Nitrogen is the most abundant element in the Earth’s atmosphere. Around 78% N2; and 21% O2; form the air we breathe and expand into high-altitude atmosphere, the thermosphere, and eventually the ionosphere. The neutral molecules in the ionosphere are ionized by solar radiation, and some of them break up into atoms, and others become charged particles. The ionospheric ions with sufficient energy can flow out into space, and the abundances of these outflowing ionospheric ions highly impact the near-Earth plasma properties. Studies focused on outflowing O+ ions have been conducted for many years. However, the contribution of N+ to the outflow solution is still largely unknown due to the instrumental limitations. We developed a first-principled physics model to understand how N+ and molecular ions, including NO+, N2+, and O2+, acquire the sufficient energy to escape Earth’s atmosphere. This study reveals the importance of N+ ions in the high-altitude polar ionosphere, from few hundred kilometers to thousands of kilometers in the space, and examines the possible mechanisms to accelerate and removed them from Earth’s atmosphere.

The vertical opacity structure of the martian atmosphere is important for understanding the distribution of ice (water and carbon dioxide) and dust. We present a new dataset of extinction opacity profiles from the NOMAD/UVIS spectrometer aboard the ExoMars Trace Gas Orbiter, covering one and a half Mars Years (MY) including the MY 34 Global Dust Storm and several regional dust storms. We discuss specific mesospheric cloud features and compare with existing literature and a Mars Global Climate Model (MGCM) run with data assimilation. Mesospheric opacity features, interpreted to be water ice, were present during the global and regional dust events and correlate with an elevated hygropause in the MGCM, providing further evidence for the role of regional dust storms in driving atmospheric escape as reported elsewhere. The season of the dust storms also had an apparent impact on the resulting lifetime of the cloud features, with events earlier in the dusty season correlating with longer-lasting mesospheric cloud layers. Mesospheric opacity features were also present during the dusty season even in the absence of regional dust storms, and interpreted to be water ice based on previous literature. The assimilated MGCM temperature structure agreed well with the UVIS opacities, but the MGCM opacity field struggled to reproduce mesospheric ice features, suggesting a need for further development of water ice parameterizations. The UVIS opacity dataset offers opportunities for further research into the vertical aerosol structure of the martian atmosphere, and for validation of how this is represented in numerical models.

Slow earthquakes follow a power-law size distribution with an exponential taper for the largest events. We investigated changes in the size distribution of shallow tectonic tremor events during two prolonged tremor episodes (>1 month) along the Nankai trough and found that the slope of the size distributions increased while the cut-off magnitudes decreased late during each episode, as tremor activity waned. Interpreting these changes with the two-dimensional probabilistic cell automaton model of slow earthquakes, we found that a decrease in event ignition probability or an increase in energy dissipation during slip can qualitatively explain the observed changes. These changes imply that a decrease in accumulated stress or pore-fluid pressure on the fault interface occurred during each tremor episode. Because the tremor source migrates during an episode, the changes in the size distribution parameters can be attributed to spatial variations or temporal changes in the source characteristics.

The retrieval of atmospheric composition from remote sensing measurements is a complex process that requires the integration of cross cutting domain knowledge into a coherent software package. The complexity is increased many times over when the software has to handle multiple types of instruments, operating in different spectral regions, each with their own peculiarities. This is further compounded when trying to combine information from multiple instruments for joint retrievals. Yet, there is enough overlap between the radiative transfer and retrieval techniques used by various missions that it is wasteful to continually reinvent the wheel every time. The Reusable Framework for Atmospheric Composition (ReFRACtor) is an extensible multi-instrument atmospheric composition retrieval framework that supports and facilitates data fusion of radiance measurements from different instruments in the ultraviolet, visible, near- and thermal-infrared. This framework is being developed to provide a community available software package that uses robust software engineering practices with well tested, community accepted algorithms and techniques. ReFRACtor is geared not only for the creation of end to end production systems, but also towards independent investigative scientists who need a software package to help answer atmospheric composition questions. We will explain how the use of succint interfaces between components provides advantages for future proofing, flexibility and reusability. Examples will be given for translating the logical separation of mathematical and scientific concepts into software components. We will describe how having a Python interface to fast compiled algorithms is helpful for rapid prototyping of new systems. The experience of early adopter scientists will also be discussed to give a perspective from outside the software development team.

