Bias-Corrected Sea Ice Thickness from Satellite, Aircraft, and Subsurface Measurements

 Bias-Corrected

The primary objective of this research is to construct a comprehensive bias-corrected sea ice thickness record and use it to better quantify and understand the dramatic changes that have been observed in the Arctic ice pack. To do this all available Arctic sea ice thickness observations will be integrated, from satellite, aircraft, and subsurface measurements, and used to identify and correct systematic errors through comparisons with a common reference. With the resultant record four science questions will be answered:

• What are the systematic differences between different measurement systems for sea ice thickness?

• What are the spatial patterns in the trends in ice thickness and what explains them?

• How are the mechanisms controlling sea ice extent and volume changing and how are they related to changes in atmospheric and oceanic circulation patterns in lower latitudes?

• How can improved estimates of sea ice thickness help improve seasonal predictions of sea ice conditions?

To answer these questions this project will concentrate on four primary technical objectives:

• Expand our existing Unified Sea Ice Thickness Climate Data Record (Sea Ice CDR) to include ICESat, IceBridge, and CryoSat-2 estimates of the ice thickness.

• Improve the atmospheric forcing of our advanced coupled ice-ocean model and the critically important estimates of the snow depth on sea ice through the use of the new NASA reanalysis data set MERRA and create a retrospective simulation of the ice thickness for 1979 to the present.

• Create a Bias-corrected Observed Ice Thickness Record consisting of all of the observations in the Sea Ice CDR adjusted by subtracting a constant bias for each system which is found relative to a standard observation system (submarines).

• Calibrate the retrospective simulations of ice thickness from our numerical model against the aggregate of all the observation systems by removing the mean difference between the model and the observations to create a Calibrated Model Ice Thickness Record.

These new data products will then be used to analyze and answer the science questions posed above. Linkages between the changes in the ice thickness and in the thermodynamic and dynamic processes that determine the thickness to changes in hemispheric circulation and heat transport patterns will be analyzed with the MERRA reanalysis data set. The new ice thickness estimates will also be used to improve on-going seasonal predictions of sea ice extent.

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