Abstract
Resource managers at the state, federal, and tribal levels make decisions on a weekly to quarterly basis, and fishers operate on a similar timeframe. To determine the potential of a support tool for these efforts, a seasonal forecast system is experimented with here. JISAO’s Seasonal Coastal Ocean Prediction of the Ecosystem (J-SCOPE) features dynamical downscaling of regional ocean conditions in Washington and Oregon waters using a combination of a high-resolution regional model with biogeochemistry and forecasts from NOAA’s Climate Forecast System (CFS). Model performance and predictability were examined for sea surface temperature (SST), bottom temperature, bottom oxygen, pH, and aragonite saturation state through model hindcasts, reforecast, and forecast comparisons with observations. Results indicate J-SCOPE forecasts have measurable skill on seasonal timescales. Experiments suggest that seasonal forecasting of ocean conditions important for fisheries is possible with the right combination of components. Those components include regional predictability on seasonal timescales of the physical environment from a large-scale model, a high-resolution regional model with biogeochemistry that simulates seasonal conditions in hindcasts, a relationship with local stakeholders, and a real-time observational network. Multiple efforts and approaches in different regions would advance knowledge to provide additional tools to fishers and other stakeholders.
Highlights
Ecological forecasting is considered a key science capability required to support US coastal ecosystems into the future[1,2]
J-SCOPE forecasts rely on output from Climate Forecast System (CFS) for the climate forcing, so it is worthwhile considering the quality of CFS predictions for context
CFS has measurable skill in predicting sea surface temperature (SST) in the Northeast Pacific for lead times of less than six months[26,39], and for the spatial mean SST of the California Current System (CCS), skill is typically greater than simple persistence when predicting spring temperatures from previous months
Summary
Ecological forecasting is considered a key science capability required to support US coastal ecosystems into the future[1,2]. We use ROMS as the link from short-term climate forecasts to ecological processes relevant to fishery managers and stakeholders, and to an Integrated Ecosystem Assessment[16,3]. We provide forecasts through an IOOS regional association, the Northwest Association of Networked Ocean Observing Systems (NANOOS), in order to promote and evaluate results to determine the usefulness of the information with Pacific Northwest managers, fishers, and scientists. Our work mirrors similar seasonal forecasting efforts for Australian marine resources, where a coarser scale (2 degree x 0.5–1.5 degree) predictive ocean-atmosphere model has been developed[17]. One of the key steps in the Australian research has been to evaluate and convey skill and accuracy of the forecast products[21], which will be our focus below Another key lesson of these Australian case studies is that a forecast system must focus on specific predictable phenomena that trigger stakeholder decisions. The northern portion of the CCS benefits from substantial predictability on seasonal time horizons, as forecast by CFS26, but the mechanisms contributing to that predictability require further analysis
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