Subsurface characterization is important for the detection and development of underground resources. Useful subsurface models can correctly make production forecast and optimize development plans, such as infill well location in an aquifer, geothermal, and hydrocarbon reservoir development. A useful subsurface model should honor geological concepts as well as all the available measurements, such as fluid production history, geophysical measurements. However, common subsurface modeling methods cannot efficiently honor the two concepts. To build subsurface models in a way that it is easy to condition them to both geological concepts and available measurements, we develop a new machine learning method, referred to as the stochastic pix2pix method. In this method, we use convolutional neural networks and adversarial neural networks to stochastically generate new subsurface models matching both geological concepts and static measurements, such as seismic and well data. This method first extracts the depositional patterns from analog training images, such as outcrops, high-resolution seismic images, and depositional process-based reservoir models, and then minimizes the Jensen-Shannon entropy between the training images and new subsurface models, as well as the mismatch of static measurements. The hydraulic inverse problem is solved with a machine learning-based proxy model on the model parameter space defined by stochastic pix2pix. The stochastic pix2pix method helps maintain the match of geological concepts and static measurements during the inversion. To verify and benchmark our procedure, we show the conditional subsurface models generated with stochastic pix2pix reproduce the geological concepts as good as synthetic unconditional process-based models. we successfully build reservoir models for channel and turbidite fan systems, where the depositional patterns of common geobodies are well reproduced. The synthetic well data, seismic interpretation, net-to-gross ratio, and time records of fluid production are well-matched with this new method. Additionally, we generate conditional subsurface models 90% faster than with conventional object-based modeling methods and with more accurate reproductions of the available measurements.

Declining sea ice in the Arctic Ocean is exposing its coasts to more frequent and intense forms of wave energy and storm surge. As a result, erosion rates along some stretches of coastline in the Alaskan Arctic have doubled since the middle of the 20th century and now rank among the highest in the world. People concentrated near the coast are being heavily impacted by erosion, with some facing relocation. Coastal erosion is projected to increase the cost of maintaining infrastructure by billions of dollars in the coming decades. The financial impact of enhanced erosion will likely be further exacerbated by emerging geopolitical pressures, including the discovery of natural resources, opening of new shipping routes, and construction of support facilities in the Arctic. Scientific knowledge and engineering tools for predicting coastal erosion and guiding land-use decision are not well-suited for the ice-bonded bluffs of the Alaskan Arctic. Investigation of the oceanographic, thermal, and mechanical processes that are relevant to permafrost bluff failure along Arctic coastlines is thus needed. We introduce a geomechanical simulation framework, informed by field observation and laboratory testing, that focuses on the impact of bluff geometry and material variability on permafrost bluff stress states associated with a 9-km stretch of Alaskan Arctic coastline fronting the Beaufort Sea that is prone to toppling-mode block failure. Our approach is advantageous in that it is based on measurable physical properties (e.g., the bluff geometry, permafrost bulk density, Young’s Modulus, and Poisson’s Ratio) and does not require the potential failure to be defined a priori, but rather, the failure area can be interpreted from the multidimensional patterns of stress produced by the model. Our findings highlight how (1) block failure characteristics could be tied to variations in the intensity and duration of the storm energy that intersects the coastline and (2) how deformation processes that create non-uniform patterns of displacement may play a role in localizing block failure. We propose that this kind of physics-based simulation approach can facilitate hypothesis testing regarding the prediction of decadal-scale erosion rates for increasingly dynamic coastal permafrost systems.

Subsurface engineering applications, such as the development of enhanced geothermal systems and unconventional oil and gas reservoirs, and the geologic disposal of CO 2 and waste water, involve fluid injection into the rock masses deep underground. Elevated fluid pressure can trigger shear slip(s) of pre-existing natural fractures, resulting in permeability changes. The mechanism of slip-induced permeability variation, however, is still not fully understood, and the permeability evolution associated with multiple slips is even more complex. We therefore performed laboratory experiments to investigate the fracture permeability evolution induced by shear slip in both saw-cut and natural fractures with rough surfaces. Our experiments show that the triggering fluid pressures required to induce slip in natural fractures are larger than in saw-cut fractures, likely due to the rougher surface of the natural fractures. We further observe that a critical shear displacement dominates the permeability evolution. When the accumulative shear displacement reaches the critical shear displacement, we find an initial permeability increase for natural fractures, followed by a perme-ability decrease after the most significant slip event. For the saw-cut fractures, the first slip shows the largest shear displacement and related permeability change, while further slips result in diminishing displacements. From the beginning to the end of all experiments, no consistent permeability increase or decrease is observed. Although the change of the fracture surface was not measured quantitatively, we found gouge material after rinsing each natural sample. tribute the slip-induced permeability evolution to the relationship between the damage of the main asperities, which decreases permeability, and the scale of the shear displacement, which increases permeability through shear dilation.

