{"id":7415,"date":"2023-11-15T09:23:17","date_gmt":"2023-11-15T09:23:17","guid":{"rendered":"https:\/\/dailyai.com\/?p=7415"},"modified":"2023-11-15T11:28:59","modified_gmt":"2023-11-15T11:28:59","slug":"googles-graphcast-model-predicts-weather-better-than-the-rest","status":"publish","type":"post","link":"https:\/\/dailyai.com\/da\/2023\/11\/googles-graphcast-model-predicts-weather-better-than-the-rest\/","title":{"rendered":"Googles GraphCast-model forudsiger vejret bedre end resten"},"content":{"rendered":"<p><strong>Google DeepMinds maskinl\u00e6ringsmodel, GraphCast, slog traditionelle vejrprognosemetoder med en vis afstand i tidlige tests.<\/strong><\/p>\n<p>At forudsige vejret pr\u00e6cist er en vanskelig opgave, der bliver eksponentielt kompleks, jo flere dage ud i fremtiden vi \u00f8nsker at forudsige.<\/p>\n<p>Det er derfor, meteorologiske organisationer er afh\u00e6ngige af verdens kraftigste supercomputere til at knuse de komplekse forudsigelsesalgoritmer, der fort\u00e6ller os, om det vil regne i morgen eller ej.<\/p>\n<p>IFS-modellen (Integrated Forecasting System), som European Centre for Medium-Range Weather Forecasts (ECMWF) bruger, anses for at v\u00e6re den mest n\u00f8jagtige europ\u00e6iske vejrmodel. Og GraphCast har lige sl\u00e5et den med flere l\u00e6ngder.<\/p>\n<p><a href=\"https:\/\/deepmind.google\/discover\/blog\/graphcast-ai-model-for-faster-and-more-accurate-global-weather-forecasting\/\" target=\"_blank\" rel=\"noopener\">GraphCast<\/a> var i stand til at forudsige vejret 10 dage i forvejen hurtigere og mere pr\u00e6cist end ECMWF i mere end 90% af 1.380 verifikationsm\u00e5l.<\/p>\n<p>Det er praktisk at vide, om du skal tage din paraply med p\u00e5 arbejde, men at forudsige ekstreme vejrbegivenheder pr\u00e6cist er der, hvor GraphCast kan f\u00e5 en betydelig indflydelse.<\/p>\n<p>I september, da orkanen Lee var 9 dage fra at g\u00e5 i land, arbejdede vejrkontorerne h\u00e5rdt p\u00e5 at forudsige, hvilken by der ville blive h\u00e5rdest ramt af stormen.<\/p>\n<p>IFS-modellen gav en grov forudsigelse af, at orkanen ville ramme nogle nord\u00f8stlige byer eller muligvis g\u00e5 helt forbi dem. I mellemtiden forudsagde GraphCast, at orkanen Lee ville ramme Nova Scotia.<\/p>\n<p>F\u00f8rst 3 dage senere kom IFS til samme konklusion, som i sidste ende viste sig at v\u00e6re korrekt. Forestil dig den forbedring af ressourceanvendelsen og beredskabet, som 3 ekstra dage ville muligg\u00f8re.<\/p>\n<p>Pushmeet Kohli, VP for forskning hos Google DeepMind, sagde: \"Vejrforudsigelse er et af de mest udfordrende problemer, som menneskeheden har arbejdet med i lang, lang tid. Og hvis man ser p\u00e5, hvad der er sket i de sidste par \u00e5r med klimaforandringerne, er det et utroligt vigtigt problem.\"<\/p>\n<blockquote class=\"twitter-tweet\">\n<p dir=\"ltr\" lang=\"en\" style=\"text-align: center;\">Vi pr\u00e6senterer GraphCast: vores avancerede AI-model, der leverer 10-dages vejrudsigter med hidtil uset n\u00f8jagtighed p\u00e5 under et minut. \ud83c\udf26\ufe0f<\/p>\n<p>Det kan endda hj\u00e6lpe med at forudsige cykloners potentielle baner l\u00e6ngere ude i fremtiden.<\/p>\n<p>S\u00e5dan her fungerer det. \ud83e\uddf5 <a href=\"https:\/\/t.co\/ygughpkdeP\">https:\/\/t.co\/ygughpkdeP<\/a> <a href=\"https:\/\/t.co\/0Y6DyBXDow\">pic.twitter.com\/0Y6DyBXDow<\/a><\/p>\n<p style=\"text-align: center;\">- Google DeepMind (@GoogleDeepMind) <a href=\"https:\/\/twitter.com\/GoogleDeepMind\/status\/1724443443873624115?ref_src=twsrc%5Etfw\">14. november 2023<\/a><\/p>\n<\/blockquote>\n<p><script async src=\"https:\/\/platform.twitter.com\/widgets.js\" charset=\"utf-8\"><\/script><\/p>\n<h2>Hvordan fungerer det?<\/h2>\n<p>Traditionelle modeller som IFS bruger \"numerisk vejrforudsigelse\" (NWP). Det indeb\u00e6rer indsamling af enorme m\u00e6ngder data fra vejrsensorer, som derefter indl\u00e6ses i komplekse ligninger, som supercomputere behandler.<\/p>\n<p>Ligningerne justeres af hold af eksperter og er blevet mere og mere pr\u00e6cise, men de kr\u00e6ver stadig en masse computerkraft og tager lang tid at komme frem til en forudsigelse.<\/p>\n<p>NWP fors\u00f8ger i bund og grund at bruge algoritmer til at modellere, hvordan atmosf\u00e6ren fungerer, for at forudsige, hvad der vil ske som det n\u00e6ste.<\/p>\n<p>Det, GraphCast g\u00f8r, er meget enklere, men kan ikke klares med traditionelle ligninger.