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On the formulation of sea-ice models. Part 2: Lessons from multi-year adjoint sea ice export sensitivities through the Canadian Arctic Archipelago.

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  • Computer Science
  • Medicine
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Abstract

ceaice_part2.dvi On the formulation of sea-ice models. Part 2: Lessons from multi-year adjoint sea ice export sensitivities through the Canadian Arctic Archipelago. Patick Heimbach a,1, Dimitris Menemenlis b, Martin Losch c, Jean-Michel Campin a and Chris Hill a aDepartment of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA bJet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA cAlfred-Wegener-Institut fu¨r Polar- und Meeresforschung, Postfach 120161, 27515 Bremerhaven, Germany Abstract The adjoint of an ocean general circulation model is at the heart of the ocean state estimation system of the Estimating the Circulation and Climate of the Ocean (ECCO) project. As part of an ongoing effort to extend ECCO to a coupled ocean/sea- ice estimation system, a dynamic and thermodynamic sea-ice model has been de- veloped for the Massachusetts Institute of Technology general circulation model (MITgcm). One key requirement is the ability to generate, by means of automatic differentiation (AD), tangent linear (TLM) and adjoint (ADM) model code for the coupled MITgcm ocean/sea-ice system. This second part of a two-part paper de- Preprint submitted to Elsevier 19 January 2010 scribes aspects of the adjoint model. The adjoint ocean and sea ice model is used to calculate transient sensitivities of solid (ice & snow) freshwater export through Lancaster Sound in the Canadian Arctic Archipelago (CAA). The adjoint state pro- vides a complementary view of the dynamics. In particular, the transient, multi-year sensitivity patterns reflect dominant pathways and propagation timescales through the CAA as resolved by the model, thus shedding light on causal relationships, in the model, across the Archipelago. The computational cost of inferring such causal relationships from forward model diagnostics alone would be prohibit

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