Natural Variability of Arctic and Antarctic Sea Ice : Insight From Pre-industrial CMIP5 Runs
Understanding natural variability of Arctic and Antarctic sea ice is important for explaining and predicting observed sea ice variability. Motivated by this, I undertook this study that analyzes sea ice variability in pre-industrial control runs for a subset of Earth System Models (ESMs) and Climate...
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| Other Authors: | , |
| Format: | Doctoral or Postdoctoral Thesis |
| Language: | English |
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Universität Bremen
2018
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| Online Access: | https://media.suub.uni-bremen.de/handle/elib/1504 https://nbn-resolving.org/urn:nbn:de:gbv:46-00106780-11 |
| Summary: | Understanding natural variability of Arctic and Antarctic sea ice is important for explaining and predicting observed sea ice variability. Motivated by this, I undertook this study that analyzes sea ice variability in pre-industrial control runs for a subset of Earth System Models (ESMs) and Climate Models (CMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5), and the Alfred Wegener Institute Climate Model (AWI-CM). I compare the general characteristics of simulated mean sea ice conditions in the Arctic and Antarctic for the selected models. I find that the main characteristics of Arctic sea ice are better simulated than that of Antarctic sea ice. None of the selected models were able to simulate all of the Antarctic sea ice characteristics properly.Inter-model spread of winter sea ice volume and summer sea ice extent in both hemispheres is large, with the spread exceeding the limits of natural variability. The drivers of the Arctic sea ice minimum in September and the Antarctic sea ice minimum in February are studied using composite analysis. In the Arctic, events of low sea ice extent in September are related to (1) Sea Ice Thickness (SIT) Memory (2) a negative Sea Level Pressure (SLP) and a positive Sea Surface Temperature (SST) anomaly in the Barents Sea in March, (3) the deepening of the Aleutian Low in March with imprints of ENSO and PDO, and (4) a positive SLP anomaly in the Beaufort Sea in July. I also find that events of low September sea ice extent minima tend to cluster in time. I suggest that in addition to low frequency climate variability, clustering of low September sea ice extent events depends on the memory of the Arctic sea ice system provided by SIT and ocean surface heat content. The occurrences of the aforementioned atmospheric patterns are random, in the sense that they are not necessarily taking place in the same years. An important characteristic of the events analyzed is an anomalous thin Arctic sea ice cover in winter that preconditions these late summer events. The ... |
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