The representation of synoptic-scale cyclone climatology in CMIP6 models over Atlantic Canada using self-organizing maps

Abstract

This study compares the ability of selected CMIP6 Earth System Models (ESMs) to simulate synoptic-scale cyclone climatology over Atlantic Canada by examining their representation of pressure anomalies against that of ERA5 reanalysis data. A Self-Organizing Map (SOM) was trained using daily mean sea level pressure (MSLP) anomalies from both historical model simulations and ERA5 reanalysis data for the warm and cold seasons over a 45 year period. The ESMs are assessed based on their ability to reproduce the frequency and spatial structure of synoptic pressure anomaly patterns using both statistical and visual inspection techniques. Results indicate notable inter-model variability, with MPI-ESM1-2-HR and MRI-ESM2-0 showing relatively stable performance across both seasons, NorESM2-MM excelling in the cold season but declining in the warm season, and CMCC-CM2-HR4 exhibiting the highest biases overall. In general, models captured cold-season patterns more faithfully than warm-season ones. This research contributes an understanding on how to compare ESM biases in simulating cyclone climatology and also informs future efforts in regional climate impact assessment in the region surrounding Newfoundland.