Collaborative Research: P2C2--Constraining Cloud and Convective Parameterizations Using Paleoclimate Data Assimilation

本研究的总体目标是通过整合古气候数据和气候模式模拟，为推进云和对流过程的模式表示开发一个新的框架。具体而言，研究策略包括三个主要目标：(1)利用广泛的云和对流参数集集合，对末次盛冰期（LGM）、全新世中期（MH）和工业化前（PI）时期进行完全耦合的同位素模拟；(2)分别利用海温和水同位素指标对扰动参数集合（PPE）进行古气候资料同化；(3)利用LGM、MH和PI同化的后验数据来确定哪些云和对流参数与代理数据最匹配，然后利用这些参数集进行当前和双倍二氧化碳（CO2）实验，以计算平衡气候敏感性的缩小估计。平衡气候敏感性（ECS）是一个关键的气候指标，它量化了大气二氧化碳相对于PI水平增加一倍时全球平均地表温度的上升。在未来预估中，水文气候、极端温度和气候系统其他方面的变化与模式的ECS密切相关。几十年来，尽管使用了多种证据，但对ECS的估计仍然很宽泛。这种扩散的一个持久来源与云和对流过程有关，这些过程发生的尺度太小，无法明确解决，因此需要在气候模式中进行参数化。本项目旨在解决这一问题。潜在的更广泛的影响包括气候模型的改进，与美国国家航空航天局合作的高中教师和研究生的学期和暑期实习经验，通过花园州路易斯斯托克斯少数民族参与联盟的本科生参与研究。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The general goal of the research is to develop a new framework for advancing model representations of cloud and convective processes by integrating paleoclimate data and climate model simulations. Specifically, the research strategy consists of three main objectives: (1) conduct fully coupled, isotope-enabled simulations for the Last Glacial Maximum (LGM), mid-Holocene (MH), and pre-industrial (PI) time periods using a wide ensemble of cloud and convective parameter sets; (2) perform paleoclimate data assimilation on the perturbed parameter ensemble (PPE) using sea surface temperature (SST) and water isotope proxies, respectively; and (3) use the posteriors from the LGM, MH, and PI assimilations to identify which cloud and convection parameters provide the best match to the proxy data, then conduct present-day and doubled carbon dioxide (CO2) experiments with these parameter sets to calculate a narrowed estimate of equilibrium climate sensitivity.Equilibrium climate sensitivity (ECS) is a key climate metric that quantifies the rise in global mean surface temperature in response to doubling of atmospheric CO2 relative to PI levels. Changes in hydroclimate, temperature extremes, and other aspects of the climate system in future projections are closely tied to a model’s ECS. For decades, estimates of ECS have remained wide despite improvements from using multiple lines of evidence. One persistent source of this spread is related to cloud and convective processes, which occur at scales too small to be explicitly resolved, and thus require parameterizations to be represented in climate models. This project seeks to address this issue.The potential Broader Impacts include improvement in climate models, school term and summer internship experience for a high school teacher and graduate student in collaboration with NASA, involvement of undergraduate students in research through the Garden State Louis Stokes Alliance for Minority Participation.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.