On 29 July 2021, an Mw 8.2 megathrust earthquake struck the Alaska Peninsula. Quantifying the coseismic slip and the afterslip that followed this earthquake provides us the opportunity to clarify the megathrust slip budget and the earthquake hazard potential there. However, the estimated coseismic slip distribution inversion result is strongly affected by assumptions made in the inversion. The spatial pattern of stress-driven afterslip is mainly controlled by the coseismic slip distribution, so that it can provide new information about the coseismic slip distribution and is useful to assess the assumptions made in the coseismic inversion. The orientation and relative magnitudes of postseismic displacements at sites on the Alaska Peninsula require that the afterslip be concentrated ~130km from the trench. As a result, coseismic slip models including slip at that distance or less to shore, predict postseismic deformation that systematically misfits the observations. A narrower coseismic rupture plane with an abrupt downward termination of slip provides a much better fit to the observed postseismic signal than models where the slip tapers gently with depth. We considered multiple different viscoelastic relaxation models and find that these conclusions about the coseismic model are required regardless of the viscoelastic relaxation models used. The contribution of viscoelastic relaxation to the observed signal is not negligible, and the early postseismic observations are best reproduced with a model that features a 50 km thick elastic lithosphere for the overriding plate, and an elastic cold nose to the mantle wedge.

Early Postseismic Deformation of the 29 July 2021 Mw8.2 Chignik Earthquake Provides New Constraints on the Downdip Coseismic SlipZ. Zhuo1, J.T. Freymueller1, Z. Xiao2, J. Elliott1, and R. Grapenthin31Michigan State University2Kunming University of Science and Technology3University of Alaska FairbanksCorresponding author: Zechao Zhuo([email protected])Key Points:The spatial pattern of afterslip provides new information about the coseismic slip distribution of the 2021 Mw8.2 Chignik earthquake.Displacements due to viscoelastic depend strongly on the viscosity model, but sensitive to the details of the coseismic slip.The maximum depth of the Chignik coseismic rupture constrained by the stress-driven afterslip is about 35km based on the lab2.0 geometry.AbstractOn 29 July 2021, an Mw 8.2 megathrust earthquake struck the Alaska Peninsula. Quantifying the coseismic slip and the afterslip that followed this earthquake provides us the opportunity to clarify the megathrust slip budget and the earthquake hazard potential there. However, the estimated coseismic slip distribution inversion result is strongly affected by assumptions made in the inversion. The spatial pattern of stress-driven afterslip is mainly controlled by the coseismic slip distribution, so that it can provide new information about the coseismic slip distribution and is useful to assess the assumptions made in the coseismic inversion. The orientation and relative magnitudes of postseismic displacements at sites on the Alaska Peninsula require that the afterslip be concentrated ~130km from the trench. As a result, coseismic slip models including slip at that distance or less to shore, predict postseismic deformation that systematically misfits the observations. A narrower coseismic rupture plane with an abrupt downward termination of slip provides a much better fit to the observed postseismic signal than models where the slip tapers gently with depth. We considered multiple different viscoelastic relaxation models and find that these conclusions about the coseismic model are required regardless of the viscoelastic relaxation models used. The contribution of viscoelastic relaxation to the observed signal is not negligible, and the early postseismic observations are best reproduced with a model that features a 50 km thick elastic lithosphere for the overriding plate, and an elastic cold nose to the mantle wedge.

We simulated tsunami propagation for several scenario slip distributions for the 1938 MW 8.3 earthquake along the Alaska Peninsula, and compared these to the observed records at Unalaska/Dutch Harbor and Sitka. The Sitka record is sensitive to the depth of slip but not the along-strike location, and is fit best by slip at shallow depth. The Unalaska record is sensitive mainly to the along-strike location of slip, and is fit best by slip that is concentrated in the eastern part of the presumed 1938 rupture zone. The tsunami data show that the actual 1938 earthquake rupture zone was smaller than previously thought, likely ~200 km in length, and had no slip near the Shumagin Islands or in the 2020 Simeonof earthquake’s rupture zone. The rupture models that best predict the 1938 tsunami lie within the region of high present day slip deficit inferred from GPS.

