Radar Improves Understanding of Estuarine Internal Waves
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ISSUE
Circulation in the Columbia River estuary is influenced by tidal forcing, river discharge and wind stress. Through their interactions with the river bottom, these forces generate a variety of ecologically-relevant phenomena that have been difficult to observe on a continuous basis. Of these phenomena, internal waves are known to be generated in the lower estuary, and may influence local vertical density structure and system-wide transport processes controlling salinity intrusion and Myrionecta rubra blooms.
APPROACH
Internal waves are underwater waves on subsurface density gradients. They move the surface very little but can move subsurface water by large amounts. They are produced only on the proper tidal phase. Because of their signature on the water surface, internal waves should be detectable by radar. To test this hypothesis, CMOP researchers installed a coherent X-band (9.36 GHz) radar on the Astoria-Megler bridge (see figure). This radar collects data every fifteen minutes over an area of 39 km2 from which images of surface roughness and velocity can be obtained. (View river radar data) The radar has been running nearly continuously since spring 2009.
Black lines show spatial coverage of the radar (A) from the Astoria-Megler bridge (right) to the river mouth (left) (background courtesy Google Earth). The red rectangle shows the approximate location of internal waves. (B) Photo of the surface expression of internal waves taken from the R/V Pt. Sur at 1600 PDT on Sept. 8, 2009 (courtesy Craig McNeil). (C & D) Images produced from radar data showing internal waves at 1740 PDT on that day. Total power is related to internal wave amplitude while spacing indicates wavelength.
FINDINGS
This radar has collected data on internal waves as well as up- and down-stream surface currents, perturbations of surface roughness along the edge of deep channels, and wetting or drying of areas of the river. It has consistently detected the generation and propagation of internal waves in the North Channel of the estuary. Location and time of generation are consistent with shipboard observations and data collected by underwater unmanned vehicles (AUVs) during a CMOP research campaign in late summer 2009 (see figure). They are also consistent with anticipated generation mechanisms: a strongly stratified fluid moving over a sharp slope. This indicates a large subsurface density gradient and waves that can contribute to mixing.
IMPLICATIONS
Traditional means of studying internal waves such as shipboard measurements or satellite imagery do not capture their long-term generation patterns or their evolution. Continuous monitoring using radar overcomes this limitation. The radar can detect internal waves throughout the tidal cycle, thus enabling the study of their generation mechanisms and estimation of their effects on mixing in the estuary. Moreover, these results are synergistic with other CMOP research. For instance, radar data can guide field campaigns by identifying internal wave location and timing for shipboard and AUV operations. In turn, these operations can provide ground truth for the radar data with measurements of water velocity, water displacement, and phase speed of the internal waves.
MORE
These results provide information on the effects of tidal flow over the bathymetry at the mouth of the Columbia River for comparison with a non-hydrostatic numerical circulation model being developed by CMOP modelers. Characterizing the internal wave field in the highly dynamic Columbia River estuary will help explain mixing and transport regimes, which ultimately govern patterns of biological production and determine the suitability of habitats for many estuarine species.
CREDITS
This work was conducted at the Applied Physics Laboratory of the University of Washington (APL-UW), and is a collaborative effort of William Plant, Gordon Farquharson, Chris Siani, Ken Hayes, and William Keller. Complementary efforts: local logistical support by the Astoria field team (Oregon Health & Science University, OHSU); observations (shipboard and with AUVs) by Craig McNeil (APL-UW); non-hydrostatic modeling by Joseph Zhang and Antonio Baptista (OHSU); web representation by CMOP cyber team (OHSU).
