Thickness of Arctic sea ice Reconstructed by Data assimilation and artificial Intelligence Seamlessly (TARDIS)
Satellites have been measuring the extent of the whole Arctic sea ice since the late 70’s. But only since 2010 are they also able to measure its thickness and thus monitor the decline of its total volume. This information would have been invaluable for climate studies had these new satellites been sent in orbit ten years earlier. In the absence of a time machine, can we learn enough from the last decade (since 2010) to reconstruct an earlier decade? What we have is a numerical model that can reproduce the known physics and assimilate satellite measurements of the ocean and sea ice during the well-observed decade; this is a well-established tool but it cannot use the scattered ice thickness measurements before the satellites: research cruises, older satellites, and proxy measurements. A more recent tool introduced by the TARDIS team now allows us to combine data assimilation and machine learning to build data-driven relationships between them. TARDIS will apply this method in order to finally reconstruct the past ice thickness for climate studies. If TARDIS succeeds at time travelling and spatial interpolation over the Arctic sea ice, the team will consider analogous applications of the same methodology.
Project facts
Name
Thickness of Arctic sea ice Reconstructed by Data assimilation and artificial Intelligence Seamlessly (TARDIS)
Status
Active
Duration
01.10.21 - 30.09.25
Location
Tromsø
Total budget
13.806.000 NOK
Publications
Linking scales of sea ice surface topography: evaluation of ICESat-2 measurements with coincident helicopter laser scanning during MOSAiC – Ricker, Robert; Fons, Steven; Jutila, Arttu; Hutter, Nils; Duncan, Kyle; Farrell, Sinead L.; Kurtz, Nathan T.; Hansen, Renee Mie Fredensborg. 2023, The Cryosphere. NORCE, UNIVMARYL, NASA, AWI, UoW, NTNU, UNIS, DTU.
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