An outstanding challenge in modeling the radiative properties of stratiform rain systems is an accurate representation of the mixed-phase hydrometeors present in the melting layer. The use of ice spheres coated with meltwater or mixed-dielectric spheroids have been used as rough approximations, but more realistic shapes are needed to improve the accuracy of the models. Recently, realistically structured synthetic snowflakes have been computationally generated, with radiative properties that were shown to be consistent with coincident airborne radar and microwave radiometer observations. However, melting such finely-structured ice hydrometeors is a challenging problem, and most of the previous efforts have employed heuristic approaches. In the current work, physical laws governing the melting process are applied to the melting of synthetic snowflakes using a meshless-Lagrangian computational approach henceforth referred to as the Snow Meshless Lagrangian Technique (SnowMeLT). SnowMeLT is capable of scaling across large computing clusters, and a collection of synthetic aggregate snowflakes from NASA’s OpenSSP database with diameters ranging from 2–10.5 mm are melted as a demonstration of the method. To properly capture the flow of meltwater, the simulations are carried out at relatively high resolution (15 μm), and a new analytic approximation is developed to simulate heat transfer from the environment without the need to simulate the atmosphere explicitly.

Sediment progradation and spreading is a key process during gravity-driven, thin-skinned deformation in salt-bearing passive margins. However, to what degree the size and shape of a progradational sedimentary wedge control gravity-driven deformation is still not clear. We use analogue modelling to compare two endmember configurations constrained by critical wedge theory, in which the sediment wedge has different initial depositional slopes: a 5° critical (stable) slope and a 27° unstable slope. In both configurations, differential loading initiates spreading characterized by a basinward migrating system of linked proximal extension and distal contraction with a translational domain in between. With a critical frontal slope, the translational domain expands as the contractional domain migrates forward with viscous flow evenly distributed. With a steep frontal slope, both extensional and contractional domains migrate at similar rate due to more localized viscous flow under the wedge toe producing diagnostic structures of late extension overprinting early contraction. In both cases, salt flow is dominated by Poiseuille flow with only a subordinate contribution from Couette flow, contrasting to classical gravity gliding systems dominated by Couette flow. Comparison with previous studies reveal similar structural styles and viscous flow patterns. Our study highlights the geometric variations of sedimentary wedges result in variable responses in gravity spreading systems. With a steep frontal slope, the sediment wedge is more likely to collapse and develop spreading associated structures. However, such steep slope systems may not be very common in salt-bearing passive margins as they are less likely to occur in nature.

Corridors of size-selected crescent-shaped dunes, known as barchans, are commonly found in water, air, and other planetary environments. The growth of barchans results from the interplay between a fluid flow and a granular bed, but their size regulation involves intricate exchanges between different barchans within a field. One size-regulating mechanism is the binary interaction between nearby dunes, when two dunes exchange mass via the near flow field or by direct contact (collision). In a recent Letter (Assis & Franklin, GRL, 2020), we identified five different patterns arising from binary interactions of subaqueous barchans, and proposed classification maps. In this paper, we further inquire into binary exchanges by investigating the motion of individual grains while barchans interact with each other. The experiments were conducted in a water channel where the evolution of pairs of barchans in both aligned and off-centered configurations was recorded by conventional and high-speed cameras. Based on image processing, we obtained the morphology of dunes and motion of grains for all interaction patterns. We present the trajectories of individual grains, from which we show the origin and destination of moving grains, and their typical lengths and velocities. We also show that grains from the impacting dune spread with a diffusion-like component over the target barchan, and we propose a diffusion length. Our results provide new insights into the size-regulating mechanisms of barchans and barchanoid forms found on Earth and other planets.

