Collisionless shocks in astrophysical plasmas are important thermalizers, converting some of the incident flow energy into thermal energy, and non-thermalizers, partitioning that energy in unequal ways to different particle species, sub-populations thereof, and field components. This partition problem, or equivalently the shock equation of state, lies at the heart of shock physics. Here we employ systematically a framework to capture all the incident and downstream energy fluxes at two example traversals of the Earth's bow shock by the Magnetospheric Multiscale Mission. Here and traditionally such data has to be augmented by information from other spacecraft, e.g., to provide more accurate measurements of the cold solar wind beam. With some care and fortuitous choices, the energy fluxes are constant, including instantaneous measurements through the shock layer. The dominant incident proton ram energy is converted primarily into downstream proton enthalpy flux, the majority of which is actually carried by a small fraction of suprathermal protons. Fluctuations include both real and instrumental effects. Separating these, resolving the solar wind beam, and other considerations point the way to a dedicated mission to solve this energy partition problem across a full range of plasma and shock conditions.

Based on manually analyzed waveforms recorded by the permanent Ecuadorian network and our large aftershock deployment installed after the Pedernales earthquake, we derive three-dimensional Vp and Vp/Vs structures and earthquake locations for central coastal Ecuador using local earthquake tomography. Images highlight the features in the subducting and overriding plates down to 35 km depth. Vp anomalies (~4.5 – 7.5 km/s) show the roughness of the incoming oceanic crust (OC). Vp/Vs varies from ~1.75 to ~1.94, averaging a value of 1.82 consistent with terranes of oceanic nature. We identify a low Vp (~5.5 km/s) region extending along strike, in the marine forearc. To the North, we relate this low Vp and Vp/Vs (<1.80) region to a subducted seamount that might be part of the Carnegie Ridge (CR). To the South, the low Vp region is associated with high Vp/Vs (>1.85) which we interpret as deeply fractured, probably hydrated OC caused by the CR being subducted. These features play an important role in controlling the seismic behavior of the margin. While subducted seamounts might contribute to the nucleation of intermediate megathrust earthquakes in the northern segment, the CR seems to be the main feature controlling the seismicity in the region by promoting creeping and slow slip events (SSE) offshore that can be linked to the updip limit of large megathrust earthquakes in the northern segment and the absence of them in the southern region over the instrumental period.

We report Magnetospheric Multiscale observations of large amplitude, parallel, electrostatic, proton plasma frequency waves on the magnetospheric side of the reconnecting magnetopause. The waves are often found in the magnetospheric separatrix region and in the outflow near the magnetospheric ion edge. Statistical results from five months of data show that these waves are closely tied to the presence of cold (typically tens of eV) ions, found for 88% of waves near the separatrix region, and that plasma properties are consistent with ion acoustic wavegrowth. We analyze one wave event in detail, concluding that the wave is ion acoustic. We provide a simple explanation for the mechanisms leading to the development of the ion acoustic instability. These waves can be important for separatrix dynamics by heating the cold ion component and providing a mechanism to damp the kinetic Alfvén waves propagating away from the reconnection site.

Prediction of rapid intensification in tropical cyclones prior to landfall is a major societal issue. While air-sea interactions are clearly linked to storm intensity, the connections between the underlying thermal conditions over continental shelves and rapid intensification are limited. Here, an exceptional set of in-situ and satellite data are used to identify spatial heterogeneity in sea surface temperatures across the inner core of Hurricane Sally (2020), a storm that rapidly intensified over the shelf. A leftward shift in the region of maximum cooling was observed as the hurricane transited from the open gulf to the shelf. This shift was generated, in part, by the surface heat flux in conjunction the along and across-shelf transport of heat from storm-generated coastal circulation. The spatial differences in the sea surface temperatures were large enough to potentially influence rapid intensification processes suggesting that coastal thermal features need to be accounted for to improve storm forecasting as well as to better understand how climate change will modify interactions between tropical cyclones and the coastal ocean.

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.

