 |
| Titel |
Evaluation of the simulation of Arctic sea ice in the CMIP5 climate models |
| VerfasserIn |
Bo Qiu, Lujun Zhang, Weidong Guo |
| Konferenz |
EGU General Assembly 2014
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250088467
|
| Publikation (Nr.) |
 EGU/EGU2014-2571.pdf |
|
|
|
|
|
| Zusammenfassung |
| Sea ice is a significant component in the Earth’s climate system. Coupled climate system
models are important tools for the study of sea ice, its internal processes, interaction with
other components, and projection of future changes. This paper evaluates the model’s
simulation capability in Arctic sea ice for the fifth phase of the Coupled Model
Inter-comparison Project (CMIP5) models that were run with historical forcing compared
with satellite-derived observations for 1979–2005.
The results show as following: Arctic sea ice spatial distribution is well captured by most
of the models. The majority of models is simulating annual cycles that are phased at least
approximately correctly, but the magnitude of sea ice extent differs from that observed in over
the last 30 years. Many of the models have a negative bias compared to the satellite
data in late summer. From 1979 to 2005, the largest sea ice extent decreases are
observed during July–September, with the greatest monthly decrease in September
(-0.59x106km2dec-1). The Arctic sea ice simulated by the models shows a trend of
decrease, but has very large differences in magnitude. The Arctic sea ice extent simulated by
the models shows a decrease in each month, with the smallest multi-model mean monthly
decline of -0.22x106km2dec-1 in June and the greatest of -0.53x106km2dec-1 in
September.
The Arctic sea ice extent reduces 1.02x106km2 in response to 1.0° C increase of surface
air temperature, as the uncertainties of the climate models, the Arctic sea ice extent of models
have a decrease of ice range from 0.62x106 to 1.68x106km2. Meanwhile, the trends and
sensitivities vary largely across ensemble members in the same model, indicating
impacts of initial condition on evolution of feedback strength with model integrations. |
|
|
|
|
|
|