On the temporal upscaling of evapotranspiration from instantaneous remote sensing measurements to 8-day mean daily-sums
Introduction
Evapotranspiration (E) is a major component of the terrestrial hydrological cycle (ca. 60% of land precipitation) (Trenberth et al., 2007). It controls land-atmosphere feedbacks via modulating land surface energy budget, and constitutes an important source of water vapor to the atmosphere (Raupach, 1998). In turn, atmospheric water vapor is the most significant greenhouse gas and thus plays a fundamental role in weather and climate (Held and Soden, 2000, IPCC, 2007). Understanding E is important for socio-economic reasons, such as regulating available water for human use (Brauman et al., 2007). Thus, there have been diverse efforts to monitor E regularly in a regional scale using satellite remote sensing imagery (Anderson et al., 2008, Diak et al., 2004, Nishida et al., 2003).
The applicability of remote sensing-based estimates of E is hampered because satellites have limited temporal coverage, resulting in snapshots of E at a particular point in space and time. Thus, it is a challenge to compare E estimates from different sites that are taken at different times of the day. For practical purposes, time-integrated E is more meaningful for managing water resources and for comparison with accumulated precipitation (Baldocchi and Ryu, 2011). An 8-day mean daily sum is selected in this study as the 8-day period corresponds to the cycle of MODIS global coverage (Masuoka et al., 1998).
A common approach to estimate time-integrated E is to assume that the evaporative fraction, EF, (the ratio of latent heat flux, λE, to available energy, A, which is taken to be equal to the net radiation (Rn) minus the soil heat flux (G)) is constant during daytime, so daytime total E can be estimated by multiplying an instantaneous EF and daytime integrated A (Brutsaert and Sugita, 1992, Crago, 1996, Jackson et al., 1983, Verma et al., 1992). Anderson et al. (2007) further developed this idea by coupling a planetary boundary layer model with two snapshots in the morning from Geostationary Operational Environmental Satellites (GOES) for calculating instantaneous λE and EF, and finally extrapolated these values to a daily scale using hourly A derived from GOES. However, the constant EF assumption was developed in homogeneous grasslands or crops. In addition, one study reported that EF varies considerably during daytime depending on soil moisture status and leaf area index (Leuning et al., 2004). Satellite-based estimation of instantaneous soil heat flux is still a challenge, in particular for open canopies. In fact, the constant EF approach was identified as a major source of uncertainty in the remote sensing-based E estimates (Ferguson et al., 2010).
An alternative approach includes developing a constant linear regression equation between mid-day flux values and the daily mean flux values using flux tower data. For example, Sims et al. (2005) tested a linear regression between a single-hour extraction of gross primary productivity (GPP) to a mean value of 24-h GPP for a 8-day period using flux tower data. These authors found a consistent linear regression that held across a range of plant functional types and times of year, based on 8 eddy covariance flux towers within the United States and Canada. However, it is unclear if the constant scaling factor holds in other latitudes and longitudes or if the technique is valid for E.
We report that both the constant EF and the constant scaling factor approaches do not provide robust upscaled estimates. Thus, developing an alternative scheme is warranted. We demonstrate that the averaged ratio of a half-hourly-sum of potential solar radiation (RgPOT, extraterrestrial irradiance on a plane parallel to the Earth's surface) to the daily-sum of RgPOT over a 8-day period can be used to upscale instantaneous λE(t) to a 8-day mean daily sum λE. To test the efficacy of the scheme, we used data from 34 eddy covariance flux tower across 7 plant functional types spanning the range from boreal to tropical climatic zones. The scientific questions for this study include: (1) How does the upscaling factor from this new scheme vary with plant functional types and climatic zones?, (2) Can the upscaling scheme developed from the half-hourly flux tower data be used for instantaneous satellite data? and (3) Can the upscaling scheme be applied for estimation of other biological and environmental variables such as gross primary productivity (GPP) and solar irradiance?
Section snippets
Flux tower sites description and data processing
We analyzed λE data from 34 sites including 7 plant functional types (PFTs) ranging from boreal to tropical climatic zones extracted from LaThuile 2007 FLUXNET dataset v.2 (www.fluxdata.org) (Table 1). We selected at least three sites for each PFT which showed data gaps less than 30 days per year, and selected one year of measurements per site that was represented by a minimum data gaps over the available years. Data gaps were filled using the marginal distribution sampling method in an
Testing the constant evaporative fraction approach
We tested the constant EF approach using the flux tower data (Fig. 1). We randomly selected a half-hourly E data in the morning (10:00–12:00 hh) or in the afternoon (12:00–14:00 hh) to follow satellite overpass in the morning (Fig. 1a and c) or afternoon (Fig. 1b and d), upscaled to daily E using the constant EF, then averaged over 8-day intervals for all 34 sites. On daily E, we found that the constant EF approach caused −13% relative bias (the ratio of bias to the mean) with 49% relative root
Summary and conclusions
We presented a temporal upscaling scheme for E from instantaneous measurements near mid-day to 8-day mean values by using the ratio of half-hourly RgPOT to the daily sum RgPOT (Eq. (3)). Based on the data from 34 flux tower sites, we found that the upscaled 8-day mean daily E showed a clear linear relation (r2 = 0.97), good agreement (relative RMSE = 14%) and little bias (−2.7%) with the observed 8-day daily E using flux tower data only. At the individual site level, the upscaling-scheme derived E
Acknowledgements
This work used eddy covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux (U.S. Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program (DE-FG02-04ER63917 and DE-FG02-04ER63911)), AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada (supported by CFCAS, NSERC, BIOCAP, Environment Canada, and NRCan), GreenGrass, KoFlux (supported by Sustainable Water Resources Center of
References (81)
- et al.
