The Impact of Rapidly-Varying Heat Fluxes on Air-Sea Interaction and Climate Variability

快速变化的热通量对海气相互作用和气候变化的影响

• 批准号: 0552047
• 负责人: Philip Sura
• 金额: $ 30万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-15 至 2008-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0552047&HistoricalAwards=false
• 关键词: Impact; Rapidly; Varying; Heat; Fluxes

The main focus of the research is to study the impact of rapidly varying (on daily and sub-daily timescales) sea surface heat fluxes on atmosphere-ocean coupling. Literature indicates that the clear separation between the dynamical timescales of the ocean and atmosphere allows a simple paradigm for much air-sea interaction in which the rapidly varying component of surface heat fluxes is approximated by a stochastic term. However, this heat flux term depends upon not only the "fast" atmosphere but also upon the "slow" ocean. Thus, the stochastic noise should not be independent of the oceanic state, contrary to most past studies. Notably, such state-dependent (multiplicative) noise can alter low-frequency ocean dynamics through a process known as noise-induced drift. Accurate representation of this drift is necessary but difficult in climate models, since noise-induced drift cannot be simply parameterized by constant terms as its strength depends on the variance of the heat flux variability, a function of time and space. The aim of this project is to understand how the multiplicative noise character of the heat flux contributes to climate variability and predictability on interannual to inter-decadal timescales, and how it might contribute to biases found in many coupled models. Thus, it is imperative to study the effect of state-dependent rapidly varying heat fluxes (including heat advection through ocean currents, surface heat fluxes, entrainment, and horizontal mixing) using observations and coupled model runs. Since deviations from Gaussianity, or anomalous statistics, can shed light on the underlying state-dependent character of the heat fluxes, one of the main objective of the research is to globally map the non-Gaussianity (e.g., higher moments: skewness, kurtosis) of oceanic and atmospheric quantities relevant for atmosphere-ocean coupling from a broad range of observational datasets and a hierarchy of coupled model runs. Experiments with coupled models will also be used to understand how details of numerical coupling impact model representation of this process. Intellectual Merit: A meticulous study of fast-varying heat fluxes and its impact on air-sea interaction is important because the fast-varying variability of heat fluxes must be accurately simulated to correctly model sea surface temperature (SST) and air temperature (TAIR) variability, and the coupling scheme must be appropriate to capture heat flux variability on daily and sub-daily time scales. The PI will (1) extend a systematic stochastic framework that has been developed over the last decade to understand the interaction of slowly and rapidly varying components of the climate system, such as SST and TAIR anomalies, and (2) develop improved coupling schemes and the implementation of stochastic parameterizations in weather and climate models. Broader Impacts: The research will further our understanding on how the ocean interacts with the atmosphere and vice versa and helps climate diagnostics and modeling communities. The results will be disseminated as maps of non-Gaussian statistics of various quantities on the NOAA-CIRES CDC web page.

该研究的主要重点是研究快速变化（在日和次日时间尺度上）海面热通量对大气-海洋耦合的影响。文献表明，海洋和大气的动态时间尺度之间的明显分离为许多空气-海洋相互作用提供了一个简单的范式，其中表面热通量的快速变化分量通过随机项来近似。然而，这个热通量项不仅取决于“快”的大气，还取决于“慢”的海洋。因此，与过去的大多数研究相反，随机噪声不应独立于海洋状态。值得注意的是，这种状态相关（乘性）噪声可以通过称为噪声引起的漂移的过程改变低频海洋动力学。在气候模型中准确表示这种漂移是必要的，但很困难，因为噪声引起的漂移不能简单地用常数项参数化，因为其强度取决于热通量变化的方差（时间和空间的函数）。该项目的目的是了解热通量的乘性噪声特征如何影响年际至年代际时间尺度上的气候变化和可预测性，以及它如何导致许多耦合模型中发现的偏差。因此，有必要利用观测和耦合模型运行来研究与状态相关的快速变化的热通量（包括通过洋流的热平流、表面热通量、夹带和水平混合）的影响。由于与高斯性或异常统计的偏差可以揭示热通量的潜在状态相关特征，因此研究的主要目标之一是从广泛的观测数据集和层次结构中全局绘制与大气-海洋耦合相关的海洋和大气量的非高斯性（例如，高矩：偏度、峰度）。 耦合模型运行。耦合模型的实验也将用于了解数值耦合的细节如何影响该过程的模型表示。 智力优点：对快速变化的热通量及其对海气相互作用的影响进行细致的研究非常重要，因为必须准确模拟热通量的快速变化变化，以正确模拟海面温度（SST）和气温（TAIR）变化，并且耦合方案必须适合捕获日和亚日时间尺度上的热通量变化。 PI 将 (1) 扩展过去十年开发的系统随机框架，以了解气候系统缓慢和快速变化组成部分的相互作用，例如 SST 和 TAIR 异常，以及 (2) 开发改进的耦合方案并在天气和气候模型中实施随机参数化。 更广泛的影响：这项研究将进一步了解海洋与大气如何相互作用，反之亦然，并有助于气候诊断和建模社区。结果将作为各种数量的非高斯统计图在 NOAA-CIRES CDC 网页上传播。