Robust Solar Radiation Modification Strategy for Achieving Temperature Targets
気温目標達成のための頑健な太陽放射改変戦略 (AI 翻訳)
Guoliang Zheng, Jianmin Wu, Zhang Tl, Hua Liao
🤖 gxceed AI 要約
日本語
本研究は、ミンマックス後悔（MMR）基準を統合評価モデルに組み込み、冷却効率やSRM関連被害、気候感度の不確実性下で気温目標を頑健に達成するSRM戦略を解析。結果、2050年頃までは抑制的、その後は加速的な二段階展開が最適で、目標未達リスクと福利損失のバランスを取る。
English
This study develops a solar radiation modification (SRM) decision framework embedding the min-max regret rule into an integrated assessment model to robustly achieve temperature targets under uncertainty in cooling efficiency, SRM damages, and climate sensitivity. Results show a two-phase strategy—restrained deployment before mid-century and accelerated deployment after—balancing target-failure risk against welfare costs, remaining robust across uncertainty sets.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本ではSRMは主流ではないが、気候リスク管理や不確実性下の政策判断への示唆は、気候変動適応策や長期的な排出削減戦略の補完として検討価値がある。
In the global GX context
Contributes to global climate policy debates on SRM governance and robust decision-making under uncertainty, relevant to temperature-target commitments (e.g., Paris Agreement) but tensions with decarbonization-first GX agendas.
👥 読者別の含意
🔬研究者:Provides a novel IAM framework for climate engineering policy under deep uncertainty, useful for robustness analysis methods.
🏛政策担当者:Offers a structured approach to weigh SRM deployment risks and welfare trade-offs when considering climate targets.
📄 Abstract（原文）
Solar radiation modification (SRM) provides an additional cooling option for limiting warming, but uncertainties about its realized cooling outcomes challenge the robustness of temperature-target strategies. This study develops an SRM decision framework that is robust in achieving the temperature target by embedding the min-max regret (MMR) rule into an integrated assessment model. We evaluate SRM strategies under uncertainty in cooling efficiency, SRM-related damages, and climate sensitivity. The results show that policies designed for adverse cooling-response states can better avoid temperature-target failure but generate great welfare losses from over-deployment. The MMR-based strategy exhibits distinct phasing, with restrained deployment before mid-century and accelerated deployment thereafter. Sensitivity analyses show that this two-phase pattern remains robust across alternative uncertainty sets. Overall, the robust framework balances the risk of temperature-target failure against the welfare cost of over-deployment under persistent uncertainties.
🔗 Provenance — このレコードを発見したソース
- openalex https://pmc.ncbi.nlm.nih.gov/articles/PMC13396980/first seen 2026-08-01 05:22:52
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