is not always assured for remote sensing applications, for which only the specific timeof-day of the satellite overpass must be clear. Hence, analyses that do not assess errors associated with all-sky (clear and cloudy) conditions have limited applicability for operational remote sensing applications.…”

Section: Published By Copernicus Publications On Behalf Of the Europementioning

confidence: 99%

“…Both methods have demonstrated value for upscaling specific time-of-day ET estimates to daily, 8-day, and monthly scales (Ryu et al, 2012;Van Niel et al, 2012). In addition, specifically for applications over agricultural areas, Trezza (2002) introduced the use of standardized reference evapotranspiration (ET o ) as an upscaling variable, based on the assumption that ET o incorporates most of the main meteorological factors that influence the evaporative process.…”

Section: Published By Copernicus Publications On Behalf Of the Europementioning

confidence: 99%

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

Cammalleri

Anderson

Kustas

2014

Hydrol. Earth Syst. Sci.

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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.

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Temporal upscaling of instantaneous evapotranspiration on clear‐sky days using the constant reference evaporative fraction method with fixed or variable surface resistances at two cropland sites

Tang

Sun

et al. 2017

JGR Atmospheres

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Surface evapotranspiration (ET) is an important component of water and energy in land and atmospheric systems. This paper investigated whether using variable surface resistances in the reference ET estimates from the full‐form Penman‐Monteith (PM) equation could improve the upscaled daily ET estimates in the constant reference evaporative fraction (EFr, the ratio of actual to reference grass/alfalfa ET) method on clear‐sky days using ground‐based measurements. Half‐hourly near‐surface meteorological variables and eddy covariance (EC) system‐measured latent heat flux data on clear‐sky days were collected at two sites with different climatic conditions, namely, the subhumid Yucheng station in northern China and the arid Yingke site in northwestern China and were used as the model input and ground‐truth, respectively. The results showed that using the Food and Agriculture Organization (FAO)‐PM equation, the American Society of Civil Engineers‐PM equation, and the full‐form PM equation to estimate the reference ET in the constant EFr method produced progressively smaller upscaled daily ET at a given time from midmorning to midafternoon. Using all three PM equations produced the best results at noon at both sites regardless of whether the energy imbalance of the EC measurements was closed. When the EC measurements were not corrected for energy imbalance, using variable surface resistance in the full‐form PM equation could improve the ET upscaling in the midafternoon, but worse results may occur in the midmorning to noon. Site‐to‐site and time‐to‐time variations were found in the performances of a given PM equation (with fixed or variable surface resistances) before and after the energy imbalance was closed.

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Upscaling latent heat flux for thermal remote sensing studies: Comparison of alternative approaches and correction of bias

Cited by 71 publications

References 36 publications

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

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

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

Temporal upscaling of instantaneous evapotranspiration on clear‐sky days using the constant reference evaporative fraction method with fixed or variable surface resistances at two cropland sites

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