Work

Track‐Dependent Links Between Tropical Cyclones and Extratropical Predictability in Physical and AI Models

Year: 2026

Type: article

Abstract: Global medium‐range weather forecasts suffer occasional failures (“busts”) linked to tropical cyclones (TCs). We investigate TC influences on extratropical predictability by comparing forecasts from a physics‐based model (ECMWF‐IFS) and an AI‐hybrid model (Google‐NGCM) initialized near TC genesis. Analyzing 108 out‐of‐sample Northern Hemisphere cases reveals similar extratropical error growth patterns and comparable performance between the models. This suggests that the Neural General Circulation Model (NGCM) is capable of predicting the bulk upscale effects of tropical convection without directly representing convective processes. Leveraging the NGCM's computational efficiency, we compare forecasts initialized with and without TC genesis to isolate track‐dependent forecast impacts. For Week‐2 extratropical forecasts, TC impacts are highly time‐, metric‐, and track‐dependent. The analysis confirms that some poleward‐moving TCs degrade Week‐2 US and European forecasts and suggests significant impacts from westward‐moving TCs. The findings highlight the utility of the AI‐hybrid model in predictability research and complex tropical‐extratropical teleconnections that warrant future research.

Source: Geophysical Research Letters

DOI: 10.1029/2026gl122172

Author: Gan Zhang

Institutions: University of Illinois Urbana-Champaign, University of Illinois System

Language: English

Topic: Meteorological Phenomena and Simulations

Subfield: Atmospheric Science

Field: Earth and Planetary Sciences

Domain: Physical Sciences

SDG: Climate action

Open Access status: gold

Estimated APC paid: $3,190