Rock texture has a critical influence on the way rocks weather. The most important textural factors affecting weathering are grain size and the presence of cracks and stylolites. These discontinuities operate as planes of mechanical weakness at which chemical weathering is enhanced. However, it is unclear how different rock textures impact weathering rates and the size of weathered grains. Here, we use a numerical model to simulate weathering of rocks possessing grain boundaries, cracks, and stylolites. We ran simulations with either synthetic or natural patterns of discontinuities. We found that for all patterns, weathering rates increase with discontinuity density. When the density was <~25%, the weathering rate of synthetic patterns followed the order: grid >honeycomb >Voronoi >brick-wall. For higher values, all weathering rates were similar. We also found that weathering rates decreased as the tortuosity of the pattern increased. Moreover, we show that textural patterns strongly impact the size distributions of detached grains. Rocks with an initial monomodal grain size distribution produce weathered fragments that are normally distributed. In contrast, rocks with an initial log-normal size distribution produce weathered grains that are log-normally distributed. For the natural patterns, weathering produced lower modality distributions.

Most countries around the world took actions to control COVID-19 spread that included social distancing, limiting air and ground travel, closing schools, suspending sports leagues, closing factories etc., leading to economic shutdown. The reduced traffic and human movement compared to Business as Usual (BAU) scenario was tracked by Apple and Android cellphone use; the data showed substantial reductions in mobility in most metropolitan areas. For example in Washington D.C., average distance traveled by people was ~13 km and by April when lockdown was in full effect, the distance reduced to ~5 km. Consistent with reduced mobility, air quality as indicated by satellite observations decreased substantially. Granted that year to year variability in weather patterns can have influence on observed NO2 and aerosol concentrations, but the drop in tropospheric nitrogen dioxide (NO2) observed by Sentinel 5P Tropospheric Ozone Monitoring Instrument (TROPOMI) and Suomi NPP Ozone Mapping Profiling Suite (OMPS) observations of NO2 was significant; reductions in observed NO2 were between 15% to 50% between February and April 2020 depending on location and similar reductions in NO2 amount in March and April 2020 compared to March and April 2019. Further, the changes in NO2 across the continental U.S. between 2020 and 2019 correlated well with on-road emissions but did not correlate with changes in emissions from power plants. In the first quarter of 2020, the total amount of NOx emitted on road were 200 times and 7 times larger than that from power plants in LA and NYC, respectively. These findings confirm that power plants are no longer the major source of NO2 in the United States. We also found positive correlation between NO2 and Suomi NPP Visible Infrared Imaging Radiometer Suite (VIIRS) aerosol optical depth measurements in these urban regions indicating common source sectors for NO2 and aerosols/aerosol precursors.

Remote sensing approaches based on VIS-NIR spectroscopy can be used for getting near real-time information about soil fertility. However, the main challenge limiting the application of spectroscopy in soil fertility evaluation is finding suitable data pre-processing and calibration strategies. We have compared various pre-processing techniques using the reflectance spectra obtained from AVIRIS-NG hyperspectral images, for quantification of organic carbon (OC), available phosphorus (P) and available potassium (K) in the surface soils of Surendranagar area (Western parts of India) and Raichur (Southern parts of India). Surface (0 - 0.15 m) soil samples were collected from these two areas synchronously with the dates of the AVIRIS-NG campaign. The soil samples were air dried, sieved to <2 mm, and analyzed for OC, P, and K using standard methods. The AVIRIS spectra (spectral range of 380-2500 nm with an interval of 5 nm) corresponding to soil sampling points were extracted. The pre-processing steps were used in the order: Continuum Removal (Yes/No), Moving Window Abstraction (Yes/No), No transformation or Euclidean Normalization or Standard Normal Variate (SNV), No transformation or Savitsky-Golay (SG) first-order smoothing, and No transformation or first derivative OR second derivative. We have used the partial least squares regression (PLSR) to calibrate the model from pre-processed spectra. The PLSR with Continuum Removal, SNV, SG first-order smoothing, and first derivative was selected as the best algorithm for estimating soil properties from the Western parts of India, and the corresponding R2 were 0.77 for OC, 0.79 for P and 0.83 for K (RMSE <0.3 for all the parameters). The PLSR with Moving Window Abstraction, SG first-order smoothing, and second derivative were selected as the best algorithm for estimating soil properties from the Southern parts of India, and the corresponding R2 were 0.54 for OC, 0.49 for P and 0.56 for K (RMSE <0.3 for all the parameters). These results suggest that the optimization of AVIRIS spectra using various pre-processing techniques and modeling approaches is required for rapid and non-destructive assessment and monitoring of soil health for precision agriculture.

