Collaborative Research: Connecting Seasonal to Millennial Timescales through Strongly Coupled Data Assimilation

This project seeks to address a key challenge which involves extracting information from paleoclimate proxies with resolution as fine as one month (coral records) to several decades (sediment cores). Accordingly, most efforts to date have focused on annually resolved proxies, or separate ocean and atmospheric Paleoclimate data assimilation (DA), to mitigate this technical difficulty. This potentially limits understanding the continuum of climate variability and has important implications for near-term climate forecasts, adaptation, and planning. This project uses a different approach to connecting seasonal to millennial scales, and ocean to atmosphere. Specifically, the researchers aim to develop and implement a new 4D variational framework for multiscale proxy assimilation. The project leverages recent data syntheses of proxy observations to inform the reanalysis and use independent, borehole-based thermometry, as well as a recent synthesis of documentary data for validation. The new monthly-resolved dataset will be applied to modeling and understanding tropical cyclone statistics and their relationship to large-scale dynamics using new deep-learning weather models, and also characterize the sources of climate variability on seasonal to centennial scales. The potential Broader Impacts includes support for graduate students, development of visualizations tools for K-12 education and citizen science, and publicly available data and useful for the paleoclimate and climate dynamics communities. The project will produce a new set of global climate fields bridging seasonal to centennial timescales. A major benefit to the climate community could be a unified testing ground for interannual to decadal climate forecasts, which are presently limited by the shortness of the instrumental record. 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.