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| Titel |
Global Scale Evapotranspiration: Comparison and Sensitivity Analysis of three Retrieval Algorithms |
| VerfasserIn |
Raghuveer Vinukollu, Eric Wood |
| Konferenz |
EGU General Assembly 2011
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 13 (2011) |
| Datensatznummer |
250053196
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| Zusammenfassung |
| Quantifying reliable estimates of evapotranspiration (ET) over land is an important part of the
larger effort to develop long-term Earth System Data Records (ESDRs) for the major
components (fluxes and storages) of the terrestrial water cycle and is a particular focus of the
GEWEX Landflux project. Recent progress has involved the development of global ET
datasets using a variety of sources: objective interpolation of Fluxnet tower data, land surface
model estimates and remote sensing approaches that allows for the evaluation of
uncertainties across these datasets. However, uncertainties in the inputs along with the
surface resistance parameterizations in the different models result in a wide range
of estimates, thus leading one to question the confidence levels of individual ET
datasets.
In the current study, a long-term global ET dataset has been developed for the period
1984-2007 using three process-based, remote sensing models forced using a combination of
input from remote sensing and reanalysis models. Radiation data was obtained from the
Surface Radiation Budget (SRB) project; meteorology from the MERRA reanalysis output;
and the vegetation distribution using data from AVHRR GIMMS data. The models
considered are a modified Penman-Monteith (PM-Mu), Priestley-Taylor (PT-Fi), and the
Surface Energy Balance System (SEBS). The three models adjust the surface resistances
using aerodynamic principles or provide ecophysiological constraints to account for
changing environmental factors; thus scaling ET from its potential value to the actual
estimate. Initial results show considerable differences among the model estimates.
Uncertainties in the input forcings, coupled with the sensitivity of the algorithms
to input (forcing) uncertainty, results in significant uncertainty in the derived ET
products. Understanding the sensitivity of the algorithms is a critical need. For
example, for air temperature, a 1Ë bias in Tair leads to differences of up to 50
W/m2 in latent heat flux (LE) on the annual scale. The presentation focuses on three
aspects: (1) Evaluation of the input forcings and a check of consistency across the
variables and time period considered in this study, (2) Inter-comparisons of the surface
resistance parameterizations and estimates across the three process models, and their
consistency, and (3) Sensitivity analysis of the three models to the various input forcings. |
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