Using Ocean Data to Predict Monthly Air Temperatures of California's Coastal Cities

Abstract Air temperature anomalies in the narrow California coastal boundary layer is closely associated with the adjacent coastal sea level variability. Coastal sea levels, proxies of upper ocean heat content, are regulated by alongshore winds and poleward propagating coastal Kelvin waves. Increased upper ocean heat content or higher sea level can enhance oceanic heat release to the atmosphere which will be carried inland due to the prevailing onshore winds. Based on these physical processes, sea level anomaly (SLA) and sea surface temperature (SSTA) are combined and used as a predictor here to forecast air temperature anomaly at 4 main cities along the California coast. Results show that air temperature in these land-based stations can be predicted by SLA and SSTA with 2–3 months in advance. The prediction capability is better during late summer/early fall when the upwelling is strongest. The predicting ability is limited within a 2–3 degree narrow coastal region, and it decreases rapidly for inland stations. Our work also suggests that it is very important to enhance the resolution of models near coastal region to improve seasonal prediction.