Tropical cyclone (TC) potential intensity (PI) theory has a well known form, consistent with a Carnot cycle interpretation of TC energetics, which relates PI to mean environmental conditions: the difference between surface and TC outflow temperatures and the air–sea enthalpy disequilibrium. PI has also been defined as a difference in convective available potential energy (CAPE) between two parcels, and quantitative assessments of future changes make use of a numerical algorithm based on this definition. Here, an analysis shows the conditions under which these Carnot and CAPE-based PI definitions are equivalent. There are multiple conditions, not previously enumerated, which in particular reveal a role for irreversible entropy production from surface evaporation. This mathematical analysis is verified by numerical calculations of PI’s sensitivity to large changes in surface-air relative humidity. To gain physical insight into the connection between the CAPE and Carnot formulations of PI, we use a recently developed analytic theory for CAPE to derive, starting from the CAPE-based definition, a new approximate formula for PI which nearly recovers the previous Carnot PI formula. The derivation shows that the difference in undilute buoyancies of saturated and environmental parcels which determines CAPE PI can in fact be expressed as a difference in the parcels’ surface moist static energy, providing a physical link between the Carnot and CAPE formulations of PI. This combination of analysis and physical interpretation builds confidence in previous numerical CAPE-based PI calculations that use climate model projections of the future tropical environment.

The persistent and growing spread in effective climate sensitivity (ECS) across global climate models necessitates rigorous evaluation of their cloud feedbacks. Here we evaluate several cloud feedback components simulated in 19 climate models against benchmark values determined via an expert synthesis of observational, theoretical, and high-resolution modeling studies. We find that models with smallest feedback errors relative to these benchmark values have moderate total cloud feedbacks (0.4–0.6 Wm$^{-2}$K$^{-1}$) and generally moderate ECS (3–4 K). Those with largest errors generally have total cloud feedback and ECS values that are too large or too small. Models tend to achieve large positive total cloud feedbacks by having several cloud feedback components that are systematically biased high rather than by having a single anomalously large component, and vice versa. In general, better simulation of mean-state cloud properties leads to stronger but not necessarily better cloud feedbacks. The Python code base provided herein could be applied to developmental versions of models to assess cloud feedbacks and cloud errors and place them in the context of other models and of expert judgement in real-time during model development.

The ocean’s “biological pump” significantly modulates atmospheric carbon dioxide levels. However, the complexity and variability of processes involved introduces uncertainty in interpretation of transient observations and future climate projections. Much work has focused on “parametric uncertainty”, particularly determining the exponent(s) of a power-law relationship of sinking particle flux with depth. Varying this relationship’s functional form introduces additional “structural uncertainty”. We use an ocean biogeochemistry model substituting six alternative remineralization profiles fit to a reference power-law curve, to characterize structural uncertainty, which, in atmospheric pCO2 terms, is roughly 50% of the parametric uncertainty associated with varying the power-law exponent within its plausible global range, and similar to uncertainty associated with regional variation in power-law exponents. The substantial contribution of structural uncertainty to total uncertainty highlights the need to improve characterization of biological pump processes, and compare the performance of different profiles within Earth System Models to obtain better constrained climate projections.

Directional drilling in the oil fields relies particularly on the “on-fly” measurements of the natural magnetic field (measurements while drilling; MWD); the MWD are eventually used to construct the well path. These measurements are the superposition of the signals from the internal, core and crustal, and external, ionospheric and magnetospheric sources and the noise from magnetic elements in the borehole assembly. The internal signals are mostly constant in time and accounted for through the Earth’s internal field models. The signals of external origin give rise to diurnal and irregular spatio-temporal magnetic field variations observable in the MWD. One of the common ways to mitigate the effects of these variations in the MWD is to correct readings for the data from an adjacent land-based magnetic observatory/site. This method assumes that the land-based signals are similar to those at the seabed drilling site. In this paper, we show that the sea level and seabed horizontal magnetic fields differ significantly, reaching up to 30\,\% of sea level values in many oceanic regions. We made this inference from the global forward modeling of the magnetic field using realistic models of conducting Earth and time-varying sources. To perform such modeling, we elaborated a numerical approach to efficiently calculate the spatio-temporal evolution of the magnetic field. Finally, we propose and validate a formalism allowing researchers to obtain trustworthy seabed signals using measurements at the adjacent land-based site and exploiting the modelling results, thus without needing additional measurements at the seabed site.

