A Comparison of the Predictability of Arctic and Atlantic Basin Cyclones

Arctic cyclones (ACs) are synoptic scale features that can be associated with strong winds for long periods of time, which in turn lead to rapid declines in Arctic sea ice during the summer. As a consequence, accurate sea ice predictions may require accurate predictions of cyclone-related wind speed and direction, which critically depends on the cyclone track and intensity. Despite this, there are relatively few studies that have documented the predictability of ACs during the summer, beyond a limited number of case studies. In addition, there has been no extensive comparison to determine whether these cyclones are more or less predictable relative to comparable midlatitude cyclones, which have been studied in greater detail. The goal of this study is to document the predictability of AC position and intensity forecasts over a large number of cases and compare it to Atlantic basin midlatitude cyclones using the Global Ensemble Forecast System (GEFS) Reforecast V2. This dataset contains 11-member ensemble forecasts initialized daily from 1985-present using a fixed model configuration. Here, predictability is defined as the ensemble standard deviation. In this presentation, we will document the methods used to identify cyclone cases in both basins and compare the position and intensity predictability as a function of time before cyclogenesis occurs. In addition, the role of baroclinic instability and latent heat release on cyclone predictability is evaluated by comparing the most and least predictable cyclone cases. Finally, the processes that limit the predictability of an August 2013 AC characterized by low intensity and position predictability is examined using Model for Prediction Across Scales (MPAS) ensemble forecasts.