Collaborative Research: Dynamics, Thermodynamics, and Microphysics of Extreme Rainfall Observed during PRECIP (Prediction of Rainfall Extremes Campaign In the Pacific)

合作研究：PRECIP（太平洋极端降雨预测活动）期间观测到的极端降雨的动力学、热力学和微观物理学

• 批准号: 1854559
• 负责人: Michael Bell
• 金额: $ 124.45万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1854559&HistoricalAwards=false
• 关键词: Collaborative; Research; Dynamics; Thermodynamics; Microphysics

Extreme rainfall is a high impact weather phenomenon that profoundly affects people around the world, but our fundamental understanding and quantitative forecast skill for these events remains limited. To address these important scientific and forecast challenges, the Prediction of Rainfall Extremes Campaign In the Pacific (PRECIP) in summer 2020 will be conducted to improve our understanding of the multi-scale dynamic, thermodynamic, and microphysical processes that produce extreme precipitation. Observations will be collected by the NSF/National Center for Atmospheric Research's S-PolKa and Colorado State University's SEA-POL radars, radiosondes, and disdrometers from 25 May to 10 August 2019 during the latter period of the Meiyu season over Taiwan and transition to the early period of the tropical cyclone (TC) season. The experimental design of PRECIP is motivated by four key factors: 1) a moisture-rich environment, 2) the presence of both complex terrain and an oceanic environment, 3) a dense operational observing network to augment the specialized field observations, and 4) a high frequency of a variety of heavy rainfall events. Taiwan and the western North Pacific region are a natural laboratory that optimizes all four of these criteria. With high total column water vapor in the region as a fundamental precondition, field observations will be used to test hypotheses related to the presence and roles of key ingredients and processes across scales in different heavy rainfall scenarios. PRECIP will be conducted in collaboration with the Taiwan-area Atmospheric and Hydrological Observation and Prediction Experiment (TAHOPE) and Japanese Tropical cyclones Pacific Asian Research Campaign for Improvement of Intensity estimations/forecasts (T-PARCII) to add additional synergistic research observations to the campaign.PRECIP seeks to improve our fundamental understanding and prediction of the processes that produce extreme precipitation through an ingredients-based physical framework. Research observations will be collected in four event types that meet a global definition of 'extreme' across a spectrum of rainfall intensity and duration: deep convective cores, wide convective cores, broad stratiform regions, and TCs. The field campaign is innovative in its approach to investigate the universal aspects of extreme rainfall by testing hypotheses that are not directed at only one weather phenomenon, and are therefore transferable to rainfall events that affect the United States. The experiment is designed to maximize the chances of observing a variety of heavy rainfall events in the moisture-rich natural laboratory of Taiwan and western North Pacific in order to find the commonalities. The primary objective is to simplify the complexity of multi-scale interactions by identifying key ingredients and processes in the limiting cases of high intensity and long duration events in a moisture-rich environment. Field measurements will be made to address basic research questions about key ingredients, physical processes, mesoscale structures, and prediction improvement. The core observations will consist of multi-frequency radars, radiosondes, disdrometers, and the Taiwan operational weather network that will be integrated with modeling and data analysis and assimilation to better understand the mechanisms that produce extreme rainfall.Improved forecasts and understanding of the predictability of heavy rainfall will lead to better warnings and risk communication that will have a strong positive impact on society. Improvements to our understanding of orographic and non-orographic precipitation, physical processes, and model capabilities will have broad application to improve other related weather and climate predictions. The PRECIP dataset will also lead to positive impacts in precipitation estimation, data assimilation, radar meteorology, and hydrology. Concurrent projects with TAHOPE and T-PARCII will strengthen international science collaboration in our common goal of improved extreme weather prediction and will help facilitate the application of the campaign findings toward operations in the future. The joint projects will occur during the period leading up to and including the 2020 Tokyo Olympics. The Olympics will naturally enhance the broader impacts of the PRECIP research, and will provide a focal point for education and outreach promoting the positive role of science to address global problems such as extreme weather. Additional positive broader impacts are expected for graduate students, early career scientists, and underrepresented groups through mentoring, international science collaborations, and leadership opportunities in the field.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.

