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在不整合到统计平衡的情况下调整地球系统模型
Timothy DelSole1, Michael K Tippett2
1Department of Atmospheric, Oceanic, and Earth Sciences George Mason University Fairfax VA USA.
这项研究引入了一种新的两相线性算法,用于估计地球系统模型 (ESM) 中的参数,即使是气候漂移. 这种方法提高了短时间模拟的准确性,为气候模型调整提供了有前途的方法.
科学领域:
- 气候科学 气候科学
- 计算建模 计算建模
- 统计分析 统计分析
背景情况:
- 地球系统模型 (ESM) 对气候预测至关重要,但参数估计具有挑战性.
- 模拟通常在达到统计平衡之前显示气候漂移,使参数估计复杂化.
- 现有的方法可能会产生不满意的参数估计,特别是对于短时间或漂移模拟.
研究的目的:
- 在地球系统模型 (ESM) 中开发和评估一种新的算法,用于在地球系统模型 (ESM) 中进行强大的参数估计.
- 在处理非平衡模拟和气候漂移时解决当前方法的局限性.
- 提高ESM的参数估计的准确性和可靠性,特别是社区地球系统模型版本2 (CESM2).
主要方法:
- 该研究建议将ESM时间序列视为自回归过程的输出.
- 一个新的策略将参数估计分为两个线性阶段,以克服非线性系统的局限性.
- 该算法用于估计社区地球系统模型版本2 (CESM2) 的对流方案中的参数.
主要成果:
- 修改后的算法成功地产生了精确的参数估计从扰动运行短为2年.
- 该方法有效处理显示气候漂移的模拟,产生与未明确解释气候漂移的方法相比的准确性.
- 最初的结果表明,自回归方法在严格的基于统计框架的模型调整方面具有潜力.
结论:
- 拟议的双相线性算法为调整地球系统模型 (ESM) 提供了一个有希望的策略,通过明确考虑气候漂移.
- 准确的参数估计甚至可以通过短时间的模拟和固有的气候漂移来实现.
- 目前的性能限制很可能是技术性的,并且可以接受未来的调查和改进.
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