Internal variability of sea ice and surface air temperature in a warming Arctic climate
The Arctic is one of the regions most vulnerable to climate change. Its climate is governed by self-reinforcing feedback mechanisms that amplify temperature variability and trends. As a result, Arctic surface temperatures have increased almost four times faster than the global average in recent deca...
| Main Author: | |
|---|---|
| Format: | Doctoral or Postdoctoral Thesis |
| Language: | English |
| Published: |
Universität Hamburg
2023
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/21.11116/0000-000C-8BA9-9 http://hdl.handle.net/21.11116/0000-000C-91A3-7 |
| Summary: | The Arctic is one of the regions most vulnerable to climate change. Its climate is governed by self-reinforcing feedback mechanisms that amplify temperature variability and trends. As a result, Arctic surface temperatures have increased almost four times faster than the global average in recent decades and, alongside, the Arctic sea ice is declining. Not only the trends but also the variability of these two key variables are closely linked. In this dissertation, I examine two aspects of the internal variability of sea ice and surface air temperature in a warming Arctic climate using the powerful tool of large ensemble climate simulations. The first part of this thesis focuses on the persistence/memory of Arctic sea ice on seasonal to inter-annual timescales. This is relevant for sea-ice predictions, which are of growing socio-economic interest due to the retreat of sea ice in the warming Arctic. Previous studies have identified a substantial gap between the operational forecast skill and model-based estimates of the potential predictability of Arctic sea ice. By analyzing lagged correlations of sea-ice area anomalies in large model ensembles and multiple observational products, I show that climate models significantly overestimate the memory of pan-Arctic sea-ice area from the summer months into the following year, which cannot be explained by internal variability. I further show that the overestimation arises from how the seasonal ice zone "remembers" preceding summer sea-ice area anomalies. My results suggest that there is likely a misrepresentation of processes related to the memory of sea ice in climate models, which could explain part of the gap between potential and operational forecast skill of Arctic sea-ice area. The second part of this thesis addresses the response of daily Arctic surface air temperature to global warming. While the average temperature is rapidly increasing, previous studies have shown that the variability and the amplitude of the seasonal cycle of Arctic surface air temperature are ... |
|---|