{"id":"AIBD-0750","title":"The National Hurricane Center finds that only Google DeepMind's ensemble beat its track forecast at 12 hours for Tropical Storm Chantal","summary":"NHC found that only Google DeepMind's ensemble mean beat its official track forecast for Tropical Storm Chantal at 12 hours. Chantal caused 6 direct deaths in North Carolina.","date_observed":"2025-07-04","date_basis":"event","date_precision":"day","benefit_status":"reported","source_collection":null,"source_entry":null,"account":"Tropical Storm Chantal formed off the southeastern United States on 4 July 2025 and made landfall in South Carolina early on 6 July. It caused 6 direct deaths in North Carolina, most of them in flooding from heavy rain. The US National Hurricane Center (NHC) verified its forecasts in a tropical cyclone report, first dated 3 February 2026 and revised on 29 June 2026. In a homogeneous comparison, NHC found that the Google DeepMind ensemble mean (GDMI) was the only aid to beat its official track forecast at 12 hours. NHC called GDMI a superior performer throughout the forecast period. GDMI's track errors were 15.6, 33.4, 47.4 and 64.2 nautical miles at 12 to 48 hours. The official errors were 19.5, 41.6, 60.5 and 88.7. Other aids also beat NHC's forecasts beyond 12 hours. The comparison rests on only six forecasts at 12 hours and two at 48 hours. NHC uses the model as experimental guidance and worked with Google DeepMind to develop it.","category":"aggregate result","unexpected":false,"purpose":"Google DeepMind built the experimental tropical cyclone model to give forecasters ensemble guidance on the track and intensity of storms.","system":"Google DeepMind tropical cyclone model, ensemble mean (NHC designation GDMI)","model_version":null,"developer":"Google DeepMind","deployer":"NOAA National Hurricane Center (experimental guidance), with output supplied by Google DeepMind","location":"South Carolina and North Carolina, United States","domain":"Weather forecasting / tropical cyclones","segment":null,"benefit_type":"Improved Task Accuracy","work_activities":["4.A.1.b.3"],"taxonomy_note":null,"registry_ids":{},"ratings":[{"group":"organizational","depth":2,"reason":"GDMI's track errors at 12 to 48 hours were lower than NHC's official errors in a homogeneous comparison, though over only two to six forecasts."},{"group":"societal","depth":null,"reason":"NHC does not report that the AI guidance changed warnings or outcomes in the Carolinas."}],"ai_role":{"status":"assessed","statement":"NHC verified GDMI's own track forecasts against the best track alongside the official forecast and other models, which isolates the model's skill. NHC gives no account of how forecasters used GDMI for Chantal. NHC is not fully outside the case, since it uses the model and worked with Google DeepMind to develop it."},"evidence":[{"kind":"report","citation":"Papin, P. P. Tropical Storm Chantal (AL032025), 4–7 July 2025. National Hurricane Center Tropical Cyclone Report, 29 June 2026 (original report dated 3 February 2026), p. 7 and Table 5b.","title":"Tropical Cyclone Report: Tropical Storm Chantal (AL032025)","url":"https://www.nhc.noaa.gov/data/tcr/AL032025_Chantal.pdf","date":"2026-06-29","written_by":"deployer","quote":"The only guidance aid that outperformed OFCL in 12 h was the Google DeepMind ensemble mean (GDMI), which was also a superior performer throughout the forecast period."},{"kind":"press release","citation":"National Weather Service. AI in Hurricane Forecasting at the National Hurricane Center: A Q&A with NHC's Science Operations Officer. NOAA/NWS, undated.","title":"AI in Hurricane Forecasting at the National Hurricane Center","url":"https://www.weather.gov/news/261102-AI-Hurricane-Forecasting","date":null,"written_by":"deployer","quote":"NHC has partnered directly with Google DeepMind to develop a new AI hurricane forecast model that was used experimentally during the 2025 season.","supports_benefit":false}],"replication":{"produced_by":["NHC included GDMI among the guidance models in its homogeneous comparison for Chantal.","NHC measured each model's track errors against Chantal's best track."],"must_hold":["The sample is small, with six forecasts at 12 hours and two at 48 hours.","The official forecast remains NHC's own judgment, and other aids also beat it at some lead times."],"echoes":[]},"paired_incident":null,"headline":"*GDMI* alone beat NHC's track forecast for Chantal at 12 hours","metric":"the only aid to beat its official track forecast at 12 hours","comparator":{"against":"NHC official track forecasts (OFCL) for Chantal in the homogeneous comparison","before":"OFCL errors of 19.5, 41.6, 60.5 and 88.7 n mi at 12, 24, 36 and 48 h","after":"GDMI errors of 15.6, 33.4, 47.4 and 64.2 n mi","basis":"measured","quote":"The only guidance aid that outperformed OFCL in 12 h was the Google DeepMind ensemble mean (GDMI), which was also a superior performer throughout the forecast period.","url":"https://www.nhc.noaa.gov/data/tcr/AL032025_Chantal.pdf"},"later":null,"value":null,"developer_country":"United Kingdom","deployer_country":"United States","unrated_because":null,"brief_notes":null,"brief":null,"revisions":[{"date":"2026-10-31","change":"Added the record from the report of the National Hurricane Center.","source":"https://www.nhc.noaa.gov/data/tcr/AL032025_Chantal.pdf","editor":"AIBD"}],"confidence":"claimed","shade":"low","claim_status":"The deployer's account","claim_basis":"Sources: the deployer's report and the deployer's press release. For the benefit itself, the cited sources include no independent source and no finding by an external body.","case_jurisdictions":["United