{"id":"AIBD-0753","title":"The Hong Kong Observatory finds that AI weather models such as FengWu and Pangu beat traditional models on 2024 tropical cyclone tracks","summary":"In its 2024 verification, the Hong Kong Observatory found that AI weather models matched or slightly beat traditional models for 10-day patterns and had smaller errors in typhoon tracks.","date_observed":"2025-12-01","date_basis":"source publication","date_precision":"month","benefit_status":"reported","source_collection":null,"source_entry":null,"account":"The Hong Kong Observatory (HKO) has run AI weather models in real time since mid-2023, including FengWu, FuXi, Pangu and AIFS. In an article on its website dated December 2025, HKO reports its verification of forecast models for 2024. HKO found that the AI models forecast weather patterns on a large scale over 10 days about as well as traditional models, or slightly better. For medium-range forecasts of tropical cyclone tracks over the western North Pacific and the South China Sea, the AI models did better. Their mean errors in track were generally smaller than those of traditional models. HKO adds that AI track errors at day 5 are still 300 to 400 kilometers. The AI models also underestimate the intensity of mature cyclones. In Super Typhoon Saola in 2023, the Pangu model forecast much weaker winds than traditional models did. HKO forecasters weigh AI and traditional models together and adjust products for local conditions.","category":"aggregate result","unexpected":false,"purpose":"Huawei, the Shanghai Artificial Intelligence Laboratory, Fudan University and ECMWF built Pangu-Weather, FengWu, FuXi and AIFS to forecast global weather with models trained on decades of past weather data.","system":"AI weather prediction models run in real time by HKO, including FengWu, FuXi, Pangu-Weather and AIFS","model_version":null,"developer":"Shanghai Artificial Intelligence Laboratory (FengWu), Fudan University (FuXi), Huawei Cloud (Pangu-Weather) and ECMWF (AIFS)","deployer":"Hong Kong Observatory","location":"Hong Kong, China (western North Pacific and South China Sea)","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":"HKO found smaller mean errors in tropical cyclone tracks for the AI models than for traditional models in 2024."}],"ai_role":{"status":"assessed","statement":"HKO verified the AI models' own forecasts against traditional models over 2024, which isolates the models' skill. HKO describes the models as deep learning systems trained on decades of meteorological data. HKO runs the models itself, so it is their operator, while the makers are outside HKO. No effect on HKO's official forecasts is measured."},"evidence":[{"kind":"report","citation":"Hong Kong Observatory. Applications of Artificial Intelligence Models in Weather Forecasting. Article by LAI Sin-ki, December 2025.","title":"Applications of Artificial Intelligence Models in Weather Forecasting","url":"https://www.hko.gov.hk/en/education/weather/data-and-technology/00761-Applications-of-Artificial-Intelligence-Models-in-Weather-Forecasting.html","date":null,"written_by":"deployer","quote":"According to the Observatory's verification on weather prediction models in 2024, the performance of various AI models in forecasting large-scale weather patterns over the next 10 days has already reached a level similar to or even slightly surpassed that of traditional models."}],"replication":{"produced_by":["HKO ran the AI models in real time and turned their output into forecasting products such as charts of tropical cyclone tracks.","HKO corrected model biases from past performance with statistical and machine learning methods."],"must_hold":["Forecasters still weigh several traditional and AI models and adjust for local conditions.","Intensity forecasts for mature cyclones come from traditional models, since AI models underestimate them."],"echoes":[]},"paired_incident":null,"headline":"HKO finds that AI models such as *FengWu* tracked 2024 typhoons better","metric":null,"comparator":{"against":"Traditional numerical weather prediction models verified by HKO for 2024","before":null,"after":null,"basis":"measured","quote":"A summary of forecast track errors for tropical cyclones in the western North Pacific and the South China Sea in 2024 (Figure 2) indicates that the mean errors of AI models (solid lines) are generally smaller than those of traditional models (dashed lines).","url":"https://www.hko.gov.hk/en/education/weather/data-and-technology/00761-Applications-of-Artificial-Intelligence-Models-in-Weather-Forecasting.html"},"later":null,"value":null,"developer_country":"Multiple: China, United Kingdom","deployer_country":"China (Hong Kong)","unrated_because":null,"brief_notes":null,"brief":null,"revisions":[{"date":"2026-10-31","change":"Added the record from the report of the Hong Kong Observatory.","source":"https://www.hko.gov.hk/en/education/weather/data-and-technology/00761-Applications-of-Artificial-Intelligence-Models-in-Weather-Forecasting.html","editor":"AIBD"}],"confidence":"claimed","shade":"low","claim_status":"The deployer's account","claim_basis":"Sources: the deployer's report. The cited evidence includes no independent source and no finding by an external body.","case_jurisdictions":["Hong Kong","China"],"profile":{"case_id":"AIBD-0753","catalog_version":"1.0.0","source_fingerprint":"be4e28e32631248b74ea1ceffc2caba031baf2bfb0f1103d602f575574e46bd3","collection_refs":[{"collection_id":"aibd","version":"2026-10-31"}],"source_ids":["AIBD-0753-source-0001"],"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":"Shanghai Artificial Intelligence Laboratory (FengWu), Fudan University (FuXi), Huawei Cloud (Pangu-Weather) and ECMWF (AIFS)","deployer":"Hong Kong Observatory"}},"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":"HKO verified the AI models' own forecasts against traditional models over 2024, which isolates the models' skill. HKO describes the models as deep learning systems trained on decades of meteorological data. HKO runs the models itself, so it is their operator, while the makers are outside HKO. No effect on HKO's official forecasts is measured."