Impacts of Background Field Removal on the Seasonal Cycle and Trend of Cyclone Statistics

Abstract

Extratropical cyclones are responsible for much of the high impact weather in the mid-latitudes. Many objective algorithms have been developed to track cyclones and compile cyclone statistics. In this study, winter cyclones are tracked based on minima in mean sea level pressure (MSLP) from multiple reanalysis datasets (20th Century Reanalysis, ERA-40, NCEP/NCAR Reanalysis, and ERA-Interim) to explore the impacts of the removal of a background field on cyclone statistics. We compare unfiltered cyclones, defined as local minima in the total MSLP data, with filtered cyclones, defined as minima in pressure perturbation after removing a large-scale, low-frequency background field. The results show that while cyclone counts are generally consistent across datasets, the removal of the background field significantly alters the seasonal cycle, long-term trends, and the relationship between cyclone activity and large-scale circulation patterns such as the NAO, PNA, and precipitation.