Clay deposits in playa lake/salar environments are now recognized as a significant deposit type for economic concentrations of lithium. Clayton Valley, Nevada, the location of North America’s only lithium brine producer, also has paleo-lacustrine lithium clay deposits of significance, including the Zeus property lithium clay deposit in the eastern part of the valley. This study presents new mineralogical studies on the Zeus property lithium clays to help understand their genesis and the potential economic extraction. The Zeus property (owned by Noram Ventures Ltd.) currently has an inferred resource of 17 million tonnes @ 1060 ppm Li (96,500 tonnes Li2CO3 equivalent). Initial XRD and glycolation techniques for two Zeus property bulk samples, one from the surface (relatively oxidized) and the other from ~35 m depth (relatively reduced) indicate that the clay fraction (~50%) includes smectite, illite/muscovite, chlorite, and a significant amount of amorphous matter believed to be poorly crystalline smectite + illite. The non - clay fraction has calcite, quartz and sanidine. Hectorite, sulfates, borates and halides have not been detected (yet). TIMA (Tescan Integrated Mineral Analyzer, using SEM backscatter and X-ray imaging), and petrography will help determine the mode and mineral chemical compositions in more detail, as well as addressing the relative abundance of authigenic vs. transported clay material. Initial indications are that the smectite and illite are authigenic, and formed in and below a playa lake with evolving lithium (and other cation) concentrations. The lithium budget is likely controlled by smectite and illite. Lithium adsorption onto illite and smectite surfaces and crystal edges is dependent on lithium concentration in brine solutions. Smectite adsorbs significantly higher lithium concentrations and has a higher cation exchange capacity than illite. The apparent absence of hectorite may indicate that smectite and illite formed at low temperatures, away from the influence of hydrothermal fluids and hot springs, which are present on the western side of Clayton Valley. Hectorite is relatively refractory and hinders lithium extraction in weak acid solutions. Leaching tests are underway to determine the most effective methods to extract lithium from the clays, and membrane filtration/ion filtration techniques will be tested for lithium solute concentration and purification.

As the largest natural source of sulfur-containing gases into the atmosphere, ocean organism-derived dimethyl sulfide (DMS) has been considered to play a critical role in the Earth’s climate system. Yet there are great uncertainties in modeling the spatiotemporal variations of DMS and incomplete knowledge of influencing factors in different oceanic regions. Moreover, little is known about the future change of global DMS, which limits our understanding of the feedback of marine ecosystem to climate change. Here we develop an artificial neural network model and combine data mining approaches to address these issues. Phytoplankton biomass and salinity are currently predominant factors associated with DMS variability in the coastal and Arctic regions, respectively. In the mid- and low-latitude open oceans, nutrients and temperature are also crucial factors in addition to radiation and mixed layer depth, and their relationships with DMS show reversals when passing certain thresholds. Although the global average DMS concentration and emission slightly decline from 2005 to 2100, they may change considerably in specific regions. In contrast to the DMS decreases in the low-latitudes mainly related with phosphate reduction and temperature rise and in the North Atlantic subpolar gyre attributed to salinity decline, warming will cause DMS increase in the Southern Ocean and sea ice loss will dramatically enhance DMS emission in the Arctic. Although the global negative feedback loop between oceanic DMS and climate may not operate, the future spatial redistribution of DMS may lead to the change in cloud cover pattern and significantly affect regional climate.

