Analytical studies of astromaterials samples returned by NASA space missions generate unique and highly valuable data that contribute fundamentally to our knowledge and understanding of the origin and evolution of Earth, our solar system, and the universe. These data need to be openly accessible and curated in a manner that maximizes their reuse in and utility for future science and that ensures their quality and long-term preservation. In several recent strategic documents and reports, NASA recognizes this need [1] and is adjusting its science information policies [2]. In 2020, NASA charged the Planetary Data Ecosystem Independent Review Board (PDE-IRB) to conduct a review of the planetary data landscape and make recommendations for improving access to and use of planetary science data by the science community [3]. This presentation will highlight features and services of the Astromaterials Data System that align the IRB’s recommendations. The Astromaterials Data System (Astromat) is a data infrastructure that has been funded by NASA since 2018 to curate, archive, and publish analytical data that are generated from astromaterials samples collected by NASA missions and curated at the Johnson Space Center in the Astromaterials Research & Exploration Science Division. Astromat’s mission is to: preserve astromaterials data and ensure their long-term access and reusability for new science endeavors; restore legacy data of astromaterials samples acquired in the past; synthesize historic and new data into a comprehensive, analysis-ready data store that allows scientists to use new technologies such as Machine Learning and Artificial Intelligence to explore and mine these data in previously impossible ways. Astromat operates a data repository where researchers can deposit their data for archiving and publications, specifically to comply with new journal policies and guidelines for Open and FAIR data and Data Management Plans required by funders. The repository follows international best practices. Astromat also maintains the Astromat Synthesis, a relational database that integrates legacy and new data into a harmonized data collection that allows users to find and extract data at the granularity of individual analytical measurements and combine these into customized new compilations for advanced data analysis. [1] SMD’s Strategy for Data Management and Computing for Groundbreaking Science 2019-2024. [2] Scientific Information policy for the Science Mission Directorate, SMD Policy Document SPD-41 (August 2021). [3] Besse, S., et al. (2021). LPI Contributions 2549, 7070.

Detailed rock magnetic analyses of ultramafic rock samples recovered from the Wadi Tayin massif as part of the Oman Drilling Project provide a unique opportunity to understand the magnetic properties of oceanic lithosphere and its alteration since obduction. We examined 300 - 400-meter-long cores from 3 sites (BA1B, BA3A, and BA4A) that transected the crust-mantle boundary. Serpentinization which produces a small amount of magnetite from olivine alteration appears to play an important role in shaping the magnetic signature of the rocks recovered from these holes. Our investigation reveals new features which have not been reported in previous studies of ophiolite largely based on surface rock samples. It appears that when serpentinization reaches a certain point (65%) a sharp increase in magnetic susceptibility occurs. In general, the uppermost section (0 – 40 m) shows higher susceptibility than the deeper part. Also, higher susceptibility is found in dunite-dominated sections than those composed of harzburgite. Overall, our observations indicate that mantle rocks of Semail ophiolite were produced by multi-stage hydrothermal alterations.

Microbial-induced calcium carbonate precipitation (MICP) is an innovative technique used for soil improvement, for controlled reduction of permeability in porous media or immobilization of soil contaminants. The application of MICP in the field is influenced by the environmental factors. In the present study, the main purpose is to explore the effectiveness of MICP in treating porous media at different environmental temperatures and reveal the underlying mechanisms. The microstructure characteristics were investigated via SEM imaging, EDS and XRD analyses and consolidated drained triaxial compression tests were performed to examine the performance of MICP-treated samples. Results indicate that the shear strength depends heavily on the treatment temperature, which was mainly due to the different content, size and distribution of CaCO3 in samples at different conditions. The observations of pore-scale characteristics revealed that low temperature (4℃) and high temperature (50℃) produced less CaCO3 precipitation, resulted in smaller carbonate crystals precipitation and thus lower strength. In contrast, samples treated at room temperature and 35 ℃ show more CaCO3 precipitation and greater strength. The crystal forms, though, were not influenced by the temperature. The climate conditions are a very important parameter that needs to be tuned specifically for the purposes of each MICP application (whether controlled alteration of permeability or for soil stabilization). However, in most MICP field applications, temperature is nearly impossible to control, and in such conditions where bacterial activity is reduced, the alteration of the MICP recipe is required, and specifically the number of bacterial solution injections are worth to be considered.