A subglacial groundwater system beneath Taylor Glacier discharges hypersaline, iron-rich brine episodically at the glacier surface to create Blood Falls; however, the triggering mechanism for these brine release events is not yet understood. We document wintertime brine discharge using time-lapse photography to show that the mechanism does not require melt-induced hydrofracture. Further, we analyze local seismic data to test a hypothesis that fracturing generates elevated surface wave energy preceding and/or coinciding with brine release events. Our results show no discernible elevated Rayleigh wave activity prior to or during Blood Falls brine release. Instead, we find a pattern of seismic events dominated by a seasonal signal, with more Rayleigh events occurring in the summer than the winter from the Blood Falls source area. We calculate that the volumetric opening of cracks that would generate Rayleigh waves at our detection limits are of similar size to myriad cracks in glacier ice, lake ice, and frozen sediment in the terminus area. We therefore propose that any fracturing coincident with brine release activity likely consists of a series of smaller opening events that are masked by other seismicity in the local environment.

We report the characterisation of anthropogenic magnetic particulate matter (MPM) collected on leaves from roadside Callistemon trees from Lahore, Pakistan, and on known sources of traffic-related particulates to assess the potential of first-order reversal curve (FORC) diagrams to discriminate between different sources of anthropogenic magnetic particles. Magnetic measurements on leaves indicate the presence of surface-oxidised magnetite spanning the superparamagnetic (< 30 nm) to single-domain (~30-70 nm) to vortex size range (~70-700 nm). Fe-bearing particles are present both as discrete particles on the surface of larger mineral dust or carbonaceous particles and embedded within them, such that their aerodynamic sizes may be decoupled from their magnetic grain sizes. FORC diagrams of brake-pad residue specimens show a distinct combination of narrow central ridge, extending from 0-200 mT, and a low-coercivity, vertically spread signal, attributed to vortex and multi-vortex behaviour of metallic Fe. This is in agreement with scanning electron microscopy results that show the presence of metallic as well as oxidised Fe. Exhaust-pipe residue samples display a more conventional ‘magnetite-like’ signal comprising a lower coercivity central ridge (0-80 mT) and a tri-lobate signal attributed to vortex state and/or magnetostatic interactions. The FORC signatures of leaf samples combine aspects of both exhaust residue and brake-pad endmembers, suggesting that FORC fingerprints have the potential to identify and quantify the relative contributions from exhaust and non-exhaust (brake-wear) emissions. Such measurements may provide a cost-effective way to monitor the changing balance of future particulate emissions as the vehicle fleet is electrified over the coming years.

