Abstract

Abstract The impact of melt ponds on sea ice albedo has been observed and documented. In general circulation models, ponds are now accounted for through indirect diagnostic treatments (“implicit” schemes) or prognostic melt-pond parameterizations (“explicit” schemes). However, there has been a lack of studies showing the impacts of these schemes on simulated Arctic climate. We focus here on rectifying this using the general circulation model HadGEM3, one of the few models with a detailed explicit pond scheme. We identify the impact of melt ponds on the sea ice and climate, and associated ice–ocean–atmosphere interactions. We run a set of constant forcing simulations for three different periods and show, for the first time, that using mechanistically different pond schemes can lead to very significantly different sea ice and climate states. Under near-future conditions, an implicit scheme never yields an ice-free summer Arctic, while an explicit scheme yields an ice-free Arctic in 35% of years and raises autumn Arctic air temperatures by 5° to 8°C. We find that impacts on climate and sea ice depend on the ice state: under near-future and last-interglacial conditions, the thin sea ice is very sensitive to pond formation and parameterization, whereas during the preindustrial period the thicker sea ice is less sensitive to the pond scheme choice. Both of these two commonly used parameterizations of sea ice albedo yield similar results under preindustrial conditions but in warmer climates lead to very different Arctic sea ice and ocean and atmospheric temperatures. Thus, changes to physical parameterizations in the sea ice model can have large impacts on simulated sea ice, ocean, and atmosphere. Significance Statement This study investigates the impacts of melt ponds on Arctic sea ice under different climate conditions, using the HadGEM3-GC3.1-LL general circulation model (GCM). Additionally, we study the impact of changing the type of pond scheme used. We find that changing the pond scheme causes large differences to how a GCM simulates Arctic sea ice, the ocean, and the atmosphere, for both near-future and warmer paleoclimate conditions. These large differences have not been found previously, because this is one of the first GCM studies of this type. Our results demonstrate the importance of melt ponds, and their wider impacts on ocean and atmosphere. Furthermore, they suggest that better evaluation of the representation of sea ice processes is vital for the robust projection of future climate change.

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