Wave energy has received significant attention in both academic and industrial areas during the past few decades. Among all of Wave Energy Devices (WEC) devices, many researchers focus on modeling the point absorber since it can provide a large amount of power in a small simple device when compared with other technologies. In this present work, we developed an efficient Structured Adaptive Mesh Refinement (SAMR) framework to model the interactions between the wave and pointer absorber by directly solving the Naiver-Stokes equation in a conservative manner. In particular, the level set function is used to capture the air-water interface, and re-initialization across different levels is applied. The Discrete Immersed Boundary Method (DIBM) is applied to describe geometry of the pointer absorber and include its effects on the incoming wave, which is generated in the inlet and absorbed by using a sponger layer closed to the outlet. To save computational cost, meshes are only refined near the air-water interface and surface of point absorber. Specially, both non-subcycling, where a uniform time step is employed for all variables on composite levels, and subcycling, in which variables on different levels advance via different time steps, are embedded in the SAMR framework. Cases about wave generation and fluid-structure interaction are obtained to validate the above proposed algorithm. Results show that subcycling takes significantly less CPU hours than non-subcycling to model the wave and pointer absorber interaction. Heave motions under different wave inputs are compared with previous experiments as well as results from potential flow theory, which shows viscous effects are important in this process. Future work including coupling AMR with Turbulent Models (e.g. RANS or LES) are also listed as an extension.

The crustal seismogenic thickness (CST) has direct implications on the magnitude and occurrence of crustal earthquakes, and therefore, on the seismic hazard of high-populated regions. Amongst other factors, the seismogenesis of rocks is affected by in-situ conditions (temperature and state of stress) and by their heterogeneous composition. Diverse laboratory experiments have explored the frictional behavior of the most common materials forming the crust and upper most mantle, which are limited to the scale of the investigated sample. However, a workflow to up-scale and validate these experiments to natural geological conditions of crustal and upper mantle rocks is lacking. We used NW South America as a case-study to explore the spatial variation of the CST and the potential temperatures at which crustal earthquakes occur, computing the 3D steady-state thermal field taking into account lithology-constrained thermal parameters. Modelled hypocentral temperatures show a general agreement with the seismogenic windows of rocks and mineral assemblies expected in the continental crust. A few outliers in the hypocentral temperatures showcase nucleation conditions consistent with the seismogenic window of olivine-rich rocks, and are intepreted in terms of uncertainties in the Moho depths and/or in the earthquake hypocenters, or due to the presence of ultramafic rocks within the allochthonous crustal terranes accreted to this complex margin. Our results suggest that the two largest earthquakes recorded in the region (Murindo sequence, in 1992) nucleated at the lower boundary of the seismogenic crust, highlighting the importance of considering this transition into account when characterizing seismogenic sources for hazard assessments.

By using the magnetic field data from of Van Allen Probes, we analyzed the distribution characteristics of the electromagnetic environment in the inner magnetosphere on different Dst* index and magnetic local time (MLT). Our results show that for the response of different current systems, the dawn-dusk and noon-midnight asymmetry distribution of the residual magnetic field δB increases with Dst* index. When Dst* < -60 nT, a ‘banana’-shaped geomagnetic field negative disturbance peak region appears in the sector from midnight to dusk. Then, we obtained the azimuthal current density and found the asymmetric internal eastward and external westward ring current. Through the vector analysis of three-dimensional current density, the current density vector distribution in the magnetic equatorial plane (MEP) is completely displayed for the first time, which directly proves the existence of banana current near r = 3.0 - 4.0 RE during strong geomagnetic storms.

We use a newly updated GPS dataset and the GPS Imaging technique to show that the relief of the Apennines Mountain chain in Italy is currently increasing along its entire length by 1-2 mm/yr. We image positive uplift along the entire length of the Apennine crest including the northern Apennines, Calabria and northern Sicily. The maximum uplift rate is aligned with the topographic drainage divide, the greatest elevations and the zone of horizontal extension accommodating east-northeast translation of the Adriatic microplate relative to the Tyrrhenian Basin. Uplift occurs in a 100 - 150 km wide zone with a profile similar to the long wavelength topography, but not to shorter wavelength topography generated by active faulting and erosion. A zone of lower amplitude uplift aligns with the restive volcanic fields and high geothermal potential west of the Apennines, e.g., at Campi Flegrei, Alban Hills, and Monte Amiata-Larderello. Several factors including consistency of the geodetic rate with geologic uplift rates, and incompatibility with transient hydrological or earthquake cycle effects imply that it is a long-lived feature. Uplift occurs despite that the expected consequence of extension is crustal thinning and subsidence, suggesting a causal relationship between gravitational forces and active extension. Anomalies in gravity and upper mantle seismic velocity suggest that elevation gain is driven by forces originating in the mantle. We use these observations to address the hypothesis that these forces result from upward flow of asthenosphere beneath the Apennines, although the spatial and temporal scale of the mantle circulation is unclear.

