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Over the continental slope off Oregon at the US West Coast, at 44.6°N, vertical stratification is found to be anomalously weak in July–August of 2014 and 2015 both in a regional ocean circulation model and conductivity–temperature–depth (CTD) profile observations. To understand the responsible mechanism, we focus on the layer between the isopycnal surfaces σθ = 26.5 and 26.25 kg m−3 that is found between depths 100 and 300 m and represents material properties characteristic of the slope poleward undercurrent and shelf‐slope exchange. This layer thickness, about 50 m on average, can be twice as large during the above‐mentioned periods. In the 2009–2018 model analysis, this anomaly is revealed over the continental slope only in summers 2014 and 2015 and only off the Oregon and Washington coasts (40°–47°N). The stratification anomaly is explained as the effect of advection of the seasonal along‐slope potential vorticity (PV) gradient by an anomalously strong poleward slope current. In the annual cycle, the zone of strong along‐slope PV gradient is found between 40° and 47°N, supported by the local upwelling that results in the injection of the large PV in the bottom boundary layer over the shelf followed by its offshore transport in the slope region. The positive along‐slope current anomaly propagates to Oregon with coastally trapped waves as part of the El Niño oceanic response and can be up to 0.1 m s−1. Advection by this anomalous poleward current results in transporting the seasonal PV gradient earlier in the season than on average. Plain Language Summary: Understanding the oceanic dynamics along the continental slopes is important for understanding material exchanges between the coastal and interior ocean and biological diversity. Analysis of a high‐resolution, three‐dimensional ocean circulation model helps explain observed variability over the slope. Associated with the global anomaly pattern called El Niño, the along‐slope poleward current off Oregon was anomalously strong in summers 2014 and 2015. This anomalous transport caused alongshore displacement of the water masses from the south resulting in the vertical spreading of the subsurface oceanic layers. Key Points: In summer 2014 and 2015, the model and data reveal episodes of anomalously weak stratification over the continental slope off OregonAdvection of the seasonal potential vorticity gradient by the anomalously strong slope current drives the weaker stratification anomalyThe poleward along‐slope current anomaly is part of the El Niño oceanic response propagated with coastally trapped waves [ABSTRACT FROM AUTHOR]

Outputs of the regional ocean circulation model are analyzed to demonstrate the measurable impact of the El Niño remote oceanic forcing mechanism along the US West Coast during the major heat wave period of 2014–2016. The 2‐km horizontal resolution model, based on the Regional Ocean Modeling System (ROMS), was run for the period of 2009–2018. Though the model does not assimilate observations, it performs well by comparison with time series data explaining observed variability on temporal scales from several days to seasonal and interannual. The El Niño‐related oceanic anomalies provided by a global state estimate are introduced in the regional model at the southern boundary at 24N. These propagate alongshore with coastally trapped waves (CTWs) and influence the variability off Oregon (41°–46°N). In particular, CTWs are evident in the subsurface along‐slope current, vs, and in the depth of the 26.5 kg m−3 isopycnal surface over the slope, z26.5. In summer 2014 and 2015, vs anomalies are positive (northward) and z26.5 anomalies are negative (deeper) along the US West Coast. In addition to the CTW patterns, z26.5 anomalies also exhibit slow‐moving features associated with undercurrent widening, separation, and subsurface eddy variability. Over the Oregon shelf, El Niño conditions contributed to the sharp weakening of the southward alongshore current throughout the water column in July 2014 and 2015, despite the near‐average southward, upwelling‐favorable winds. Plain Language Summary: El Niño is a large‐scale anomalous pattern that originates in the atmosphere and the ocean in the equatorial Pacific ocean. It occurs once every several years at irregular time intervals and impacts the weather and ocean variability at great distances, in particular reaching the Pacific coast of the United States. In this study, a high‐resolution, three‐dimensional computer ocean circulation model is utilized to track the El Niño‐related signal propagating as very long oceanic waves along the continental slope from Mexico to the United States and Canada in 2014 and 2015. This propagation is best seen in the subsurface alongshore currents and in the depression of the surfaces of constant density over the continental slope. The model compares well to satellite and in‐situ observations. Carefully designed numerical models can be utilized for multiyear simulations to aid scientific discoveries. Key Points: El Niño anomalies propagating with coastally trapped waves (CTWs) impact the coastal ocean variability off Oregon 2014–2016In summers 2014 and 2015, the subsurface along‐slope velocity anomalies are poleward, propagating as CTWOn the shelf, alongshore southward currents are sharply reduced in July 2014 and 2015 despite the upwelling winds are strong [ABSTRACT FROM AUTHOR]