Hydroperiod, or the amount of time a lentic waterbody contains water, shapes communities of aquatic organisms. Precise measurement of hydroperiod features such as inundation timing and duration can help predict community dynamics and ecosystem stability. In areas defined by high spatial and temporal variability, fine-scale temporal variation in inundation timing and duration may drive community structure, but that variation may not be captured using common approaches including remote sensing technology. Here, we provide methods to accurately capture inundation timing by fitting hidden Markov models to measurements of daily temperature standard deviation collected from temperature loggers. We describe a rugged housing design to protect loggers from physical damage and apply our methods to a group of intermittent ponds in southeastern Arizona, showing that initial pond inundation timing is highly variable across a small geographic scale (~50km2). We also compare a 1-logger (pond only) and 2-logger (pond + control) design and show that, although a single logger may be sufficient to capture inundation timing in most cases, a 2-logger design can increase confidence in results. These methods are cost-effective and show promise in capturing variation in intraregional inundation timing that may have profound effects on aquatic communities, with implications for how these communities may respond to hydroperiod alteration from a changing climate.

Ionospheric perturbations induced by tsunamis and earthquakes can be used for tsunami early warning and remote sensing of earthquakes, provided the perturbations are characterized properly to distinguish them from the ones caused by other sources. The ionospheric perturbations are increasingly being obtained from Global Positioning System (GPS) based Total Electron Content (TEC) measurements sampled at uniform time intervals. However, the sampling is not uniform in space. The nonuniform spatial sampling along the GPS satellite tracks introduces aliasing if it is not accounted while computing the ionospheric perturbations. All the methods hitherto used to detect the co-seismic and tsunamigenic ionospheric perturbations did not account the nonuniform spatial sampling while computing these perturbations. In addition, the residual approach used to obtain the perturbations by detrending the TEC time series using high-order polynomial fit introduces artifacts. These aliasing and artifacts corrupt amplitude, Signal-to-Noise Ratio (SNR), phase, and frequency of ionospheric perturbations which are vital to distinguish the perturbations induced by tsunamis and earthquakes from the rest. We show that Spatio-Periodic Leveling Algorithm (SPLA) successfully removes such aliasing and artifacts. The efficiency of SPLA in removing the aliases and artifacts is validated under two simulated scenarios, and using GPS observations carried out during two natural disasters – the 2004 Indian Ocean tsunami and the 2015 Nepal-Gorkha earthquake. We, further, studied the severity of aliasing and artifacts on co-seismic and tsunamigenic perturbations by analyzing its characteristics employing SNR, spatiotemporal, and wavelet analyses. The results reveal that removal of aliasing and artifacts using SPLA i) increases the SNR up to ~149% compared to the residual method and ~39% compared to the differential method, ii) distinctly resolves signals from sharp static variations, and iii) detects 50% more co-seismic ionospheric perturbations and 25% more tsunami-induced ionospheric perturbations in the two events studied. Cross-correlation of the perturbation time series obtained using the residual method and SPLA reveals that aliasing and artifacts shift the time of occurrence by -7.64 minutes to +4.21 minutes. Further, the results show that the SPLA efficiently detects the ionospheric perturbations at low elevation angles, thereby removes the need of applying elevation cut-off and increases the area of ionospheric exploration of a GPS receiver.

Changes in the concentration of greenhouse gases within the atmosphere lead to changes in radiative fluxes throughout the atmosphere. The value of this change, called the instantaneous radiative forcing, varies across climate models, due partly to differences in the distribution of clouds, humidity, and temperature across models, and partly due to errors introduced by approximate treatments of radiative transfer. This paper describes an experiment within the Radiative Forcing Model Intercomparision Project that uses benchmark calculations made with line-by-line models to identify parameterization error in the representation of absorption and emission by greenhouse gases. The clear-sky instantaneous forcing by greenhouse gases to which the world has been subject is computed using a set of 100 profiles, selected from a re-analysis of present-day conditions, that represent the global annual mean forcing with sampling errors of less than 0.01 \si{\watt\per\square\meter}. Six contributing line-by-line models agree in their estimate of this forcing to within 0.025 \si{\watt\per\square\meter} while even recently-developed parameterizations have typical errors four or more times larger, suggesting both that the samples reveal true differences among line-by-line models and that parameterization error will be readily resolved. Agreement among line-by-line models is better in the longwave than in the shortwave where differing treatments of the water vapor vapor continuum affect estimates of forcing by carbon dioxide and methane. The impacts of clouds on instantaneous radiative forcing are roughly estimated, as are adjustments due to stratospheric temperature change. Adjustments are large only for ozone and for carbon dioxide, for which stratospheric cooling introduces modest non-linearity.

