SENSITIVITY OF MODELED SEA ICE TO EXTERNAL FORCING AND PARAMETERIZATIONS OF HEAT EXCHANGE PROCESSES

A dynamic–thermodynamic sea ice model with 50-km spatial and 24-hour temporal resolution and zero-dimensional thermodynamic sea ice models are used to investigate the spatial and temporal variability of the sea ice cover and the surface energy exchange in the Arctic Basin. The models satisfactorily reproduce the averaged main characteristics of the sea ice and the sea ice extent in the Arctic Basin. At times the evaluation of atmospheric forcing data from NCEP, generally accepted for sea ice climate models, shows large disagreement with data from meteorological observations from drifting stations. The numerical experiments with zero-dimensional sea ice model reveal that negative feedback existing in nature and reproduced in the models artificially reduce the influence of inaccuracy of forcing parameters on the results of modeling sea ice thickness, but distort information about main surface heat fluxes. The possible approach to improve NCEP atmospheric surface data, based on the Rossby-number similarity theory and universal dimensionless functions is outlined. INTRODUCTION Recent reports of the decrease in sea ice extent (e.g. Parkinson et al., 1999) and thickness (Rothrock et al., 1999) in the Arctic Basin stimulate attempts to explain this remarkable change in the main features of the Arctic climate system. One of the main ways to understand the reasons for climate changes is to use numerical modeling to reproduce observed environmental characteristics and to study the possible mechanisms responsible for such changes. Explanation of these changes, however, depends crucially on the model used for investigating long-term sea ice changes in the Arctic and the external forcing applied in the model. Many authors (e.g. Maslanik et al., 2000) explain the decrease in sea ice cover in the eastern part of the Arctic Basin during last decades as a consequence of increased open water and thin ice, forced primarily by ice dynamics. As a result, the surface albedo decreases; the absorbed solar radiation at the surface and in the oceanic mixed layer likewise increases; and, finally, the lateral and bottom melting increases. Hilmer and Lemke (2000), on the other hand, conclude from 1 International Arctic Research Center, University of Alaska Fairbanks, P.O. Box 757335, Fairbanks, USA 2 Arctic and Antarctic Research Institute, St. Petersburg, Russia sensitivity simulations that most of the thinning can be attributed to changes in the surface-level air temperature rather than to changes in the circulation. Using Thorndike’s simple model, Rothrock et al. (1999) discuss possible thermodynamic processes that could produce the observed thinning, such as an increase in the oceanic heat flux, an increase in the poleward atmospheric heat transport and the consequent increase in the incoming longwave radiation, or an increase in the downwelling shortwave radiation. Other proposed reasons for the decrease in sea ice thickness and extent are changes in snow precipitation and snow depth or an increase in ice export from the Arctic Basin. Unfortunately, existing data sets from different reanalyzes, which are needed as forcing for climatic sea ice models, continue to have uncertainties, particularly in the surface fields and fluxes, as described by the World Meteorological Organization (1999). The same problems restrict the use of coupled models for studying climate anomalies in the Arctic sea ice (Maslanik et al., 2000). Because of these shortcomings in the various data sets, almost all of the sea ice models use the NCEP/NCAR reanalysis data (Kalnay et al., 1996) entirely or use only the near-surface air temperature and surface-level pressure together with different climatic mean values of other atmospheric forcing parameters. The restrictions of such approaches for projecting the long-term variability of the sea ice cover will be shown below. We will analyze results from numerical experiments with a dynamic-thermodynamic and a zero-dimensional thermodynamic sea ice models, forced with atmospheric data from NCEP (1948–1997) and with data of field observations executed on the Russian and US drifting stations (1954–1990), to study the sensitivity of modeled sea ice and air-sea ice interaction processes to external forcing and some parameterizations of heat fluxes used in sea ice models. DATA To investigate how NCEP reproduces recent climate in the Central Arctic Basin we put together daily averaged data of standard meteorological observations executed on drifting stations, further named as NP data, and NCEP data, interpolated to the points where drifting station sailed each particular day. Comparison had been carried out for January and July, typical winter and summer months.