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| Titel |
Bayesian climate projection for the northern subpolar land based on ensemble of global climate models forced by SRES A1B scenario |
| VerfasserIn |
Alexey V. Eliseev, Maxim M. Arzhanov, Igor I. Mokhov |
| 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 |
250046722
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| Zusammenfassung |
| Contemporary global climate models (GCMs) still markedly disagree on magnitude of
climate changes, in particular, in middle to subpolar latitudes over Eurasia and North
America. In this work, a GCM–ensemble based climate projection is performed for the
pan–Arctic in the 21st century. We consider an atmospheric output of the SRES
A1B simulations with ten CMIP3 global climate models. To assess the change
of soil state in the pan–Arctic regions, off–line simulations are performed with a
model for thermal and hydrological processes in soil developed at the A.M.Obukhov
Institute of Atmospheric Physics, Russian Academy of Sciences (IAP RAS). The
IAP RAS soil model is forced by output of above–mentioned simulations with
global climate models. Ensemble mean and ensemble standard deviation for any
variable are calculated by using Bayesian averaging which allows to enhance a
contribution of more realistic models and diminish that of less realistic models. The
Bayesian weights for each model are calculated based on their performance for the
present–day surface air temperature (SAT) and permafrost distributions, and for
SAT trend during the 20th century. It is obtained that the models basically agree
on statistically significant warming in the northernmost regions of Eurasia and
North America with typical values from 3 K to 6 K for annual mean and from
4 K to 12 K for winter. This warming is very robust within the ensemble because
respective Bayesian intermodel standard deviations are typically below 0.5 K in the
pan–Arctic regions. Ensemble mean soil moisture content depletes in subpolar
latitudes and increases in middle latitudes of these continents. However, Bayesian
intermodel standard deviation is comparable in magnitude to change in ensemble
mean soil water content. As a result, changes in soil moisture content during the
whole 21st century for this ensemble are interpreted as statistically non–robust.
The models agree on drastic permafrost degradation during the 21st century. The
area underlain by near–surface permafrost decreases from the contemporary value
16 ± 3 mln km2 to 8 ± 3 mln km2. The latter results in development of risk for
geocryological subsidence. This risk is largest in the southern and western parts of
Siberia, in Tibet and in the band stretched from Alaska to the Labrador Peninsula. |
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