CAREER: Hydrological Sensitivity Across Timescales

职业：不同时间尺度的水文敏感性

• 批准号: 2047270
• 负责人: Jie He
• 金额: $ 85.44万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2026-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2047270&HistoricalAwards=false
• 关键词: CAREER; Hydrological; Sensitivity; Across; Timescales

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).As greenhouse gas concentrations continue to rise, the Earth’s surface will continue to warm, and the amount of rainfall is expected to change substantially. Predicting how rainfall will change is of great importance for preparing adaptation and mitigation plans. Currently, predictions of long-term rainfall changes rely predominantly on simulations of climate models. However, models disagree on many aspects of rainfall changes, which greatly undermines the usefulness of rainfall predictions. Because observations are generally too short to be used to directly infer long-term rainfall changes, constraining model predictions has been a great challenge. Fortunately, there are abundant observations of short-term (for example, annual or monthly) rainfall variations. These observations allow scientists to study mechanisms of rain, some of which operate at both short and long timescales. The investigator has identified several aspects of long-term rainfall changes that are fundamentally tied to how rainfall responds to short-term surface temperature variations. Based on such relationships, he will evaluate long-term rainfall predictions from climate models by using observed short-term rainfall variations. This work will yield a better understanding of the uncertainty in rainfall predictions and will identify key processes of which observational constraints are available to improve models. This method will then be applied to a state-of-the-art global climate model, where the identified observational constraints will be used to improve model parameters and ultimately, its prediction of future rainfall changes.By understanding mechanisms of rainfall changes and causes of prediction uncertainties, this project will identify key processes that require observational validation to improve model predictions. Such an improvement will ultimately help society to cope better with climate variations. The educational component of this project involves the teaching and application of climate models at graduate, undergraduate and high school levels. Specifically, the investigator will (1) create a hands-on a climate modeling course for graduate students in climate science, (2) design a climate science and modeling module that can be incorporated into high school science curriculum, and (3) train undergraduate students to conduct and analyze climate model experiments via the summer NSF Research Experiences for Undergraduates Program.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.

该奖项的全部或部分资金根据《2021 年美国救援计划法案》（公法 117-2）提供。随着温室气体浓度持续上升，地球表面将持续变暖，降雨量预计将发生变化预测降雨量将如何变化对于制定适应和缓解计划非常重要。目前，长期降雨量变化的预测主要依赖于气候模型的模拟，然而，模型在降雨量变化的许多方面存在分歧，这极大地影响了气候变化的预测。由于观测通常太短而无法直接推断长期降雨变化，因此约束模型预测一直是一个巨大的挑战，幸运的是，有大量的短期观测（例如年度或月度）。这些观测使科学家能够研究降雨机制，其中一些机制在短期和长期范围内发挥作用，研究人员已经确定了长期降雨变化的几个方面，这些变化在根本上与降雨对短期地表温度的反应有关。根据这种关系，他将评估。通过使用观测到的短期降雨变化来根据气候模型进行长期降雨预测这项工作将更好地了解降雨预测的不确定性，并将确定可用于改进模型的观测约束的关键过程。应用于最先进的全球气候模型，其中确定的观测约束将用于改进模型参数，并最终预测未来降雨变化。通过了解降雨变化的机制和预测不确定性的原因，该项目将确定需要观察验证来改进模型的关键流程这种改进最终将帮助社会更好地应对气候变化。该项目的教育部分涉及研究生、本科生和高中阶段的气候模型教学和应用。具体而言，研究人员将（1）创建一只手。 -为气候科学研究生开设气候建模课程，(2) 设计一个可以纳入高中科学课程的气候科学和建模模块，以及 (3) 培训本科生在暑假期间进行和分析气候模型实验NSF 本科生研究经验计划。该奖项反映了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，NSF 的法定使命被认为值得支持。

项目成果

Diverging hydrological sensitivity among tropical basins

热带盆地之间水文敏感性的差异

• DOI: 10.1038/s41558-024-01982-8
• 发表时间: 2024-04
• 期刊: Nature Climate Change
• 影响因子: 30.7
• 作者: He, Jie;Lu, Kezhou;Fosu, Boniface;Fueglistaler, Stephan A.
• 通讯作者: Fueglistaler, Stephan A.

Origins of Uncertainty in the Response of the Summer North Pacific Subtropical High to CO 2 Forcing

夏季北太平洋副热带高压对CO 2 强迫响应的不确定性来源

• DOI: 10.1029/2023gl105042
• 发表时间: 2023-11
• 期刊: Geophysical Research Letters
• 影响因子: 5.2
• 作者: Lu, Kezhou;He, Jie;Simpson, Isla R.
• 通讯作者: Simpson, Isla R.