}}},"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":"HKO verified the AI models' own forecasts against traditional models over 2024, which isolates the models' skill. HKO describes the models as deep learning systems trained on decades of meteorological data. HKO runs the models itself, so it is their operator, while the makers are outside HKO. No effect on HKO's official forecasts is measured."}}},"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":"HKO found smaller mean errors in tropical cyclone tracks for the AI models than for traditional models in 2024."}]}},"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. The cited evidence includes 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":"HKO found smaller mean errors in tropical cyclone tracks for the AI models than for traditional models in 2024."}]}},"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":"HKO found smaller mean errors in tropical cyclone tracks for the AI models than for traditional models in 2024."}]}},"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. The cited evidence includes 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-0753-source-0001"],"reviewed_on":"2026-10-29"},"review_state":"reviewed","coverage":"complete","display":{"answer":"The deployer's account. Sources: the deployer's report. The cited evidence includes 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":"routine use","answer":"The system was in routine use. HKO has run the models in real time since mid-2023, and its forecasters refer to them in daily operations.","scope":"The period and activity described in the case."}},"provenance":{"kind":"source_review","basis":"Editorial assignment.","record_fields":["account","evidence"],"source_refs":["AIBD-0753-source-0001"],"reviewed_on":"2026-10-29"},"review_state":"reviewed","coverage":"complete","display":{"answer":"The system was in routine use. HKO has run the models in real time since mid-2023, and its forecasters refer to them in daily operations.","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-0753"}},"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":"The Hong Kong Observatory (HKO) has run AI weather models in real time since mid-2023, including FengWu, FuXi, Pangu and AIFS. In an article on its website dated December 2025, HKO reports its verification of forecast models for 2024. HKO found that the AI models forecast weather patterns on a large scale over 10 days about as well as traditional models, or slightly better. For medium-range forecasts of tropical cyclone tracks over the western North Pacific and the South China Sea, the AI models did better. Their mean errors in track were generally smaller than those of traditional models. HKO adds that AI track errors at day 5 are still 300 to 400 kilometers. The AI models also underestimate the intensity of mature cyclones. In Super Typhoon Saola in 2023, the Pangu model forecast much weaker winds than traditional models did. HKO forecasters weigh AI and traditional models together and adjust products for local conditions.","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":"HKO found smaller mean errors in tropical cyclone tracks for the AI models than for traditional models in 2024."}]}},"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":"Huawei, the Shanghai Artificial Intelligence Laboratory, Fudan University and ECMWF built Pangu-Weather, FengWu, FuXi and AIFS to forecast global weather with models trained on decades of past weather data."}},"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":"Hong Kong, China (western North Pacific and South China Sea)","developer_country":"Multiple: China, United Kingdom","deployer_country":"China (Hong Kong)"}},"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":"Huawei, the Shanghai Artificial Intelligence Laboratory, Fudan University and ECMWF built Pangu-Weather, FengWu, FuXi and AIFS to forecast global weather with models trained on decades of past weather data."