Evaluating the predictive skill of a regional model in forecasting the California Undercurrent
In the summer of 2017, I worked with Dr. Samantha Siedlecki to compare velocity output from a regional model to acoustic doppler current profiler (ADCP) shipboard data to assess the model’s predictive skill for forecasting the California Undercurrent (CUC). This project was especially impactful for fishery management because the strength of the CUC affects migration patterns of Pacific hake. This experience helped me get comfortable using large data sets and coding in MATLAB, and the summer ended with my first experience presenting my own research. To the right is a brief video summary of what my summer at JISAO entailed, and below is my poster from the intern research symposium at the end of the summer.
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