The Effects of Spectral Nudging on Arctic Temperature and Precipitation as Produced by the Pan-Arctic WRF

Pan-Arctic WRF (PAW) simulations produced using a 50-km domain developed for the fully-coupled Regional Arctic Climate Model (RACM) were found to produce deep atmospheric circulation biases over the northern Pacific Ocean, manifested in pressure, geopotential height, and temperature fields. Possible remedies to correct these large biases, such as modifying the physical domain or using different initial/boundary conditions, were unsuccessful.

Spectral (interior) nudging was introduced as a way of constraining the model to be more consistent with observed behavior. However, such control over numerical model behavior raises concerns over how much nudging may affect unforced variability and extremes. Strong nudging may reduce or filter out extreme events, since the nudging pushes the model toward a relatively smooth, large-scale state. The question then becomes - what is the minimum spectral nudging needed to correct biases while not limiting the simulation of extreme events? To determine this, we performed case studies using a six-member PAW ensemble on the RACM grid with varying spectral nudging strength, using WRF's standard nudging as a reference point. We simulated two periods, one in a cold season (January 2007) and one in a warm season (July 2007).

Precipitation and 2-m temperature fields were extracted from the output and analyzed to determine how changing spectral nudging strength impacts both temporal and spatial temperature and precipitation extremes. The maximums and minimums over the simulation period were also examined. Results suggest that there is a marked lack of sensitivity to varying degrees of nudging. Moreover, given that nudging is an artificial forcing applied in the model, an important outcome of this work is that nudging strength apparently can be considerably smaller than WRF's standard strength and still produce reliable simulations.