A slope at Barry Arm, in Alaska’s Prince William Sound, is deforming at a varying rate up to tens of meters per year above a retreating glacier and deep fjord that is a popular recreational destination. If the estimated 500 million cubic meters of unstable material on this slope were to fail catastrophically, the impact of the landslide with the ocean would produce a tsunami that would not only endanger those in its immediate vicinity, but likely also those in more distant areas such as the port of Whittier, 50 km away. The discovery of this threat was happenstance, and the response so far has been cobbled together from over a dozen existing grants and programs. Remotely sensed imagery could have revealed this hazard a decade ago, but nobody was looking, highlighting our lack of coordination and preparedness for this growing hazard driven by climate change. As glaciers retreat, they can simultaneously destabilize mountain slopes and expose deep waters below, creating the potential for destructive tsunamis. The settings where this risk might occur are easily identified, but more difficult to assess and monitor. Unlike for volcanoes, active faults, landslides, and tectonic tsunamis, the US has conducted no systematic assessment of tsunamis generated by subaerial landslides, nor has the US established methods for monitoring or issuing warnings for such tsunamis. The U.S. National Tsunami Warning Center relies on seismic signals and sea-level measurements to issue warnings; however, landslides are more difficult to detect than earthquakes, and the resultant tsunamis often would reach vulnerable populations and infrastructure before water level gages could help estimate the magnitude of the tsunami. Also, integrating precursory motion and other clues of an impending slope failure into a tsunami warning system has only been done outside the US (e.g Norway: Blikra et al., 2012). Barry Arm is a dramatic case study highlighting these challenges and may provide a model for mitigating the threat of tsunamis generated by subaerial landslides enabled by glacial retreat elsewhere.

In Southeast Alaska, extreme uplift rates are primarily caused by glacial isostatic adjustment (GIA), as a result of ice thickness changes from the Little Ice Age to the present combined with a low-viscosity asthenosphere. Previous GIA models adopted a 1-D Earth structure. However, the actual Earth structure is likely more complex due to the long history of subduction and tectonism and the transition from a continental to an oceanic plate. Seismic evidence shows a laterally heterogenous Earth structure. In this study a numeral model is constructed for Southeast Alaska, which allows for the inclusion of lateral viscosity variations. The viscosity follows from scaling relationships between seismic velocity anomalies and viscosity variations. We use this scaling relationship to constrain the thermal effect on seismic variations and investigate the importance of lateral viscosity variations. We find that a thermal contribution to seismic anomalies of 10% is required to explain the GIA observations. This implies that non-thermal effects control seismic anomaly variations in the shallow upper mantle. Due to the regional geologic history, it is likely that hydration of the mantle impact both viscosity and seismic velocity. The best-fit model has a background viscosity of 5.0×10^19 Pa-s, and viscosities at ~80 km depth range from 1.8×10^19 to 4.5×10^19 Pa-s. A 1-D averaged version of the 3-D model performed slightly better, however, the two models were statistically equivalent within a 2σ measurement uncertainty. Thus, lateral viscosity variations do not contribute significantly to the uplift rates measured with the current accuracy and distribution of sites.

Near-field observations of tsunami waves generated by the Mw9.2 1964 Alaska earthquake reveal a complex relationship between coseismic slip and the tsunami wavefield in the source area. The documented times and amplitudes of first arrivals, measured runup heights and inundation areas along the coasts of the Kenai Peninsula and Kodiak Island show that secondary splay faults played an important role in generating destructive tsunami waves. We find that a splay fault extending to about 150°W is required to fit tsunami first arrivals on the Kenai Peninsula, but that the splay fault did not rupture along the entire length of the Kenai Peninsula. This extent supports the connection of splay faulting to a persistent Prince William Sound asperity. Our results also show that the contribution of coseismic horizontal displacements into the initial tsunami wave field does not change the pattern of tsunami arrivals much, but increases the amplitude. The coseismic deformation model of Suito and Freymueller (2009) explains the pattern of tsunami arrivals in the Kodiak Island region well, indicating that it provides a good estimate of slip on the megathrust in the Kodiak asperity. The sensitivity of the near-field arrival information to the coseismic slip model shows that such data are important in distinguishing between slip on splay faults and on the megathrust, and in discriminating between competing slip models.