Alex Fisher Affiliate afisher1@uw.edu |
Education
B.S. Civil & Environmental Engineering, University of Washington, 2011
M.S. Civil & Environmental Engineering. Specialization: Environmental Fluid Mechanics & Hydrology, Stanford University, 2012
Ph.D. Marine, Estuarine and Environmental Science, University of Maryland, 2017
Publications |
2000-present and while at APL-UW |
AUV observations of Langmuir turbulence in a stratified shelf sea Fisher, A.W., and N.J. Nidzieko, "AUV observations of Langmuir turbulence in a stratified shelf sea," J. Phys. Oceanogr., 54, 1903-1920, doi:0.1175/JPO-D-23-0136.1, 2024. |
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1 Sep 2024 |
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Measurements collected by a REMUS 600 AUV off the coast of southern California demonstrate large-scale coherent wave-driven vortices, consistent with Langmuir turbulence (LT), played a dominant role in structuring turbulent dissipation within the oceanic surface boundary layer. During a 10-hour period with sustained wind speeds of 10 m s-1, Langmuir circulations were limited to the upper third of the surface mixed layer by persistent stratification within the water column. The ensemble-averaged circulation, calculated using conditional averaging of AD2CP velocity profiles using elevated backscattering intensity associated with subsurface bubble clouds, indicates that LT vortex pairs were characterized by an energetic downwelling zone flanked by broader, weaker upwelling regions with vertical velocity magnitudes similar to previous numerical studies of LT. Horizontally-distributed microstructure estimates of turbulent kinetic energy dissipation rates were lognormally-distributed near the surface in the wave mixing layer with the majority of values falling between wall layer scaling and wave transport layer scaling. Partitioning dissipation rates between downwelling centers and ambient conditions suggests that LT may play a dominant role in elevating dissipation rates in the OSBL by redistributing wave breaking turbulence. |
The next wave: Buoy arrays for deterministic wave prediction in real-time Thomson, J., A. Fisher, and C.J. Rusch, "The next wave: Buoy arrays for deterministic wave prediction in real-time," In Proc., IEEE/OES 13th Current, Waves and Turbulence Measurement (CWTM), 18-20 March 2024, Wanchese, NC, doi:10.1109/CWTM61020.2024.10526333 (IEEE, 2024). |
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15 May 2024 |
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This work uses sparse arrays of ocean wave buoys to create a linear reconstruction of the sea surface and provide deterministic wave predictions at a future time and nearby position (i.e., within a few wavelengths). The predictions are constrained to be within the statistics of recently observed waves. This recently established method is applied in post-processing at two distinct projects related to 1) a wave energy converter and 2) an offshore wind platform. The conditions range from scale-model tank testing to an operational open-ocean wind farm. Relative to a conventional statistical forecasting with random waves, the method achieves at least 60% improvement in prescribing the next several waves arriving at a given target location. Work is ongoing to implement this method in realtime, using radio modems to transmit raw motion data (5 Hz sampling) from the buoy array to a central node that continually updates a 30-second prediction window with less than 1-second latency. The deterministic wave predictions can be used to improve control strategies for platforms at sea, with improvements in efficiency and reductions in dynamic loads. |
Rapid deterministic wave prediction using a sparse array of buoys Fisher, A., J. Thomson, and M. Schwendeman, "Rapid deterministic wave prediction using a sparse array of buoys," Ocean Eng., 228, doi:10.1016/j.oceaneng.2021.108871, 2021. |
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15 May 2021 |
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A long-standing problem in maritime operations and ocean development projects has been the prediction of instantaneous wave energy. Wave measurements collected using an array of freely drifting arrays of Surface Wave Instrument Float with Tracking (SWIFT) buoys are used to test methods for phase-resolved wave prediction in a wide range of observed sea states. Using a linear inverse model in directionally-rich, broadbanded wave fields can improve instantaneous heave predictions by an average of 63% relative to statistical forecasts based on wave spectra. Numerical simulations of a Gaussian sea, seeded with synthetic buoys, were used to supplement observations and characterize the spatiotemporal extent of reconstruction accuracy. Observations and numerical results agree well with theoretical deterministic prediction zones proposed in previous studies and suggest that the phase-resolved forecast horizon is between 13 average wave periods for a maximum measurement interval of 10 wave periods for ocean wave fields observed during the experiment. Prediction accuracy is dependent on the geometry and duration of the measurements and is discussed in the context of the nonlinearity and bandwidth of incident wave fields. |