{"query_echo":{"q":"","filters":{"analysis_type":["climate model comparison"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'climate model comparison' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":1,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=climate+model+comparison","stability":"beta","ai_marking":{"digital_source_type":{"uri":"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia","name":"Created using Generative AI"},"notice":"Summary and key insights are generated using artificial intelligence."},"results":[{"id":"wwatt-000044","url":"https://climateinsightsdirectory.org/document/wwatt-000044","title":"Attribution of the 2018 heat in Northern Europe","publisher":{"name":"World Weather Attribution","organization":"world-weather-attribution"},"document_type":"research paper","language":"en","date_published":"2018-07-28","source_url":"https://www.worldweatherattribution.org/attribution-of-the-2018-heat-in-northern-europe/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The study assesses the 2018 heatwave in Northern Europe using observational data and climate models to determine the role of human-induced warming. It finds that the probability of such an event has increased across the region, with the most significant increases in probability estimated in Ireland, Denmark, and the Netherlands. While the heat was most extreme in the high Arctic (northern Finland), where it exceeded historical records, the risk ratio was more easily quantified in southern regions. The authors conclude that anthropogenic climate change made these heatwaves more likely, though the exact magnitude of the increase is harder to quantify in Scandinavia due to high natural variability.","ai_generated":true,"unit":"wwatt-000044#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Anthropogenic climate change has increased the probability of the 2018 heatwave occurring across Northern Europe, with the likelihood generally estimated to be more than twice as high as it would have been without human influence.","ai_generated":true,"unit":"wwatt-000044#insight-1","date_modified":"2026-10-23"},{"text":"The heatwave was most extreme in the high Arctic, specifically in northern Finland, where temperatures reached levels not previously measured in over a century of data.","ai_generated":true,"unit":"wwatt-000044#insight-2","date_modified":"2026-10-23"},{"text":"In Ireland and Denmark, the increase in the probability of such heatwaves is well-supported by both observations and climate models, with a risk ratio of approximately two in Dublin and four in Denmark.","ai_generated":true,"unit":"wwatt-000044#insight-3","date_modified":"2026-10-23"},{"text":"In the Netherlands, observational data shows a much larger increase in the probability of hot extremes than climate models suggest, a discrepancy the authors note is a known issue in Central Europe.","ai_generated":true,"unit":"wwatt-000044#insight-4","date_modified":"2026-10-23"},{"text":"While anthropogenic climate change is concluded to have increased the odds of the 2018 heatwave in Scandinavia, the exact magnitude cannot be quantified because the high variability of summer weather makes the observational trend undetectable.","ai_generated":true,"unit":"wwatt-000044#insight-5","date_modified":"2026-10-23"},{"text":"The return periods for the 2018 heat events varied by location, being approximately 5 years in the Netherlands and 10 years in southern Scandinavia and Ireland, while exceeding 90 years in northern Finland.","ai_generated":true,"unit":"wwatt-000044#insight-6","date_modified":"2026-10-23"}],"climate_tags":["anthropogenic climate change","heat wave","extreme event attribution","climate modeling"],"geography_discussed":["Ireland","Netherlands","Denmark","Norway","Sweden","Finland","France","Scandinavia"],"frame_perspective":[],"analysis_type":["probabilistic event attribution","observational trend analysis","climate model comparison"]}]}