The complexity of Alaska presents several challenges for earthquake early warning systems. These include the presence of offshore earthquakes, transform boundaries and crustal faults extending hundreds of kilometers, deep earthquakes, and a complicated coastline. This variety, combined with population centers spread far apart, makes it challenging to anticipate an earthquake early warning system's performance and to design a network accordingly. As Alaska begins to plan for earthquake early warning, our objective is to envision how and how well it might function in Alaska. We present here sets of scenarios with warning time and ground motion estimates for a variety of communities. These scenarios are designed to be meaningful test cases for Alaska earthquake early warning while also exploring how changes in source characteristics--such as magnitude, depth, location, and fault system--impact the timeliness of warnings. We combine travel time estimates, source time models, and the current seismic network to model hypothetical detection and alert times. We compare warning times to peak ground motions to determine the warning effectiveness. Our results suggest the potential for timely warnings up to Modified Mercalli Intensity 6 in the case of shallow earthquakes. More ideal scenarios, including deep earthquakes, could receive advanced warning for shaking up to intensity 8. Informed by these results, we discuss where we expect an Alaska earthquake early warning system to excel and what challenges should be tackled to improve other areas. Finally, we offer ways in which our results and insights can inform future works related to earthquake early warning in Alaska.

Volcanic eruptions pose major threats to society, including loss of human life, negative economic impacts, and environmental ramifications. As the global population continues to grow, so does the amount of people living in proximity to volcanoes. Volcanic eruptions are often triggered by perturbations in the magmatic system, which are caused by a variety of magmatic processes, such as magma recharge, magma ascent, and magma mingling. We applied diffusion chronometry, the technique of modeling chemical diffusion across mineral zones, to the 2009 eruption of Redoubt, and the 2016-2017 eruption of Bogoslof, in order to determine and date the pre- and syn-eruptive magmatic processes that triggered and drove the recent eruptions of these two, high-threat, Alaskan volcanoes. At Redoubt, our results, combined with multidisciplinary observations preceding the 2009 eruption, indicate that Redoubt experienced protracted magma recharge between the 1989-1990 and 2009 eruptions, with notably drastic increases in monitoring parameters occurring 3-4 months before the 2009 eruption. At Bogoslof, we analyze both the first and final products from the 9-month long 2016-2017 eruption. Analyses of the early products indicate that pre- eruptive magma recharge occurred in the weeks to months before eruption onset. This interpretation is supported by the seismic swarm that occurred approximately two months before the eruption began. Conversely, our analyses of the final erupted products of Bogoslof reveal that the distinct boundaries in mineral phases formed due to magma decompression caused by the shallow emplacement of magma occurring throughout the second phase of the eruption. The oldest crystal timescales from the second eruptive phase correspond to March 2017, correlating with increases in both seismicity and SO2 emissions. By determining and pinpointing the magma processes associated with volcanic eruptions in time and space, we gain insights into the pre- and syn-eruptive nature of the magma system. Our results aid in interpreting interdisciplinary monitoring data, and contribute to the development of new eruption forecasting tools.