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 100–250 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. Plain Language Summary: Slow‐slip earthquakes, a special class of earthquake in which slip along a fault occurs over periods of days to years without producing shaking, have increasingly been found to occur in the subsea segments of subduction zones worldwide. There is evidence that these offshore slow‐slip earthquakes can occur within the same region where large, damaging earthquakes are generated and that they may precede and potentially trigger these events. Offshore slow‐slip earthquakes cause the seafloor to move vertically by up to a few centimeters, which can be detected by measuring the pressure on the seafloor if the effects of ocean tides and circulation can be corrected for. In this study, we search for evidence of slow‐slip earthquakes in seafloor pressure data from the Cascadia Subduction Zone, off the U.S. and Canadian west coast, and assess how to best reduce oceanographic signals in these data in order to reliably observe slow‐slip deformation. No evidence for these events is seen in Cascadia pressure data from 2011 to 2015. Using a combination of observational data and model simulations, we show that oceanographic signals can be largely eliminated from seafloor pressure measurements if instruments are placed in rows of constant depth. A network of 22 instruments would be sufficient to monitor for large offshore slow‐slip earthquakes offshore central Oregon, but smaller events would be difficult to detect with this method. By increasing our ability to detect these slow‐slip earthquakes, we can better understand subduction zone processes and their relation to large, damaging megathrust earthquakes. Key Points: In Cascadia, differencing tidally filtered, depth‐matched seafloor pressure records can reduce oceanographic noise to less than 1‐cm RMSModels of offshore SSEs in Cascadia suggest that a network of depth‐matched sensors at 30‐km spacing can detect Mw 6.4 and larger eventsNo offshore slow‐slip earthquakes are detected in the available Cascadia seafloor pressure data from 2011 to 2015 [ABSTRACT FROM AUTHOR]

Spurious long-distance correlations in estimates of the background error covariance can deteriorate the performance of ensemble-based data assimilation methods. In this study, a localization method, called Monte Carlo (MC) localization, is presented to remove these correlations. It is particularly useful for use in high-dimensional ensemble-variational data assimilation systems. In this method, raw ensemble members are truncated by multiplying them with functions having compact support. This creates a larger ensemble, in which points spaced farther apart than the size of the compact support have zero correlation. The localized background error covariance is then estimated as the sample covariance of this larger ensemble. It is hypothesized that this localized background error covariance can be approximated by the MC approximation method using a limited set of the truncated ensemble members. This hypothesis is tested here on a grid with 1001 grid points and assuming a Gaussian true background error covariance. It is found that the mean relative error has an upper bound that scales with the inverse square root of the number of truncated ensemble members. In the case studied the size of the support for which the localized background covariance best approximates the true background covariance increases with increasing number of raw ensemble members and is close to 4 times the standard deviation of the Gaussian when 20 raw ensemble members are used. In the Fourier space the localization manifests itself as a convolution resulting in smoothing of the power spectral density of the ensemble members. [ABSTRACT FROM AUTHOR]

This paper presents a least squares method to estimate the horizontal (isotropic or anisotropic) spatial covariance of two-dimensional orthogonal vector components, without introducing an intervening mapping step and biases, from the spatial covariance of the nonorthogonally and irregularly sampled raw scalar velocities. The field is assumed to be locally homogeneous in space and sampled in an ensemble so the unknown spatial covariance is a function of spatial lag only. The transformation between the irregular grid on which nonorthogonal scalar projections of the vector are sampled and the regular orthogonal grid on which they will be mapped is created using the geometry of the problem. The spatial covariance of the orthogonal velocity components of the field is parameterized by either the energy (power) spectrum in the wavenumber domain or the lagged covariance in the spatial domain. The energy spectrum is constrained to be nonnegative definite as part of the solution of the inverse problem. This approach is applied to three example sets of data, using nonorthogonally and irregularly sampled radial velocity data obtained from 1) a simple spectral model, 2) a regional numerical model, and 3) an array of high-frequency radars. In tests where the true covariance is known, the proposed direct approaches fitting to parameterizations of the nonorthogonally and irregularly sampled raw data in the wavenumber domain and spatial domain outperform methods that map the data to a regular grid before estimating the covariance. [ABSTRACT FROM AUTHOR]

A linearized baroclinic, spectral-in-time tidal inverse model has been developed for assimilation of surface currents from coast-based high-frequency (HF) radars. Representer functions obtained as a part of the generalized inverse solution show that for superinertial flows information from the surface velocity measurements propagates to depth along wave characteristics, allowing internal tidal flows to be mapped throughout the water column. Application of the inverse model to a 38 km × 57 km domain off the mid-Oregon coast, where data from two HF radar systems are available, provides a uniquely detailed picture of spatial and temporal variability of the M[sub 2] internal tide in a coastal environment. Most baroclinic signal contained in the data comes from outside the computational domain, and so data assimilation (DA) is used to restore baroclinic currents at the open boundary (OB). Experiments with synthetic data demonstrate that the choice of the error covariance for the OB condition affects model performance. A covariance consistent with assumed dynamics is obtained by nesting, using representers computed in a larger domain. Harmonic analysis of currents from HF radars and an acoustic Doppler profiler (ADP) mooring off Oregon for May–July 1998 reveals substantial intermittence of the internal tide, both in amplitude and phase. Assimilation of the surface current measurements captures the temporal variability and improves the ADP/solution rms difference. Despite significant temporal variability, persistent features are found for the studied period; for instance, the dominant direction of baroclinic wave phase and energy propagation is always from the northwest. At the surface, baroclinic surface tidal currents (deviations from the depth-averaged current) can be 10 cm s[sup –1] , 2 times as large as the depth-averaged current. Barotropic-to-baroclinic energy conversion is generally weak within the model domain over the shelf but reaches 5 mW m[sup –2] at times over the slopes of Stonewall Bank. [ABSTRACT FROM AUTHOR]