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<big><font color="#3366ff">PhD defense on October 16</font></big><br>
<br>
<b>Name</b><br>
Marie Kapsch<br>
Department of Meteorology, Stockholm University, Sweden<br>
<br>
<b>Title</b><br>
The atmospheric contribution to Arctic sea-ice variability<br>
<br>
<b>Time and place</b><br>
Friday 16 October 2015, 10.00<br>
Nordenskiöldsalen, Geo building, U house, floor 3<br>
<br>
<b>Abstract</b><br>
The Arctic sea-ice cover plays an important role for the global
climate system. Sea ice and the overlying snow cover reflect up to
eight times more of the solar radiation than the underlying ocean.
Hence, they are important for the global energy budget, and changes
in the sea-ice cover can have a large impact on the Arctic climate
and beyond. In the past 36 years the ice cover reduced
significantly. The largest decline is observed in September, with a
rate of more than 12% per decade. The negative trend is accompanied
by large inter-annual sea-ice variability: in September the sea-ice
extent varies by up to 27% between years. The processes controlling
the large variability are not well understood. In this thesis the
atmospheric contribution to the inter-annual sea-ice variability is
explored. The focus is specifically on the thermodynamical effects:
processes that are associated with a temperature change of the ice
cover and sea-ice melt. Atmospheric reanalysis data are used to
identify key processes, while experiments with a state-of-the-art
climate model are conducted to understand their relevance throughout
different seasons. It is found that in years with a very low
September sea-ice extent more heat and moisture is transported in
spring into the area that shows the largest ice variability. The
increased transport is often associated with similar atmospheric
circulation patterns. Increased heat and moisture over the Arctic
result in positive anomalies of water vapor and clouds. These alter
the amount of downward radiation at the surface: positive cloud
anomalies allow for more longwave radiation and less shortwave
radiation. In spring, when the solar inclination is small, positive
cloud anomalies result in an increased surface warming and an
earlier seasonal melt onset. This reduces the ice cover early in the
season and allows for an increased absorption of solar radiation by
the surface during summer, which further accelerates the ice melt.
The modeling experiments indicate that cloud anomalies of similar
magnitude during other seasons than spring would likely not result
in below-average September sea ice. Based on these results a simple
statistical sea-ice prediction model is designed, that only takes
into account the downward longwave radiation anomalies or variables
associated with it. Predictive skills are similar to those of more
complex models, emphasizing the importance of the spring atmosphere
for the annual sea-ice evolution. <br>
<br>
<b>Welcome!</b><br>
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