Nearshore total water level (TWL) proxies (2018-2100) for Northern California
Dates
Publication Date
2022-10-12
Time Period
2022-10
Citation
Barnard, P.L., Erikson, L.H., Foxgrover, A.C., Limber, P.L., O'Neill, A.C., Thomas, J.A., and Vitousek, S., 2022, Coastal Storm Modeling System (CoSMoS) for Northern California 3.2: U.S. Geological Survey data release, https://doi.org/10.5066/P9048D1S.
Summary
Nearshore proxies for total water level (TWL) developed for Coastal Storm Model (CoSMoS) work in Northern California 3.2 are presented. Deterministic dynamical modeling of future climate conditions and associated hazards, such as flooding, can be computationally-expensive if century-long time-series of waves, sea level variations, and overland flow patterns are simulated. To focus such modeling on storm events of interest, local impacts over long time periods and large geographical areas are estimated. Nearshore proxies for total water level (TWL) are generated via a computationally simple approach, assuming a linear superposition of the important processes contributing to overall total water level. A time series of TWL proxies is [...]
Summary
Nearshore proxies for total water level (TWL) developed for Coastal Storm Model (CoSMoS) work in Northern California 3.2 are presented. Deterministic dynamical modeling of future climate conditions and associated hazards, such as flooding, can be computationally-expensive if century-long time-series of waves, sea level variations, and overland flow patterns are simulated. To focus such modeling on storm events of interest, local impacts over long time periods and large geographical areas are estimated. Nearshore proxies for total water level (TWL) are generated via a computationally simple approach, assuming a linear superposition of the important processes contributing to overall total water level. A time series of TWL proxies is used as the basis for 1) identifying coastal segments that respond similarly to region-wide coastal storms, 2) selecting storm events for detailed hydrodynamic modeling within CoSMoS, and 3) to drive long-term shoreline change and bluff retreat models.
