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.

极端降雨是一种高影响的天气现象，对世界各地的人们产生了深远的影响，但是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测挑战，将在2020年夏季对太平洋降雨极端运动的预测，以提高我们对产生极端降水的多规模动态，热力学和微物理过程的理解。 NSF/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，辐射仪和序列仪将于2019年5月25日至10日在台湾季节的后期和过渡到热带环酮（TC）季节的早期。沉淀的实验设计是由四个关键因素激励的：1）水分丰富的环境，2）复杂地形和海洋环境的存在，3）一个密集的操作观测网络，以增强特殊的现场观测，4）多种大降雨事件的高频。台湾和北太平洋西部是一个自然实验室，可优化所有这四个标准。作为基本先决条件，该区域的总柱状水蒸气高，将使用现场观测来测试与不同降雨场景中关键成分和过程的存在和作用相关的假设。 将与台湾地区的大气和水文观察和预测实验（Tahope）和日本热带气旋亚洲亚洲亚洲研究活动进行合作进行降水，以改善强度估计/预测/预测（T-PARCII）（T-PARCII），以添加促进运动的其他研究型研究。研究观察结果将以四种符合全球降雨强度和持续时间的“极端”定义的事件类型收集：深对流岩心，广泛的对流岩心，宽阔的层状区域和TC。 通过测试仅针对一种天气现象的假设来调查极端降雨的普遍方面的方法，这是创新的，因此可以转移到影响美国的降雨事件中。该实验旨在最大程度地观察台湾和北太平洋西部的富含水分的自然实验室中的各种大降雨事件的机会，以找到共同点。主要目的是通过在高强度和长时间持续时间事件的限制案例中识别重要的成分和过程来简化多尺度相互作用的复杂性。将进行现场测量，以解决有关关键成分，物理过程，中尺度结构和预测改进的基础研究问题。核心观察将包括多频雷达，辐射仪，分解仪和台湾运营天气网络，该网络将与建模和数据分析和同化，以更好地理解产生极端降雨的机制。提高预测和对大降雨的预测能力的理解将带来更好的战争和风险沟通，这会导致对社会的积极影响，这将对社会产生积极影响。我们对地形和非图降水，物理过程和模型功能的理解的改善将有广泛的应用，以改善其他相关的天气和气候预测。爆炸数据集还将导致降水估计，数据同化，雷达气象和水文学的积极影响。与Tahope和T-Parcii的同时项目将加强国际科学的合作，以改善极端天气预测的共同目标，并将有助于促进竞选发现将来对运营的应用。联合项目将发生在2020年东京奥运会之前和包括2020年的期间。奥运会自然会增强爆炸式研究的更广泛影响，并为教育和外展提供一个焦点，并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，国际科学合作和领域的领导机会，预计研究生，早期职业科学家和人数不足的群体预计会产生更大的积极影响。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准来通过评估来进行评估的。

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.

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.

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.