The carbon budget of newly established temperate grassland depends on management intensity
Agric. Ecosyst. Environ.
(2007) - et al.
A two-source time-integrated model for estimating surface fluxes using thermal infrared remote sensing
Remote Sens. Environ.
(1997) - et al.
A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales
Remote Sens. Environ.
(2008) - et al.
Long term carbon dioxide exchange above a mixed forest in the Belgian Ardennes
Agric. For. Meteorol.
(2001) - et al.
How plant functional-type, weather, seasonal drought, and soil physical properties alter water and energy fluxes of an oak-grass savanna and an annual grassland
Agric. For. Meteorol.
(2004) - et al.
Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer
Agric. For. Meteorol.
(1991) Conservation and variability of the evaporative fraction during the daytime
J. Hydrol.
(1996)- et al.
The carbon uptake of a mid latitude pine forest growing on sandy soil
Agric. For. Meteorol.
(2002) - et al.
Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites
Remote Sens. Environ.
(2008) - et al.
Effects of climate variability on the carbon dioxide, water, and sensible heat fluxes above a ponderosa pine plantation in the Sierra Nevada (CA)
Agric. For. Meteorol.
(2000)
Estimation of daily evapotranspiration from one time-of-day measurements
Agric. Water Manage.
A coupled 1-D atmosphere and 3-D canopy radiative transfer model for canopy reflectance, light environment, and photosynthesis simulation in a heterogeneous landscape
Remote Sens. Environ.
Impact of changing soil moisture distribution on net ecosystem productivity of a boreal aspen forest during and following drought
Agric. For. Meteorol.
Carbon and water fluxes over a temperate Eucalyptus forest and a tropical wet/dry savanna in Australia: measurements and comparison with MODIS remote sensing estimates
Agric. For. Meteorol.
The interrelationship and characteristic distribution of direct, diffuse and total solar radiation
Solar Energy
Carbon dioxide and energy fluxes from a boreal mixedwood forest ecosystem in Ontario, Canada
Agric. For. Meteorol.
An assessment of storage terms in the surface energy balance of maize and soybean
Agric. For. Meteorol.
The astronomical-almanacs algorithm for approximate solar position (1950–2050)
Solar Energy
Nocturnal evapotranspiration in eddy-covariance records from three co-located ecosystems in the Southeastern US: implications for annual fluxes
Agric. For. Meteorol.
Applications of solutions to non-linear energy budget equations
Agric. For. Meteorol.
Expanding global mapping of the foliage clumping index with multi-angular POLDER three measurements: evaluation and topographic compensation
ISPRS-J. Photogramm. Remote Sens.
Evaluation of land surface radiation balance derived from Moderate Resolution Imaging Spectrometer (MODIS) over complex terrain and heterogeneous landscape on clear sky days
Agric. For. Meteorol.
On the correct estimation of effective leaf area index: does it reveal information on clumping effects?
Agric. For. Meteorol.
How to quantify tree leaf area index in a heterogeneous savanna ecosystem: a multi-instrument and multi-model approach
Agric. For. Meteorol.
Seasonal variation of carbon dioxide exchange in rice paddy field in Japan
Agric. For. Meteorol.
First operational BRDF, albedo nadir reflectance products from MODIS
Remote Sens. Environ.
Exploring the functional significance of forest diversity: a new long-term experiment with temperate tree species (BIOTREE)
Perspect. Plant Ecol. Evolut. Syst.
Midday values of gross CO2 flux and light use efficiency during satellite overpasses can be used to directly estimate eight-day mean flux
Agric. For. Meteorol.
Environmental control of net ecosystem CO2 exchange in a treed, moderately rich fen in northern Alberta
Agric. For. Meteorol.
Annual carbon dioxide exchange in irrigated and rainfed maize-based agroecosystems
Agric. For. Meteorol.
New refinements and validation of the MODIS land-surface temperature/emissivity products
Remote Sens. Environ.
Seasonal and annual variation of carbon exchange in an evergreen Mediterranean forest in southern France
Global Change Biol.
A climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing. 1. Model formulation
J. Geophys. Res.
Forest and agricultural land-use-dependent CO2 exchange in Thuringia, Germany
Global Change Biol.
A synthesis of forest evaporation fluxes from days to years as measured with eddy covariance
Savanna fires and their impact on net ecosystem productivity in North Australia
Global Change Biol.
The nature and value of ecosystem services: an overview highlighting hydrologic services
Annu. Rev. Environ. Resour.
Application of self-preservation in the diurnal evolution of the surface-energy budget to determine daily evaporation
J. Geophys. Res.
Nighttime transpiration in woody plants from contrasting ecosystems
Tree Physiol.
Simple scaling of photosynthesis from leaves to canopies without the errors of big-leaf models
Plant Cell Environ.
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