@article {RN125,
	title = {Optimizing Sensor Configurations for the Detection of Slow-Slip Earthquakes in Seafloor Pressure Records, Using the Cascadia Subduction Zone as a Case Study},
	journal = {Journal of Geophysical Research-Solid Earth},
	year = {2019},
	type = {Journal Article},
	abstract = {We present seafloor pressure records from the Cascadia Subduction Zone, alongside oceanographic and geophysical models, to evaluate the spatial uniformity of bottom pressure and optimize the geometry of sensor networks for resolving offshore slow-slip transients. Seafloor pressure records from 2011 to 2015 show that signal amplitudes are depth-dependent, with tidally filtered and detrended root-mean-squares of <2 cm on the abyssal plain and >6 cm on the continental shelf. This is consistent with bottom pressure predictions from circulation models and comparable to deformation amplitudes from offshore slow slip observed in other subduction zones. We show that the oceanographic component of seafloor pressure can be reduced to <=1-cm root-mean-square by differencing against a reference record from a similar depth, under restrictions that vary with depth. Instruments at 100{\textendash}250 m require depths matched within 10 m at separations of <100 km, while locations deeper than 1,400 m are broadly comparable over separations of at least 300 km. Despite the significant noise reduction from this method, no slow slip was identified in the dataset, possibly due to poor spatiotemporal instrument coverage, nonideal deployment geometry, and limited depth-matched instruments. We use forward predictions of deformation from elastic half-space models and hindcast pressure from circulation models to generate synthetic slow-slip observational records and show that a range of slip scenarios produce resolvable signals under depth-matched differencing. For future detection of offshore slow slip in Cascadia, we recommend a geometry in which instruments are deployed along isobaths to optimize corrections for oceanographic signals.},
	issn = {2169-9313},
	doi = {10.1029/2019JB018053},
	author = {Fredrickson, E. K. and Wilcock, W. S. D. and Schmidt, D. A. and MacCready, P. and Roland, E. and Kurapov, A. L. and Zumberge, M. A. and Sasagawa, G. S.}
}
@article {RN75,
	title = {Why Gliders Appreciate Good Company: Glider Assimilation in the Oregon-Washington Coastal Ocean 4DVAR System With and Without Surface Observations},
	journal = {Journal of Geophysical Research: Oceans},
	volume = {124},
	number = {1},
	year = {2019},
	pages = {750-772},
	type = {Journal Article},
	abstract = {Gliders are low-power autonomous underwater vehicles used to obtain oceanic measurements in vertical sections. Assimilation of glider temperature and salinity into coastal ocean circulation models holds the potential to improve the ocean subsurface structure estimate. In this study, the impact of assimilation of glider observations is studied using a four-dimensional variational (4DVAR) data assimilation and forecast system set offshore of Oregon and Washington on the U.S. West Coast. Four test cases are compared: (1) no assimilation, (2) assimilation of glider temperature and salinity data alone, (3) assimilation of the glider data in combination with the surface observations including satellite sea surface temperature, sea surface height, and high-frequency radar surface velocities, and (4) assimilation of the surface data alone. It is found that the assimilation of glider observations alone creates unphysical eddies in the vicinity of the glider transect. As a consequence, the forecast errors in the surface velocity and temperature increase compared to the case without data assimilation. Assimilation of surface and subsurface observations in combination prevents these features from forming and reduces the errors in the forecasts for the subsurface fields compared to the other three experiments. These improvements persisted in 21-day forecasts run after the last data assimilation cycle.

},
	issn = {2169-9275},
	doi = {10.1029/2018JC014230},
	url = {https://doi.org/10.1029/2018JC014230},
	author = {Pasmans, I. and Kurapov, A. L. and Barth, J. A. and Ignatov, A. and Kosro, P. M. and Shearman, R. K.}
}
