Challenges in the Description of Sea Ice for a Kilometer-Scale Weather Forecasting System

Abstract

Abstract Simulation of atmosphere–ocean–ice interactions in coupled Earth modeling systems with kilometer-scale resolution is a new challenge in operational numerical weather prediction. This study presents an assessment of sensitivity experiments performed with different sea ice products in a convective-scale weather forecasting system for the European Arctic. On kilometer-scale resolution sea ice products are challenged by the large footprint of passive microwave satellite observations and issues with spurious sea ice detection of the higher-resolution retrievals based on synthetic aperture radar instruments. We perform sensitivity experiments with sea ice concentration fields of 1) the global ECMWF-IFS forecast system, 2) a newly developed multisensor product processed through a coupled sea ice–ocean forecasting system, and 3) the AMSR2 product based on passive microwave observations. There are significant differences between the products on O(100) km scales in the northern Barents Sea and along the Marginal Ice Zone north of the Svalbard archipelago and toward the Fram Strait. These differences have a direct impact on the modeled surface skin temperature over ocean and sea ice, the turbulent heat flux, and 2-m air temperature (T2M). An assessment of Arctic weather stations shows a significant improvement of forecasted T2M in the north and east of Svalbard when using the new multisensor product; however, south of Svalbard this product has a negative impact. The different sea ice products are resulting in changes of the surface turbulent heat flux of up to 400 W m−2, which in turn results in T2M variations of up to 5°C. Over a 2-day forecast lead time this can lead to uncertainties in weather forecasts of about 1°C even hundreds of kilometers away from the sea ice. Significance Statement Weather forecasting in polar regions requires an accurate description of sea ice properties due to the very important atmosphere–ocean–ice interactions. With the increasing resolution of weather forecasting systems, there is also a need to advance the resolution of the sea ice characteristics in the models. This is, however, not straightforward due to various issues in the sea ice satellite products. This study explores new products and approaches to integrate high-resolution sea ice in a weather prediction system. We find that the model is sensitive to the choice of the sea ice product and that it is still challenging to provide an accurate sea ice field on a kilometer-scale resolution.