CAREER: Observation-Driven Mapping of the Linkages between the Terrestrial Water, Energy and Carbon Cycles

职业：观测驱动的陆地水、能源和碳循环之间联系的绘图

• 批准号: 1944457
• 负责人: Leila Farhadi
• 金额: $ 49.97万
• 依托单位: George Washington University
• 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: 2020-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1944457&HistoricalAwards=false
• 关键词: CAREER; Observation; Driven; Mapping; Linkages

The exchange of water, energy, and carbon between the land, biosphere and atmosphere play a key role in the Earth’s climate. The terrestrial or land component of water, energy and carbon cycles are strongly linked and operate in a harmonized manner. For example, an increase in atmospheric carbon dioxide modifies the amount of vegetation biomass, thus altering ecosystem photosynthesis and transpiration (hence, heat exchange) rates. Land Surface Models used in hydrologic, ecological and climate models require accurate representation of the links between terrestrial cycles. The lack of direct observation of key variables that can quantify these linkages result in uncertain projections from these models. Using satellite information on land surface state measurements of soil moisture, soil temperature and vegetation index, this project applies a novel observation-driven approach to diagnose and map the linkages at regional scale. Mapping the linkages across different seasons, ecological and environmental conditions advances understanding of how the terrestrial water, energy and carbon cycles are linked and operate in the real world. The educational goal of this CAREER proposal is to enhance environmental knowledge and promote scientific discovery on the part of graduate, undergraduate and 6-12th precollege students in the Washington DC area. This education effort includes engaging minority students from local schools in STEM fields with a focus on climate and land-atmosphere interaction. This research addresses the current knowledge gap in understanding the spatio-temporal variations of land-atmosphere interactions/couplings. The research plan includes (i) developing a state of the art framework based on a variational methodology to diagnose and map the linkages between the terrestrial water, energy and carbon cycles across a range of temporal and spatial scales from the implicit information contained in land surface state observations; (ii) testing the methodology at point scale (field site, synthetic simulations) and at large scale (Continental US) (iii) and expanding our fundamental understanding of the coupling between the terrestrial cycles by mapping and studying the linkages across different biomes, echo hydrological regions, seasons and environmental conditions. The observation-driven form of the linkages between the cycles can be used to guide improvements in the predictive capabilities of Land Surface/Earth System models and hence improve simulation of regional land surface fluxes, climate and climate projections. The research method and the low order inverse modeling techniques developed in this proposal is of interest to a broad community, including physicists, applied mathematicians, meteorologists, climate scientists and hydrologists. The educational plan leverages the GLOBE (Global Learning and Observations to Benefit the Environment) framework to engage 6-12 students from the DC metro area in STEM by engaging them in activities that will enhance their understanding of land atmosphere interaction. We will ensure long-term sustainability of this program by developing a network of participating teachers, online resources, and program assessment and evaluation tools.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.

陆地、生物圈和大气之间的水、能量和碳的交换在地球气候中发挥着关键作用。水、能源和碳循环的陆地部分密切相关，并以协调的方式运行。例如，大气二氧化碳的增加改变了植被生物量，从而改变了生态系统的光合作用和蒸腾（因此，热交换）速率。水文、生态和气候模型中使用的陆地表面模型需要准确表示陆地循环之间的联系。由于缺乏对可以量化这些联系的关键变量的直接观察，导致这些模型的预测不确定。该项目利用有关土壤湿度、土壤温度和植被指数的地表状态测量的卫星信息，应用一种新颖的观测驱动方法来诊断和绘制区域尺度的联系。绘制不同季节、生态和环境条件之间的联系有助于加深对陆地水、能源和碳循环在现实世界中如何联系和运作的理解。该职业提案的教育目标是提高华盛顿特区研究生、本科生和 6-12 年级预科生的环境知识并促进科学发现。这项教育工作包括让当地学校的少数族裔学生参与 STEM 领域，重点关注气候和土地与大气的相互作用。这项研究解决了当前在理解陆地-大气相互作用/耦合的时空变化方面的知识差距。该研究计划包括（i）开发一个基于变分方法的最先进框架，根据陆地表面状态观测中包含的隐含信息，诊断和绘制一系列时间和空间尺度上的陆地水、能源和碳循环之间的联系； (ii) 在点尺度（现场、综合模拟）和大规模（美国大陆）测试该方法。 周期之间联系的观测驱动形式可用于指导改进陆地表面/地球系统模型的预测能力，从而改进对区域陆地表面通量、气候和气候预测的模拟。该提案中开发的研究方法和低阶逆向建模技术引起了广泛群体的兴趣，包括物理学家、应用数学家、气象学家、气候科学家和水文学家。该教育计划利用 GLOBE（全球学习和观察以造福环境）框架，通过让来自 DC 都市区的 6-12 名学生参与 STEM 活动，增强他们对陆地大气相互作用的理解。 我们将通过开发参与教师网络、在线资源以及项目评估和评价工具来确保该项目的长期可持续性。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力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

Estimation of Root Zone Soil Moisture Profile by Reduced-Order Variational Data Assimilation Using Near Surface Soil Moisture Observations

使用近地表土壤湿度观测通过降阶变分数据同化估计根区土壤湿度剖面

• DOI: 10.1109/jstars.2022.3147166
• 发表时间: 2022
• 期刊: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
• 影响因子: 5.5
• 作者: Heidary, Parisa;Farhadi, Leila;Altaf, Muhammad Umer
• 通讯作者: Altaf, Muhammad Umer

A Reduced-Adjoint Variational Data Assimilation for Estimating Soil Moisture Profile from Surface Soil Moisture Observations

从表层土壤湿度观测估计土壤湿度剖面的减少伴随变分数据同化

• DOI: 10.1109/igarss47720.2021.9554864
• 发表时间: 2021
• 期刊: International Geoscience and Remote Sensing Symposium
• 作者: Heidary, Parisa;Farhadi, Leila;Altaf, Muhammad Umer
• 通讯作者: Altaf, Muhammad Umer