Cenozoic growth of the Andes has been strongly influenced by subduction dynamics, reactivation of inherited crustal heterogeneities, and the superposed effects of climate. Subduction of the submarine Carnegie Ridge has fundamentally impacted late Cenozoic magmatism and tectonic activity in the northern Andes. Time-temperature inverse modeling of new thermochronological data from the Western Cordillera of Ecuador reveals two phases of cooling separated by isothermal conditions. The first cooling phase immediately postdates early and middle Miocene magmatism in the Western Cordillera and is attributed to post-magmatic thermal relaxation. The second cooling phase started after 6 Ma, which we infer to record the exhumation in the Western Cordillera, coeval with the last cooling phase in the Eastern Cordillera. Based on these findings we posit that the onset of subduction of the Carnegie Ridge at ~6-5 Ma increased plate coupling at the subduction interface and promoted shortening and regional rock uplift in the northern Andes. Overall, our results highlight the essential role of bathymetric anomalies in driving regional upper-plate deformation at non-collisional convergent plate margins.

Sunlight plays an important role in regulating the nutrient cycle in streams. Throughout the years, more streams are buried to accommodate for residential or commercial facilities. This results in severe impacts on the health of streams due to altered exposure to sunlight, air, and soil; it subsequently affects the growth of aquatic and riparian vegetation, thus impairing the water quality of streams. Although urbanization effects on urban surface streams are well understood, the adverse effects of burying streams on dissolved oxygen (DO), reaeration, photosynthesis and respiration processes have been mainly remained theoretical. This study evaluated the effect of stream piping on DO for two sections of Stroubles Creek in Blacksburg, VA through comparing the water quality prior to entering, and post exiting the buried sections of the Creek. Monitoring DO was conducted through manual readings and continuous measurement for a number of days in Fall 2015 and 2016. The results indicated that the water DO level decreased by approximately 11% as water flowed through the buried sections. The covered section of the stream also caused variability of the water temperature, resulting a possible disturbance to the downstream ecosystem. The buried channels-induced DO variations effects on the Brook Trout (Salvelinus sp.), a sensitive species present at the Stroubles Creek headwaters was also assessed. Further, the photosynthesis rate, reaeration coefficient, and daily respiration rate were computed prior and after one of buried channels through a series of mathematical and empirical approaches to assess the buried channels effect on the aforementioned parameters. The photosynthesis and respiration rates were reduced at the inlet compared to outlet, primarily due to less solar radiation and aquatic vegetation oxygen uptake, however, reaeration rate was increased at the outlet compared to inlet. This study can assist the decision makers and resource planners in taking the appropriate decisions regarding daylighting stream channels to improve water quality or/and accommodate increasing demand for urbanization.

The devastating impacts of the widespread flooding and landsliding in Puerto Rico following the September 2017 landfall of Hurricane Maria highlight the enhanced hazard potential from increasingly extreme storms in mountainous humid-tropical climate zones. Long-standing conceptual models for hydrologically driven hazards in Puerto Rico posit that hillslope soils remain wet throughout the year and antecedent soil wetness imposes a negligible effect on hazard potential. Our post-Maria in situ hillslope hydrologic observations indicate that while some slopes remain wet throughout the year, others exhibit appreciable seasonal and intra-storm subsurface drainage. Therefore, we used receiver-operating characteristic analysis and the Threat Score (TS) skill statistic to evaluate the performance of hydro-meteorological (soil wetness and rainfall) versus intensity-duration (rainfall only) hillslope hydrologic response thresholds that identify the onset of positive pore-water pressure, a predisposing factor for widespread slope instability in this region. We found that the hydro-meteorological thresholds outperformed intensity-duration thresholds for a seasonally wet, coarse-grained soil (TS = 0.8 vs. 0.6, respectively), although they did not outperform intensity-duration thresholds for a perennially wet, fine-grained soil (TS = 0.2 vs. 0.2, respectively). These soils types may also produce radically different stormflow responses, with subsurface flow being more common for the coarse-grained soils underlain by intrusive rocks versus infiltration excess and/or saturation excess for the fine-grained soils underlain by volcaniclastic rocks. We conclude that variability in soil-hydraulic properties, as opposed to the humid-tropical climate zone, is the dominant factor that controls runoff generation and modulates the importance of antecedent soil wetness for our hillslope hydrologic response thresholds. Our findings encourage further deployment of continuous in situ hydrologic monitoring to facilitate the development of empirical hillslope hydrologic response and landslide thresholds for regional-scale hazard warning systems that must account for spatially variable soil types.