States"],"profile":{"case_id":"AIBD-0750","catalog_version":"1.0.0","source_fingerprint":"b466d39ffa20f99e69a7295b7111afdd8c29bfb04063397a4b364b96eddc46a2","collection_refs":[{"collection_id":"aibd","version":"2026-10-31"},{"collection_id":"viator","version":"2026-10-25"}],"source_ids":["AIBD-0750-source-0001","AIBD-0750-source-0002"],"families":{"strategic assessments":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"Editorial assignment.","review_state":"not_assessed","coverage":"partial","record_ids":[]},"evaluations":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"Editorial assignment.","review_state":"not_assessed","coverage":"partial","record_ids":[]},"monetary observations":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"Editorial assignment.","review_state":"not_assessed","coverage":"partial","record_ids":[]},"institutional decisions":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"Editorial assignment.","review_state":"not_assessed","coverage":"partial","record_ids":[]}},"fields":{"actors[]":{"state":"value_present","value":{"kind":"record_fields","fields":{"developer":"Google DeepMind","deployer":"NOAA National Hurricane Center (experimental guidance), with output supplied by Google DeepMind"}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["developer","deployer"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"actors[].ownership_control":{"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"},"ai_contribution":{"state":"value_present","value":{"kind":"record_fields","fields":{"ai_role":{"status":"assessed","statement":"NHC verified GDMI's own track forecasts against the best track alongside the official forecast and other models, which isolates the model's skill. NHC gives no account of how forecasters used GDMI for Chantal. NHC is not fully outside the case, since it uses the model and worked with Google DeepMind to develop it."}}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["ai_role"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"ai_relationship":{"state":"value_present","value":{"kind":"record_fields","fields":{"category":"aggregate result","ai_role":{"status":"assessed","statement":"NHC verified GDMI's own track forecasts against the best track alongside the official forecast and other models, which isolates the model's skill. NHC gives no account of how forecasters used GDMI for Chantal. NHC is not fully outside the case, since it uses the model and worked with Google DeepMind to develop it."}}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["ai_role","category"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"assessments[].alternatives":{"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"},"assessments[].assessor_date":{"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"},"assessments[].depth":{"state":"value_present","value":{"kind":"record_fields","fields":{"ratings":[{"group":"organizational","depth":2,"reason":"GDMI's track errors at 12 to 48 hours were lower than NHC's official errors in a homogeneous comparison, though over only two to six forecasts."},{"group":"societal","reason":"NHC does not report that the AI guidance changed warnings or outcomes in the Carolinas."}]}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["ratings"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"assessments[].display_confidence":{"state":"value_present","value":{"kind":"structured","data":{"confidence":"low","evidence_word":"claimed","claim_status":"The deployer's account","basis":"Sources: the deployer's report and the deployer's press release. For the benefit itself, the cited sources include no independent source and no finding by an external body.","interpretation":"Existing display rule preserved; the richer outcome-specific confidence question still needs review."}},"provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"assessments[].rationale":{"state":"value_present","value":{"kind":"record_fields","fields":{"ratings":[{"group":"organizational","depth":2,"reason":"GDMI's track errors at 12 to 48 hours were lower than NHC's official errors in a homogeneous comparison, though over only two to six forecasts."},{"group":"societal","reason":"NHC does not report that the AI guidance changed warnings or outcomes in the Carolinas."}]}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["ratings"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"assessments[].rubric_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"},"assessments[].status_basis":{"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"},"assessments[].target":{"state":"value_present","value":{"kind":"record_fields","fields":{"ratings":[{"group":"organizational","depth":2,"reason":"GDMI's track errors at 12 to 48 hours were lower than NHC's official errors in a homogeneous comparison, though over only two to six forecasts."},{"group":"societal","reason":"NHC does not report that the AI guidance changed warnings or outcomes in the Carolinas."