気候変動シミュレーションの大規模なアンサンブルにおけるモデリングの不確実性の定量化
James M Murphy1, David M H Sexton, David N Barnett
1Hadley Centre for Climate Prediction and Research, Met Office, FitzRoy Road, Exeter EX1 3PB, UK. james.murphy@metoffice.com
Nature
|August 13, 2004
まとめ
この研究では,大規模な気候モデルを使って気候変動の不確実性を定量化しています. これは,二酸化炭素の倍増による地球温度の上昇に対する信頼性の高い確率範囲を提供します.
科学分野:
- 気候科学 気候科学
- 地球システム科学 地球システム科学
- 環境モデリング
背景:
- グローバルな気候モデルは,将来の気候変動を予測するために不可欠です.
- モデルパラメータの不確実性は,幅広い予測につながります.
- 異なる気候モデルの相対的な質を評価することは困難です.
研究 の 目的:
- モデル不確実性と一致する気候変動の範囲を体系的に決定する.
- CO2の倍増に対する気候感受性の確率密度関数を推定する.
- 地域的な気候変動予測のより信頼性の高い範囲を提供するために.
主な方法:
- 異なるパラメータによる気候モデルバージョンの53人構成のアンサンブルの構築.
- 気候感受性に対する確率密度関数の推定.
- 確率密度関数を客観的な信頼性推定と専門家の助言で制限する.
主要な成果:
- 大気中のCO2の倍増に対する気候感受性に対する5-95%の確率範囲は,2.4-5.4°Cと推定されています.
- アンサンブルアプローチは,従来の方法よりも地域的な気候変動の幅が広いことを示しています.
- 客観的な信頼性推定は,モデル不確実性の評価を改善する.
結論:
- この体系的なアプローチは,気候変動予測の不確実性を軽減します.
- この発見は,気候変動への適応と緩和計画を立てるためのより堅実な基盤を提供します.
- 様々なパラメータを持つアンサンブルモデリングは,気候変動の影響を評価するための優れた方法を提供します.
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