Emissions of nitrogen oxides (NOx = NO + NO2) in the United States have declined significantly during the past three decades. However, satellite observations since 2009 indicate total column NO2 is no longer declining even as bottom-up inventories suggest continued decline in emissions. Multiple explanations have been proposed for this discrepancy including 1) the increasing relative importance of non-urban NOx to total column NO2, 2) differences between background and urban NOx lifetimes, and 3) that the actual NOx emissions are declining more slower after 2009. Here we use a deep learning model trained by NOx emissions and surface observations of ozone to assess consistency between the reported NOx trends between 2005-2014 and observations of surface ozone. We find that the 2005-2014 trend from older satellite-derived emission estimates produced at low spatial resolution best reproduce ozone in low NOx emission (background) regions, reflecting the blending of urban and background NOx in these low-resolution top-down analyses. The trend from higher resolution satellite-based estimates, which are more capable of capturing the urban emission signature, is in better agreement with ozone in high NOx emission regions, and is consistent with the trend based on surface observations of NO2. In contrast, the 2005-2014 trend from the US Environmental Protection Agency (EPA) National Emission Inventory (NEI) results in an underestimate of ozone. Our results confirm that the satellite-derived trends reflect anthropogenic and background influences and that the 2005-2014 trend in the NEI inventory is overestimating recent reductions in NOx emissions.

Understanding the physical mechanisms responsible for the cross-scale energy transport and plasma heating from solar wind into the Earth’s magnetosphere is of fundamental importance for magnetospheric physics and for understanding these processes in other places in the universe with comparable plasma parameter ranges. This paper presents observations from Magnetosphere Multi-Scale (MMS) mission at the dawn-side high-latitude dayside boundary layer on 25th of February, 2016 between 18:55-20:05 UT. During this interval MMS encountered both inner and outer boundary layer with quasi-periodic low frequency fluctuations in all plasma and field parameters. The frequency analysis and growth rate calculations are consistent with the Kelvin-Helmholtz Instability (KHI). The intervals within low frequency wave structures contained several counter-streaming, low- (0-200 eV) and mid-energy (200 eV-2 keV) electrons in the loss cone and trapped energetic (70-600 keV) electrons in alternate intervals. Wave intervals also showed high energy populations of O+ ions, likely of ionospheric or ring current origin. The counter-streaming electron intervals were associated with a large-magnitude field-aligned Poynting fluxes. Burst mode data at the large Alfven velocity gradient revealed a strong correlation between counter streaming electrons, enhanced parallel electron temperatures, strong anti-field aligned wave Poynting fluxes, and wave activity from sub-proton cyclotron frequencies extending to electron cyclotron frequency. Waves were identified as Kinetic Alfven waves but their contribution to parallel electron heating was not sufficient to explain the > 100 eV electrons, and rapid non-adiabatic heating of the boundary layer as determined by the characteristic heating frequency, derived here for the first time.

Tropical marginal seas host unique sedimentary archives that may be exploited to reveal past changes in continental erosion, chemical weathering, and ocean dynamics. However, these records can be challenging to interpret due to the complex interactions between climate and particulate transport across ocean margins. For the southern South China Sea over the last 90 thousand years, we observe a contrasting temporal relationship between the deposition of clay minerals (smectite) and magnetic minerals (hematite), which were associated with two different hydrodynamic modes. Fine-grained clay minerals can be carried in suspension by ocean currents, leading to a rapid response to regional climate-driven inputs. In contrast, changes in magnetic mineralogy were closely associated with bedload transport and resuspension linked to glacial-interglacial sea-level variability. Overall, this study indicates that the transfer pathways and mechanisms imparted by varying hydrodynamic conditions exert a substantial influence on the distribution of terrigenous material in continental shelf sediments.

Storms can have a direct impact on sea ice, but whether their effect is seen weeks to months later has received little attention. The immediate and longer term impacts of an idealized open water wind storm are investigated with a one-dimensional coupled ice-ocean model. Storms with different momentum, duration and date of occurrence are tested. During the storm, the mechanical forcing causes a deepening of the mixed layer, leading to an increase in mixed layer heat content, despite a decrease in mixed layer temperature. This results in a delay in sea ice formation that ranges between a few hours to weeks compared to the control run, depending on the storm characteristics. Throughout the freezing period, the storm-induced thick mixed layer experiences little variability, preventing warm water entrainment at the base of the mixed layer. This leads to faster sea ice growth compared to the control run, resulting in sea ice thickness differences of a few millimeters to around 10 cm before the melting onset. These results are stronger for runs with higher momentum storms which cause greater mixed layer deepening. Storms occurring in early August, when the ocean surface heat flux is positive, also amplify the results by forcing a greater increase in mixed layer heat content. The impacts of the storms are sensitive to the initial stratification, and amplified for a highly stratified ocean. We suggest that localized storms could significantly influence the seasonal dynamics of the mixed layer and consequently impact sea ice conditions.