极端降雨是一种影响深远的天气现象，深刻影响着世界各地的人们，但我们对这些事件的基本理解和定量预测技能仍然有限。为了应对这些重要的科学和预报挑战，2020年夏季太平洋极端降雨预测运动（precep）将开展，以提高我们对产生极端降水的多尺度动力学、热力学和微物理过程的理解。美国国家科学基金会/国家大气研究中心的S-PolKa和科罗拉多州立大学的SEA-POL雷达、无线电探空仪和分差仪将于2019年5月25日至8月10日在台湾梅雨季节后期和热带气旋（TC）季节早期过渡期间收集观测数据。precp实验设计的动机有四个关键因素：1)丰富的水分环境；2)复杂地形和海洋环境的存在；3)密集的业务观测网络，以增加专业的野外观测；4)各种强降雨事件的高频率。台湾和北太平洋西部地区是优化这四个标准的天然实验室。以该地区高水柱总水汽为基本前提条件，将利用实地观测来检验不同强降雨情景中各尺度关键成分和过程的存在及其作用的假设。该计划将与台湾地区大气水文观测与预报试验（TAHOPE）和日本热带气旋强度改进太平洋亚洲研究运动（T-PARCII）合作进行，为该运动增加额外的协同研究观测。precp旨在通过基于成分的物理框架，提高我们对产生极端降水过程的基本理解和预测。研究观测将收集在降雨强度和持续时间范围内满足全球“极端”定义的四种事件类型：深对流核、宽对流核、宽层状区和tc。实地活动在调查极端降雨的普遍方面的方法上是创新的，它通过测试假设，而不是针对一种天气现象，因此可以转移到影响美国的降雨事件。本实验旨在最大限度地利用台湾与北太平洋西部富湿的自然实验室观测各种强降雨事件的机会，以寻找其共性。主要目标是通过确定高强度和长时间事件在富湿环境中的限制情况下的关键成分和过程，简化多尺度相互作用的复杂性。将进行实地测量，以解决关键成分、物理过程、中尺度结构和预测改进等基础研究问题。核心观测将包括多频雷达、无线电探空仪、地面仪和台湾业务天气网络，这些网络将与建模、数据分析和同化相结合，以更好地了解产生极端降雨的机制。改进预报和了解强降雨的可预测性将导致更好的预警和风险通报，这将对社会产生强烈的积极影响。我们对地形和非地形降水、物理过程和模式能力的理解的提高将广泛应用于改善其他相关的天气和气候预测。precp数据集还将对降水估算、数据同化、雷达气象和水文产生积极影响。与TAHOPE和T-PARCII同时进行的项目将加强国际科学合作，以实现我们改进极端天气预报的共同目标，并将有助于促进将活动结果应用于未来的行动。这些联合项目将在2020年东京奥运会之前和之后的一段时间内进行。奥运会自然会增强precp研究的广泛影响，并将为教育和推广提供一个焦点，促进科学在解决极端天气等全球问题方面的积极作用。通过指导、国际科学合作和该领域的领导机会，预计将对研究生、早期职业科学家和代表性不足的群体产生更广泛的积极影响。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

A Comparison of the Polarimetric Radar Characteristics of Heavy Rainfall From Hurricanes Harvey (2017) and Florence (2018)

• DOI: 10.1029/2019jd032212
• 发表时间: 2020-05
• 期刊: Journal of Geophysical Research: Atmospheres
• 作者: Jennifer C. DeHart;M. Bell

The parametric hurricane rainfall model with moisture and its application to climate change projections

• DOI: 10.1038/s41612-022-00308-9
• 发表时间: 2022-11-04
• 期刊: NPJ CLIMATE AND ATMOSPHERIC SCIENCE
• 影响因子: 9
• 作者: Kim, Dasol;Park, Doo-Sun R.;Bell, Michael M.
• 通讯作者: Bell, Michael M.

An Ensemble-Based Analysis of a Liminal Extreme Rainfall Event near Taiwan

台湾附近一次阈值极端降雨事件的集合分析

• DOI: 10.3390/atmos13071011
• 发表时间: 2022
• 期刊: Atmosphere
• 影响因子: 2.9
• 作者: Cole, Alexandra S.;Bell, Michael M.;DeHart, Jennifer C.
• 通讯作者: DeHart, Jennifer C.

Improving Short-Term QPF Using Geostationary Satellite All-Sky Infrared Radiances: Real-Time Ensemble Data Assimilation and Forecast during the PRECIP 2020 and 2021 Experiments

使用对地静止卫星全天红外辐射改善短期 QPF：PRECIP 2020 和 2021 实验期间的实时集合数据同化和预测

• DOI: 10.1175/waf-d-22-0156.1
• 发表时间: 2023
• 期刊: Weather and Forecasting
• 影响因子: 2.9
• 作者: Zhang, Yunji;Chen, Xingchao;Bell, Michael M.
• 通讯作者: Bell, Michael M.