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| Titel |
An analysis of the daily precipitation variability in the Himalayan orogen using a statistical parameterisation and its potential in driving landscape evolution models with stochastic climatic forcing |
| VerfasserIn |
Eric Deal, Jean Braun |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250108664
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| Publikation (Nr.) |
 EGU/EGU2015-8428.pdf |
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| Zusammenfassung |
| A current challenge in landscape evolution modelling is to integrate realistic precipitation
patterns and behaviour into longterm fluvial erosion models. The effect of precipitation on
fluvial erosion can be subtle as well as nonlinear, implying that changes in climate (e.g.
precipitation magnitude or storminess) may have unexpected outcomes in terms of erosion
rates. For example Tucker and Bras (2000) show theoretically that changes in the variability
of precipitation (storminess) alone can influence erosion rate across a landscape. To
complicate the situation further, topography, ultimately driven by tectonic uplift but shaped
by erosion, has a major influence on the distribution and style of precipitation. Therefore, in
order to untangle the coupling between climate, erosion and tectonics in an actively uplifting
orogen where fluvial erosion is dominant it is important to understand how the ’rain
dial’ used in a landscape evolution model (LEM) corresponds to real precipitation
patterns.
One issue with the parameterisation of rainfall for use in an LEM is the difference
between the timescales for precipitation (≈¤ 1 year) and landscape evolution (> 103
years). As a result, precipitation patterns must be upscaled before being integrated into a
model. The relevant question then becomes: What is the most appropriate measure of
precipitation on a millennial timescale? Previous work (Tucker and Bras, 2000; Lague, 2005)
has shown that precipitation can be properly upscaled by taking into account its variable
nature, along with its average magnitude. This captures the relative size and frequency of
extreme events, ensuring a more accurate characterisation of the integrated effects of
precipitation on erosion over long periods of time. In light of this work, we present a
statistical parameterisation that accurately models the mean and daily variability of ground
based (APHRODITE) and remotely sensed (TRMM) precipitation data in the Himalayan
orogen with only a few parameters. We also demonstrate over what spatial and temporal
scales this parameterisation applies and is stable. Applying the parameterisation over the
Himalayan orogen reveals large-scale strike-perpendicular gradients in precipitation
variability in addition to the long observed strike-perpendicular gradient in precipitation
magnitude. This observation, combined with the theoretical work mentioned above,
suggests that variability is an integral part of the interaction between climate and
erosion.
References
Bras, R. L., & Tucker, G. E. (2000). A stochastic approach to modeling the role of rainfall
variability in drainage
basin evolution. Water Resources Research, 36(7), 1953-1964. doi:10.1029/2000WR900065
Lague, D. (2005). Discharge, discharge variability, and the bedrock channel profile.
Journal of Geophysical Research, 110(F4), F04006. doi:10.1029/2004JF000259 |
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