Dataset Identified

Gulf of Mexico Sea Level Anomalies Using ECCO Sensitivities and CMIP6 Prediction Models: 21st Century Predictions

Identified On: Apr 18 2023 19:23 UTC
UDI: H5.x993.000:0004
Project Information

Funded By:
National Academies of Sciences Gulf Research Program

Funding Cycle:
Healthy Ecosystems 5

Research Group:
Coherent dynamic sea-level changes along the Gulf Coast: physics, seasonal predictions, and long-term projections

Point of Contact

Andrew Delman
University of California Los Angeles
andrewdelman@g.ucla.edu

Abstract:

This dataset uses the hybrid dynamical prediction approach (Frederikse et al., 2022) to generate predictions of sea level anomalies at lead times of up to 24 years. The inputs used to generate the predictions are adjoint sensitivities from the Estimating the Circulation and Climate of the Ocean (ECCO) state estimate, and surface fluxes as output from a range of CMIP6 prediction models.