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| Titel |
Assimilating soil moisture into an Earth System Model |
| VerfasserIn |
Tobias Stacke, Stefan Hagemann |
| Konferenz |
EGU General Assembly 2017
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250148843
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| Publikation (Nr.) |
 EGU/EGU2017-13136.pdf |
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| Zusammenfassung |
| Several modelling studies reported potential impacts of soil moisture anomalies on regional
climate. In particular for short prediction periods, perturbations of the soil moisture state may
result in significant alteration of surface temperature in the following season. However, it is
not clear yet whether or not soil moisture anomalies affect climate also on larger temporal
and spatial scales.
In an earlier study, we showed that soil moisture anomalies can persist for several seasons
in the deeper soil layers of a land surface model. Additionally, those anomalies can influence
root zone moisture, in particular during explicitly dry or wet periods. Thus, one prerequisite
for predictability, namely the existence of long term memory, is evident for simulated soil
moisture and might be exploited to improve climate predictions. The second prerequisite is
the sensitivity of the climate system to soil moisture. In order to investigate this sensitivity for
decadal simulations, we implemented a soil moisture assimilation scheme into the
Max-Planck Institute for Meteorology’s Earth System Model (MPI-ESM). The assimilation
scheme is based on a simple nudging algorithm and updates the surface soil moisture state
once per day.
In our experiments, the MPI-ESM is used which includes model components for the
interactive simulation of atmosphere, land and ocean. Artificial assimilation data is created
from a control simulation to nudge the MPI-ESM towards predominantly dry and wet states.
First analyses are focused on the impact of the assimilation on land surface variables and
reveal distinct differences in the long-term mean values between wet and dry state
simulations. Precipitation, evapotranspiration and runoff are larger in the wet state
compared to the dry state, resulting in an increased moisture transport from the
land to atmosphere and ocean. Consequently, surface temperatures are lower in
the wet state simulations by more than one Kelvin. In terms of spatial pattern, the
largest differences between both simulations are seen for continental areas, while
regions with a maritime climate are least sensitive to soil moisture assimilation. |
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