Poor understanding of aerosol-cloud interactions and cloud feedback processes in the Arctic climate system limit our ability to constrain future climate in the region and one important knowledge gap is the source of particles upon which cloud droplets and ice crystals have formed. If representative cloud-water can be obtained from Arctic clouds, it’s chemical composition can be analysed to infer the sources of particles present within it. However, the balloon-borne active cloud water sampling systems required to obtain such samples have not previously been feasible due to their weight and the challenging environmental conditions. Here we present a miniaturised cloud-water sampler for balloon-borne collection of cloud water which was deployed during the Microbiology-Ocean-Cloud-Coupling in the High Arctic (MOCCHA) campaign in August and September 2018 along with the deployment protocol required to obtain representative samples in the pristine conditions encountered. We present the chemical composition of the samples obtained as well as the ice-nucleating activity of the samples and discuss the implications of our results on aerosol-cloud interactions in the high Arctic.

Insight and other observations of the Martian surface at different locations have recorded the diurnal variation in surface pressure (Ps) with two rapid fluctuations that occur at dawn and dusk (around LT0800 and LT2000). These short-period surface pressure perturbations at specific local times are typically observed near Martian equinox. Similar phase-locked surface pressure fluctuations over most areas of the middle and low latitudes are simulated by the Martian General Circulation Model at the Dynamic Meteorology Laboratory (LMD). This phenomenon is thus likely to be global rather than local. By reconstructing the surface pressure variation from the horizontal mass flux, the pressure fluctuations in a sol can be attributed to the diurnal variation in the horizontal wind divergence and convergence in the Martain tropical troposphere in the GCM simulations. The background diurnal variation in Ps is related to the diurnal migrating tidal wind, while the enhanced convergence due to the overlap of the 4-hour and 6-hour tides before LT0800 and LT2000 is responsible for the Ps peaks occurring at dawn and twilgith. Although the amplitudes of the 4-hour and 6-hour tides are smaller than those of diurnal tides, the phases of these tides remain similar in the Martain troposphere, which suggests that the convergences and divergences due to 4 h/6 h tidal winds at different altitudes are in phase and together create a mass flux comparable to that induced by diurnal/semidiurnal components and lead to rapid pressure fluctuations.

A document by Yusuke Kuwahara. Click on the document to view its contents.

Southeast Asia is a hotspot of riverine export of terrigenous organic carbon to the ocean, accounting for ~10% of the global land-to-ocean riverine flux of terrigenous dissolved organic carbon (tDOC). While anthropogenic disturbance is thought to have increased the tDOC loss from peatlands in Southeast Asia, the fate of this tDOC in the marine environment and the potential impacts of its remineralization on coastal ecosystems remain poorly understood. We collected a multi-year biogeochemical time series in the central Sunda Shelf (Singapore Strait), where the seasonal reversal of ocean currents delivers water masses from the South China Sea first before (during Northeast Monsoon) and then after (during Southwest Monsoon) they have mixed with run-off from peatlands on Sumatra. The concentration and stable isotope composition of dissolved organic carbon, and colored dissolved organic matter spectra, reveal a large input of tDOC to our site during Southwest Monsoon. Using isotope mass balance calculations, we show that 60–70% of the original tDOC input is remineralized in the coastal waters of the Sunda Shelf, causing seasonal acidification by up to 0.10 pH units. The persistent CO2 oversaturation drives a CO2 efflux of 4.1 – 8.2 mol C m-2 yr-1 from the Singapore Strait, suggesting that a large proportion of the remineralized peatland tDOC is ultimately emitted to the atmosphere. However, incubation experiments show that the remaining 30–40% tDOC exhibits surprisingly low lability to microbial and photochemical degradation, suggesting that up to 20–30% of peatland tDOC might be relatively refractory and exported to the open ocean.

Located in northern Dominican Republic, the Early Cretaceous Rio Boba mafic-ultramafic plutonic sequence constitutes a lower crust section of the Caribbean island arc, made up by gabbroic rocks and subordinate pyroxenite. Modal compositions, mineral chemistry, whole-rock compositions and thermobarometric calculations indicate that pyroxenites and gabbronorites represent a cumulate sequence formed by fractionation of tholeiitic magmas with initially very low H2O content in the lower crust of the arc (0.6-0.8 GPa). Melts evolved along a simplified crystallization sequence of olivine ® pyroxenes ® plagioclase ® Fe-Ti oxides. The magmatic evolution of the Rio Boba sequence and associated supra-crustal Puerca Gorda metavolcanic rocks is multi-stage and involves the generation of magmas from melting of different sources in a supra-subduction zone setting. The first stage included the formation of a highly depleted substrate as result of decompressional melting of a refractory mantle source, represented by a cumulate sequence of LREE-depleted IAT and boninitic gabbronorites and pyroxenites. The second stage involved volumetrically subordinate cumulate troctolites and gabbros, which are not penetratively deformed. The mantle source was refractory and enriched by a LILE-rich hydrous fluid derived from a subducting slab and/or overlying sediments, and possibly by a LREE-rich melt. The third stage is recorded in the upper crust of the arc by the Puerca Gorda ‘normal’ IAT protoliths, which are derived from an N-MORB mantle source enriched with a strong subduction component. This magmatic evolution has implications for unravelling the processes responsible for subduction initiation and subsequent building of the Caribbean island arc.

