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The authors recommend AI forecasts for impact warnings only alongside a physics-based forecast."}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["summary","account"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"systems[].autonomy_permissions":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].component_role":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].deployment_configuration":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].inputs_outputs":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].model_name":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].model_version":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].product_name":{"state":"value_present","value":{"kind":"record_fields","fields":{"system":"GraphCast and Pangu-Weather"}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["system"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"systems[].provider":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"taxonomy_crosswalks[]":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"title":{"state":"value_present","value":{"kind":"record_fields","fields":{"title":"ETH Zurich and University of Bern researchers find that GraphCast and Pangu-Weather beat ECMWF's ensemble mean on the February 2020 UK storms","headline":"*GraphCast* and *Pangu-Weather* foresee Britain's February 2020 storms"}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["title","headline"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"version":{"state":"value_present","value":{"kind":"identifiers","identifiers":["39e0a925ed5802f340d07fc9d7f61f650c1f51916d27fd4a21e29733508c98a1"],"role":"SHA-256 of the complete public record and its assessments"},"provenance":{"kind":"curatorial","basis":"SHA-256 of the public record, its assessments, and its displayed answers and notes, excluding its own identifier and the derived coverage summary.","record_fields":[],"source_refs":[]},"review_state":"record_mapped","coverage":"complete"},"workflow":{"state":"value_present","value":{"kind":"record_fields","fields":{"account":"Researchers at ETH Zurich, the University of Bern, the University of Lausanne and Columbia University studied three storms that hit the United Kingdom in February 2020. Storms Ciara, Dennis and Jorge came in close succession, with strong winds and heavy rain. The authors compared GraphCast and Pangu-Weather with the mean of ECMWF's 50-member operational ensemble, cycle 46r1. They checked all forecasts against ERA5, and the storms fell outside the AI models' training periods. The authors report that the AI models tended to outperform the ensemble mean for pressure at sea level at weekly timescales, and to a lesser extent for surface winds. GraphCast had the lowest pressure error, an average of 3.23 hPa. Some single ensemble members matched or occasionally beat the AI models. The authors add that weaker links between errors in different variables may mean that the AI models overlook physical constraints. The journal npj Natural Hazards published the study on 27 May 2026. The authors recommend AI forecasts for impact warnings only alongside a physics-based forecast.","replication":{"produced_by":["Forecasts of the three storms were scored against ERA5 at 1.5 degrees.","The two AI models were compared with the ensemble mean and with its best member."],"must_hold":["The storms must fall outside the AI models' training periods.","Impact warnings need a physics-based forecast alongside the AI forecast."],"echoes":[]}}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["account","replication"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"}},"summary":{"total":91,"addressed":91,"known":28,"reviewed":2,"reviewed_complete":2,"reviewed_partial":0,"record_mapped":26,"review_not_assessed":63,"not_assessed":0,"complete":false,"by_state":{"value_present":28,"not_reported":0,"unresolved":63,"not_assessed":0,"not_applicable":0,"withheld":0,"source_unavailable":0}}},"presentation_version":"884afd4eaa4995684f680ce25ef5bf17b5bcc02c650edd834a23ab41910a3a28"}