Collaborative Research: Examining Cloud-Radiation Feedback at Convective Scales in Tropical Cyclones
Collaborative Research: Examining Cloud-Radiation Feedback at Convective Scales in Tropical Cyclones
批准号:
2331121
负责人:
Yunji Zhang
金额:
$4.63万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-11-01 至 2026-10-31
中文摘要
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英文摘要
The overarching goal of this research is to expand our understanding of how tropical cyclones (e.g., hurricanes and typhoons) form and intensify. Tropical cyclones are the leading driver of losses to life and property in the US, with coastal population growth and climate change exacerbating these impacts. However, many gaps remain in understanding their formation and intensification, despite decades of study. This project therefore addresses an issue that only grows more pressing with time. The investigators will examine the interaction between clouds and radiation. Recent work reveals that this interaction accelerates the formation of tropical cyclones. This project will advance our understanding of this feedback at the scales of individual thunderstorm systems. By doing so, this research will ultimately help improve the forecasting of tropical cyclones, which will in turn help mitigate losses of life and property when they make landfall. The project will also directly support the leadership and professional development of early-career scientists, graduate researchers, and undergraduate researchers. In support of advancing STEM education, the project team will conduct K-12 educational outreach through “Skype a Scientist” and other virtual activities.To address science gaps related to cloud–radiation feedback in tropical cyclones (TCs), this research will address the following questions:1. What are the responses of buoyancy, vertical motion, and moist entropy to cloud–radiation forcing (CRF) on convective scales in tropical shallow convection, deep convection, and stratiform rainfall?2. What are the unique roles of radiative feedback in these regimes in accelerating convective upscale development and TC genesis, and through what mechanism(s) do they do so?3. How robust are simulated convective-scale responses to CRF to changes in model framework, physical parameterization, and grid resolution?These questions will be addressed through a series of novel, process-oriented numerical model experiments using both regional and global convection-permitting modeling. Following a hypothesis-driven approach, model experiments will be executed to examine the transient response of clouds and deep convection (i.e., on time scales down to ~1 hour and less) to the removal and switch-on of cloud–radiative forcing (CRF). A novel aspect of the experiments is the selective inclusion/exclusion of CRF in specific populations of clouds and precipitation. This approach is motivated by the novel hypothesis that CRF in stratiform rain and anvil clouds plays a leading role in accelerating TC genesis. These experiments will be cast in both realistic and idealized frameworks to support both robustness and representativeness. The project will also entail studying model uncertainty tied to the numerical representation of hydrometeors and radiative forcing in distinct cloud populations, being among the first to examine and document this sensitivity at convective scales in the context of TC genesis. The results of this project are therefore expected to support the advancement of model prediction and forecasting across a broad range of scales and settings. Since CRF is recognized to be an important physical process on a wide range of physical scales, the new lessons arising from this work are expected to apply more broadly than the TC subject.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.
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Coupling of Gravity Waves and Convection, and Their Impacts on the Dynamics and Predictability of Multiscale Processes Associated with Moist Baroclinic JetFront Systems
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批准号:1712290
-
项目类别:Continuing Grant
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资助金额:$68.31万
-
财政年份:2017
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负责人:Yunji Zhang
-
依托单位:
国内基金
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