Fluctuation-Dissipation, Stochasticity, and Climate-Dependent Subgrid-Scale Parameterizations for Efficient Climate Models

高效气候模型的波动耗散、随机性和气候相关的次网格尺度参数化

• 批准号: 254867285
• 负责人: Professor Dr. Ulrich Achatz
• 金额: --
• 依托单位: Russian Foundation for Basic Research
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2014
• 资助国家: 德国
• 起止时间: 2013-12-31 至 2018-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/254867285?language=en
• 关键词: Fluctuation; Dissipation; Stochasticity; Climate; Dependent

For several applications in climate modeling, e.g. paleoclimatology or climate sensitivity studies, there is need for an especially efficient atmosphere component. Low-order models, based on empirical orthogonal functions (EOFs) and using an empirical deterministic linear subgrid-scale (SGS) parameterization, compare well with general circulation models, so that they could be an interesting tool in this regard. A remaining problem has been the climate sensitivity of the empirical SGS parameterization. Two closely interrelated approaches shall be investigated to address this: (1) Recent work indicates that the fluctuation-dissipation theorem (FDT) has a potential for predicting the response of an empirical SGS parameterization to external perturbations, especially if the system which it is applied to has enough fast components. The barotropic vorticity equation used in that study allows only barotropic planetary waves. It is to therefore to be expected that in a more realistic setting the FDT strategy will be even more fruitful. Hence, and also on the path to successively increasing realism, it is planned to extend the FDT approach to low-order models of quasigeostrophic three-layer (QG3L) dynamics, allowing synoptic-scale baroclinic waves, with an empirical linear-stochastic (Ornstein-Uhlenbeck, OU) parameterization.(2) Even more based on first principles than the approach with an empirical OU parameterization is stochastic mode reduction (SMR). The explicit derivation of the effective fast-mode impact in SMR, with multiplicative noise and nonlinear deterministic terms supplementing the forcing and additive noise of an OU parameterization, is expected to yield more robust a model behavior in a perturbed climate than a direct, purely data-driven, OU parameterization of the SGS. As models developed by such methods tend to have a climate bias, however, and given the success of the empirical methods described above, it is intended to try and improve the performance of SMR low-order models by empirically modifying their deterministic forcing and linear dynamics. Once more in the QG3L context, the FDT shall be used for predicting the response of all empirical elements in the modified SMR models to external perturbations.The ultimate purpose of these efforts is an efficient atmospheric model, based on first principles as much as presumably possible at the present state of the art, and using the FDT for controlling the climate dependence of the remaining empirical elements.

对于气候建模中的多种应用，例如古气候学或气候敏感性研究，需要特别有效的大气成分。基于经验正交函数 (EOF) 并使用经验确定性线性亚网格尺度 (SGS) 参数化的低阶模型与一般环流模型进行了很好的比较，因此它们在这方面可能是一个有趣的工具。剩下的问题是经验 SGS 参数化的气候敏感性。应研究两种密切相关的方法来解决这个问题：（1）最近的工作表明，波动耗散定理（FDT）有可能预测经验SGS参数化对外部扰动的响应，特别是如果它所应用的系统具有足够快的组件。该研究中使用的正压涡度方程仅允许正压行星波。因此，可以预期，在更现实的环境中，FDT 策略将更加富有成效。因此，在逐步提高真实性的道路上，计划将 FDT 方法扩展到准地转三层 (QG3L) 动力学的低阶模型，允许天气尺度的斜斜波，并具有经验线性随机（Ornstein-Uhlenbeck，OU）参数化。（2）比经验 OU 的方法更基于第一原理 参数化是随机模式缩减（SMR）。 SMR 中有效快速模式影响的显式推导，以及乘性噪声和非线性确定性项补充了 OU 参数化的强迫和加性噪声，预计将在扰动气候中产生比直接、纯数据驱动的 SGS OU 参数化更稳健的模型行为。然而，由于此类方法开发的模型往往存在气候偏差，并且考虑到上述经验方法的成功，因此旨在通过经验修改其确定性强迫和线性动力学来尝试提高SMR低阶模型的性能。再次在 QG3L 背景下，FDT 将用于预测修改后的 SMR 模型中所有经验元素对外部扰动的响应。这些努力的最终目的是建立一个高效的大气模型，尽可能基于当前技术水平的第一原理，并使用 FDT 来控制其余经验元素的气候依赖性。