}]}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["ratings"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"availability":{"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"},"brief":{"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"},"case_kind":{"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"},"case_links[]":{"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"},"claims[].evidence_links":{"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"},"claims[].evidence_strength":{"state":"value_present","value":{"kind":"structured","data":{"answer":"The deployer's account. Sources: the deployer's report and the deployer's press release. For the benefit itself, the cited sources include no independent source and no finding by an external body.","evidence_word":"claimed","claim_status":"The deployer's account"}},"provenance":{"kind":"source_review","basis":"Editorial assignment.","record_fields":["evidence"],"source_refs":["AIBD-0750-source-0001","AIBD-0750-source-0002"],"reviewed_on":"2026-10-29"},"review_state":"reviewed","coverage":"complete","display":{"answer":"The deployer's account. Sources: the deployer's report and the deployer's press release. For the benefit itself, the cited sources include no independent source and no finding by an external body.","inferred":false}},"claims[].missingness":{"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"},"claims[].proposition":{"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"},"cross_border_flows[]":{"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"},"decisions[].action_outcome":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"institutional decisions"},"decisions[].grounds":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"institutional decisions"},"decisions[].institution_task":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"institutional decisions"},"decisions[].success_criterion":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"institutional decisions"},"deployment_stage":{"state":"value_present","value":{"kind":"structured","data":{"classification":"pilot","answer":"The system was used in a pilot. NHC used Google DeepMind's model as experimental guidance during the 2025 season.","scope":"The period and activity described in the case."}},"provenance":{"kind":"source_review","basis":"Editorial assignment.","record_fields":["account","evidence"],"source_refs":["AIBD-0750-source-0001"],"reviewed_on":"2026-10-29"},"review_state":"reviewed","coverage":"complete","display":{"answer":"The system was used in a pilot. NHC used Google DeepMind's model as experimental guidance during the 2025 season.","inferred":false}},"economics[].amount":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"monetary observations"},"economics[].costs[]":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"monetary observations"},"economics[].counterfactual":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"monetary observations"},"economics[].currency_price_basis":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"monetary observations"},"economics[].gross_net":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"monetary observations"},"economics[].measure_type":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"monetary observations"},"economics[].period_unit":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"monetary observations"},"economics[].realization":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"monetary observations"},"economics[].recipient_payer":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"monetary observations"},"economics[].return_payback":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"monetary observations"},"economics[].valuation_method":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"monetary observations"},"evaluations[].ai_uplift":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"evaluations"},"evaluations[].comparator":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"evaluations"},"evaluations[].design":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"evaluations"},"evaluations[].effect":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"evaluations"},"evaluations[].exposure":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"evaluations"},"evaluations[].id":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"evaluations"},"evaluations[].measurement_method":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"evaluations"},"evaluations[].metric":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"evaluations"},"evaluations[].reproduction_materials":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"evaluations"},"evaluations[].setting_sample":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"evaluations"},"evaluations[].uncertainty_limitations":{"state":"unresolved","review_state":"not_assessed","coverage":"partial","family":"evaluations"},"external_references[]":{"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"},"follow_up[]":{"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"},"human_oversight":{"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"},"id":{"state":"value_present","value":{"kind":"record_fields","fields":{"id":"AIBD-0750"}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["id"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"infrastructure_dependencies[]":{"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"},"outcomes[].beneficiaries":{"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"},"outcomes[].beneficiary_count":{"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"},"outcomes[].benefit_type":{"state":"value_present","value":{"kind":"record_fields","fields":{"benefit_type":"Improved Task Accuracy"}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["benefit_type"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"outcomes[].claim":{"state":"value_present","value":{"kind":"record_fields","fields":{"account":"Tropical Storm Chantal formed off the southeastern United States on 4 July 2025 and made landfall in South Carolina early on 6 July. It caused 6 direct deaths in North Carolina, most of them in flooding from heavy rain. The US National Hurricane Center (NHC) verified its forecasts in a tropical cyclone report, first dated 3 February 2026 and revised on 29 June 