Monitoring Changes in Ocean Temperatures Using Ambient Noise

Monitoring changes in ocean temperature, while difficult, is pertinent to establish trends in ocean temperatures over many time scales. Climate change has impacted the ocean temperatures because the ocean absorbs most of the excess heat from greenhouse gas emissions. Many processes and systems, such as marine species and ecosystems, are sensitive to ocean temperature. Looking into changes in the travel time of Rayleigh waves, a type of surface wave, between seismic stations may be useful to infer changes in ocean temperature in the region. Seismic interferometry, also referred to as Greens function retrieval, is used to obtain travel time. This study focuses on five hydrophones and seismometers off the coast of Washington and Oregon. The first step is to cross-correlate the ambient noise recorded at pairs of stations. The result is Greens function, a response measured at one station with the impulse source at the other, and it reveals the travel time of the Rayleigh wave between the stations. With travel time in the ocean largely dependent on the temperature, changes in travel time indicates changes in ocean temperature. This study focuses on waves with periods of 1 to 10 seconds as they are the most sensitive to changes in temperature in the water column. Hydrophones that are close together (<30 km) show strong signals from 10 days and a higher number of stacked cross-correlated data. Hydrophones that are far apart (>370 km) show weak signals at ten to eighty days stacked. Adding more data will reveal at what point it becomes clear. The next step is to compare results and signal strength to the cross-correlation of seismometers from these stations, giving insight into which device provides better signal. This is potentially constructive to monitoring changes in ocean temperatures.