Landfast ice in Alaska is experiencing rapid changes in extents and duration, impacting the safety and utility of the ice for Arctic coastal communities. This study presents findings from an updated landfast ice dataset spanning from 1996 to 2023, comprising 7797 Seaward Landfast Ice Edge (SLIE) images derived from a combination of sources including prior work by Mahoney et al. (2014) and new analysis of operational ice charts produced by the National Weather Service Alaska Sea Ice Program (ASIP) and National Ice Center (NIC). We referred to this new dataset as the EM2024 dataset. Analysis of the entire EM2024 dataset reveals a declining trend in landfast ice extent and season length across Alaska. To better understand the nature of these changes and explore options for more robust detection of landfast ice for future datasets, we compared the EM2024 data for the winter period of 2017-2021 with SLIE data derived from Interferometric Synthetic Aperture Radar (InSAR). We used coherence to identify areas of landfast ice and the interferograms to derive the phase gradient as a proxy for estimating the relative stability of the landfast ice. We built on a pervious study by Dammann et al. (2019) by assigning quantitative phase gradient values to identify 3 distinct stability regimes of landfast ice: Bottomfast (|▽ϕ| < 0.14 radians/pixel), Stabilized (0.14 ≤ |▽ϕ| ≤ 0.47 radians/pixel), and Nonstabilized (|▽ϕ| > 0.47 radians/pixel). The monthly average phase gradient decreases as the season progresses, achieving the maximum stability in April or May depending on the region. This study provides an updated assessment of landfast ice conditions in Alaska and introduces a novel approach to identify relatively stable areas of landfast ice using InSAR. These findings have implications for enhancing the safety and planning of activities on landfast ice for Arctic coastal communities.

The Triassic-Jurassic boundary is associated with one of the big five Phanerozoic mass extinction events and is characterized by global negative δ13C excursions, indicating a major disruption in the carbon cycle. The end-Triassic extinction event was caused by Central Atlantic Magmatic Province volcanism, that initiated the breakup of the supercontinent Pangea. Abundant greenhouse gas emissions, including CO2 and CH4, from the volcanic activity, affected multiple environmental factors. Global warming, ocean acidification, deoxygenation, mass mortality, and lithological change are documented across the boundary. These environmental fluctuations are also observed due to human-induced global climate change, making understanding the end-Triassic extinction significant. Northern Alaska during the Late Triassic has evidence of being the location of an upwelling zone, influencing redox conditions on the sea floor. I hypothesize that isotopic, geochemical and petrographic analyses into Northern Alaska’s Late Triassic Otuk Formation will give a better understanding of the depositional environments in which it formed. Our research has documented the Triassic-Jurassic boundary using carbon and nitrogen isotopes in the rock record, where previously it was not well recorded in Alaska. Research into the Otuk Formation also helped identify the high petroleum potential of these organic-rich rocks. Late-Triassic Northern Alaska rocks were deposited in marine oxic to anoxic conditions, impacting organic burial and paleo¬ redox conditions. Paleo-redox conditions of euxinic environments were identified through the presence of pyrite framboids. A negative carbon isotope excursion was identified in the Otuk Formation, also corresponding with a change in lithofacies and fossil size and abundance. Sedimentary petrology and TOC values documented environmental changes from oxic bivalve¬ rich facies to dark, low-oxygen, organic shales across the Triassic-Jurassic boundary. The Triassic- Jurassic boundary is observed in Northern Alaska, and can act as a marker for multiple environmental changes at that time.

Modern polar regions are critical breeding grounds for over 250 species of birds. Some migrate to high latitudes for access to seasonally abundant resources during reproductive periods, whereas others are year-round residents. Despite the major role these birds play in polar ecosystems, we know very little of the origins of the utilization of polar ecosystems for nesting due to the rarity of avialan fossils from high latitudes. The avialan fossil record spans 150 million years, yet evidence for high-latitude bird reproduction extends only to the Eocene La Meseta Formation of Antarctica (56-33.6 Ma). Here, we report a remarkable polar avifauna from the northernmost fossil-bearing Late Cretaceous ecosystem in the world, the Prince Creek Formation of northern Alaska (PCF). The PCF was deposited at 80-85°N paleolatitude, where continuous summer daylight would have lasted nearly six months. It preserves an ancient polar ecosystem including avian and non-avian dinosaurs, mammals, and fishes. The PCF avialan material was found as part of a decade-long microfossil analysis of channel lag deposits. Numerous skeletal elements, representing almost the entire avialan skeleton, constitute one of the most comprehensive and well-preserved Late Cretaceous avifaunas in the world. These fossils share morphological affinities with hesperornithines, ichthyornithines, and crown birds. Further, abundant perinatal fossils represent the youngest-known growth stages of Mesozoic euornithines. This is the oldest direct evidence for polar bird reproduction and demonstrates that multi ---taxic bird nesting has occurred in the High Arctic for at least 73 million years--nearly half the tenure for birds on Earth. Likewise, these fossils demonstrate that this behavior originated in the Mesozoic ancestors of modern birds, millions of years before the radiation of crown group birds following the end-Cretaceous mass extinction.

