High Resolution Internal Wave Tracking via Remote Sensing with Comparison to In-Situ Measurements

Alexandra J Simpson1, Merrick C Haller2, Jacqueline McSweeney3 and James A Lerczak3, (1)Oregon State University, Civil & Construction Engineering, Corvallis, OR, United States, (2)Oregon State University, School of Civil and Construction Engineering, Corvallis, OR, United States, (3)Oregon State University, College of Earth, Ocean, and Atmospheric Sciences, Corvallis, OR, United States
Abstract:
During August-September 2017, a large field program (Inner Shelf Dynamics) was conducted near Point Sal, California. The experiment aimed to better describe interacting nonlinear processes of the inner shelf, and included observations from many in situ and remote sensing platforms, as well as numerical modeling. The present work describes the use and analysis of shore-based X-band radar observations to provide a synoptic picture of internal wave propagation over spatial scales of kilometers, at resolution of tens of meters and several minutes. The radar images internal waves as bands of high and low intensity due to changes of surface roughness resulting from internal wave kinematics. These spatial and temporal observations are used to measure internal wave speeds and directions across and along the inner shelf (depths 10-50m). We estimate IW cross-shore speeds and incident angles through the use of parallel space-time (Hovmöller) transects. Phase analysis from transect pairs allows extraction of local IW propagation angles, and speeds of individual IWs are found through edge detection in the Hovmöller diagrams. The estimated speeds and angles are compared to estimates from in situ observations. Speeds and directions derived from the radar observations are in general agreement with in situ estimates and both are similar to that predicted by linear theory. However, under certain conditions internal wave speeds exceed the linear speed suggesting the importance of nonlinearity. Continuing analysis is focused on wave-to-wave speed variability among packets of IWs, and understanding how IW transformation observations vary with ambient stratification conditions.