Previous studies have interpreted Last Interglacial (LIG; ~129-116 ka) sea-level estimates in multiple different ways to calibrate projections of future Antarctic ice-sheet (AIS) mass loss and associated sea-level rise. This study systematically explores the extent to which LIG constraints could inform future Antarctic contributions to sea-level rise. We develop a Gaussian process emulator of an ice-sheet model to produce continuous probabilistic projections of Antarctic sea-level contributions over the LIG and a future high-emissions scenario. We use a Bayesian approach conditioning emulator projections on a set of LIG constraints to find associated likelihoods of model parameterizations. LIG estimates inform both the probability of past and future ice-sheet instabilities and projections of future sea-level rise through 2150. Although best-available LIG estimates do not meaningfully constrain Antarctic mass loss projections or physical processes until 2060, they become increasingly informative over the next 130 years. Uncertainties of up to 50 cm remain in future projections even if LIG Antarctic mass loss is precisely known (+/-5 cm), indicating there is a limit to how informative the LIG could be for ice-sheet model future projections. The efficacy of LIG constraints on Antarctic mass loss also depends on assumptions about the Greenland ice sheet and LIG sea-level chronology. However, improved field measurements and understanding of LIG sea levels still have potential to improve future sea-level projections, highlighting the importance of continued observational efforts.

We demonstrate scintillation analysis from a network of geodetic Global Positioning System (GPS) receivers which provide data at 1-second resolution. We introduce proxy phase ($\sigma_{TEC}$) and amplitude ($SNR_4$) scintillation indices and validate them against the rate of change of TEC index (ROTI), and $S_4$. Additionally, we validate scintillation observations against a CASES scintillation receiver. We develop receiver dependent scintillation event thresholding using hardware-dependent noise variance. We analyze six-days adjacent to the 7-8 September 2017 geomagnetic storm, using 169 receivers covering magnetic latitudes between 15$^\circ$ and 65$^\circ$ in the American longitude sector. We leverage the available spatial sampling coverage to construct 2-D maps of scintillation and present episodic evolution of scintillation intensifications during the storm. We show that low-latitude and high-latitude scintillation morphology match well-established scintillation climatology patterns. At mid-latitudes, spatiotemporal evolution of scintillation partially agrees with known scintillation patterns. Additionally, the results reveal previously undocumented mid-latitude scintillation producing structures. The results provide an unprecedented view into the spatiotemporal development of scintillation-producing plasma irregularities and provide a resource to further exploit scintillation evolution at large spatial scales.

Turbulent mixing induced by breaking internal waves is key to the ocean circulation and global tracer budgets. While the classic marginal shear instability of Richardson number ∼ 1/4 has been considered as potentially relevant to turbulence wave breaking, its relevance to energetic zones where tides, winds, and buoyancy gradients excite non-linearly interacting processes has been suspect. We show that shear instability is indeed relevant in the ocean interior and propose an alternative generalized marginal stability criterion, based on the ratio of Ozmidov and Thorpe turbulence scales, which not only applies to the ocean interior, but remains relevant within turbulent boundary layers. This allows for accurate quantification of the transition from downwelling to upwelling zones in a recently emerged paradigm of ocean circulation. Our results help climate models more accurately calculate the mixing-driven deep ocean circulation and fluxes of tracers in the ocean interior.