The subduction zone of the Cocos Plate beneath Southern Mexico has major variations in the megathrust geometry and behavior. The subduction segment beneath the Oaxaca state of Mexico has relatively frequent large earthquakes on the shallow part of the megathrust and within the subducting slab, and it also has large aseismic slow-slip events. The slab geometry under Oaxaca includes part of the subhorizontal “flat-slab” zone extending far from the trench beneath southern Mexico and the beginning of its transition to more regular subduction geometry to the southeast. We study the rupture of the 16 February 2018 Mw 7.2 Pinotepa earthquake near Pinotepa Nacional in Oaxaca that was a thrust event on the subduction interface. The Pinotepa earthquake was about 350 km away from the 8 September 2017 Mw 8.2 Tehuantepec earthquake in the subducting slab offshore Oaxaca and Chiapas; it was in an area of Coulomb stress decrease from the M8.2 quake, so it seems unlikely to be a regular aftershock and was not triggered by the static stress change. Geodetic measurements from interferometric analysis of synthetic aperture radar (InSAR) and time-series analysis of GPS station data constrain finite-fault slip models for the M7.2 Pinotepa earthquake. We analyzed InSAR data from Copernicus Sentinel-1A and -1B satellites and JAXA ALOS-2 satellite. Our Bayesian (AlTar) static slip model for the Pinotepa earthquake shows all of the slip confined to a very small (10-20 km diameter) rupture, similar to some early seismic waveform fits. The Pinotepa earthquake ruptured a portion of the Cocos megathrust that has been previously mapped as partially coupled and shows that at least small asperities in that zone of the subduction interface are fully coupled and fail in high-stress drop earthquakes. The previous 2012 Mw 7.4 Ometepec earthquake is another example of asperity in the partially coupled zone but was not imaged by InSAR so the rupture extent is not so well constrained. The preliminary NEIC epicenter for the Pinotepa earthquake was about 40 km away (NE) from the rupture imaged by InSAR, but the NEIC updated epicenter and Mexican SSN location are closer. Preliminary analysis of GPS data after the Pinotepa earthquake indicates rapid afterslip on the megathrust in the region of coseismic slip. Atmospheric noise masks the postseismic signal on early InSAR data.

Understanding past changes in precipitation extremes could help us predict their dynamics under future conditions. We present a novel approach for analyzing trends in extremes and attributing them to changes in the local precipitation regime. The approach relies on the separation between intensity distribution and occurrence frequency of storms. We examine the relevant case of the eastern Italian Alps, where significant trends in annual maximum precipitation over the past decades were observed. The model is able to reproduce observed trends at all durations between 15 minutes and 24 hours, and allows to quantify trends in extreme return levels. Despite the significant increase in storms occurrence and typical intensity, the observed trends can be only explained considering changes in the tail heaviness of the intensity distribution, that is the proportion between heavy and mild events. Our results suggest these are caused by an increased proportion of summer convective storms.

Markov Chain Monte Carlo (MCMC) sampling of solutions to large-scale inverse problems is, by many, regarded as being unfeasible due to the large number of model parameters. This statement, however, is only true if arbitrary, local proposal distributions are used. If we instead use a global proposal, informed by the physics of the problem, we can dramatically improve the performance of MCMC and even solve highly nonlinear inverse problems with vast model spaces. This is illustrated by a seismic full-waveform inverse problem in the acoustic approximation, involving close to 10^6 parameters.

Constraining the subsurface thermal regime is of importance not just to the offshore hydrocarbon exploration industry but also for understanding the geothermal regime in context of microbiological activity. This regime is tested through the use of seismic data to noninvasively estimate subsurface temperatures through the identification of bottom simulating reflectors (BSRs) at the base gas hydrate stability zone (GHSZ) to mark out an isotherm. This reflection seismic thermometry methodology is applied to the Blake Ridge, offshore east coast USA, where ODP Leg 164 boreholes provide temperature data required for thermal model constraints. 3D thermal modelling using reflection seismic data is used to examine the lateral variability of the shallow thermal regime while 1D thermal modelling is applied to ODP Sites 994, 995 and 997. The resulting estimated subsurface temperature profiles had a margin of error of 13.9% compared to in situ temperature measurements recorded from the boreholes. This method of thermal modelling could significantly expand the application of thermal data from ODP sites to areas covered by seismic data, which would considerably benefit researchers worldwide in industry and academia.