<\/p>\n<p>GraphCast-modellen bruger maskinl\u00e6ringsbaseret vejrforudsigelse (MLWP) og er tr\u00e6net p\u00e5 omkring 50 \u00e5rs historiske vejrdata.<\/p>\n<p>Derefter tager den disse data, og i stedet for at skabe en model af vores atmosf\u00e6re leder den efter m\u00f8nstre i dataene. En AI-model er fantastisk til at finde subtile m\u00f8nstre, som det er umuligt for faste ligninger at opdage.<\/p>\n<p>GraphCast ser grundl\u00e6ggende p\u00e5 de aktuelle vejrdata og siger: \"Sidste gang jeg s\u00e5 disse forhold, var det n\u00e6ste, der skete ...\" og laver derefter en forudsigelse.<\/p>\n<p>Detaljeringsgraden, eller opl\u00f8sningen, af GraphCast-forudsigelser er ikke s\u00e5 god som traditionelle modeller, men den er meget mere pr\u00e6cis og meget hurtigere.<\/p>\n<p>Hvor en supercomputer ville v\u00e6re n\u00f8dt til at knuse vejrdata i timevis for at komme med en forudsigelse, kan GraphCast producere et resultat p\u00e5 mindre end et minut p\u00e5 en enkelt Google TPU v4-maskine.<\/p>\n<p>MLWP er st\u00e6rkt afh\u00e6ngig af historiske data fra traditionelle NWP-modeller, s\u00e5 den vil ikke erstatte dem helt endnu.<\/p>\n<p>Men at bruge et v\u00e6rkt\u00f8j som GraphCast sammen med de nuv\u00e6rende metoder vil hj\u00e6lpe med at forudsige ekstreme vejrbegivenheder hurtigere og mere pr\u00e6cist.<\/p>\n<p>Google DeepMind g\u00f8r GraphCast til open source, og det bruges allerede af ECMWF.<\/p>","protected":false},"excerpt":{"rendered":"<p>Google DeepMinds maskinl\u00e6ringsmodel, GraphCast, slog traditionelle metoder til vejrudsigter med en vis afstand i tidlige tests. At forudsige vejret pr\u00e6cist er en vanskelig opgave, der bliver eksponentielt kompleks, jo flere dage ud i fremtiden vi \u00f8nsker at forudsige. Derfor er meteorologiske organisationer afh\u00e6ngige af verdens kraftigste supercomputere til at udregne de komplekse forudsigelsesalgoritmer, der fort\u00e6ller os, om det vil regne i morgen eller ej. IFS-modellen (Integrated Forecasting System), som European Centre for Medium-Range Weather Forecasts (ECMWF) bruger, anses for at v\u00e6re den mest n\u00f8jagtige europ\u00e6iske vejrmodel. Og GraphCast har lige sl\u00e5et den med flere l\u00e6ngder.<\/p>","protected":false},"author":6,"featured_media":7417,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[83],"tags":[102,105],"class_list":["post-7415","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-product","tag-google","tag-machine-learning"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Google\u2019s GraphCast model predicts weather better than the rest | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/da\/2023\/11\/googles-graphcast-model-predicts-weather-better-than-the-rest\/\" \/>\n<meta property=\"og:locale\" content=\"da_DK\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Google\u2019s GraphCast model predicts weather better than the rest | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Google DeepMind\u2019s machine learning model, GraphCast, beat traditional weather forecasting methods by some distance in early testing. Predicting the weather accurately is a difficult task that becomes exponentially complex the more days into the future we want to predict. This is why meteorological organizations rely on the world\u2019s most powerful supercomputers to crunch the complex predictive algorithms that tell us if it will rain tomorrow or not. The Integrated Forecasting System (IFS) model that the European Centre for Medium-Range Weather Forecasts (ECMWF) uses is considered the most accurate European weather model. And GraphCast just beat it by a long way.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dailyai.com\/da\/2023\/11\/googles-graphcast-model-predicts-weather-better-than-the-rest\/\" \/>\n<meta property=\"og:site_name\" content=\"DailyAI\" \/>\n<meta property=\"article:published_time\" content=\"2023-11-15T09:23:17+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-11-15T11:28:59+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/11\/weather-prediction.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1000\" \/>\n\t<meta property=\"og:image:height\" content=\"373\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Eugene van der Watt\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@DailyAIOfficial\" \/>\n<meta name=\"twitter:site\" content=\"@DailyAIOfficial\" \/>\n<meta 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