2026. In a homogeneous comparison, NHC found that the Google DeepMind ensemble mean (GDMI) was the only aid to beat its official track forecast at 12 hours. NHC called GDMI a superior performer throughout the forecast period. GDMI's track errors were 15.6, 33.4, 47.4 and 64.2 nautical miles at 12 to 48 hours. The official errors were 19.5, 41.6, 60.5 and 88.7. Other aids also beat NHC's forecasts beyond 12 hours. The comparison rests on only six forecasts at 12 hours and two at 48 hours. NHC uses the model as experimental guidance and worked with Google DeepMind to develop it.","benefit_type":"Improved Task Accuracy"}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["account","benefit_type"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"outcomes[].distribution":{"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"},"outcomes[].duration":{"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"},"outcomes[].id":{"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"},"outcomes[].stakeholder_group":{"state":"value_present","value":{"kind":"record_fields","fields":{"ratings":[{"group":"organizational","depth":2,"reason":"GDMI's track errors at 12 to 48 hours were lower than NHC's official errors in a homogeneous comparison, though over only two to six forecasts."},{"group":"societal","reason":"NHC does not report that the AI guidance changed warnings or outcomes in the Carolinas."}]}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["ratings"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"outcomes[].status":{"state":"value_present","value":{"kind":"record_fields","fields":{"benefit_status":"reported"}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["benefit_status"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"outcomes[].tradeoffs":{"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"},"outcomes[].unexpected":{"state":"value_present","value":{"kind":"record_fields","fields":{"unexpected":false,"purpose":"Google DeepMind built the experimental tropical cyclone model to give forecasters ensemble guidance on the track and intensity of storms."}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["unexpected","purpose"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"places[]":{"state":"value_present","value":{"kind":"record_fields","fields":{"location":"South Carolina and North Carolina, United States","developer_country":"United Kingdom","deployer_country":"United States"}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["location","developer_country","deployer_country"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"purpose":{"state":"value_present","value":{"kind":"record_fields","fields":{"purpose":"Google DeepMind built the experimental tropical cyclone model to give forecasters ensemble guidance on the track and intensity of storms."}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["purpose"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"record_dates":{"state":"value_present","value":{"kind":"record_fields","fields":{"date_observed":"2025-07-04","date_basis":"event","date_precision":"day","revisions":[{"date":"2026-10-31","change":"Added the record from the report of the National Hurricane Center.","source":"https://www.nhc.noaa.gov/data/tcr/AL032025_Chantal.pdf","editor":"AIBD"}]}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["date_observed","date_basis","date_precision","revisions"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"replication.attempts[]":{"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"},"replication.conditions":{"state":"value_present","value":{"kind":"record_fields","fields":{"replication":{"produced_by":["NHC included GDMI among the guidance models in its homogeneous comparison for Chantal.","NHC measured each model's track errors against Chantal's best track."],"must_hold":["The sample is small, with six forecasts at 12 hours and two at 48 hours.","The official forecast remains NHC's own judgment, and other aids also beat it at some lead times."],"echoes":[]}}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["replication"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"revision_history[]":{"state":"value_present","value":{"kind":"record_fields","fields":{"revisions":[{"date":"2026-10-31","change":"Added the record from the report of the National Hurricane Center.","source":"https://www.nhc.noaa.gov/data/tcr/AL032025_Chantal.pdf","editor":"AIBD"}]}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["revisions"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"sector":{"state":"value_present","value":{"kind":"record_fields","fields":{"domain":"Weather forecasting / tropical cyclones"}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["domain"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"sources[].access_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"},"sources[].citation_locator":{"state":"value_present","value":{"kind":"record_fields","fields":{"evidence":[{"kind":"report","citation":"Papin, P. P. Tropical Storm Chantal (AL032025), 4–7 July 2025. National Hurricane Center Tropical Cyclone Report, 29 June 2026 (original report dated 3 February 2026), p. 7 and Table 5b.","title":"Tropical Cyclone Report: Tropical Storm Chantal (AL032025)","url":"https://www.nhc.noaa.gov/data/tcr/AL032025_Chantal.pdf","date":"2026-06-29","written_by":"deployer","quote":"The only guidance aid that outperformed OFCL in 12 h was the Google DeepMind ensemble mean (GDMI), which was also a superior performer throughout the forecast period."