Volcanic eruptions pose hazards to human lives and livelihoods (Loughlin et al., 2015). To mitigate these hazards, volcano monitoring groups aim to detect signs of unrest and eruption as early as possible. Prior to eruption volcanoes may show various signals of unrest, including: increased surface temperatures, surface deformation, increased seismicity, increased degassing, and more. Here we focus on one approach to monitor volcanic unrest: detecting high-temperature localized volcanic heat emissions, otherwise known as hotspots. The presence of hotspots can indicate subsurface and surface volcanic processes that precede, or coincide with, eruptions. Space-borne infrared sensors can identify hotspots in near-real-time; however, automatic hotspot detection systems are needed to efficiently analyze the large quantities of data produced. While hotspots have been automatically detected for over 20 years with simple thresholding algorithms, new computer vision technologies, such as convolutional neural networks (CNNs), enable improved detection capabilities. Here we introduce HotLINK: the Hotspot Learning and Identification Network, a CNN-based model to detect volcanic hotspots in VIIRS (Visible Infrared Imaging Radiometer Suite) imagery. We find that HotLINK achieves an accuracy of 96% when evaluated on a validation dataset of ~1,700 unseen images from Mount Veniaminof and Mount Cleveland volcanoes, Alaska, and 95% when evaluated on a test dataset of ~3,000 images from six additional Alaska volcanoes (Augustine Volcano, Bogoslof Island, Okmok Caldera, Pavlof Volcano, Redoubt Volcano, Shishaldin Volcano). Additional testing on ~700 labeled MODIS images demonstrates that our model is applicable to this sensor's data as well, achieving an accuracy of 98%. We apply HotLINK to 10 years of VIIRS data and 22 years of MODIS data for the eight aforementioned Alaska volcanoes. From these time series we find that HotLINK accurately characterizes background and eruptive periods, similar to a threshold-based method, MIROVA, but also detects more subtle warming signals, potentially related to volcanic unrest. In particular, analysis of the Mount Veniaminof record demonstrates that HotLINK is able to detect subtle hotspot signals that are coincident with elevated seismicity, potentially indicative of surface heating due to shallow magma intrusion and/or degassing. We identify three advantages to our model over its predecessors: (1) the ability to detect more subtle volcanic hotspots and produce fewer false positives, especially in daytime imagery; (2) the incorporation of probabilistic predictions for each detection that provide a measure of detection confidence; and (3) its transferability to multiple sensors and multiple volcanoes without the need for threshold tuning, suggesting the potential for global application. HotLINK is able to identify eruptions and potentially precursory warming signals in infrared satellite data, making it a valuable tool for monitoring volcanoes and tracking their heat released over time.

