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| Titel |
The drivers of ET sensitivity for different climate zones |
| VerfasserIn |
Danlu Guo, Seth Westra, Holger Maier |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250130725
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| Publikation (Nr.) |
 EGU/EGU2016-11022.pdf |
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| Zusammenfassung |
| Assessing evapotranspiration (ET) sensitivity is critical to understand the impact of different
climate variables for ET estimation under changing climate. This study assesses the ET
sensitivity across a large number of plausible climate conditions as a function of both the
baseline hydroclimatic conditions and the ET model choice. We first define the plausible
ranges of change for each variable based on available climate projections, over which the ET
sensitivity will be estimated. We investigate the impact of different hydro-climatic conditions
on the sensitivity of the Penman-Monteith PET estimates with 30 study sites across Australia.
By perturbing each ET-related climate variable individually within their plausible range, we
observe that the baseline conditions, especially T , RH, Rs and PET, play important roles on
the ET sensitivity. Importantly, humid temperate catchments show higher sensitivity to
climate changes while catchments within the dry and hot regions tend to maintain a
more stable PET in the future. PET also shows higher sensitivity to changes in
climate variables under energy-limited conditions, which can mean an elevated
water loss through increasing actual ET and can have substantial implications on
water balance under changing climates. To allow comparison of ET sensitivities
across 11 alternative ET models with different input data requirements, we then
followed the global sensitivity analysis in which the ET-related climate variables are
perturbed jointly. From different ET models, we obtained contrasting ranges of ET
estimates and identified different key climate variables that drive the estimates, which
can be explained by their different process representations and assumptions. The
results highlighted the importance of ensemble modelling for enhancing our overall
understanding of the expected ranges of ET estimates under future climate changes. |
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