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The authors report that, at the 1 mm threshold, AIFS had the highest detection rate and GraphCast the highest net skill, a CSI of 0.424 against 0.389 for WRF. AIFS and GraphCast cut temperature RMSE by 19.0% and 17.6% against the assimilated WRF. The order reversed for heavy rain. At 20 mm in 6 hours, WRF scored 0.160, ahead of AIFS at 0.141 and GraphCast at 0.114, and FuXi forecast no exceedances. GraphCast kept its skill in 2021, after its training period, while AIFS was fine-tuned on years that cover all three events. 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Physics vs. AI in weather prediction: evaluating GraphCast, AIFS, and FuXi against an observation-corrected WRF model for flash floods. Geoscientific Model Development 19, 9831-9855 (2026).","title":"Physics vs. AI in weather prediction: evaluating GraphCast, AIFS, and FuXi against an observation-corrected WRF model for flash floods","url":"https://gmd.copernicus.org/articles/19/9831/2026/","date":"2026-10-13","written_by":"independent","quote":"At the 1 mm threshold AIFS achieves the highest detection rate (POD 0.835) and GraphCast the highest net categorical skill (CSI 0.424, against 0.415 for AIFS and 0.389 for the assimilated WRF), and AIFS and GraphCast reduce temperature RMSE by 19.0 % and 17.6 % relative to assimilated WRF"}]}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["evidence"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"sources[].upstream_sources":{"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"},"strategic_assessments[]":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"strategic assessments"},"summary":{"state":"value_present","value":{"kind":"record_fields","fields":{"summary":"For three Luxembourg flash floods, GraphCast and AIFS detected light rain and forecast temperature better than a regional model that assimilates observations. The regional model won on heavy rain.","account":"Two researchers at the University of Luxembourg compared GraphCast, AIFS Single 1.0 and FuXi with a regional WRF model that assimilates observations. They covered flood events in Luxembourg and the Greater Region in July 2016, May and June 2018 and July 2021. Forecasts were checked at 259 to 280 stations per event that were independent of the assimilated observations. The authors report that, at the 1 mm threshold, AIFS had the highest detection rate and GraphCast the highest net skill, a CSI of 0.424 against 0.389 for WRF. AIFS and GraphCast cut temperature RMSE by 19.0% and 17.6% against the assimilated WRF. The order reversed for heavy rain. At 20 mm in 6 hours, WRF scored 0.160, ahead of AIFS at 0.141 and GraphCast at 0.114, and FuXi forecast no exceedances. GraphCast kept its skill in 2021, after its training period, while AIFS was fine-tuned on years that cover all three events. Geoscientific Model Development published the study on 13 October 2026."}},"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, AIFS Single 1.0 and FuXi"}},"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":"University of Luxembourg researchers find that GraphCast and AIFS beat a regional model on light rain and temperature in three flood events","headline":"*GraphCast* and *AIFS* catch light rain in Luxembourg's flood events"}},"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":["9697d91534dd8846a737f5390dda8f481232c94257e8cff0d28c8994ae8c680e"],"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":"Two researchers at the University of Luxembourg compared GraphCast, AIFS Single 1.0 and FuXi with a regional WRF model that assimilates observations. They covered flood events in Luxembourg and the Greater Region in July 2016, May and June 2018 and July 2021. Forecasts were checked at 259 to 280 stations per event that were independent of the assimilated observations. The authors report that, at the 1 mm threshold, AIFS had the highest detection rate and GraphCast the highest net skill, a CSI of 0.424 against 0.389 for WRF. AIFS and GraphCast cut temperature RMSE by 19.0% and 17.6% against the assimilated WRF. The order reversed for heavy rain. At 20 mm in 6 hours, WRF scored 0.160, ahead of AIFS at 0.141 and GraphCast at 0.114, and FuXi forecast no exceedances. GraphCast kept its skill in 2021, after its training period, while AIFS was fine-tuned on years that cover all three events. Geoscientific Model Development published the study on 13 October 2026.","replication":{"produced_by":["The AI models and WRF drew initial and boundary data from ERA5 for about 90 simulated days each.","Forecasts were scored at stations screened to be independent of the assimilated observations."],"must_hold":["Forecasts of the heavy rain that causes floods need the regional model, which scored better at high thresholds.","The event must lie outside the AI model's training data for a fair test."],"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":"723b194b89f2908a5d7eeda1ea063856fab823a9f7434316850764410721c91a"}