用户量身定制的气候模型组合成员的子选择,用于影响研究
Anna E Sikorska-Senoner1, Jan Rajczak2, Massimiliano Zappa3
1Federal Office of Meteorology and Climatology MeteoSwiss, Zurich-Airport, Switzerland; Center for Climate Systems Modeling C2SM, ETH Zurich, Zurich, Switzerland.
The Science of the total environment
|August 27, 2024
概括
气候模型组合对于影响研究至关重要,但随机选择是常见的. 这项研究引入了一种新的方法,根据气候变化信号强度来选择有意义的合奏成员,从而提高一致性.
科学领域:
- 气候科学 气候科学
- 环境建模环境建模
背景情况:
- 气候模型组合是各个部门区域和地方影响研究的重要投入.
- 目前的做法往往涉及随机选择合奏成员由于计算约束,导致潜在的不一致性.
- 影响研究需要从偏差调整和缩小的全球和区域气候模型中获得区域规模的气候数据.
研究的目的:
- 开发一个针对用户量身定制的程序,用于对各种应用进行有意义的气候模型组合成员的次选择.
- 解决需要一种系统的方法来选择合唱团成员,而不仅仅是随机选择.
主要方法:
- 基于关键气候指数的气候变化信号 (CCS) 排名组成员的新程序.
- 选择三名代表性的合唱团成员:最强,最弱和中位数CCS.
- 使用水文冲击模型证明该方法的稳定性.
主要成果:
- 介绍了一种系统的方法来预选相关的气候组合成员.
- 该方法确保选择代表一系列气候变化信号的成员.
- 选择程序的稳定性在水文影响建模框架内得到了验证.
结论:
- 拟议的程序有助于影响建模人员选择合适的,具体案例的气候组合成员.
- 这种系统方法提高了气候变化影响研究的一致性和可比性.
- 改进的组合选择导致更可靠的环境和社会经济影响评估.
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