Abstract
Abstract. Sea ice plays an important role in the air–ice–ocean interaction, but it is often represented simply in many regional atmospheric models. The Noah sea ice scheme, which is the only option in the current Weather Research and Forecasting (WRF) model (version 3.6.1), has a problem of energy imbalance due to its simplification in snow processes and lack of ablation and accretion processes in ice. Validated against the Surface Heat Budget of the Arctic Ocean (SHEBA) in situ observations, Noah underestimates the sea ice temperature which can reach −10 °C in winter. Sensitivity tests show that this bias is mainly attributed to the simulation within the ice when a time-dependent ice thickness is specified. Compared with the Noah sea ice model, the high-resolution thermodynamic snow and ice model (HIGHTSI) uses more realistic thermodynamics for snow and ice. Most importantly, HIGHTSI includes the ablation and accretion processes of sea ice and uses an interpolation method which can ensure the heat conservation during its integration. These allow the HIGHTSI to better resolve the energy balance in the sea ice, and the bias in sea ice temperature is reduced considerably. When HIGHTSI is coupled with the WRF model, the simulation of sea ice temperature by the original Polar WRF is greatly improved. Considering the bias with reference to SHEBA observations, WRF-HIGHTSI improves the simulation of surface temperature, 2 m air temperature and surface upward long-wave radiation flux in winter by 6, 5 °C and 20 W m−2, respectively. A discussion on the impact of specifying sea ice thickness in the WRF model is presented. Consistent with previous research, prescribing the sea ice thickness with observational information results in the best simulation among the available methods. If no observational information is available, we present a new method in which the sea ice thickness is initialized from empirical estimation and its further change is predicted by a complex thermodynamic sea ice model. The ice thickness simulated by this method depends much on the quality of the initial guess of the ice thickness and the role of the ice dynamic processes.
Highlights
Regional climate models (RCMs) are useful tools for understanding the processes in the polar climate system, and they have been widely used to provide detailed projections of future climate change over polar regions
Previous research has shown that the simplification in the Noah sea ice model can lead to problems of energy imbalance when used for polar climate simulation (Valkonen et al, 2014)
To determine the possible added value from a complex thermodynamic sea ice model, high-resolution thermodynamic snow and ice model (HIGHTSI) is coupled into the polar-modified Weather Research and Forecasting (WRF) model
Summary
Regional climate models (RCMs) are useful tools for understanding the processes in the polar climate system, and they have been widely used to provide detailed projections of future climate change over polar regions. As the lower boundary condition for the atmospheric model, the simplified thermodynamic sea ice model could exert biased forcing to the atmosphere (Valkonen et al, 2014) To overcome this problem, efforts have been made in order to better represent the sea ice in RCMs. For example, studies have shown that properly specifying the sea ice thickness and snow on ice have a considerable impact on the simulation of surface temperature (Rinke et al, 2006; Hines et al, 2015). This means simplifications and lack of important thermodynamic processes exist in the current WRF and Polar WRF (version 3.6.1) These shortages in the model can lead to a problem of energy imbalance in snow and ice, which is an important issue in regional climate simulation.
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