[[["わかりやすい","easyToUnderstand","thumb-up"],["問題の解決に役立った","solvedMyProblem","thumb-up"],["その他","otherUp","thumb-up"]],[["必要な情報がない","missingTheInformationINeed","thumb-down"],["複雑すぎる / 手順が多すぎる","tooComplicatedTooManySteps","thumb-down"],["最新ではない","outOfDate","thumb-down"],["翻訳に関する問題","translationIssue","thumb-down"],["サンプル / コードに問題がある","samplesCodeIssue","thumb-down"],["その他","otherDown","thumb-down"]],[],[[["\u003cp\u003eWeatherNext Gen offers an experimental dataset of global medium-range ensemble weather forecasts, utilizing Google DeepMind's diffusion-based model.\u003c/p\u003e\n"],["\u003cp\u003eWeatherNext Graph provides an experimental dataset of global medium-range weather forecasts using Google DeepMind's graphical neural network model.\u003c/p\u003e\n"],["\u003cp\u003eBoth WeatherNext Gen and WeatherNext Graph include both real-time and historic weather data.\u003c/p\u003e\n"],["\u003cp\u003eBoth of the models in question include data regarding precipitation and temperature.\u003c/p\u003e\n"]]],["WeatherNext Gen and WeatherNext Graph are experimental datasets providing global, medium-range weather forecasts. These datasets, produced by operational versions of Google DeepMind's models, include both real-time and historical data. WeatherNext Gen utilizes a diffusion-based ensemble model, while WeatherNext Graph uses a graphical neural network. Both datasets cover forecasts, precipitation, and temperature, and are tagged with the \"gcp-public-data-weathernext\" identifier.\n"],null,[]]
