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Claire L. Parkinson

Abstract

Occurrence of the Weddell polynya, a large open-water area in the midst of the wintertime pack ice of the southern ocean, is examined through a sequence of numerical simulations of the sea ice cover. Using mean climatological input data, the numerical model realistically simulates the emergence of the polynya through the encircling of an open water region by ice. In addition, with only the wind fields altered, the model successfully simulates winter seasons totally lacking a Weddell polynya. Since the vertical ocean heat flux inserted into the model is spatially-invariant, these results call into question—without actually refuting—those explanations of the polynya based exclusively on oceanographic factors. On the other hand, the failure of the modeled polynya to survive the winter season without significant weakening, as the observed polynya did in each of the years 1974–76, suggests that the oceanography and/or the ocean/atmosphere feedbacks are essential to the polynya maintenance, even if not to the polynya formation.

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Claire L. Parkinson

Abstract

Well-established satellite-derived Arctic and Antarctic sea ice extents are combined to create the global picture of sea ice extents and their changes over the 35-yr period 1979–2013. Results yield a global annual sea ice cycle more in line with the high-amplitude Antarctic annual cycle than the lower-amplitude Arctic annual cycle but trends more in line with the high-magnitude negative Arctic trends than the lower-magnitude positive Antarctic trends. Globally, monthly sea ice extent reaches a minimum in February and a maximum generally in October or November. All 12 months show negative trends over the 35-yr period, with the largest magnitude monthly trend being the September trend, at −68 200 ± 10 500 km2 yr−1 (−2.62% ± 0.40% decade−1), and the yearly average trend being −35 000 ± 5900 km2 yr−1 (−1.47% ± 0.25% decade−1).

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Claire L. Parkinson and Gerald F. Herman

Abstract

A four-month simulation of the thermodynamic portion of the Parkinson-Washington sea ice model was conducted using atmospheric boundary conditions that were obtained from a pre-computed seasonal simulation of the Goddard Laboratory for Atmospheric Sciences' Gencral Circulation Model (GLAS GCM). The sea ice thickness and distribution were predicted for the 1 January–30 April period based on the GCM-generated fields of solar and infrared radiation, specific humidity and air temperature at the surface, and snow accumulation. The sensible heat and evaporative fluxes at the surface are mutually consistent with the ground temperatures generated by the ice model and the air temperatures generated by the atmospheric model.

In general, in the Northern Hemisphere the predicted ice distributions and the wintertime accretion and southward advance of the pack ice are well simulated. The computed ice thickness in the Southern Hemisphere appears reasonable, but the Antarctic melt season is extended, causing ice coverage to be less than observed in late March and April. During the Northern Hemisphere winter, the simulated ice accretion is the result of the net deficit of longwave radiation, heat gained from the ocean, am sensible heat lost to the atmosphere. In the early part of the Southern Hemisphere summer, the melting essentially balances the excess of solar over longwave radiation at the surface, while later in the simulation accretion balances the longwave and convective heal losses.

The results show that the Parkinson–Washington sea ice model produces acceptable ice concentrations and thicknesses when used in conjunction with the GLAS GCM for the January to April transition period. These results suggest the feasibility of fully coupled ice-atmosphere simulations with these two models.

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Claire L. Parkinson, David Rind, Richard J. Healy, and Douglas G. Martinson

Abstract

The Goddard Institute for Space Studies global climate model (GISS GCM) is used to examine the sensitivity of the simulated climate to sea ice concentration specifications in the type of simulation done in the Atmospheric Model Intercomparison Project (AMIP), with specified oceanic boundary conditions. Results show that sea ice concentration uncertainties of ±7% can affect simulated regional temperatures by more than 6°C, and biases in sea ice concentrations of +7% and −7% alter simulated annually averaged global surface air temperatures by −0.10° and +0.17°C, respectively, over those in the control simulation. The resulting 0.27°C difference in simulated annual global surface air temperatures is reduced by a third, to 0.18°C, when considering instead biases of +4% and −4%. More broadly, least squares fits through the temperature results of 17 simulations with ice concentration input changes ranging from increases of 50% versus the control simulation to decreases of 50% yield a yearly average global impact of 0.0107°C warming for every 1% ice concentration decrease, that is, 1.07°C warming for the full +50% to −50% range. Regionally and on a monthly average basis, the differences can be far greater, especially in the polar regions, where wintertime contrasts between the +50% and −50% cases can exceed 30°C. However, few statistically significant effects are found outside the polar latitudes, and temperature effects over the nonpolar oceans tend to be under 1°C, due in part to the specification of an unvarying annual cycle of sea surface temperatures. The ±7% and ±4% results provide bounds on the impact (on GISS GCM simulations making use of satellite data) of satellite-derived ice concentration inaccuracies, ±7% being the current estimated average accuracy of satellite retrievals and ±4% being the anticipated improved average accuracy for upcoming satellite instruments. Results show that the impact on simulated temperatures of imposed ice concentration changes is least in summer, encouragingly the same season in which the satellite accuracies are thought to be worst. Hence, the impact of satellite inaccuracies is probably less than the use of an annually averaged satellite inaccuracy would suggest.

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