Impact cratering is an important geological process that affects all planetary bodies in our solar system. As rock breakdown plays a vital role in the evolution of landforms and sediments on a planetary scale, it is crucial to assess the role of inheritance in the subsequent breakdown of impactites (impact rocks). The shock pressure of several gigapascals generated during the impact can exceed the effective strength of target lithology by three to four orders of magnitude and is responsible for melting, vaporisation, shock metamorphism, pore collapse, vesiculation fracturing and fragmentation of rocks. Environmental conditions and heterogeneities in rock properties exert an important control in rock breakdown. Similar to other subaerial rocks, impactites are affected by a range of rock breakdown processes. In order to better understand the role of low-shock inheritance on rock breakdown, a rock breakdown experiment was conducted in a simulated environmental cabinet under conditions similar to terrestrial semi-arid conditions. We cycled temperature (-2 to 35°C) and relative humidity (13-45%) through 39 accelerated diurnal cycles (each of 8 hours duration). We used 41 impactite samples in the experiment that included low shocked sedimentary and crystalline rocks, impact melt rocks and impact breccias. Mechanical (Equotip and weighing), photographic (photographic monitoring), microscopic and solid-state methods (petrographic microscopy, powder X-ray diffraction, scanning electron microscopy, X-ray computed tomography) were used to characterise the rock samples relative to unshocked rocks, and to assess the shock related changes before and after the experiments. The low shocked sedimentary rocks showed a decrease in porosity by 38% (Coconino Sandstone) and 88% (Moenkopi Sandstone) compared to unshocked counterparts. Macrofractures of 0.1-0.2 mm and microfractures 0.1-5 µm in aperture were observed in all types of impactites. The results showed that impactites exhibited an accelerated decline in strength compared to non-impacted control samples. However, rock type and impact deformation history were key parameters controlling the rate of deterioration.

The 25-27 August geomagnetic storm was the third largest storm in 24th solar cycle, which was a surprising space event that generated in the background of very low solar activity. This study presents an overview of temporal-spatial behaviors of ionospheric plasma irregularities as functions of geographic longitude, latitude and altitude by ground-based (GNSS receivers and ionosonde) instruments and space-borne (Swarm-A and Swarm-B) satellites. The results not only reveal the enhanced equatorial ionization anomaly (EIA) and hemispheric asymmetry over the Asian-Australian and American sectors in a particular time, but also discover the development of hemispheric asymmetric features of global ROTI in the main and recovery phases. In addition, this storm also triggered positive plasma irregularities in altitudes of 100 to 150km near Auroral zone, and the changed ratio of bottom-side plasma irregularities exceeded 250%, which has been cross validated by multiple instrument and TIE-GCM’s simulation. Furthermore, the thermospheric density ratio O/N2, equatorial electrojet and vertical E×B drifts suffered from the storm largely, the equatorial and mid-latitude plasma irregularities may be a combined action of thermospheric composition change, equatorial electrojet and vertical E×B drifts. Finally, the storm also induced positive Joule heating irregularities in Auroral ionosphere in altitudes of 100 to 400km with a maximum changed ratio of >200%, as well as the cross Polar voltage enhanced to ~90kv. The Polar ionospheric irregularities may be associated with the additional energy input through the ways of particle precipitation, Joule heating and ionospheric currents intensification.

Sulfate (SO42-) reduction is a major SO42- output flux from Earth’s oceans, but an imbalance between recent estimates of this flux and corresponding input fluxes suggests inaccuracy in our understanding. Here, we combine global geographic trends in aqueous and dissolved-phase sedimentary data to resolve this inaccuracy. [SO42-] profiles from 700+ sites partition into geographically-distinct k-means clusters based on net sulfate reduction rate (nSRR). Pairing nSRRs with literature-derived pyrite accumulation rates confirms that shelf and slope pyrite burial dominate burial globally. Our results also suggest that sampling and measurement biases have led to erroneously high prior global output estimates and can account for the flux imbalance. Disparate mean d34S values for shelf versus deeper ocean pyrite indicate that sea level change may be an overlooked mechanism for forcing past changes in seawater d34S.

