Browsing College of Natural Science and Mathematics (CNSM) by Subject "observations"
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Anisotropy in the Alaska subduction zone: shear-wave splitting observations from local and teleseismic earthquakesShear-wave splitting observations can provide insight to mantle flow due to the link between the deformation of mantle rocks and their direction dependent seismic wave velocities. We identify shear-wave anisotropy in the Cook Inlet segment of the Alaska subduction zone by analyzing splitting parameters of S phases from local intraslab earthquakes between 50 and 200 km depths and SKS waves from teleseismic events. These earthquakes were recorded from 2015-2017 (local S) and 2007-2017 (SKS) by stations from SALMON (Southern Alaska Lithosphere and Mantle Observation Network), TA (EarthScope Transportable Array), MOOS (Multidisciplinary Observations Of Subduction), AVO (Alaska Volcano Observatory), and the permanent network. Automatic phase picking (dbshear) of 12095 local earthquakes (Ml ≥ 1.5) recorded at 84 stations yielded 678 high-quality splitting measurements (filtered 0.2-1 Hz). Teleseismic SKS phases recorded at 112 stations with 26,143 event-station pairs resulted in 360 high-quality SKS splitting measurements (filtered 0.02-1 Hz and 0.01-1 Hz). Measurements for both datasets were made using the SC91 minimum eigenvalue method with software package MFAST. We compare local S and SKS splitting patterns both from previous studies and our own analysis and find that they are most similar in the far forearc, at the Kenai Peninsula, below which there is no mantle wedge. Anisotropy in the subducting Pacific lithosphere and subslab asthenosphere is likely here as both S and SKS display plate convergence fast directions and SKS measurements exhibit delay times too long (∼2 s) to be explained solely by lithospheric anisotropy. Large splitting delay times (∼0.5 s) for local measurements that mainly sample slab further indicate that the Pacific slab lithosphere contains significant anisotropy. We also observe anisotropy in the mantle wedge indicated by an increase in delay time as focal depth increases for stations with ray paths dominantly sampling wedge. These measurements display trench-perpendicular and plate convergence fast directions consistent with 2D corner flow in the mantle wedge. Both datasets show trench-parallel splitting directions in select areas of the arc/forearc that overlie parts of the mantle wedge and nose. B-type olivine in the mantle nose, subslab asthenospheric flow, flow around the slab edge, and anisotropy in the Pacific lithosphere all could be invoked to explain this pattern. While we are unable to distill the anisotropy to a single responsible structure, the sharp transition in the local S data splitting pattern from trench-perpendicular in the backarc to trench-parallel across the arc suggests B-type olivine in the mantle nose. For an overall model, we favor 2D corner flow of A-type olivine in the mantle wedge induced by downdip motion of the slab, B-type olivine in the nose, and plate convergence parallel anisotropy in the subslab asthenosphere and subducting Pacific lithosphere to explain the observed splitting patterns. It is clear that the subducting slab's structure and motion are the dominant influence on anisotropy and mantle flow regimes here. The differences in local S and SKS splitting results motivate further study on frequency dependence of splitting measurements and emphasize the need for a better understanding of which earth structures are responsible for the observed splitting patterns globally. This study constitutes the first comprehensive local splitting study in Alaska and refutes the common interpretation of along arc flow in the mantle wedge proposed by many previous splitting studies in Alaska.
Data analysis and data assimilation of Arctic Ocean observationsArctic-region observations are sparse and represent only a small portion of the physical state of nature. It is therefore essential to maximize the information content of observations and bservation-conditioned analyses whenever possible, including the quantification of their accuracy. The four largely disparate works presented here emphasize observation analysis and assimilation in the context of the Arctic Ocean (AO). These studies focus on the relationship between observational data/products, numerical models based on physical processes, and the use of such data to constrain and inform those products/models to di_erent ends. The first part comprises Chapters 1 and 2 which revolve around oceanographic observations collected during the International Polar Year (IPY) program of 2007-2009. Chapter 1 validates pan- Arctic satellite-based sea surface temperature and salinity products against these data to establish important estimates of product reliability in terms of bias and bias-adjusted standard errors. It establishes practical regional reliability for these products which are often used in modeling and climatological applications, and provides some guidance for improving them. Chapter 2 constructs a gridded full-depth snapshot of the AO during the IPY to visually outline recent, previouslydocumented AO watermass distribution changes by comparing it to a historical climatology of the latter 20th century derived from private Russian data. It provides an expository review of literature documenting major AO climate changes and augments them with additional changes in freshwater distribution and sea surface height in the Chukchi and Bering Seas. The last two chapters present work focused on the application of data assimilation (DA) methodologies, and constitute the second part of this thesis focused on the synthesis of numerical modeling and observational data. Chapter 3 presents a novel approach to sea ice model trajectory optimization whereby spatially-variable sea ice rheology parameter distributions provide the additional model flexibility needed to assimilate observable components of the sea ice state. The study employs a toy 1D model to demonstrate the practical benefits of the approach and serves as a proof-of-concept to justify the considerable effort needed to extend the approach to 2D. Chapter 4 combines an ice-free model of the Chukchi Sea with a modified ensemble filter to develop a DA system which would be suitable for operational forecasting and monitoring the region in support of oil spill mitigation. The method improves the assimilation of non-Gaussian asynchronous surface current observations beyond the traditional approach.