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Home » Identifying processes controlling the representation of coastal sea level in climate models

Identifying processes controlling the representation of coastal sea level in climate models

Statement of the problem: As climate models improve in resolution, and their output is
increasingly integrated into risk assessment, planning, and adaptation efforts, it is critical to
assess their ability to represent coastal processes. In particular, the representation of dynamic sea
level (DSL) is of considerable societal interest, due to the substantial vulnerability of economic,
cultural, and ecological resources to sea level change and variability. Preliminary analysis
indicates that time-mean dynamic sea level (MDSL) gradients are often poorly represented at the
coast in current-generation climate models, calling into question their ability to robustly project
future changes and variability.
Rationale: Emerging models, especially those with higher horizontal resolution (≤0.25o), show
an improved representation of coastal ocean dynamics. Simultaneously, new observational
products are becoming available that better resolve DSL near coastlines, and recent theoretical
advances permit a physical interpretation of DSL gradients. These elements provide a strong
basis for: 1) development of coastal sea level diagnostics; and 2) interpretation of the processes
underlying model-data differences.
Summary of Work: This project will develop mean dynamic sea level (MDSL) diagnostics near
coastlines that allow the representation of key underlying processes to be assessed, prioritized,
and improved in the next generation of climate models. Four activities will be pursued:
(1) Regional MDSL reference products, with improved representation near coastlines, will be
developed by merging altimeter and tide gauge datasets in key boundary current regions;
(2) Biases in modeled MDSL fields (relative to reference products) will be analyzed and
interpreted, using output from a hierarchy of GFDL ocean and climate models spanning a
range of horizontal resolutions;
(3) Key processes underlying GFDL model MDSL biases will be identified using alongshore
and area-integrated momentum balances;
(4) Targeted, process-oriented, MDSL diagnostics will be integrated into the MDTF
framework and applied to the modern ocean state of CMIP6 simulations, providing
context for ongoing ocean model development at GFDL.
Relevance to NOAA, MAPP, the competition, and society:
The improved understanding of processes influencing MDSL, and their representation in a
hierarchy of climate models, will: 1) inform priorities for model development efforts at GFDL
and NCAR (through the MOM6 ocean model) and 2) lead to an improved basis for assessments
of coastal flooding in a changing climate (a CPO high-priority climate risk). The proposed model
diagnostics directly address gaps in the area of open- and coastal ocean systems within the
MDTF software package. For the larger scientific community, these diagnostics will be
integrated into the MTDF and applied across a wide range of CMIP6 models, allowing a broad
understanding of the processes responsible for climate model biases in different regions of the
global ocean. The project will also develop improved MDSL products along the coastlines near
boundary currents. In total, this project extends NOAA’s core capabilities of understanding and
modeling the changing climate system, developing projections of impacts, and providing
decision support to meet the broad societal challenge of coastal and climate resilience.

Climate Risk Area: Coastal Inundation

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