The post-subduction tectonic evolution of northern Borneo, which experienced two sequential subduction episodes of opposite polarity in the Neogene, is still widely debated with first-order questions such as whether the region has been in a state of compression or extension remaining unresolved. We use waveform data recorded from a dense seismic network in northern Borneo to investigate crustal thickness variations through the application of Virtual Deep Seismic Sounding (VDSS). The new results reveal an extensive area of thin crust in central and southeastern Sabah that appears to extend northeast into the Sulu Sea, where rifting initiated. We also compute local earthquake focal mechanisms, which suggest that extension is ongoing, though now dominated by orogen collapse in the NW. Together these results point to the pervasiveness of regional extension tectonics over the last 15-20 Myr and its role in the post-subduction cycle of plate tectonics in SE Asia.

Fundamentally related to the ultraviolet (UV) divergence problem in Physics, conventional wisdom in seismology is that the smallest earthquakes, which are numerous and often go undetected, dominate the triggering of major earthquakes, making accurate forecasting of the latter difficult if not inherently impossible. Using the general class of epidemic type aftershock sequence (ETAS) models and rigorous pseudo-prospective experiments, we show that ETAS models that feature a specific magnitude correlation between triggered and triggering earthquakes and a magnitude-dependent Omori kernel, significantly outperform simpler ETAS models, in which these features are absent. Using the best forecasting model, we then show that large earthquakes are preferentially triggered by large events. These findings have far-reaching implications for short-term and medium-term seismic risk assessment, as well as for the development of a deeper theory without UV cut-off that is locally self-similar.

Hot spring localities on continents may represent the most probable locales for the formation of early life constituents on Earth. Apart from liquid water and carbohydrates, these components also include elements like boron that are crucial for stabilization of the complex organic molecules that constitute life. Many of these life sustaining ingredients are commonly found in the vicinity of terrestrial hot springs. Analogously, similar existing or extinct hot spring localities on other planets may constitute prospective astrobiological sites. In the present study, we have characterized the complete mineralogical assemblage of the Puga hot spring deposit, Ladakh, India, using detailed spectroscopic and X-ray diffraction studies. The spectroscopic characterization was done using field based visible/near-infrared (VNIR; 400-2500 nm) and lab measured mid-infrared (MIR, 4000-400 cm-1) hyperspectral data. The identified mineral phases include Na-borates, such as, borax and tincalconite, and hydrous sulfates such as jarosite, alunite, copiapite, tamarugite and gypsum, in conjunction with native sulfur, halite and opaline silica. Borate minerals have been identified from the valley-fill material along with halite and opaline silica, whereas sulfates occur alongside crystalline sulfur deposits. We have compared mineral assemblages found in Puga with other hot spring/hydrothermal deposits on Earth identified as martian analog sites, and also with mineral assemblages identified in situ on Mars. We argue that the spectral characterization of hydrated borates in natural association with hydrous sulfates can be used for identification of fossilized martian hydrothermal settings that are prospective in the search for extinct/extant extra-terrestrial life.

We investigate the impact of source-side 3D velocity structure on teleseismic travel-time in back projection (BP) analysis of large earthquakes. We use travel-time data of teleseismic events recorded by the Hi-Net array to reveal how travel-time errors vary with source location. In a source area of a few hundred km, where travel-time error varies dominantly linearly, we propose a new interpolation scheme using earthquakes located around the rupture of the main-shock to calibrate the travel-time error, and validate it by relocating inland M>5.0 earthquakes in central Japan. We then apply it to image the rupture of the 2002 Denali earthquake. The calibrated BP result shows that most of the high-frequency radiators are <15 km away from the surface rupture trace. The new result reveals that the rupture started on the Susitna Glacier Fault with a speed of ~1.4km/s, then propagated onto the Denali Fault and accelerated to a super-shear speed approaching the crustal P-wave velocity at approximately 30km. The location of super-shear transition and rupture speed in BP are highly consistent with that inferred from the timing and amplitude ratio of the super-shear and trailing Rayleigh pulses observed on the near fault PS-10 station. Subsequently, the rupture stagnated for ~15s before penetrating through the largest asperity, re-accelerated to a speed of ~5.2 km/s and continued on the last 60 km of the Denali fault and part of Totschunda Fault. This application shows the great potential of the new BP calibration strategy to refine the rupture imaging of other mega-earthquakes.

