Unique Turbulence Dynamics in Hurricane Boundary Layers and Improving Their Parameterizations in Numerical Weather Prediction Models

飓风边界层中独特的湍流动力学及其在数值天气预报模型中的参数化改进

基本信息

批准号：
2228299
负责人：
Mostafa Momen
金额：
$ 45.82万
依托单位：
University of Houston
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-11-01 至 2025-10-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2228299&HistoricalAwards=false
关键词：
Unique Turbulence Dynamics Hurricane Boundary

项目摘要

Hurricanes have been the costliest natural disaster in US history thus far by causing billions of dollars in damage. Ocean warming and climate change can exacerbate tropical cyclone destruction by increasing the frequency and intensity of future major hurricanes. Only four recent hurricanes — Katrina, Sandy, Maria, and Harvey — resulted in more than $450B in damages and about 5,000 fatalities. Thus, it is imperative for the scientific community to better understand and forecast hurricane dynamics and its turbulent winds in order to effectively mitigate their economic ramifications. Although turbulence plays a significant role in hurricane evolution, it is neither thoroughly understood nor parameterized in hurricane flows. Given the remarkable impacts of future hurricanes on humans and the lack of a reliable turbulence scale model for such rotating flows, a high-fidelity hurricane model is now essential. This project aims to address this knowledge gap using a combination of numerical weather prediction (NWP) models and observations to thrust forward the understanding of hurricane turbulence, and to develop practical methodologies for improving hurricane forecasts in NWP models.The research provides pathways to new frontiers in turbulence theory and modeling of hurricane flows. In particular, the driving hypothesis of the project is “turbulence dynamics in hurricane boundary layers (HBLs) are significantly different from typical atmospheric boundary layers (ABLs) due to rotation in HBLs and their large Rossby number (centrifugal/Coriolis force); therefore, existing turbulence models in NWPs limit the accuracy of hurricane forecasts.” This hypothesis will be tested by answering these open research questions 1) How do hurricanes modulate the characteristic mixing length scales and turbulence dynamics in the HBL? and 2) How should the horizontal and vertical turbulent fluxes of an HBL be parameterized in NWPs compared to typical ABLs? To answer these questions, a unique combination of high-fidelity large-eddy simulations (LESs), NWPs, and observations will be employed. The preliminary results support the project’s central hypothesis by demonstrating remarkably different turbulence structures and energy spectra in HBLs when compared to typical ABLs, and substantial improvements in NWP’s hurricane forecasts when current turbulence models are altered. Hence, addressing the above questions will advance the field of physical and dynamic meteorology by elucidating the distinctive turbulence mechanisms in hurricanes compared to conventional much-studied ABLs. Other notable expected outcomes of the project include an extensive dataset of high-resolution LESs of HBLs, new physics-based turbulence closures with rotation correction that are specifically designed for real hurricanes, and a dataset of improved hurricane simulations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

到目前为止，飓风一直是美国历史上最昂贵的自然灾害，造成数十亿美元的损失。海洋变暖和气候变化会通过增加未来重大飓风的频率和强度来加剧热带气旋破坏。最近只有四起飓风 - 卡特里娜飓风，桑迪，玛丽亚和哈维 - 造成了超过450b美元的损失和约5,000人的死亡。这是科学界必须更好地理解和预测飓风动态及其动荡的风，以便有效地减轻其经济后果。尽管湍流在飓风的进化中起着重要作用，但在飓风流中既没有被彻底理解也没有参数。鉴于未来飓风对人类的显着影响以及缺乏可靠的湍流量表模型，因此现在必不可少的高保真飓风模型。该项目旨在通过数值天气预测（NWP）模型和观察结果的结合来解决这一知识差距，以推动对飓风湍流的理解，并开发用于改善NWP模型中森林森林的实用方法。该研究为飓风理论和飓风范围的建模提供了新领域的途径。特别是，该项目的驾驶假设是“飓风边界层中的湍流动力学（HBL）与典型的大气边界层（ABLS）显着不同，因为HBL的旋转及其较大的Rossby数字（Centrifugal/Coriolis Force）（因此，NWPS中的现有湍流模型）;该假设将通过回答这些开放研究问题来检验1）飓风如何调节HBL中的特征混合长度尺度和湍流动力学？ 2）与典型的ABL相比，在NWP中，HBL的水平和垂直湍流应如何在NWP中进行参数？为了回答这些问题，将采用高保真大型模拟（少），NWP和观察结果的独特组合。与典型的ABL相比，HBLS中的湍流结构和能量光谱明显不同，并且在改变当前的飓风模型时，HBLS的湍流结构和能量光谱明显不同，从而支持该项目的中心假设。因此，解决上述问题将通过阐明飓风的独特湍流机制与常规研究的ABL相比，通过阐明飓风的独特湍流机制来推动物理和动态气象的领域。该项目的其他值得注意的预期结果包括大量高分辨率的HBL，新的基于物理的湍流封闭，具有专门为实际飓风设计的旋转校正，以及改进的飓风模拟数据集。该奖项反映了NSF的法定任务，并通过评估了CR的支持，该奖项反映了CR的支持者，其知识均受到评估。