Taylor, Paul Duncan; (2003) Mathematical modelling the formation and evolution of melt ponds on sea ice. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Sea ice is formed in the polar oceans by the freezing of seawater. It is a sensitive component of the global climate, and its influence on climate is significant through feedbacks, such as the albedo-feedback mechanism. Melt ponds are pools of melt water formed annually on the Arctic sea ice surface. Melt ponds form because of preferential absorption of solar radiation compared to bare sea ice and snow. This thesis investigates the evolution of melt ponds on the surface of sea ice, primarily through numerical modelling, and also through simple studies of individual processes that are deemed to be important in the evolution of melt ponds. The theoretical model of melt ponds upon sea ice developed in this thesis is based upon the mushy layer equations and a relatively simple two-stream radiation model. A sea ice mushy layer consists of a solid ice matrix surrounded by brine. The two- stream radiation model has been used in previous sea ice studies, and incorporates a summertime parameterisation of optical properties based upon SHEBA field data. Stationary solutions of the model, without melt ponds or snow, are analysed, showing potentially two stationary ice thicknesses for a given set of forcing data. However, a linear stability analysis reveals that only the larger of the two solutions is stable. Fundamental summertime processes are investigated and discussed. These include melt pond thermal stability, melt pond drainage, and the evolution of sea-ice lenses (ice formed at the interface of fresh drained water and the salty ocean). The full melt-pond-sea-ice thermo-radiative model is forced using primarily SHEBA data. Model sensitivity to processes and important parameters is investigated. The model simulates the evolution of ponds well and demonstrates the importance of radiative effects on summertime evolution. The potential application of the model to GCMs is discussed.

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