ABSTRACT

Marine heatwaves (MHWs) are devastating periods of extreme sea surface temperatures (SST) that disrupt marine ecosystems and the fishing industries that rely on them. Their effects include increased economic tension between nations and an unprecedented harmful algal bloom that threatened public health. These events have been observed throughout the global ocean, with several large scale persistent events occurring in the mid-latitudes over the last decade. Climate model simulations suggest that under continued global warming we can expect MHWs to become longer lasting, more frequent and intense, pushing ecological systems beyond their thermal coping limit, leading to irreversible impacts to the environment. While the satellite record of SST over the last 40 years allows characterization of past MHWs, the number of these devastating midlatitude events is limited, making it difficult to assess how unusual the events are. Event based analysis of the causes and consequences of individual events has given insight into important processes that control these particular events, but whether these processes remain important in the future is unclear. This research will make use of an extensive set of existing model simulations, including both different model configurations and ensembles or multiple realizations of similar runs for better statistical convergence. The analysis will yield insights into both the fidelity of the simulations in critical parts of the ocean and the predictability of heat waves. The impacts of MHWs are profound to both human and natural systems, and quantifying both the impact of climate change on their properties as well as an examination of the predictability of these events will ultimately help to mitigate and prepare for potential impacts in the future. Two graduate students will be trained to use the National Center for Atmospheric Research (NCAR) analysis tools, as well as work with NCAR scientists in developing new tools in Python for use in future analyses of extreme ocean events. The research team will also work with the Northwest Association of the Networked Ocean Observing Systems (NANOOS), hosted at the University of Washington, and the North Carolina Nature Conservancy office to write short articles about the results of this research. Results of this research will also be incorporated into undergraduate courses in coastal oceanography and climate at the University of Washington and the University of Wisconsin.

This project will take advantage of a suite of model simulations performed using the CESM (Community Earth System Model) including forced and coupled simulations at both low and high resolutions. An assessment of statistics of MHWs will be performed using a 40-member large ensemble of the climate from 1920 to 2100 allowing statistical robustness of event characteristics. Additional analysis of high resolution forced and coupled simulations will allow assessment of the fidelity of the representation of MHWs in boundary current regions where large biases are known to exist in low resolution simulation. In addition, a decadal prediction system using the same model version as the large ensemble will allow exploration of the role of ocean initialization in the predictability of these dangerous events. Typical analysis of MHW properties has used pointwise metrics, or metrics defined as area averages over fixed boxes. New integrated metrics for MHW characterization will be created that allow for MHWs that change shape and position over time, and will take into account heat stored below the surface. The role of climate variability in controlling MHWs will be assessed using the large ensemble, while comparison of high and low resolution models will allow for assessment of the robustness of the results from low resolution models. The focus on midlatitude events will include assessment of how ocean heat storage and re-emergence affect properties of MHWs.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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