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A New Way to Model Sea Ice Thickness

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Sea ice, which is constantly thickening and thinning, plays an important role in the Earth's climate system. We sit down with USGS scientist Dave Douglas to discuss a newly developed modeling approach to estimate sea ice thickness—this is the only model based entirely on historic observations, and it was developed by scientists from the USGS and the Russian Academy of Sciences in Moscow.




Public Domain.


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Jessica Robertson

Hello and welcome to the USGS CoreCast. I'm Jessica Robertson. 

Today we are going to discuss a newly developed modeling approach to estimate sea ice thickness. This is the only model based entirely on historic observations. 

Sea ice, which is constantly thickening and thinning, plays an important role in the Earth's climate system. Understanding these fluctuations of sea ice thickness is important for improving global climate models. 

This new approach to estimate sea ice thickness was developed by scientists with the U.S. Geological Survey and the Russian Academy of Sciences in Moscow. 

Today, I'd like to welcome and introduce you to our guest: USGS scientist David Douglas. He is one of the scientists who helped develop and implement this new model. 

Thank you for joining us today, Dave.


Thank you for the invitation.


So, can you tell us a little bit about this new method and how it works?


Yeah, Jessica. We began by assembling all documented measurements of sea ice thickness that were available from submarine cruises and surface drilling missions. And then we assumed that the thickness of the ice, when it was measured, was an expression of the environmental conditions that the ice had experienced during its recent past. 

So what we did is we followed each of these parcels of ice with known thickness backwards in time for up to 3 years using ice motion data from the National Snow and Ice Data Center. 

And, as we followed each parcel ice, we accumulated information about the surface temperatures and the solar radiation that the ice had experienced. 

And then we fit a model to estimate the ice thickness based on these 3-year histories of environmental data. 

We used a type of model called a neural network. 


What were the results from using this model?


At the time we conducted the study, available data about the motion of the sea ice allowed us to make monthly estimates from January of 1982 to January of 2003. 

We found that during the 1980s, average thickness of the ice increased, and along with the thickening there was a corresponding increase in the total volume of the ice.

This thickening of the ice occurred during a period when the atmospheric circulation patterns in the Arctic promoted cold temperatures and the wind patterns tended to re-circulate the ice so it could grow older and thicker.

But after 1989, the ice began thinning and the total volume of the ice also decreased. This thinning was associated with a period when the Arctic's atmosphere promoted warmer temperatures and winds that tended to flush a lot of the older ice out of the Artic.

Then, interestingly, in the late 1990s and through the end of our study in 2003, our results indicate that the ice began to slightly thicken, but we did not detect a corresponding increase in the total volume of the ice.

And we found this unusual that ice thickness and volume were no longer changing together.


How do you explain why the total sea ice volume stayed constant even though the ice thickened?


Well, we propose that the ice volume stayed constant during the late 1990s and early 2000s because while the ice was thickening in the high latitudes of the Arctic, the surrounding sea ice was melting. 

But sea ice can only become so thick, and if the Arctic ice continues to melt, the total volume of the Arctic ice will decrease. 


Since this study estimated sea ice thickness from 1982-2003, do you plan to continue estimates for 2004 and onward?


Yeah, we certainly do. The most dramatic losses in sea ice cover have occurred since 2003, and we hypothesize that the thickness and volume are probably both declining now. 

Since the end of our study, more submarine measurements of ice thickness have become available, as well as more recent data about the ice motion, which we need for our modeling. 

So we are presently expanding and implementing our models to study how the ice thickness has changed since 2003.


And, how is this model different or similar to other models scientists are using to estimate sea ice thickness?


Our neural network model complements other approaches. These are largely known as thermodynamic models and they simulate the growth and melt of ice based on physical principles. 

While our model results are largely similar to those of the thermodynamic models, there are subtle differences.

As you know Jessica, science benefits from having different models because they provide us comparative outputs that we can judge to then make model improvements. 


And ultimately what was the reason for developing this new model?


As you mentioned earlier, sea ice thickness does play an important role in the Earth's climate system and for improving climate models.

But I am a biologist with the USGS's Biological Division, and my colleagues are from the Institute of Ecology at the Russian Academy of Sciences. And when we began collaborating on sea ice studies almost 20 years ago, it was because sea ice is the primary habitat of polar bears and Pacific walruses, which are both populations of animals that we share internationally.


Well, it's been a real pleasure speaking with you today and thank you for joining us Dave!


It's my pleasure Jessica—thank you. 


Information on this model, as well as study results from 1982-2003, was recently published in the Journal of Climate and can be accessed through the American Meteorological Society's Web site at

For additional information on USGS sea ice research, including this new publication, you can visit and search through our recent publications on sea ice.

As always, CoreCast is a product of the U.S. Geological Survey, Department of the Interior.

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Music credit

"130 GuitarOverdrive2" by dimlif

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