Collaborative Research: Reducing Model Uncertainty by Improving Understanding of Pacific Meridional Climate Structure during Past Warm Intervals

合作研究：通过提高对过去温暖时期太平洋经向气候结构的理解来降低模型不确定性

• 批准号: 2303567
• 负责人: Jiang Zhu
• 金额: $ 17.01万
• 依托单位: University Corporation For Atmospheric Res
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-12-15 至 2026-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2303567&HistoricalAwards=false
• 关键词: Collaborative; Research; Reducing; Model; Uncertainty

The general science goal of the research is to advance understanding of feedback from cloud and moist convection to carbon dioxide radiative forcing, which is one of the most fundamental questions in modern climate science. This project specifically seeks to advance several key aspects of climate modeling and future climate projections by identifying model parameters that can reproduce both past and present-day sea surface temperature gradients and north-south precipitation delta-deuterium gradients. The rational for the research strategy is founded on the notion that the reduction in the tropical to mid-latitude sea surface temperature gradient, as shown by proxy records across Pacific and Atlantic Ocean basins, is a common feature of past warm intervals but remains difficult for climate models to replicate. This model-data discrepancy (termed “the low-gradient problem”) is closely tied to the parameterizations of cloud, moist convection, and ocean mixing, which remain highly uncertain and limit the confidence of predicted future climate change by models. Narrowing down this uncertainty can benefit from data from past climates and targeted paleoclimate simulations.The potential Broader Impacts of this project include supporting early career scientists, post-doctoral scholar, graduate student, and undergraduate support and mentoring, and workshops for high school students.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.

该研究的一般科学目标是将反馈从云和水分连接与二氧化碳辐射强迫的连接提高理解，这是现代气候科学中最根本的问题之一。该项目专门旨在通过识别可以重现过去和现在的海面温度梯度和南北降水量梯度的模型参数来推动气候建模和未来气候预测的几个关键方面。研究策略的理性是基于这样一个概念，即在太平洋和大西洋贝斯的代理记录表明，热带向中纬度海面温度梯度的减少是过去温暖间隔的共同特征，但对于气候模型而言仍然很难复制。这种模型数据差异（称为“低梯度问题”）与云，潮湿转化和海洋混合的参数紧密相关，这些参数仍然高度不确定并限制了模型预测未来气候变化的信心。缩小这种不确定性可以从过去的登山者和有针对性的古气候模拟的数据中受益。该项目的潜在广泛影响包括支持早期的职业科学家，博士后学校，研究生和本科生的支持和精神上的支持以及高中生的研讨会，这对NSF的法规委员会的良好态度和诚实的构成了诚实的依据。