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Understanding Systematic Model Biases in Simulating the Pacific Dynamic Sea Level Variability and Change

Dynamic sea level (DSL) in the Pacific Ocean is an important indicator of climate variability
and change. Due to the dominant thermosteric effect, the Pacific DSL reflects the vertically
integrated ocean temperature anomalies and temporally accumulated ocean heat uptake/release.
Recently, Peyser et al. (2016) identified an east-west see-saw as the dominant variability mode of
DSL in the tropical Pacific. This see-saw is closely related to the variability and change of global
mean surface temperature. However, climate models tend to show systematic and outstanding
biases in simulating this see-saw variability, potentially influencing the accuracy of future climate
and sea level predictions and projections.

The primary goal of this project is to investigate the mechanisms responsible for the
systematic biases of the new CMIP6 models in simulating the Pacific DSL variability and change,
provide strategies and pathways for model development and improvement, and eventually reduce
model uncertainty in future climate and sea level predictions and projections. More specifically,
the objectives are to: a) analyze observational, reanalysis and modeling data to better understand
internal DSL variability and externally forced DSL changes in the Pacific; b) quantify the biases
of the CMIP6 models in simulating the Pacific DSL variability and change as well as their climate
and coastal impacts, and compare the results with those from CMIP5; and c) use the GFDL high
resolution coupled climate models (CM4, CM2.5 and CM2.6) and ocean model (MOM6) to
systematically study the sources of the model biases and the critical processes that can lead to
model improvement. To achieve the goal, we will perform systematic data analyses and
comparison, and conduct a series of sensitivity experiments. We will focus on various critical
atmospheric and oceanic processes and identify their roles in causing model biases in simulating
the Pacific DSL variability and change.

This proposal is closely relevant to the MAPP competition: Addressing key issues in CMIP6-
era Earth system models. The NOAA’s long-term goals include improved scientific understanding
of the changing climate system and its impacts, and assessments of current and future states of the
climate system that identify potential impacts and inform science, service, and stewardship
decisions. One focus of CPO’s climate research portfolio is on climate intelligence which includes
observations, modeling and prediction. We anticipate that the outcome of this project will meet
NOAA’s goals by deepening our understanding about the causes of the Pacific DSL variability
and change and the mechanisms for systematic and outstanding model biases, thereby helping
reduce model uncertainty and leading to more accurate climate and sea level predictions and
projections including extreme events. During the project, the PIs will closely interact with the
CMIP, FAFMIP and OMIP modeling communities and contribute to the related IPCC assessments.

Climate Risk Area: Coastal Inundation

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