Melt ponds play an important role in the seasonal evolution of Arctic sea ice. During the melt season, snow atop the sea ice begins to metamorphose and melt, forming ponds on the ice. These ponds reduce the albedo of the surface, allowing for increased solar energy absorption and thus further melting of snow and ice. Analyzing the spatial distribution and temporal evolution of melt ponds helps us understand the sea ice processes that occur during the summer melt season. It has been shown that the inclusion of melt pond parameters in sea ice models increases the skill of predicting the summer sea ice minimum extent. Previous studies have used remote sensing imagery to characterize surface features and calculate melt pond statistics. Here we use new observations of melt ponds obtained by the Digital Mapping System (DMS) flown onboard NASA Operation IceBridge (OIB) during two Arctic summer melt campaigns which surveyed thousands of kilometers of sea ice and resulted in more than 45,000 images. One campaign was conducted in the Beaufort Sea (July 2016), and one in the Lincoln Sea and the Arctic Ocean north of Greenland (July 2017). Using these data we expect to advance our understanding of the differences and similarities between melt pond features on young, thin sea ice seen in the Beaufort Sea versus those on multi-year ice. We have developed a pixel-based classification scheme by considering the different RGB spectral values associated with each surface type. We identify four sea ice surface types (level ice, rubbled ice, open water, and melt ponds). The classification scheme enables the calculation of parameters including melt pond fraction, ice concentration, melt pond area, and melt pond dimensions. We compare results with data from the Airborne Topographic Mapper (ATM), a laser altimeter also operated during these OIB missions. Given the extent over which the OIB data are available, regional information may be derived. Leveraging existing satellite data products, we examine whether the high-resolution airborne statistics are representative of the region and can be scaled up for comparison against satellite-derived parameters such as ice concentration and extent.

Current estimates of the impact of an increase in greenhouse gas concentrations on global warming, including by the IPCC and in General Circulation Models, are based on radiative forcing. Two recently published formulations of the theoretical foundation for radiative forcing are reviewed. Radiative forcing at the tropopause is calculated by assuming that the absorption of terrestrial radiation by greenhouse gases is determined by their spectral properties, using a radiative transmittance function based on the line strength and line shape of the absorption lines and the vertical optical mass, whilst, under conditions of local thermodynamic equilibrium, the emission of radiation at each layer of the atmosphere is given by the Planck blackbody function at the local atmospheric temperature. Radiative forcing is given by the net change in radiative flux at the troposphere due to an increase in greenhouse gases. Climate change is seen to take place when the system responds to restore the radiative equilibrium. Without any theoretical foundation, a linear relationship between the change in surface temperature in °C and radiative forcing is assumed. Here, IPCC 2013’s estimate of radiative forcing of 2.83 W/m2 due to the increase in greenhouse gases from 1750 to 2011 is used to calculate the resulting change in radiative flux at the Earth’s surface under reasonable assumptions, and the Stefan-Boltzmann law is applied to calculate the change in surface temperature of between 0.8 and 1.0 °C. This represents a climate sensitivity of around 0.32 °C/(W/m2), about one third of the climate sensitivity of 1.0 °C/(W/m2) used by IPCC 2013 that was obtained from the mean regression-based values of 30 climate models.

Prior analyses of oceanic magnetic induction within Jupiter’s large icy moons have assumed uniform electrical conductivity. However, the phase and amplitude responses of the induced fields will be influenced by the natural depth-dependence of the electrical conductivity. Here, we examine the amplitudes and phase delays for magnetic diffusion in modeled oceans of Europa, Ganymede, and Callisto. For spherically symmetric configurations, we consider thermodynamically consistent interior structures that include realistic electrical conductivity along the oceans’ adiabatic temperature profiles. Conductances depend strongly on salinity, especially in the large moons. The induction responses of the adiabatic profiles differ from those of oceans with uniform conductivity set to values at the ice–ocean interface, or to the mean values of the adiabatic profile, by more than 10\% for some signals. We also consider motionally induced magnetic fields generated by convective fluid motions within the oceans, which might optimistically be used to infer ocean flows or, pessimistically, act to bias the ocean conductivity inversions. Our upper-bound scaling estimates suggest this effect may be important at Europa and Ganymede, with a negligible contribution at Callisto. Based on end-member ocean compositions, we quantify the magnetic induction signals that might be used to infer the oxidation state of Europa’s ocean and to investigate stable liquids under high-pressure ices in Ganymede and Callisto. Fully exploring this parameter space for the sake of planned missions requires thermodynamic and electrical conductivity measurements in fluids at low temperature and to high salinity and pressure as well as modeling of motional induction responses.