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Title: ハイブリッド雲微物理モデルの開発
Other Titles: Development of Hybrid Microphysical Cloud model
Authors: 久芳, 奈遠美1 Browse this author
Authors(alt): Kuba, Naomi1
Issue Date: 31-Mar-2014
Publisher: 北海道大学低温科学研究所
Journal Title: 低温科学
Journal Title(alt): Low Temperature Science
Volume: 72
Start Page: 65
End Page: 69
Abstract: 気候変動予測において重要な雲の降水形成効率や放射特性は雲粒の数密度や粒径分布といった雲の微細構造に大きく依存し, 雲の微細構造は雲凝結核として機能する大気中のエアロゾル粒子に左右される. そこでエアロゾル粒子が雲の微細構造に及ぼす影響を精度よく見積もるため, 移流に関してはパーセルモデルと格子モデル, 雲粒の成長に関しては粒子法とビン法の両者を組み合わせたハイブリッド雲微物理モデルを開発した. このモデルでは,雲凝結核の雲粒への活性化は粒子法搭載パーセルモデルでラグランジュ的に計算し, 格子点上では雲粒及び雨滴の凝結成長・衝突併合・分裂を2モーメントビン法でセミラグランジュ的に計算し, 重力落下および移流は格子間でオイラー的に計算する. 本稿では, 雲粒の数密度や粒径分布を陽に計算できるモデルの解説と, このモデルを用いて行った研究事例について紹介する.
Precipitation efficiency and radiative properties of clouds are important factors for the prediction of climate change. These properties of clouds are significantly dependent on cloud microphysical structure (number concentration and size distribution of cloud droplets), which are affected by the aerosol particles to act as cloud condensation nuclei(CCN). We developed a hybrid cloud microphysical model which can calculate the number concentration and size distribution explicitly. A parcel model and a grid model comprise the cloud model, a particle method and a bin method comprise microphysical model. The condensational growth and activation of CCN in each parcel is estimated in a Lagrangian framework. Changes in cloud droplet size distribution arising from condensation, coalescence, and break-up are calculated on grid points using a two-moment bin method in a semi-Lagrangian framework. Sedimentation and advection of cloud/rain droplets are estimated in an Eulerian framework. Results of studies on the effects of CCN on cloud microphysical structure using this hybrid cloud microphysical model are described in this paper.
Description: Ⅱ. 詳細雲微物理モデルの開発と応用
Type: bulletin (article)
Appears in Collections:低温科学 = Low Temperature Science > 第72巻

Submitter: 低温科学研究所図書室

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