The Kelvin-Helmholtz instability (KHI) at Earth’s magnetopause and associated turbulence are suggested to play a role in the transport of mass and momentum from the solar wind into Earth’s magnetosphere. We investigate electromagnetic turbulence observed in KH vortices encountered at the dusk flank magnetopause by the Magnetospheric Multiscale (MMS) spacecraft under northward interplanetary magnetic field (IMF) conditions in order to reveal its generation process, mode properties, and role. A comparison with another MMS event at the dayside magnetopause with reconnection but no KHI signatures under a similar IMF condition indicates that while high-latitude magnetopause reconnection excites a modest level of turbulence in the dayside low-latitude boundary layer, the KHI further amplifies the turbulence, leading to magnetic energy spectra with a power-law index –5/3 at magnetohydrodynamic scales even in its early nonlinear phase. The mode of the electromagnetic turbulence is analyzed with a single-spacecraft method based on Ampère’s law, developed by Bellan (2016), for estimating wave vectors as a function of spacecraft-frame frequency. The results suggest that the turbulence does not consist of propagating normal-mode waves, but is due to interlaced magnetic flux tubes advected by plasma flows in the vortices. The turbulence at sub-ion scales in the early nonlinear phase of the KHI may not be the cause of the plasma transport across the magnetopause, but rather a consequence of three-dimensional vortex induced reconnection, the process that can cause an efficient transport by producing tangled reconnected field lines.

In this paper, we leverage open data and open-source software to develop flexible, probabilistic monthly and seasonal (three-month) precipitation forecasts for the Pacific region. We use data from a Multi-Model Ensemble (MME), i.e. a large ensemble of state-of-the-art General Circulation Models (GCMs) and make use of recent developments in the Python open-source software ecosystem allowing the processing of large datasets on standard consumer grade laptops or desktop computers, of particular relevance in the Pacific context. The validation of the deterministic MME forecasts against reanalysis and observational products shows good performance, and confirms that an MME outperforms even the best single GCM. We show that the MME’s forecast performance is modulated by the phases and characteristics of the El Nino Southern Oscillation (ENSO), with the longitude of the maximum Sea Surface Temperature anomalies playing a major role. We suggest that these findings could be used to provide additional confidence information along with the operational MME forecasts. Validation metrics for the probability of drought conditions, alternatively defined as seasonal rainfall accumulations below the climatological 1 tercile (percentile 33) or 1st quartile (percentile 25) show that the MME forecasts are reliable enough for most of the region. We provide an example of how this probabilistic forecast information can be integrated with real-time rainfall monitoring, in order to highlight areas in the tropical Pacific region which are at risk of water stress (i.e., where rainfall has recently been in deficit and forecasts indicate a high likelihood of dry conditions to persist or worsen).

The southern Granite-Rhyolite province contains a comprehensive record of lithospheric evolution in North America. During the last decade, increased seismicity along with improved seismic monitoring installations in Oklahoma provided a rich catalog of local earthquakes. The source-receiver geometry of this dataset is well posed to illuminate the middle and lower crust through long offset recordings of the Pg phase. We present a 3-D P-wave velocity model for central and north Oklahoma developed through a non-standard processing scheme applied to local earthquake waveforms recorded from 2010-2017, focusing on the deeper crust. We employed common-mid-point sorting, stacking, and inversion of Pg-phases which resulted in a set of localized velocity-depth functions up to depths of 40 km. Using this methodology, we significantly increased the S/N ratio for far offset (~250 km) local earthquake waveforms which led to the increase in depth of investigation for our final 3-D velocity model. We find high velocity (> 7 km/s) lower crust throughout the investigated area which suggests a mafic lower crust. The high velocities support previously established models which state that the lower crust of the Granite-Rhyolite province was derived from melting of older crust. We further relate shallow and middle crustal velocity anomalies to other data sets such as gravimetric and magnetic anomalies, and the spatial distribution of earthquakes. We interpret the Nemaha Fault system as a deep-rooted discontinuity which separates two crustal domains. On the contrary, we do not find clear evidence for the existence of the Midcontinent rift (MCR) in northern Oklahoma.