Fluid injection stimulates seismicity far from active tectonic regions, however the details of how fluids modify on-fault stresses and initiate seismic events remains poorly understood. We conducted laboratory experiments using a biaxial loading apparatus with a 3 m saw-cut granite fault and compared events induced at different background shear stress levels. Water was injected at 10 mL/min and normal stress was constant at 4 MPa. In all experiments, aseismic slip initiated on the fault near the location of fluid injection and dynamic rupture eventually initiated from within the aseismic slipping patch. When the fault was near critically stressed, seismic slip initiated only seconds after MPa-level injection pressures were reached and the dynamic rupture propagated beyond the fluid pressure perturbed region. At lower stress levels, dynamic rupture initiated hundreds of seconds later and was limited to regions where aseismic slip had significantly redistributed stress from within the pressurized region to neighboring locked patches. We find that slow slip initiated when local stresses exceeded Coulomb failure criteria, but initiation of dynamic rupture required additional criteria to be met. Even high background stress levels required aseismic slip to modify on-fault stress to meet initiation criteria. We also observed slow slip events prior to dynamic rupture. Overall, our experiments suggest that initial fault stress, relative to fault strength, is a critical factor in determining whether a fluid-induced rupture will “runaway” or whether a fluid-induced rupture will remain localized to the fluid pressurized region.

To investigate the mechanisms involved during semi-brittle flow, we deformed Carrara marble over a confining pressure (Pc) range of 10-300 MPa and room temperature to ≈10% strain. We apply triaxial loading to intact Carrara marble and collect mechanical, ultrasound pulsing, and acoustic emission (AE) data during pressurization and deformation stages. The pulsing and AE waveforms are recorded using a pair of piezoelectric sensors. At lower Pc, microcracking is the dominant deformation mechanism, whereas at higher Pc, crystal-plastic mechanisms such as twinning and dislocation glide are favored. These changes in the activity of defect populations are manifested in changes in mechanical properties, velocity variations, and AE characteristics. Samples at higher Pc exhibit higher strength and require more work for fault-development. Transition from localized faulting to distributed barreling is observed between 50 and 100 MPa Pc. We track precise velocity variations from the pulsing waveforms using correlation-based methods. During the pressurization stage, the velocity increases logarithmically with Pc between 0-100 MPa, followed by a linear increase at higher pressures. During the deformation stage, the compressional wave velocity initially increases before the yield point due to closing of crevices, and then decreases exponentially after the yield point. The rate of this velocity decay is smaller as Pc increases, owing to reduced microcracking with very little change at Pc ≥ 200 MPa. AE data show that individual defect types emit characteristic patterns. Twinning produces repetitive patterns of low amplitude, short signals localized in frequency space whereas microcracks are more energetic, emit over a much broader frequency range, and show more variation in signal shape and duration. The AE spectra shift from ≈ 500 kHz to ≈15 MHz mean frequency as Pc increases, which is associated with increasing twinning activity. This acoustic data agree with microstructural observations of microcracks and crystal-plastic deformation in the samples. By joint-analyzing the stress-strain and velocity evolutions with AE observations, we obtain detailed changes in the micro-mechanisms accommodating strain in the Carrara marble and constrain the deformation modes as it goes through the brittle-plastic transition.

We describe new cosmogenic Be-10 and C-14 exposure age dating on previously glaciated bedrock samples from Lyell Canyon as constraints to model the glacier’s rate and timing of thinning and retreat after the Last Glacial Maximum (LGM). Close analysis of deglaciation following the LGM (22-12 ka) can offer insight into how glacier retreat proceeds in a warming climate. The extent and age of the LGM glaciation in Yosemite National Park, California are relatively well-constrained. Our new exposure ages from Yosemite can quantify the change of the glaciation after the LGM. This is important because the rate and timing of glacier retreat after the LGM allows us to learn about the LGM-Holocene climate transition. We collected 16 granodiorite bedrock samples from the Lyell Canyon walls in three vertical transects: at the end, in the middle, and near the head of Lyell Canyon. Sample elevations range from 2781m to 3388m. The samples are being processed for cosmogenic Be-10 and C-14 concentrations (for the lower and higher elevations in the transects, respectively). Together with previously acquired Be-10 exposure ages from glacial polished bedrock and boulders at the canyon floor, our vertical transects will help to define the relationship between glacier retreat and thinning along the valley. The combination of different nuclide measurements has the potential to reveal whether the glacier melted rapidly or went through multiple thinning and thickening cycles. We created several simple forward models of cosmogenic Be-10 and C-14 exposure ages on the valley wall for different glacier thinning patterns: (i) rapid thinning, (ii) thinning and thickening cycles during the melting, (iii) thickening first, followed by thinning, and (iv) breaking an upper small cirque glacier from the main glacier during the thinning. After we have obtained all our data, we will compare the exposure age data to our modeled scenarios, as well as local paleoclimate records, to quantify the glacier’s geometry and mass balance during the climate warming period. Understanding the timing, rates, and patterns of LGM retreat and thinning constitute a useful test case that aids mountain glacier melting predictions and water budget planning under contemporary climate change in analogous environments.