},{"kind":"press release","citation":"National Weather Service. AI in Hurricane Forecasting at the National Hurricane Center: A Q&A with NHC's Science Operations Officer. NOAA/NWS, undated.","title":"AI in Hurricane Forecasting at the National Hurricane Center","url":"https://www.weather.gov/news/261102-AI-Hurricane-Forecasting","written_by":"deployer","quote":"NHC has partnered directly with Google DeepMind to develop a new AI hurricane forecast model that was used experimentally during the 2025 season.","supports_benefit":false}]}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["evidence"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"sources[].id":{"state":"value_present","value":{"kind":"identifiers","identifiers":["AIBD-0750-source-0001","AIBD-0750-source-0002"],"role":"Existing evidence items, in their original order"},"provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"review_state":"record_mapped","coverage":"complete"},"sources[].language":{"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"},"sources[].relationship":{"state":"value_present","value":{"kind":"record_fields","fields":{"evidence":[{"kind":"report","citation":"Papin, P. P. Tropical Storm Chantal (AL032025), 4–7 July 2025. National Hurricane Center Tropical Cyclone Report, 29 June 2026 (original report dated 3 February 2026), p. 7 and Table 5b.","title":"Tropical Cyclone Report: Tropical Storm Chantal (AL032025)","url":"https://www.nhc.noaa.gov/data/tcr/AL032025_Chantal.pdf","date":"2026-06-29","written_by":"deployer","quote":"The only guidance aid that outperformed OFCL in 12 h was the Google DeepMind ensemble mean (GDMI), which was also a superior performer throughout the forecast period."},{"kind":"press release","citation":"National Weather Service. AI in Hurricane Forecasting at the National Hurricane Center: A Q&A with NHC's Science Operations Officer. NOAA/NWS, undated.","title":"AI in Hurricane Forecasting at the National Hurricane Center","url":"https://www.weather.gov/news/261102-AI-Hurricane-Forecasting","written_by":"deployer","quote":"NHC has partnered directly with Google DeepMind to develop a new AI hurricane forecast model that was used experimentally during the 2025 season.","supports_benefit":false}]}},"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":"NHC found that only Google DeepMind's ensemble mean beat its official track forecast for Tropical Storm Chantal at 12 hours. Chantal caused 6 direct deaths in North Carolina.","account":"Tropical Storm Chantal formed off the southeastern United States on 4 July 2025 and made landfall in South Carolina early on 6 July. It caused 6 direct deaths in North Carolina, most of them in flooding from heavy rain. The US National Hurricane Center (NHC) verified its forecasts in a tropical cyclone report, first dated 3 February 2026 and revised on 29 June 2026. In a homogeneous comparison, NHC found that the Google DeepMind ensemble mean (GDMI) was the only aid to beat its official track forecast at 12 hours. NHC called GDMI a superior performer throughout the forecast period. GDMI's track errors were 15.6, 33.4, 47.4 and 64.2 nautical miles at 12 to 48 hours. The official errors were 19.5, 41.6, 60.5 and 88.7. Other aids also beat NHC's forecasts beyond 12 hours. The comparison rests on only six forecasts at 12 hours and two at 48 hours. NHC uses the model as experimental guidance and worked with Google DeepMind to develop it."}},"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":"Google DeepMind tropical cyclone model, ensemble mean (NHC designation GDMI)"}},"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":"The National Hurricane Center finds that only Google DeepMind's ensemble beat its track forecast at 12 hours for Tropical Storm Chantal","headline":"*GDMI* alone beat NHC's track forecast for Chantal at 12 hours"}},"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":["9d9fb246f6ca65abb4d081196869d34fd0d6f220a2c2dd87cf28a0b1f311e578"],"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":"Tropical Storm Chantal formed off the southeastern United States on 4 July 2025 and made landfall in South Carolina early on 6 July. It caused 6 direct deaths in North Carolina, most of them in flooding from heavy rain. The US National Hurricane Center (NHC) verified its forecasts in a tropical cyclone report, first dated 3 February 2026 and revised on 29 June 2026. In a homogeneous comparison, NHC found that the Google DeepMind ensemble mean (GDMI) was the only aid to beat its official track forecast at 12 hours. NHC called GDMI a superior performer throughout the forecast period. GDMI's track errors were 15.6, 33.4, 47.4 and 64.2 nautical miles at 12 to 48 hours. The official errors were 19.5, 41.6, 60.5 and 88.7. Other aids also beat NHC's forecasts beyond 12 hours. The comparison rests on only six forecasts at 12 hours and two at 48 hours. NHC uses the model as experimental guidance and worked with Google DeepMind to develop it.","replication":{"produced_by":["NHC included GDMI among the guidance models in its homogeneous comparison for Chantal.","NHC measured each model's track errors against Chantal's best track."],"must_hold":["The sample is small, with six forecasts at 12 hours and two at 48 hours.","The official forecast remains NHC's own judgment, and other aids also beat it at some lead times."],"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":29,"reviewed":2,"reviewed_complete":2,"reviewed_partial":0,"record_mapped":27,"review_not_assessed":62,"not_assessed":0,"complete":false,"by_state":{"value_present":29,"not_reported":0,"unresolved":62,"not_assessed":0,"not_applicable":0,"withheld":0,"source_unavailable":0}}},"presentation_version":"94e58d56d8377acb43c4dc0852ba529de2928dd0fa62164f380a28a6a8674bcf"}