Upon the backdrop of steadily rising global average temperatures, it is the extreme weather events that are arguably more important and impactful than changing averages – especially on human health. This research examines trends in North America of three different parameters of extreme temperature events important to human thermal comfort and public health: their frequency, duration, and spatial extent. Most of the changes are expected; that is, with warmer temperatures there are more frequent extreme heat events that are lasting longer and covering more area. However, we highlight some intriguing divergences from this pattern. For example, despite quickly rising autumn temperatures in northern Canada, a concurrent decrease in temperature variability is resulting in extreme heat events remaining stable and is instead manifest more as significant decreases in extreme cold events. In parts of the western US, even though there is no significant trend in autumn mean temperatures, there is a significant rise in extreme cold events. And, in the southern High Plains in summer, despite little trend in averages, a more negative skew to the distribution is nonetheless leading to significant increases in heat events. Seasonal and geographic variability in the trends of extreme dew point events is also explored. For example, increases in extreme humidity events are ubiquitous throughout most of Canada, particularly in summer; but the US has a northeast (increasing humid events) to southwest (increasing dry events) dichotomy that is strongest in winter. While such nuances might complicate our efforts to broadly generalize the message of climate change, these distinctions suggest a renewed emphasis on local- to regional-scale analyses (rather than larger scales) when providing actionable climate information for planners and policymakers.

We propose an integrated dynamics-physics coupling framework for weather and climate-scale models. Each physical parameterization would be advanced on its natural time scale, revised to include a moist thermodynamic relationship, and finally integrated into the relevant components of the dynamical core. We show results using a cloud microphysics scheme integrated within the dynamical core of the GFDL SHiELD weather model to demonstrate the promise of this concept. We call it the in-line microphysics as it is in-lined within the dynamical core. Statistics gathered from one year of weather forecasts show significantly better prediction skills when the model is upgraded to use the in-line microphysics. However, we do find that some biases are degraded with the in-line microphysics. The in-line microphysics also shows larger-amplitude and higher-frequency variations in cloud structures within a tropical cyclone than the traditionally-coupled microphysics. Finally, we discuss the prospects for further development of this integrated dynamics-physics coupling.

In the past, global maps of major oxides and Mg # of the lunar surface had been derived from spectral data with “ground truth” geochemical information from Apollo and Luna samples. These compositional maps provide insights into the chemical variations of different geologic units, thus the regional and global geologic evolution. In this study, we produced new global maps of major oxides (Al2O3, CaO, FeO, MgO, and TiO2) and Mg # with imaging spectral data of KAGUYA multiband imager (MI) with the one dimensional-convolutional neural network（1D-CNN）algorithm, taking advantage of recently acquired geochemical information of China’s Chang’E-5 (CE-5) samples. The coefficients of determination (R2) and Root Mean Squared Error (RMSE) were selected as the model evaluation indicators, and compared with the models used by Wang et al. (2021) and Xia et al. (2019), the results showed that the 1D-CNN algorithm model used in this study had a higher degree of fit and smaller dispersion between the ground true value and the predicted value. The 1D-CNN algorithm generally performs better in describing the complex nonlinear relationship between spectra and chemical components. In addition, we present regions of mare domes in Mairan Dome (43.76°N, 49.90°W), and irregular mare patches (IMPs) in Sosigenes (8.34°N, 19.07°E) to demonstrate the geologic implications of these new maps. With the highest spatial resolution (~ 59 m / pixel), these new maps of major oxides and Mg # will serve as an important guide in the future study of lunar geology.

Modelling and monitoring seasonal snow are critical for water resource management, flood forecasting and avalanche risk prediction. Snowmelt processes are of particular importance. The behaviour of liquid water in snow has a big influence on melting processes but is difficult to measure, monitor and model. Recent work has shown the promise of electrical self potential measurements for monitoring snow hydrology. To further this aim, detailed modelling of internal water fluxes in melting snow was carried out with FSM and Crocus. These models were coupled to an electrical model of unsaturated flow in snow to create synthetic electrical self potential observations. These synthetic observations were compared to measurements made during two winter field seasons at Col de Porte in the French Alps with a prototype geophysical array installed in October 2018. Different representations of liquid water flow were used to force the electrical model to evaluate its ability to reproduce the measured self potential signals, and to investigate the suitability of the self potential array as part of a coupled geophysical monitoring and modelling system.

