CAREER: Advancing the science and education of land surface-atmosphere interactions: Interweaving multiscale experimental and modeling approaches for Land Surface Models

职业：推进地表-大气相互作用的科学和教育：将地表模型的多尺度实验和建模方法交织在一起

• 批准号: 1929792
• 负责人: Kathleen Smits
• 金额: $ 26.46万
• 依托单位: University of Texas at Arlington
• 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: 2019-04-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1929792&HistoricalAwards=false
• 关键词: CAREER; Advancing; science; education; land

CAREER: Advancing the science and education of land surface-atmosphere interactions: Interweaving multiscale experimental and modeling approaches for Land Surface Models and experiential learning A critical challenge for Land Surface Models (LSMs) is to simulate processes at the surface and the subsurface and their feedbacks to the atmosphere. Even given the same climate forcings, LSMs predict different surface fluxes and soil moisture conditions. This is due to differences in the formulations of individual processes, parameterizations of those formulations, numerical solution methods and representation of spatial heterogeneity. All of these differences contribute to LSM prediction errors and uncertainty. Increasing confidence in climate predictions requires revisiting fundamental process understanding and using that understanding to improve representations of land-atmosphere feedbacks. This research seeks to address this challenge by answering questions on multiphase fluid transport mechanisms in surface soils and mass/energy exchange at the soil-atmosphere interface. New knowledge and modeling approaches will result in improved predictions for water supply and food security as well as environmental issues across the nation. Linked to the research plan is an educational framework for engaging minority middle school students in Science, Technology, Engineering and Mathematics (STEM). Focusing on the integrating theme of water and climate, the investigator will help students make the link between STEM they learn in the classroom and environmental water resource problems in their own backyards, motivating and preparing students to pursue college studies and ultimately careers in STEM fields. The integrated activities will help to build a scientifically literate and informed citizenry, while also answering critical water and climate questions. This project will contribute substantially to the goals of the NSF in the production of interdisciplinary knowledge and the education of middle-school students, young scientists and engineers. The overarching goal of this research is to advance our understanding and modeling of mass and energy exchange at the land-atmosphere interface over a wide range of scales, and ultimately improve LSMs that are utilized in global climate prediction. The proposed research will systematically explore how the shallow subsurface and the atmosphere, specifically the layer very close to the soil surface, interact, providing new insights into mass and thermal flux process interactions that will be integrated into LSMs. A focus on scaling based on process understanding at multiple scales will allow for process-rich parameterizations for multiple land-atmosphere interaction and subsurface processes that contribute to LSMs. This vision includes unique highly controlled mechanistic studies in the laboratory, leveraging of existing laboratory and field data, modeling of critical mass and energy dynamics, and the characterization of important interactions from the laboratory to the watershed scales that drive feedbacks to climate systems. Project results will yield unique, high-fidelity data that will greatly aid in improving our understanding and modeling of the processes affected by heterogeneity at various scales and the development of methods to mechanistically represent the proposed processes at the watershed scale. A suite of climate intermediate, and fine scale computational models will be used to guide observations and interpret data; process studies will provide new algorithms and process parameterizations and evaluate model performance. Computational models in conjunction with experimental data will enable the investigator to understand governing flow and transport mechanisms under different atmospheric forcing at different scales. This research is expected to improve the representation of mass and energy exchange processes across multiple scales at the soil-land-atmosphere interface.

职业：推进土地表面 - 大气相互作用的科学和教育：与土地表面模型的多尺度实验和建模方法交织在一起，而经验式学习对陆地表面模型（LSMS）的关键挑战是模拟表面和地下的过程及其对大气层的反馈。即使考虑到相同的气候强迫，LSM也可以预测不同的表面通量和土壤水分条件。这是由于单个过程的制剂，这些公式的参数化，数值解决方案方法以及空间异质性的表示。所有这些差异都导致LSM预测错误和不确定性。 对气候预测的信心增加需要重新审视基本过程的理解，并利用这种理解来改善土地 - 大气反馈的表示。这项研究旨在通过回答有关表面土壤中多相流体传输机制和土壤 - 大气界面的质量/能量交换的问题来应对这一挑战。新的知识和建模方法将改善对全国供水和粮食安全以及环境问题的预测。与研究计划相关的是一个教育框架，可让少数中学学生参与科学，技术，工程和数学（STEM）。 研究人员专注于水和气候的综合主题，将帮助学生在课堂上学习的STEM与自己后院的环境水资源问题之间的联系，激励和准备学生从事大学学习，并最终在STEM领域的职业。综合活动将有助于建立科学识字和知情的公民，同时还回答关键的水和气候问题。该项目将在生产跨学科知识和中学学生，年轻科学家和工程师的教育中为NSF的目标做出重大贡献。 这项研究的总体目标是提高我们对陆地 - 大气界面上质量和能量交流的理解和建模，并在广泛的尺度上，最终改善在全球气候预测中使用的LSM。拟议的研究将系统地探讨浅层地下和大气，尤其是非常接近土壤表面的层，提供了将整合到LSMS中的质量和热通量工艺相互作用的新见解。基于多个尺度的过程理解的缩放的重点将允许多个陆地 - 大气相互作用和对LSM的地下过程进行富含过程的参数化。该愿景包括实验室中的独特高度控制的机械研究，现有实验室和现场数据的利用，临界质量和能量动态的建模以及从实验室到分水岭量表的重要相互作用的表征，这些量表将反馈向气候系统推向气候系统。项目结果将产生独特的高保真数据，这将极大地有助于提高我们对各种尺度上异质性影响的过程的理解和建模，并开发方法，以机械师在流域规模上代表所提出的过程。一套气候中间体和精细规模的计算模型将用于指导观察和解释数据。过程研究将提供新的算法和过程参数化并评估模型性能。与实验数据结合的计算模型将使研究人员能够在不同尺度下不同大气强迫下的流动和传输机制了解。 预计这项研究将改善土壤 - 大气界面上多个尺度的质量和能量交换过程的表示。