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How well CMIP6 captures North American storm pulses

An Eulerian three-parameter storm metric shows CMIP6 GCMs share cyclone biases versus ERA5, while 12 km CRCM6 is usually closest.

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What reference data evaluate the models?

ERA5 reanalysis.

What historical window is used?

1980–2014, one CMIP6 historical member per model.

How are storms identified?

Yearly minima of 6-hourly sea-level-pressure anomalies at each grid point.

How many storms enter the fitted composites?

The seven strongest at each grid point, not all 35 yearly events.

What three parameters describe each 3-day pulse?

Peak value, mean tendency, and asymmetry.

What common GCM bias appears in pressure peaks?

Underestimated anomalies over oceans and overestimated over land.

Which model generally has the smallest errors?

12 km CRCM6-GEM5, regardless of ERA5 versus CMIP6 drivers.

Does the driving GCM dictate CRCM6 errors?

No—three GCM-driven RCMs look similar even when drivers differ widely.

Where does higher resolution help most?

High track-density oceans such as the western and northern North Pacific.

Where is the linear 3-day fit a poor description?

Tropical regions, where cyclone signatures are nonlinear from an Eulerian view.

Why are ERA5 differences not strictly “truth errors”?

ERA5 is imperfect; a model matching an ERA5 bias looks skillful.