• Frictional ruptures initiate via a characteristic nucleation process that triggers dynamic rupture essentially • Nucleation replaces the concept of a ‘static friction coefficient’ • The nucleation process possesses unique characteristic general properties • Nucleation details depend on local topography

Marine carbonates, including shallow-water carbonates and pelagic carbonates, precipitating from seawater and representing the largest sink of calcium (Ca) and carbon (C) at Earth’s surface, could record seawater chemistry. Therefore, marine carbonates help regulate atmospheric carbon dioxide (CO2) concentration and eventually Earth’s long-term climate change. Calcium stable isotope geochemistry is a powerful tool to reconstruct paleo-seawater Ca isotopic compositions (δ44/40Casw) and to constrain the global Ca and C cycles over geological history. Here, we present a Neogene record of δ44/40Ca from pure dolomites of the core XK-1 in the South China Sea. We propose that the dolomites formed in seawater-like fluid-buffered diagenetic environments near the seawater-sediment interface. We demonstrate that XK-1 dolomites display no Ca isotope fractionation from seawater, and hence may serve as good archives of contemporaneous seawater δ44/40Ca. Further, we quantify respective contributions of shallow-water and pelagic carbonates in sequestering carbon over the Neogene, using a Ca isotope mass balance box model. We find that more CO2 may have been sequestered by pelagic carbonate burial during global cooling. The enhanced continental weathering, global cooling, sea-level fall, seawater chemical changes, and pelagic carbonate burial are tightly linked.

Carbon sequestration in geologic formations is a promising strategy that enables long-term storage of CO2. Continental flood basalts are an attractive storage option, primarily due to their reactivity. In 2009 a Basalt Pilot study was initiated in the Columbia River Basalt where ~1000 MT of CO2 was injected ~850 m into the subsurface. Two years later, 50 sidewall cores were collected from the injection zone and characterized for evidence of CO2 mineralization. This effort summarizes those key findings associated with seven sidewall cores

1. Abstract Wave propagation and diffusive transport phenomena could work as evidence of the mechanical discontinuities in material. For the problem of poor efficiency of the existing fracture simulation methods, this paper proposes crack-bearing material characterization approach by processing wave travel-time using seven data-driven classification techniques. To that end, we perform classification models to predict discontinuities orientation, dispersion, and spatial distribution prediction by learning from the different-waves simulation model. The travel-time measured by multiple sensors placed around the material perform as our input data of machine learning method. As a result, this work found that machine learning models exhibit best classification performance on classifying crack dominant orientations. Combination of compressional wave and shear wave are enough to capture the crack information in the material, however, the pressure diffusion also able to optimize our algorithms. Voting classifier and gradient boosting classifier perform the best for purposes of characterization. When compare the performance of different mechanical discontinuities, embedded closed discontinuities shows high accuracy than open discontinuities on the classification models.

Coastal marsh extent is a key variable in the protection of inland areas from storm surge, flooding, and erosion. Vegetation composition is also an important factor in the functional characteristics of coastal marsh areas in terms of both wildlife value and wave energy attenuation. As pressures from accelerating sea level rise and anthropogenic stressors grow, the protection of coastal wetlands will be increasingly essential in mitigating coastal change and preserving habitat to support fisheries and other wildlife. The increase in extent of the aggressive Phragmites australis (Cav.) Trin. ex Steud. (Common Reed) in several of Mississippi’s coastal marsh areas raises questions about how these marshes may evolve in the future, in terms of both spatial extent and ecosystem function. The goals of this study were to quantify the change in extent of P. australis along the West Pascagoula River using aerial image data and to identify the areas of greatest expansion. To assess the possible influences of salinity and wave energy, two areas were examined: one at the mouth of the river delta as it enters the Mississippi Sound, and one more protected inland area with lower salinity. A supervised maximum likelihood algorithm was used to create land cover classifications at 1 meter GSD for calendar years 1996, 2010, 2014 and 2018, with land cover classified as P. australis, other marsh vegetation, marsh-upland ecotone, wooded areas, or water. Per-pixel change detections were computed among the classification images to assess areal change in P. australis extent as compared with other land cover types. Results show an increase in P. australis extent of 157 ha (approximately 1,960%) between 1996 (8 ha) and 2018 (165 ha), with greater expansion in the inland part of the study area. These land cover classifications will also be used to quantify shoreline movement for P. australis-dominated shorelines as compared with other marsh habitats, providing insights into past and future responses of P. australis to changes in sea level compared with neighboring marsh vegetation.