We investigate the influence of local site effects on earthquake source parameter estimates using the LArge-n Seismic Survey in Oklahoma (LASSO). The LASSO array consisted of 1825 stations in a 25 km x 32 km region with extensive wastewater injection and recorded more than 1500 local events (M < 3) during spring 2016. We analyze the site amplification dependence on earthquake corner frequency (fc), seismic moment (M0), and stress drop estimated by modeling individual spectra. We evaluate and correct these site effects and compare the effectiveness of the correction to results using the spectral ratio method. We estimate local site amplification at each station using the average Peak-Ground-Velocity (PGV) of 14 regional earthquakes (~130 km away). The fc from the single spectrum method negatively correlates with site amplification, whereas M0 from the single spectrum method positively correlates with site amplification. This suggests the source parameters calculated by modeling individual spectra are biased by the local site effects. The high amplifications are typically located on young alluvial sedimentary deposits. We correct site effects by removing the trend between PGV and these two parameters in the regression analysis, which reduces the standard deviation of these parameters across the array and makes the calculated stress drop less site dependent. We compare corrections using other site-effect proxies such as the Root-Mean-Square (RMS) amplitude, surface geological formation, P-arrival-delay, and topographic slope. The PGV and the RMS corrections provide the greatest reduction of the spatial deviation of source parameters. In comparison, the spectral ratio method effectively removes the site effects using the Empirical Green’s Function (EGF) approach. The trends being removed by EGF are close to the apparent trends between the single spectrum estimated parameters and the PGV, which suggests the consistency of these different correction approaches. Our results provide a potential way to remove the site effects when only the main event spectrum is available and demonstrates the effectiveness of using the EGF approach for removing site effects. The resulting inter-station variability provides an estimate of the likely uncertainty in source parameters estimated from smaller numbers of stations.

Landslide dams can result in substantial flood hazards caused by dam formation, overtopping, and dam failure. Previous studies have established datasets on a regional or global scale and identified indices to estimate the probability of landslide dam formation. These datasets are collections of landslide dam records from multiple data sources. However, the precision and accuracy of the landslide dam record’s spatial information hinder the completeness of data and prevents the possibility of linking with other relevant datasets, and thus hinders the exploration of factors affecting landslide dam formation. We established a new global-scale landslide dam dataset, named River Augmented Global Landslide Dams (RAGLAD), which geolocates those records whose location was vaguely known or completely unknown and combined this with additional data from global fluvial datasets to make the data record more comprehensive. We use RAGLAD to study the processes of landslide dam formation. The spatial distribution of landslide dam records, data distribution, triggering processes and preconditions, and the relationships between geomorphological parameters directly derived from RAGLAD help understanding areas prone to landslide dam conditions, and delineate potential thresholds for landslide dam formation. The results are compared with relationships achieved from general landslides studies to find the specific conditions of landslide dam formation. These conditions can be further applied for filtering the potential hazard occurrence area and calculating the landslide dam formation susceptibility.