The Lower St. Lawrence Seaway (LSLS), in eastern Canada, is an important habitat for several species of endangered baleen whale. As we seek to reduce the hazards that these endangered species face from human activity, there is increasing demand for detailed knowledge of their habitat use. Only a sparse network of hydrophones exists in the LSLS to remotely observe whales. However, there is also a network of onshore seismometers, designed to monitor earthquakes, that have sufficiently high sample rates to record fin and blue whale calls. We present a simple method for detecting band-limited, regularly repeating calls, such as the 20 Hz calls of fin and blue whales, and apply the method to build a catalog of fin and blue whale detections at 14 onshore seismometers across the LSLS, over approximately a four-year period. The resulting catalog contains >600000 fin whale calls and >60000 blue whale calls. Individual calls are rarely detected at more than one seismometer. Fin whale calls recorded onshore appear to travel mainly through solid earth, rather than only entering the earth at the shoreline, and they often have a complex ~2 s sequence of P-like and S-like phases. Onshore seismometers provide a valuable, previously unused source of data for monitoring baleen whales. However, in the LSLS, the current seismometer network cannot provide high-precision whale tracking alone, so a denser deployment of onshore and/or offshore seismometers is required.

To help understand and determine the driver of jovian auroral X-rays, we present the first statistical study to focus on the morphology and dynamics of the jovian northern hot spot (NHS) using Chandra data. The catalogue we explore dates from 18 December 2000 up to and including 8 September 2019. Using a numerical criterion, we characterize the typical and extreme behaviour of the concentrated NHS emissions across the catalogue. The mean power of the NHS is found to be 1.91 GW with a maximum brightness of 2.02 Rayleighs (R), representing by far the brightest parts of the jovian X-ray spectrum. We report a statistically significant region of emissions at the NHS center which is always present, the averaged hot spot nucleus (AHSNuc), with mean power of 0.57 GW and inferred average brightness of ∼ 1.2 R. We use a flux equivalence mapping model to link this distinct region of X-ray output to a likely source location and find that the majority of mappable NHS photons emanate from the pre-dusk to pre-midnight sector, coincident with the dusk flank boundary. A smaller cluster maps to the noon magnetopause boundary, dominated by the AHSNuc, suggesting that there may be multiple drivers of X-ray emissions. On application of timing analysis techniques (Rayleigh, Monte Carlo, Jackknife), we identify several instances of statistically significant quasi-periodic oscillations (QPOs) in the NHS photons ranging from ∼ 2.3-min to 36.4-min, suggesting possible links with ultra-low frequency activity on the magnetopause boundary (e.g. dayside reconnection, Kelvin-Helmholtz instabilities).

Export of sinking particles from the surface ocean is critical for carbon sequestration and for providing energy to the deep-ocean biosphere. The magnitude and spatial patterns of this flux have been estimated in the past by in situ flux observations, satellite-based algorithms, and ocean biogeochemical models; however, these estimates remain uncertain. Here, we use a novel machine learning reconstruction of global in situ ocean particle size spectra from Underwater Vision Profiler 5 (UVP5) measurements, to determine particulate carbon fluxes. We combine global maps of particle size distribution parameters for large sinking particles with observationally-constrained empirical relationships to calculate the sinking carbon flux from the euphotic zone and the wintertime mixed layer depth. Our flux reconstructions are comparable to prior estimates, but suggest a less variable seasonal cycle in the tropical ocean, and a more persistent export in the Southern Ocean than previously thought. Because our estimates are not bounded by a specific depth horizon, we reconstruct export at multiple depths, and find that export from the wintertime mixed layer globally exceeds that from the euphotic zone. Our estimates provide a baseline for more accurate understanding of particle cycles in the ocean, and open the way to fully three-dimensional global reconstructions of particle size spectra and fluxes in the ocean, supported by the growing database of optical observations.