}},"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":"2025-12-01","date_basis":"source publication","date_precision":"month","revisions":[{"date":"2026-10-31","change":"Added the record from the report of the Hong Kong Observatory.","source":"https://www.hko.gov.hk/en/education/weather/data-and-technology/00761-Applications-of-Artificial-Intelligence-Models-in-Weather-Forecasting.html","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":["HKO ran the AI models in real time and turned their output into forecasting products such as charts of tropical cyclone tracks.","HKO corrected model biases from past performance with statistical and machine learning methods."],"must_hold":["Forecasters still weigh several traditional and AI models and adjust for local conditions.","Intensity forecasts for mature cyclones come from traditional models, since AI models underestimate them."],"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 Hong Kong Observatory.","source":"https://www.hko.gov.hk/en/education/weather/data-and-technology/00761-Applications-of-Artificial-Intelligence-Models-in-Weather-Forecasting.html","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":"Hong Kong Observatory. Applications of Artificial Intelligence Models in Weather Forecasting. Article by LAI Sin-ki, December 2025.","title":"Applications of Artificial Intelligence Models in Weather Forecasting","url":"https://www.hko.gov.hk/en/education/weather/data-and-technology/00761-Applications-of-Artificial-Intelligence-Models-in-Weather-Forecasting.html","written_by":"deployer","quote":"According to the Observatory's verification on weather prediction models in 2024, the performance of various AI models in forecasting large-scale weather patterns over the next 10 days has already reached a level similar to or even slightly surpassed that of traditional models."}]}},"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-0753-source-0001"],"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":"Hong Kong Observatory. Applications of Artificial Intelligence Models in Weather Forecasting. Article by LAI Sin-ki, December 2025.","title":"Applications of Artificial Intelligence Models in Weather Forecasting","url":"https://www.hko.gov.hk/en/education/weather/data-and-technology/00761-Applications-of-Artificial-Intelligence-Models-in-Weather-Forecasting.html","written_by":"deployer","quote":"According to the Observatory's verification on weather prediction models in 2024, the performance of various AI models in forecasting large-scale weather patterns over the next 10 days has already reached a level similar to or even slightly surpassed that of traditional models."}]}},"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":"In its 2024 verification, the Hong Kong Observatory found that AI weather models matched or slightly beat traditional models for 10-day patterns and had smaller errors in typhoon tracks.","account":"The Hong Kong Observatory (HKO) has run AI weather models in real time since mid-2023, including FengWu, FuXi, Pangu and AIFS. In an article on its website dated December 2025, HKO reports its verification of forecast models for 2024. HKO found that the AI models forecast weather patterns on a large scale over 10 days about as well as traditional models, or slightly better. For medium-range forecasts of tropical cyclone tracks over the western North Pacific and the South China Sea, the AI models did better. Their mean errors in track were generally smaller than those of traditional models. HKO adds that AI track errors at day 5 are still 300 to 400 kilometers. The AI models also underestimate the intensity of mature cyclones. In Super Typhoon Saola in 2023, the Pangu model forecast much weaker winds than traditional models did. HKO forecasters weigh AI and traditional models together and adjust products for local conditions."}},"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":"AI weather prediction models run in real time by HKO, including FengWu, FuXi, Pangu-Weather and AIFS"}},"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 Hong Kong Observatory finds that AI weather models such as FengWu and Pangu beat traditional models on 2024 tropical cyclone tracks","headline":"HKO finds that AI models such as *FengWu* tracked 2024 typhoons better"}},"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":["bd020089d88a98b19df87acbdbf772692c4697957b8e47348abbc33670fc1497"],"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":"The Hong Kong Observatory (HKO) has run AI weather models in real time since mid-2023, including FengWu, FuXi, Pangu and AIFS. In an article on its website dated December 2025, HKO reports its verification of forecast models for 2024. HKO found that the AI models forecast weather patterns on a large scale over 10 days about as well as traditional models, or slightly better. For medium-range forecasts of tropical cyclone tracks over the western North Pacific and the South China Sea, the AI models did better. Their mean errors in track were generally smaller than those of traditional models. HKO adds that AI track errors at day 5 are still 300 to 400 kilometers. The AI models also underestimate the intensity of mature cyclones. In Super Typhoon Saola in 2023, the Pangu model forecast much weaker winds than traditional models did. HKO forecasters weigh AI and traditional models together and adjust products for local conditions.","replication":{"produced_by":["HKO ran the AI models in real time and turned their output into forecasting products such as charts of tropical cyclone tracks.","HKO corrected model biases from past performance with statistical and machine learning methods."],"must_hold":["Forecasters still weigh several traditional and AI models and adjust for local conditions.","Intensity forecasts for mature cyclones come from traditional models, since AI models underestimate them."],"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":"ca23fdcdcc46f38359b561f9414ea5dc1b00ea60c1db02d1b36f4fdb1a98dd71"}