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What is Weather?01:07

What is Weather?

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Overview
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General External Flow Characteristics01:26

General External Flow Characteristics

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The study of external flow is essential for creating structures and objects that interact efficiently and safely with moving fluids, such as air or water. When a body is immersed in a flowing fluid, it experiences two primary forces: drag, which opposes motion along the flow direction, and lift, which acts perpendicular to the flow. The shape, size, and orientation of the object influence these forces.Streamlined and Blunt Bodies in External FlowObjects in fluid flow are classified as...
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Precipitation Processes01:12

Precipitation Processes

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The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
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Climate refers to the prevailing weather conditions in a specific area over an extended period. As the saying goes, “Climate is what you expect. Weather is what you get.” Climate is influenced by geographic factors, such as latitude, terrain, and proximity to bodies of water.
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Variation of Atmospheric Pressure01:18

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Change in atmospheric pressure with height is particularly interesting. The decrease in atmospheric pressure with increasing altitude is due to the decreasing gravitational force per unit area as we move away from the surface of the earth.
Assuming the air temperature is constant at a given altitude and that the ideal gas law of thermodynamics describes the atmosphere to a good approximation, one can find the variation of atmospheric pressure with height.
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Navier–Stokes Equations01:28

Navier–Stokes Equations

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For incompressible Newtonian fluids, where density remains constant, stresses show a linear relationship with the deformation rate, defined by normal and shear stresses. Normal stresses depend on the pressure exerted on the fluid and the rate of deformation in specific directions, which determines how fluid flows under varying pressures. Shear stresses, on the other hand, act tangentially across fluid layers. They explain how adjacent fluid layers slide relative to one another, connecting...
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天気と気候に関するニューラル一般循環モデル

Dmitrii Kochkov1, Janni Yuval2, Ian Langmore3

  • 1Google Research, Mountain View, CA, USA. dkochkov@google.com.

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まとめ

新しい一般循環モデル (GCM) は,ディープラーニングと物理ベースのシミュレーションを統合し,天気と気候の予測を改善します. このハイブリッドアプローチは,既存の方法と比較して,計算上の節約と競争力のある予測能力を提供します.

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科学分野:

  • 地球システム科学
  • 気候モデリング
  • 機械学習アプリケーション

背景:

  • 一般循環モデル (GCM) は,物理に基づいたシミュレーションに頼って,天気と気候の予測に不可欠です.
  • 最近の進歩は 機械学習モデルが 決定的な天気予報でGCMに匹敵するか 超えていることを示しています
  • 既存の機械学習モデルは 長期の気候シミュレーションには 安定性がないし 総合的な予測も改善していません

研究 の 目的:

  • 機械学習と微分可能な物理ベースのダイナミクスを融合させる新しい一般循環モデル (GCM) を開発する.
  • 決定的な天気予報,アンサンブル予報,長期的な気候シミュレーションにおけるGCMのパフォーマンスを評価する.
  • 新しいハイブリッドGCMの計算効率と安定性を評価する.

主な方法:

  • NeuralGCMと呼ばれるハイブリッドGCMを開発し,微分可能な大気動力学ソルバーと機械学習コンポーネントを組み合わせた.
  • 天気予報のための再分析データ (1〜15日) に関するNeuralGCMの訓練と評価.
  • NeuralGCMの気候シミュレーション能力を数十年で評価し, 140kmの解像度で海面温度を規定しました.

主要な成果:

  • NeuralGCMは最先端の機械学習モデルを使用して短期的な天気予報 (1〜10日) の競争力を発揮しています.
  • これは,欧州中期気象予報センターによる中期 (1~15日) の天気予報のアンサンブル予測と一致します.
  • NeuralGCMは10年間の気候指標を正確に追跡し,熱帯サイクロンなどの新興現象をシミュレートし,重要な計算コストを削減します.

結論:

  • エンドツーエンドのディープラーニングは,地球システム科学の伝統的なGCMタスクと互換性があり,それを強化することができます.
  • ハイブリッドアプローチは,天気と気候の予測に計算効率の良い代替手段を提供します.
  • NeuralGCMは地球の気候システムを理解するために不可欠な大規模な物理シミュレーションの約束を示しています.