More recurrent heatwaves and extreme ozone episodes are likely to occur during the next decades and a key question is about the concurrence of those hazards, the atmospheric patterns behind their appearance and their joint effect on human health. In this work, we use surface maximum temperature and O3 observations during extended summers in two cities from Morocco: Casablanca and Marrakech, between 2010 and 2019. We assess the connection between these data and climate indexes (North Atlantic Oscillation (NAO), Mediterranean Oscillation (MO) and Saharan Oscillation (SaOI)). We then identify concurrent heatwaves and ozone episodes, the weather type behind this concurrence and the combined health risks. Our findings show that the concurrence of heatwaves and O3 episodes depends both on the specific city and the large-scale atmospheric circulation. The likely identified synoptic pattern is when the country is under the combined influence of an anticyclonic area in the north and the Saharan trough extending the depression centered in the south. This pattern generates a warm flow and may foster photochemical pollution. Our study is the first step towards the establishment of an alert system. It will help to provide recommendations for coping with concurrent heatwaves and air pollution episodes.

A thermodynamic model to calculate the “Sulfide Content at Sulfide Saturation” or SCSS of basaltic and intermediate composition silicate melts has been built from four independently measurable thermodynamic entities, namely the standard state Gibbs free energy of the saturation reaction, the “sulfide capacity”, and the activities of FeO in the silicate melt and of FeS in the coexisting sulfide: ln [S2-]SCSS = ∆G(FeO-FeS)/RT + ln C(S2- )- ln a(FeO)(sil melt) + ln a(FeS)sulf The model was calibrated for silicate melts of basic and intermediate composition from published experimental results as a function of temperature, silicate melt composition, and sulfide matte composition in the system Fe-Ni-Cu-S-O at 1 bar. The likely effects of pressure and H2O content on SCSS were included in an exploratory way. The model was tuned against the large dataset of S contents in OFB glasses of Jenner and O’Neill (2012), giving it a precision comparable to that of the S analyses themselves, which is ~ 5%. All but 3% the OFB glasses were found to be sulfide saturated within uncertainty; these 3% have lost S by devolatization, revealed by their low S/Se. Applying the model to other OFB datasets suggests sulfide saturation is ubiquitous, including olivine-hosted melt inclusions proposed previously to be sulfide undersaturated. The sulfur fugacity (fS2) of undegassed Ocean Floor Basalts varies proportionally to fO2, with log10fS2 typically within the range -0.6 to +0.4.

Advances in machine learning (ML) techniques and computational capacity have yielded state-of-the-art methodologies for processing, sorting, and analyzing large seismic data sets. In this work, we consider an application of ML for automatically identifying dominant types of impulsive seismicity contained in observations from a 34-station broadband seismic array deployed on the Ross Ice Shelf (RIS), Antarctica from 2014 to 2017. The RIS seismic data contain signals and noise generated by many glaciological processes that are useful for monitoring the integrity and dynamics of ice shelves. Deep clustering was employed to efficiently investigate these signals. Deep clustering automatically groups signals into hypothetical classes without the need for manual labeling, allowing for comparison of their signal characteristics and spatial and temporal distribution with potential source mechanisms. The method uses spectrograms as input and encodes their salient features into a lower-dimensional latent representation using an autoencoder, a type of deep neural network. For comparison, two clustering methods are applied to the latent data: a Gaussian mixture model (GMM) and deep embedded clustering (DEC). Eight classes of dominant seismic signals were identified and compared with environmental data such as temperature, wind speed, tides, and sea ice concentration. The greatest seismicity levels occurred at the RIS front during the 2016 El Niño summer, and near grounding zones near the front throughout the deployment. We demonstrate the spatial and temporal association of certain classes of seismicity with seasonal changes at the RIS front, and with tidally driven seismicity at Roosevelt Island.