Process-Oriented Diagnostics for the Western Boundary Current Variability and Midlatitude Air-Sea Interaction

Western boundary currents (WBCs), such as the Kuroshio-Oyashio Extension in the North Pacific
and the Gulf Stream in the North Atlantic, are the regions of largest ocean variability and intense
air-sea interaction. In particular at interannual and longer time scales, the WBC variability
generates strong ocean-to-atmosphere heat fluxes, resulting in anomalous diabatic heating that
can impact the large-scale atmospheric circulation and the poleward heat transport in both the
ocean and atmosphere. Therefore, variability in the WBCs and associated air-sea interaction play
fundamental roles in regulating our climate. In addition, the WBCs variability have significant
impact on extreme weather, coastal ecosystem, and sea-level.
Despite the importance of WBC variability and associated midlatitude air-sea interaction, the
WBCs are the regions with some of the largest and longstanding ocean biases in the state-of-the-
art coupled climate models. There have been numerous studies on the mean state biases in
global climate models, in particular in WBC regions, and on the impact of improved spatial
resolution. However, the influence of climate model spatial resolution on the biases of the WBC
variability and associated air-sea interaction is yet to be systematically examined, despite their
strong climate impacts. Here we propose to investigate the nature and impacts of the main biases
of the WBC variability in state-of-the-art climate models based on a set of process-oriented
model diagnostics, and establish their dependence on model resolution, as well as their links to
main large-scale circulation biases. Our process-oriented diagnostics would lead to: (1) a
systematic quantification of the model biases for the oceanic and atmospheric variability in the
WBCs and resulting air-sea interaction, (2) identification of the key processes responsible for the
model biases, and their sensitivity to the horizontal resolution of the model, and (3) improved
understanding of the links between the WBC biases and the simulated large-scale atmospheric
and oceanic circulations. The diagnostics will be first developed based on various state-of-the-art
observational and reanalysis datasets. Then, they will be applied to the state-of-the-art climate
model simulations at standard resolution as well as higher resolution to investigate the role of
model resolutions in the biases and the representation of the associated processes.
This proposal targets the FY 2021 NOAA Modeling, Analysis, Predictions, and Projections
(MAPP) Program solicitation Process-Oriented Diagnostics for NOAA Climate Model
Improvement and Applications by proposing to better understand and benchmark process-level
deficiencies related to the WBC ocean variability and associated air-sea interaction in the CMIP6
and HighResMIP simulations, with additional in-depth analyses of the GFDL and NCAR models
using the proposed set of process-oriented diagnostics. Our proposed work is also directly
relevant to NOAA’s long-term climate goal of advancing scientific understanding, monitoring, and
prediction of climate and its impacts, to enable effective decisions, especially since the
improvement in the climate model processes related to the WBC variability and associated air-
sea interaction has significant implications for the prediction of our climate and its impacts.