Traditional deterministic and geostatistical methods for rainfall interpolation usually fall short of integration of data on a variety of variables. These omitted variables include seasonal variables such as time of year, topographic variables such as elevation, and/or remote sensing variables such as radar reflectivity. Meanwhile, poor quality in data on certain variables for some data points poses challenges to modelers who are using machine learning approaches to estimate rainfall amounts for locations without gauge measurements. To overcome these limitations, this presentation introduces a novel deep learning-based approach to recreate rainfall histories for large geographic areas with a high spatio-temporal resolution. The proposed approach enables integration of data on a variety of variables by adopting a multi-layer perceptron modeling framework. The introduction of binary variables on data quality as additional input variables resolves the issue of unequal data quality for different data points. As a demonstration, historical records of rainfall at hourly and daily intervals recorded at 139 rain gauge stations in or close to Harris County, Texas, from 1986 to 2013 are used, along with other auxiliary variables, to train deep learning regression models to interpolate rainfall at surface level. Results of validation and recreated spatiotemporal distributions of rainfall indicate good performance of the proposed approach compared to both gauged and radar data. The final product of the proposed approach can be applied to other regions, with information on hindcast historical rainfall events, for pluvial flood risk analysis. The approach will assist researchers and policy specialists to validate hydrologic modeling as well as for training machine learning models to identify extreme rainfall events to facilitate early warning and emergency response.

The contribution of volatile organic compounds (VOC) to ozone continues to receive attention and various localities have successively introduced measures to control VOC including limiting emissions from gas stations. Xi’an, as a major city of Fenwei Plain, has a large number of motor vehicles and a large demand for gasoline, and the VOC emission from gas stations can not be ignored in the city. In order to understand its impact on ozone and provide a reasonable basis for gas stations control and governance, this paper combines the SMOKE model to construct a gridded Xi’an gas stations VOC emissions, and uses WRF-CAMx model to study its effect on ozone concentration in summer. The results show that: (1) After considering the VOC emissions from gas stations, the concentrations of ozone (O3) and secondary organic aerosol (SOA) simulated by the sensitivity test in July 2018 were slightly higher than that results without the gas stations VOC emissions. (2) Similar to the baseline scenario, the daily change of O3 in July 2018 simulated by the control test considering gas stations VOC emissions shows a unimodal distribution; the diurnal change of secondary organic aerosol (SOA) is characterized by a high concentration in the morning even a peak. While the overall concentration level decreased in the afternoon, and gradually increased in the evening. (3) The results of sensitivity numerical test show that the gas stations VOC emissions in Xi’an just has a little influence on air quality, 63.5% hours its effect on ozone is within 0.01 μg/m³, and the VOC emissions from gas stations has different influence on ozone concentration in different hours. The maximum influence on hourly ozone concentration in Xi ’an is about 0.20 μg/m³.

Precise modeling of surface water quality requires transport theory consistent with observed data. Efforts to achieve model fits to river tracer test breakthrough curves (BTCs) have led to different approaches to the one-dimensional modeling of river corridor transport at the macroscale. The memory function model form practically generalizes most current approaches including the transient storage (TSM), multirate mass transfer, decoupled continuous time random walk, and time-fractional advection dispersion models. An alternative formulation of the memory function approach is the phase exposure-dependent exchange (PhEDEx) model, which is the TSM model that includes residence-time dependence of the rate coefficient for mass exchange from the hyporheic zone to the river. Using temporal moment analysis and numerical simulations, we explore the general consistency of the PhEDEx model with observed BTC data. With this approach the moments of the memory function can be estimated without requiring any prior information about the memory function form. We also examine means of estimating river/transport process parameters using the results of temporal moments analysis. The results show the failure of the PhEDEx model, and therefore the memory function approach, in capturing in particular the observed constancy of the BTC coefficient of skewness (CSK). The temporal moments equations can be applied as a useful tool to estimate some river/tracer test parameters such as the ratio of HZ cross-sectional area to the main flow cross-sectional area, which are time/cost consuming to measure. The applications of the analyses are demonstrated with some case studies.