Torrential rains, flooding, and storm surges are all considered meteorological and hydrological hazards. These hazards can quickly transition into disasters whenever they begin to effect human life or infrastructure. When these disasters occur, they can lead to devastating outcomes such as damage or complete loss of infrastructure, reduced crop yields and related impacts on food security, as well as risks to human life. For decades, these events have been monitored and tracked primarily from visible/infrared sensors. Unfortunately, flooding and storm surges often occur during extensive weather and cloud cover conditions, which can make monitoring these hazards across large spatial scales difficult if not impossible, especially in poorly developed regions. Synthetic Aperture Radar (SAR), with its capability to penetrate through clouds and monitor during both day and night cycles, may provide substantial improvements to flood hazard management, once robust techniques for the detection of surface water extent were developed. This thesis details the development of HYDRO30, an automatic algorithm to map surface water extent from Sentinel-1 SAR data. At its core the HYDRO30 approach automatically creates surface water extent maps by preforming adaptive thresholding on dual-polarized and radiometrically terrain corrected (RTC) SAR images. We use data from the Sentinel-1 C-band SAR constellation as input, as this constellation provides global access to free and open medium resolution SAR data that comes at a reliable sampling rate of six-to-twelve days. Such free-and-open, regularly sampled data is indispensable for hazard monitoring across regional to continental scales. In this thesis, I will show that the HYDRO30 algorithm achieves promising results in delivering robust and accurate surface water extent maps within an efficient timeline. The work presented in this thesis was developed as part of the HydroSAR project, a NASA-funded effort led by UAF to develop an automatic service for the monitoring of weather-related hazards in the Hindu Kush Himalaya. The thesis will also show an application of the HYDRO30 technology for the monitoring of flood hazards in northern Bangladesh during the 2020 south-Asian monsoon season.

Extratropical cyclones in the Bering Sea have the potential to cause widespread damage to the coastline of western Alaska, a threat that disproportionately affects Indigenous communities that inhabit these remote regions. A paucity of historical and instrumentation data in these regions, combined with the potential for increases in coastal hazards as a result of climate change, hinders coastal resilience at the local level. To address this problem, this study incorporates local and Indigenous Knowledge into a historical assessment of storm impacts in two communities in the Bering Sea, St. Paul Island and Goodnews Bay, to partially fill these gaps and improve coastal hazard mitigation and preparation. We conducted interviews with local and Indigenous Knowledge bearers in both communities, performed topographic field surveys of historical storm heights, and mapped flooding based on surface models generated from Unmanned Aircraft Systems and flood heights. Particularly impactful storms were described in storm histories, which detail information gathered from instrumentation, on-the-ground field visits, and Indigenous Knowledge interviews. Finally, an online Esri Storymap was designed as an outreach product to combine and visualize the various data products from this analysis with narrative on the experience of living through extreme storm events. This thesis integrates Western and Indigenous Knowledge into actionable, community-prioritized data products to support coastal resilience to climate changes.

