CAREER: Forecasting Impacts to Reduce Exposure to Smoke (FIRES) - Modeling wildfire smoke transport in the western U.S.

职业：预测减少接触烟雾的影响 (FIRES) - 对美国西部野火烟雾输送进行建模

• 批准号: 2048423
• 负责人: Heather Holmes
• 金额: $ 50.53万
• 依托单位: University of Utah
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2048423&HistoricalAwards=false
• 关键词: CAREER; Forecasting; Impacts; Reduce; Exposure

The largest wildfires in the United States occur in the western part of the country; an area with a population of over 77 million people. Smoke from wildfires is harmful to humans and reducing smoke-related illnesses requires limiting outdoor work and other activities in areas impacted by fire. These areas of impact can extend several hundreds of miles away from the fire, thus accurate prediction is critical to protect human health. Currently, weather and air quality models are used to provide smoke warnings to the public. However, there is a critical need to improve these models to correctly forecast the smoke transport over mountains. This research project will transform these models and advance the state-of-the-science of modeling the dynamic atmosphere over mountainous terrain. The new model will be used to develop an online smoke forecasting tool that provides warnings to protect human health during wildfire events in the western U.S. This project will enhance undergraduate STEM education by developing an online computational modeling course that fills a gap in existing curricula. Together, these educational products will enhance our ability to protect human health through accurate wildfire forecasting, while training the next generation of forecasters and increasing the scientific literacy of the Nation. Regional scale air models that simulate wildfire smoke transport have significant uncertainties over mountainous terrain due to the complexities of the atmospheric flows and difficulties in estimating smoke plume injection heights. To improve smoke plume forecasts there is a critical need to develop new models that reduce uncertainties associated with both meteorological conditions and emissions modeling. The aim of this research is to use a cross-disciplinary approach to improve our fundamental understanding of wildfire smoke plume dynamics and complex atmospheric flows governing smoke transport over mountainous terrain. Successful completion of this work has the potential to transform our knowledge of the coupled atmosphere-fire-human system and greatly improve our ability to protect human health. The central hypothesis is that atmospheric turbulence parameterizations developed for flat terrain do not correctly simulate the planetary boundary layer structure over mountainous terrain leading to biases in the chemical transport modeling of wildfire smoke plumes. The four research objectives of this project are to: 1) improve models for vertical mixing over mountains to reduce the uncertainties in modeling smoke plume transport, 2) develop a novel model for smoke plume injection height to improve the vertical distribution of wildfire smoke emissions concentrations and subsequent regional transport, 3) incorporate model improvements for atmospheric mixing and wildfire emissions into a chemical transport model to improve smoke plume forecasts in the western U.S., and 4) create an online smoke forecasting tool using the improved regional scale smoke plume transport model. The education and outreach objectives of this project are to enhance numerical educational opportunities for undergraduate students by developing an online course focusing on numerical weather prediction modeling and high-performance computing and increase collaboration with local stakeholders to provide unique service-learning style research experiences for undergraduate students related to wildfire science in Nevada. A primary product of this research will be an online smoke forecasting tool designed in collaboration with a data visualization and communication expert. This online tool will be shared with local stakeholders to help inform the public about poor air quality events by issuing warnings that aid in reducing wildfire smoke exposure.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.

美国最大的野火发生在该国西部。人口超过7700万人的地区。来自野火的烟雾对人类有害，减少与烟雾有关的疾病需要限制受火影响的地区的户外工作和其他活动。这些影响区域可以远离火灾数百英里，因此准确的预测对于保护人类健康至关重要。目前，天气和空气质量模型用于向公众提供烟雾警告。但是，需要改善这些模型以正确预测山上的烟雾运输。该研究项目将改变这些模型，并提高建模山区动态氛围的最先进。新模型将用于开发一种在线烟雾预测工具，该工具在美国西部的野火事件期间提供警告以保护人类健康，该项目将通过开发在线计算建模课程来增强本科STEM教育，以填补现有课程的空白。这些教育产品共同通过准确的野火预测来增强我们保护人类健康的能力，同时训练下一代预报员并提高国家的科学素养。模拟野火烟雾运输的区域规模空气模型由于大气流的复杂性以及估计烟雾羽状注入高度的困难，因此在山区的地形上存在明显的不确定性。为了改善烟羽预测，至关重要的需要开发新模型，以减少与气象条件和排放建模相关的不确定性。这项研究的目的是使用跨学科的方法来提高我们对野火烟雾羽状动力学和复杂的大气流的基本理解，这些大气流构成了山区地形上的烟雾运输。这项工作的成功完成有可能改变我们对耦合气氛 - 狂欢系统系统的了解，并大大提高了我们保护人类健康的能力。中心假设是，针对平坦地形开发的大气湍流参数化并未正确模拟山区地形上的行星边界层结构，从而导致野火烟羽的化学传输建模中的偏见。该项目的四个研究目标是：1）改进山脉垂直混合模型，以减少建模烟羽流的不确定性，2）为烟雾羽流注入高度开发新型模型，以改善野火烟雾排放浓度的垂直分布，并为野火烟雾的垂直分布，并随后的区域运输，3）将烟雾融合到化学混合模型中，将烟雾融合到化学混合模型中，使得烟雾使烟雾融合到化学混合模型中，以使烟雾融合到化学混合模型中，使得烟雾融合到化学混合模型中，在线烟雾预测工具，使用改进的区域规模烟羽传输模型。该项目的教育和外展目标是通过开发针对数值天气预测建模和高性能计算的在线课程来增强大学生的数字教育机会，并增加与当地利益相关者的合作，以为与内华达州的Wildfire Science相关的本科生提供独特的服务学习风格的研究经验。这项研究的主要产品将是与数据可视化和通信专家合作设计的在线烟雾预测工具。该在线工具将与当地利益相关者共享，以通过发出有助于减少野火烟雾曝光的警告来帮助公众了解空气质量差的事件。该奖项反映了NSF的法定任务，并被认为值得通过基金会的知识分子优点和更广泛的影响标准通过评估来进行评估。

项目成果

Simulating land-atmosphere coupling in the Central Valley, California: Investigating soil moisture impacts on boundary layer properties

• DOI: 10.1016/j.agrformet.2022.108898
• 发表时间: 2022-04
• 期刊: Agricultural and Forest Meteorology
• 影响因子: 6.2
• 作者: G. A. Alexander;H. Holmes;Xia Sun;D. Caputi;I. Faloona;H. Oldroyd