Large Antarctic ice volume changes characterized the middle to Late Oligocene and the first million years of climate evolution during the Miocene. However, the sea surface temperature (SST) evolution over this period remains poorly constrained, as only a few records from contrasting proxies are available. In this study, we present a long-term alkenone-derived SST record from sediments drilled by the Ocean Drilling Program (ODP) at Site 1168 in the west Tasmanian Sea spanning 29.8 Ma to 16.7 Ma. The SST record highlight that the long-term warming in the Late Oligocene linked to the end of the Middle Oligocene Glacial Interval can be recognized also at mid-to-high latitudes of the Southern Hemisphere. Warmer average temperatures (25.5°C) characterize the period from 24.6 to 22 Ma; average temperatures then decrease by 1 to 2°C into the Miocene and stabilize by 20.1 Ma. The reconstructed temperatures are highly variable in the warm Late Oligocene waters, and more stable and slightly colder in the Early to Middle Miocene. We confirm that this temperature trend is not an artefact of the latitudinal drift of the site, as the temperature anomaly relative to the modern water temperature at the paleolocation confirms the SST trends of the Oligocene. This is the first alkenone-derived record to reproduce the long-term Oligocene climate trend previously interpreted from the benthic δ18O, which recorded a warming and/or reduction in ice volume from the Middle Oligocene Glacial Interval through the latest Oligocene.

The nighttime ionospheric response to a geomagnetic storm occurred on 23-29 September 2020 is investigated over the South American, Atlantic, and West African longitude sectors using NASA’s Global-scale Observations of the Limb and Disk (GOLD) measurements. On 27 September the solar wind conditions were favorable for prompt penetration electric fields (PPEF) to influence the equatorial ionosphere over extended longitudes. The equatorial ionization anomaly (EIA) crests were shifted 8o-10o poleward compared to the quiet time monthly mean across ~65o- 35oW during the main phase. Ionosonde hmF2 (peak electron density height) measurements from Fortaleza (GG: -3.9oN and -38.4oW) indicated a stronger prereversal enhancement this evening than other nights. As a result, Equatorial Plasma Bubbles (EPB) occurred at these longitudes on this evening. This is the first simultaneous investigation of EIA morphology and EPB occurrence rate over an extended longitude range from geostationary orbit during a geomagnetic storm.

A document by Sukanta Sau. Click on the document to view its contents.

The Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC) is a data management system that provides researchers with a variety of tools to help manage data throughout the lifecycle of a project. GRIIDC was developed to fulfill the requirement that all Gulf of Mexico Research Initiative (GoMRI) funded researchers make their data publicly available. After seven years of operation and over 1,900 datasets available for download, GRIIDC has encountered many challenges, including data organization issues, researchers’ varied experience with technology, and hesitance to share data. In 2016, GRIIDC began hosting training webinars to help researchers navigate the system, submit quality data and metadata, and provide data organization best practices. As the quality of data and metadata improved, GRIIDC determined that these webinars could mitigate previous issues. In 2017, the GoMRI data policy was updated requiring that each newly funded research consortium or individual investigator complete three training sessions within specific dates of their grant agreement. The training sessions included an introduction to the GoMRI data management program, organizing data – best practices and GRIIDC submission, and how to submit data to GRIIDC. The training sessions were offered by webinar and as workshops presented at the Gulf of Mexico Oil Spill & Ecosystem Science conference. After hosting over 50 webinars, offering six workshops, and training 260 researchers, GRIIDC encountered a few issues with the required training including having to schedule individual webinars to accommodate researcher’s schedules, low attention rates, and diverse attitudes and experiences sharing data. Improvements were identified such as using software to track presentation views, making webinars more interactive, hosting additional in-person workshops, requiring a quiz at the end of the training, and allowing researchers the ability to test out of training. Even with the issues identified, GRIIDC is hopeful that the training will help researchers provide quality data submissions not only for the remaining GoMRI projects but for data they will generate in the future.

