纠正区域气候模型边界变量中的偏差,以改进高影响复合事件的模拟
Youngil Kim1, Jason P Evans2, Ashish Sharma1
1School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW, Australia.
iScience
|September 8, 2023
概括
多变量偏差校正增强了区域气候模型 (RCM) 的复合事件分析. 这种方法改善了极端天气,特别是高温和降水的模拟,提供了更准确的气候预测.
科学领域:
- 气候科学 气候科学
- 环境建模环境建模
- 极端天气事件 极端天气事件
背景情况:
- 气候模型对于评估复合事件至关重要,但系统偏差引入不确定性.
- 对变量之间的物理关系的准确表示对于表征复合事件至关重要.
研究的目的:
- 调查区域气候模型 (RCM) 输入中的系统偏差的多变量偏差校正.
- 通过增强物理关系的表示来改善复合事件的表征.
主要方法:
- 应用多变量偏差校正到RCM边界条件.
- 分析了由八种不同的危险产生的四种类型的复合事件.
- 将经过校正的RCM模拟与未经校正和无变量校正的模拟进行了比较.
主要成果:
- 多变量偏差校正大大改善了复合事件的RCM表示.
- 对于一致的高温和高降水事件,观察到显著的改善.
- 未经纠正的RCM显示了回报期的负偏差,过度模拟复合事件.
结论:
- 多变量偏差校正有效减少复合事件分析的RCM中的系统偏差.
- 这种方法提高了模拟极端天气组合,特别是温度和降水极端的准确性.
- 改进的RCM模拟对于可靠的气候变化影响评估至关重要.
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