Collaborative Research: Reducing Model Uncertainty by Improving Understanding of Pacific Meridional Climate Structure during Past Warm Intervals
INSTITUTION
Syracuse University, NY
PRINCIPAL INVESTIGATOR
Tripti Bhattacharya
FUNDING
$301K
YEAR
2023
MOONBASE SCORE
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Abstract
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.
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