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Improving the Utility of Global Climate Forecasts for Regional Fisheries Applications

Managers of fisheries and other living marine resources (LMRs) are tasked with balancing
environmental and economic interests, where the maintenance of productive industries (e.g.,
fishing and shipping) must be pursued while minimizing risks to protected species (e.g., from
bycatch and ship strikes) and ensuring that fish stocks are sustainable. To that end, forecasts of
ocean conditions in U.S. Large Marine Ecosystems (LMEs) have been identified as foundational
for emerging national efforts to increase the resilience of coastal communities. Forewarning of
ocean conditions can enable proactive decision making by fishers and fishery managers, and
incorporating climate information in fisheries management is a top priority of the NOAA National
Marine Fisheries Service [NOAA, 2015]. A key asset in this regard is the suite of subseasonal-to-
seasonal (2 week – 12 month) global climate forecasts run routinely at climate modeling centers
in the U.S. and elsewhere, which have demonstrable forecast skill for conditions over the North
American continent and in U.S. waters. However, uptake of these forecasts in LMR management
will require optimization for regional scales, and the MAPP program has identified a need to better
understand the processes underlying climate impacts on marine ecosystems and the associated
uncertainties. To address this need, we propose to quantify the dependence of forecast skill for
LMR-relevant variables in the California Current LME (CCLME) on the climate state and to
document mechanistic links between short-lead forecast skill (e.g., in the tropics) and longer-
lead forecast skill in the CCLME. In doing so, we will provide several valuable products: (i)
confidence assessments that document forecast uncertainty based on the climate state and (ii)
metrics that diagnose how well tropical-extratropical connections are captured in model forecasts
and inform CCLME forecast skill improvements. Key elements of the proposed work plan are to
(1) evaluate subseasonal-to-seasonal reforecasts from the S2S, SubX, and NMME archives for
ocean variables identified as highly impactful on LMR in the CCLME, (2) quantify hypothesized
relationships between short- and long-lead forecast skill, with the aim of using short-lead metrics
to diagnose whether forecasts are likely to be skillful at longer leads, and (3) compare skill
enhancements related to these new metrics with skill improvements enabled by dynamically
downscaled regional forecasts. The downscaled forecasts and the high-resolution regional ocean
reanalysis outputs needed for skill evaluation are available from prior projects.

Relevance to the Competition and NOAA’s Long-Term Climate Research Goals:
The proposed project directly addresses Priority Areas B and C of the competition. It addresses
Priority Area B by identifying key linkages between tropical conditions (and the broader basin-
scale climate) and forecast skill along the U.S. west coast, and between short-lead tropical forecast
skill and longer-lead U.S. west coast forecast skill for LMR-relevant physical variables. It
addresses Priority Area C by assessing model fidelity for predictability pathways, improving
prediction methodologies, and assessing the advantages of higher resolution. By enabling
improved forecasts of CCLME conditions and providing uncertainty estimates, which are crucial
to the implementation of climate-based management strategies, this project would also address
NOAA’s long-term goals for climate adaptation and mitigation and resilient coastal communities
and economies and NMFS National Climate Science Strategy objectives to track change and
provide early warning, project future conditions, and support adaptive management processes.

Climate Risk Area: Marine Ecosystems

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