Volcanic gas emissions are challenging to quantify. Achieving high confidence in gas composition, column concentrations, and emission rates acquired using remote sensing techniques is thought to require optimal atmospheric conditions. These conditions are often not met, creating a reluctance to preform measurements under non-ideal atmospheric conditions with inherent uncertainty about how useful those measurements may be. In the case of volcanic eruptions, the hazardous nature of the volcanic plume creates an environment where it is often not safe to collect measurements. This dissertation presents three projects which aim to constrain the quantity of two specific volcanic gases, mercury (Hg) and sulfur dioxide (SO₂), released under non-ideal measurement conditions. Specifically, chapter 2 aims to constrain Hg emission during volcanic eruptions, chapter 3 aims to characterize the uncertainty in SO₂ emission rates acquired under specific non-ideal atmospheric conditions, and chapter 4 aims to improve constraints on plume altitude for scanning remote sensing measurements of SO₂ emission rates acquired from a single instrument. Ash is a potential sink of volcanically-sourced atmospheric mercury, and the concentration of particle-bound Hg may provide constraints on Hg emissions during eruptions. In Chapter 2, the Hg concentrations in 227 bulk ash samples from the Mt. Spurr (1992), Redoubt (2009), and Augustine (2006) volcanic eruptions are examined to investigate large-scale spatial, temporal, and volcanic-source trends. No significant difference in Hg concentrations is found in bulk ash by distance from the eruption source or for discrete eruptive events at each volcano, suggesting that in-plume reactions converting gaseous Hg⁰ to adsorbed Hg²⁺ are happening on timescales shorter or longer than considered in this study (minutes to hours) and any additional in-plume controls may be masked by intra-volcanic sample variability. A significant difference is found in Hg concentration in ash among volcanic sources, which indicates that specific volcanoes may emit comparatively high or low quantities of Hg. These findings allow for the calculation of minimum, first-order estimates of volcanic Hg emissions during eruption in combination with total mass estimates of ashfall deposits. Mt. Spurr is found to be a high Hg emitting volcano such that its 1992 particulate Hg emissions likely contributed substantially to the global eruptive volcanic Hg budget for that year. Based on this study, previous approaches that used long-term Hg/SO₂ mass ratios to estimate eruptive total Hg under-account for Hg emitted in explosive events, and global volcanogenic Total Hg estimates need revisiting. A large source of error in SO₂ emission rates derived from mobile differential optical absorption spectroscopy (DOAS) is the uncertainty in atmospheric light paths between the scattered sunlight and the instrument, particularly under non-ideal atmospheric conditions such as the presence of clouds beneath the volcanic plume. In Chapter 3, numerical simulations using the McArtim model are used to examine the radiative transfer associated with zenith-facing mobile DOAS traverses for scenarios where there is a cloud layer between the instrument and the volcanic plume. In total, 217 permutations of atmospheric optical conditions are considered, allowing for the determination of errors associated with atmospheric scattering. Objective criteria are also developed for selecting SO₂ baselines and plume limits for each simulated traverse. This study then applies models to a real-world dataset from the 2021 Cumbre Vieja eruption to explore the effects of ground-level haze on a measured SO₂ column densities for the volcanic plume. All modeling results find large modifications in the shape of the analyzed plume SO₂ column density versus distance curve, even under scenarios with translucent clouds. Despite modification of the plume shape, the presence of a low cloud or haze layer is typically not a large source of error in determination of the total SO₂ quantity measured over the entirety of the traverse, which suggests that fairly accurate SO₂ emission rate measurements can be obtained even under non-ideal atmospheric measurement conditions. The real-world dataset from Cumbre Vieja is found to be best explained by a layer of ground-level laze containing SO₂ and a volcanic plume located between 2 - 4 km altitude. A large source of uncertainty in SO₂ emission rates derived from scanning DOAS instruments is the cross-sectional area of the detection, which is determined from the vertical and horizontal distance of the plume from the instrument. In Chapter 4, a novel method is employed to estimate plume altitude based on modeled wind speed data and validated against available webcam imagery at Cleveland Volcano in the Aleutian Islands, Alaska. This estimated plume altitude is used to calculate SO2 emission rates from single-station campaign scanning DOAS measurements at Cleveland Volcano, Gareloi Volcano, and Korovin Volcano (Alaska) in 2019, where the instrument was deployed for several days at each site. This method is also applied to a long-term dataset of scanning SO2 measurements acquired from a permanent scanning DOAS instrument installed at Cleveland Volcano September 2022 - June 2023. It is found that the method of estimating plume altitude in the long-term dataset produces a lower emission rate and a smaller sample variance than assuming a fixed summit plume altitude. The remaining variance in the data is then interpreted to represent variability in SO₂ emissions during times of relative quiescence at each studied volcano.

The distribution of fold related fractures and other mesoscopic structures in asymmetrically folded Mississippian to Pennsylvanian Lisbume Group carbonates gives clues concerning the mechanism of folding. Since fracture sets pre-date and post-date folding, it is important, but sometimes difficult, to determine which fracture sets are related to folding. Higher density of fold related fractures and dissolution cleavage in the hinges than limbs of two folds in the study area is evidence for fixed hinge detachment folding. However, geometric modeling of box shaped folds in the study area suggests that some folds may have formed by either detachment folding or trishear fault propagation folding. Formulaic modeling of fracture density in a stratigraphic section using stratigraphic attributes such as lithology, bed thickness, and chert content predicts general trends in fracture density, but other factors such as slip along bed contacts may obscure the relationship between fracture density, lithology and bed thickness.