Landcover information is of relevance for a range of applications in Arctic environments including up-scaling of in situ measurements, permafrost monitoring and modelling and climate change impact assessment. But not only natural landcover types, also the identification of human impacted areas is required. A wide range of satellite records are available, but often there are coverage and resolution limitations. Due to the spatial heterogeneity typical for the Arctic, an as high as possible spatial resolution is needed. Sentinel-1 as well as Sentinel-2 offer 10m nominal resolution for specific bands and modes and are freely available across the entire Arctic. The multi-spectral information from Sentinel-2 is specifically of value for discrimination of tundra types. The Synthetic Aperture Radar mission Sentinel-1 provides added value through representation of land surface structure features. A combination of both allows significantly improved characterization of landcover over larger areas. Here, we review recent progress in monitoring the land surface close to Arctic coasts (focus region of HORIZON2020 Nunataryuk), specifically the distribution of human impacted areas beyond of what is represented in databases such as OpenStreetMap or global settlement maps. The added value of machine learning techniques will be discussed and results based on Sentinel-1 und Sentinel-2 presented. Further on, permafrost change information provided through the ESA CCI+ Permafrost project is combined with the novel maps. The CCI+ Permafrost datasets cover 1997-2018 for ground temperature, active layer thickness and permafrost fraction with 1 km gridding (partially derived from MODIS LST, https://climate.esa.int/en/projects/permafrost/data/) and therefore allow detailed assessment of areas with human presence over permafrost.

Papers published in Science of Climate Change by Harde and Salby (2021), and by Berry (2021) contend that the well documented growth of atmospheric CO2 in recent decades is predominantly a natural phenomenon rather than human caused. Both papers are wrong on two counts. First, they focus only on their own (suspect) calculations of anthropogenic atmospheric carbon levels, rather than on measured total carbon levels. The present concentration of anthropogenic carbon in the atmosphere, even correctly calculated, does not establish the human contribution to the rise in total atmospheric carbon. Second, the models these authors develop for determining present anthropogenic atmospheric carbon levels are incompatible with 14C data. The sources of background “anomalous 14C” postulated by Harde and Salby fall well short of being large enough to salvage their model. A highly questionable assumption built into Harde and Salby’s model is explicitly identified.

This is the second half of a two-part study. In the first part, we had used the World Wide Lightning Location Network’s recorded signal amplitudes to test a model of Very Low Frequency signal transmission from the lightning to each sensor. The model predicts a dramatic worsening of transmission at low magnetic latitudes, for nighttime propagation (compared to daytime propagation) toward magnetic West. However, we found that the use of amplitudes was ill-adapted for testing the model under conditions of a deep outage of transmission. Since the relative weakening of nighttime transmission is rather counter-intuitive, we have now developed an alternative approach to testing that model prediction. This alternative approach highlights the patterns of detection/non-detection of several low-magnetic-latitude WWLLN stations and compares those patterns with the appropriate patterns of the model transmission.

Astrobiology as a field is not well known by the public, and is a difficult topic to introduce to the those who have never heard of it before. This presentation will showcase projects and experiences from a museum setting to explore how to best bring up such a complex field of science, and how astrobiologists can make their work as digestible as possible to the general public.

The Indian Ocean (IO) is witnessing acidification as a direct consequence of the continuous rising of atmospheric CO2 concentration and indirectly due to the rapid ocean warming, which disrupts the pH of the surface waters. This study investigates the pH seasonality and trends over various bio-provinces of the IO and regionally assesses the contribution of each of its controlling factors. Simulations from a global and a regional ocean model coupled with biogeochemical modules were validated with pH measurements over the basin, and used to discern the regional response of pH seasonality (1990-2010) and trend (1961-2010) in response to changes in Sea Surface Temperature (SST), Dissolved Inorganic Carbon (DIC), Total Alkalinity (ALK) and Salinity (S). DIC and SST are significant contributors to the seasonal variability of pH in almost all bio-provinces. Total acidification in the IO basin was 0.0675 units from 1961 to 2010, with 69.3% contribution from DIC followed by 13.8% contribution from SST. For most of the bio-provinces, DIC remains a dominant contributor to changing trends in pH except for the Northern Bay of Bengal and Around India (NBoB-AI) region, wherein the pH trend is dominated by ALK (55.6%) and SST (16.8%). Interdependence of SST and S over ALK is significant in modifying the carbonate chemistry and biogeochemical dynamics of NBoB-AI and a part of tropical, subtropical IO bio-provinces. A strong correlation between SST and pH trends infers an increasing risk of acidification in the bio-provinces with rising SST and points out the need for sustained monitoring of IO pH in such hotspots.