Hurricanes (tropical cyclones) and nor’easters (mid-latitude cyclones) are high-energy storms often impacting the Outer Banks (OBX) barrier islands of North Carolina (NC), USA. Storm hazards include, but are not limited to, high speed winds, coastal flooding, storm surges, and increased precipitation. As a consequence of increased storm strength and frequency, loss of life, property damage, and erosion to beaches, barrier islands, and marshes have amplified over the past 40 years. In a recent report by the National Oceanic and Atmospheric Administration (NOAA), US taxpayers expended ~$1.05 trillion on hurricane and nor’easter impacts from 1980 to 2020. Identifying historical hurricanes and nor’easters in the geologic record as washover deposits can aid in the understanding of past events and prediction of future impacts to the OBX. Storm events yielding washover deposits can be identified, mapped, and quantified using various geologic, geophysical, and remote-sensing techniques. To identify both modern and historic coastal storms, nine sediment cores and 2300 meters of ground penetrating radar (GPR) data were collected, and five trenches were dug from the surface to the water table on three washover fans on Hatteras and Pea islands, NC. Grain size distributions were measured at centimeter intervals from trenches and sediment cores. GPR data were used to map spatial extents and measure sediment thicknesses in washover deposits down to ~1 m. Radiocarbon and short-lived isotopic dating techniques were employed to ascertain ages of washover deposits identified within cores. Additionally, historical surface analyses, hurricane tracks, and buoy data from NOAA were used to correlate washover deposits to known historic and modern hurricanes or nor’easters. To date, this project has identified several discrete washover events associated with Hurricane Sandy (2012) and several nor’easters across the northern (Pea Island) and middle/southern (Hatteras Island) study sites. Radiocarbon dating from plant material indicates these sites contain a ~500 cal yr BP record of washover deposition. The significance of this project is to evaluate differential impacts of nor’easters and hurricanes on the geomorphic evolution of Pea and Hatteras islands through the integration of data from multiple methodologies.

Title: Continental Physical Oceanography and Climatic Effects on Human Lives and Infection Diseases The author watches mechanism shifts caused by climatic influences and active era of seismic energy. Thermal power is stored and released through factors of ocean temperature and evaporation. Those affect human lives and virus vectors in the fields of ocean-atmosphere interaction and seismic oceanography. My presentation includes such research topics: Inundations of max assumed tsunamis and storm surges affect human risks in seashore mega cities SST dipole-effects to global crop production through stomata closing Advection effects from SST anomalies by high potential evaporation causing dry air and losses of human lives as well as houses by forest fires Ocean Impacts to Infection Diseases through Seasonal Climate change: New Applicable fields from Geo-Health linked to continental oceanography comparing to the traditional micro-and-genetic approaches. Ocean impacts to propagation of infection diseases through seasonal climate change such as fundamental air temperature and precipitation for plants and animals Climatic influences on vectors such as mosquito (like malaria, dengue fever, etc.) through blood, virus from breath (COVID-19), and bacteria from mouth, along with the potential risks by fatal viruses of Avian (Bird) Influenza and Classical Swine Fever etc. New recognized other important factors of mega cities by continental bird’s fly-routes, wild animals multiplication and increased travel flows of global human-lives Ecological transitions of deforestation and afforestation in low land or wet-land for wild birds and animals. Satellite sensing and photosynthesis-model mapping for vegetation growth in country-scale, continental, and global watching, by monitoring microbiological diseases through insect habitats, bird’s passages and animal movements. Intensive approaches using data assimilation and synthesizing among meteorological, geophysical, biological, and hydrological factors Related Divisions: Ocean Sciences, Geo-Health, Science and Society, Natural Hazards, Hydrology, BioGeosciences

Sporadic-E (Es) layers are characterized as thin layers (1-5 km) of enhanced electron density that occur between 90-120 km in altitude. Sporadic E at mid- and low-latitudes has a reasonably well established climatology, while at high latitudes there have been fewer investigations that have characterized the climatology of sporadic E occurrence using altitude resolved measurements. Incoherent scatter radar provides direct altitude resolved measurements of the E-region ionosphere with relatively high altitude resolution. Since 2008, the Poker Flat Incoherent Scatter Radar (PFISR) has been operating in nearly continuous operations through a low duty cycle mode, thus enabling observations of sporadic E. The distinction between Es and auroral precipitation is detectable and is generally associated with the differences in structure height with Es being on average smaller in altitudinal range and shorter time duration. The purpose of this investigation is to present observations of sporadic E derived from this nearly continuous database of alternating code and Barker code PFISR data spanning the years from 2007-2021. We visually identified the sporadic E layers and have found approximately 300 events. We present statistical results of the occurrence, duration, and characteristics of high latitude sporadic E derived from these events. The preponderance of events manifested within 95 to 120 km, typically lasted 1 to 3 hours, and mostly occurred during May through September with observance peaking in July. In addition, the trends indicated a potential disconnect between sporadic-E events and auroral activity, which was previously considered the primary driving force behind high latitude sporadic-E events. The climatology of high latitude sporadic E is an important contribution that must be considered in future high latitude models of the ionosphere.