A document by Wenda Zhang. Click on the document to view its contents.

The novel technique of distributed acoustic sensing (DAS) holds great potential for underwater seismology by transforming standard telecommunication cables, such as those currently traversing most of the world’s oceans, into dense arrays of seismo-acoustic sensors. To harness these measurements for seismic monitoring, the ability to record transient ground deformations using telecommunication fibers is investigated here by analyzing ambient noise, earthquake signals, and their associated phase velocities, on DAS records from three dark fibers in the Mediterranean Sea. The recording quality varies dramatically along the fibers and is strongly correlated with the bathymetry and the apparent phase velocities of the recorded waves. Apparent velocities are determined for several well-recorded earthquakes and used to convert DAS S-wave strain spectra to ground motion spectra. Excellent agreement is found between the spectra of nearby underwater and on-land seismometers and DAS converted spectra, when the latter are corrected for site effects. Apparent velocities greatly affect the ability to detect seismic deformations: for the same ground motions, slower waves induce higher strains and thus are more favorably detected than fast waves. The effect of apparent velocity on the ability to detect seismic phases, quantified by expected signal-to-noise ratios, is investigated by comparing signal amplitudes predicted by an earthquake ground motion model to recorded noise levels. DAS detection capabilities on underwater fibers are found to be similar to those of nearby broadband sensors, and superior to those of on-land fiber segments. The results demonstrate the great potential of underwater DAS for seismic monitoring and earthquake early warning.

Recent estimates of the crustal thickness of Mars show a bimodal result of either ∼20 km or ∼40 km beneath the InSight lander. We propose an approach based on random matrix theory applied to receiver functions to further constrain the subsurface structure. Assuming a spiked covariance model for our data, we first use the phase transition properties of the singular value spectrum of random matrices to detect coherent arrivals in the waveforms. Examples from terrestrial data show how the method works in different scenarios. We identify three new converted arrivals in the InSight data, including the second multiply reflected phase from a deeper third interface. We then use this information to jointly invert receiver functions with the absolute S-wave velocity information in the polarization of body waves. Results show a crustal thickness of 43±5 km beneath the lander with two mid-crustal interfaces at depths of 8.5±1.5 km and 22±3 km.

Export of sinking particles from the surface ocean is critical for carbon sequestration and to provide energy to the deep biosphere. The magnitude and spatial patterns of this export have been estimated in the past by \emph{in situ} particle flux observations, satellite-based algorithms, and ocean biogeochemical models; however, these estimates remain uncertain. Here, we use a recent machine learning reconstruction of global ocean particle size distributions from Underwater Vision Profiler 5 (UVP5) measurements to estimate carbon fluxes by sinking particles (35 $\mu$m - 5 mm equivalent spherical diameter) from the surface ocean. We combine global maps of particle size distribution properties with empirical relationships constrained against \emph{in situ} flux observations to calculate particulate carbon export from the euphotic zone and wintertime mixed layer depths. The new flux reconstructions suggest a less variable seasonal cycle in the tropical ocean, and a more persistent export in the Southern Ocean than previously recognized. Smaller particles (less than 420 $\mu$m) contribute most of the flux globally, while larger particles become more important at high latitudes and in tropical upwelling regions. Export from the wintertime mixed layer globally exceeds that from the euphotic zone, suggesting shallow particle recycling and net heterotrophy in the deep euphotic zone. These estimates open the way to fully three-dimensional global reconstructions of particle fluxes in the ocean, supported by the growing database of \emph{in situ} optical observations.

Meteorological research satellites on polar orbits observe occasionally the Moon, when it moves through their deep space view. Over the last few decades, a large data set built up, which allows to determine the lunar flux with unprecedented accuracy especially at wavelengths, for which the Earth’s atmosphere is opaque. We determined the disk-integrated brightness temperature of the Moon at 19 wavelengths between 4 and 15 µm and at five frequencies between 89 and 190 GHz for phase angles between -80° and +70° with HIRS, AMSU-B, MHS, and ATMS on NOAA and MetOp satellites