Radiation damage in zircon directly impacts diffusion of He from the crystal lattice and is a key factor in defining the kinetics of the zircon (U-Th)/He system. Damage accumulates within a crystal as a function of time and U and Th concentration, but can be thermally annealed as well. The total level of radiation damage in a zircon crystal is governed by a thermally-activated, kinetic process, which in turn influences the interpretation of zircon (U-Th)/He dates for thermal histories. Several annealing models have been defined for the zircon system based on measurements in natural crystals; however, few studies have investigated how multiple levels of radiation damage due to zonation of actinides within a crystal may influence the annealing process. Here we use Raman spectroscopy to map the full width half maximum (FWHM) of then (SiO) band, a proxy for radiation damage, in zircon crystals from the Lucerne pluton (Maine, USA) with heterogeneous distributions of U and Th. We compare FWHM maps before and after annealing these crystals at laboratory times and temperatures. These maps show that each damage zone within a single zircon acts as an isolated domain that is dictated by an independent set of annealing kinetics. Thermally activated annealing decreases radiation damage in all radiation damage zones; however, the rate of annealing is not consistent across all zones. We identify specific modes of damage in probability density plots of all measured FWHM in a crystal that are not present in pre-annealed imagery, but persist in post-annealing Raman maps, regardless of laboratory time temperature conditions: FWHM modes at 2-5 cm, 10-15 cm, and25-30 cm. We attribute these persistent damage modes to variable annealing kinetics that are partially dependent on the level of pre-annealing damage, combined with the inability of high-damage crystals, or zones within crystals, to fully recover their crystallinity. That is, some damage is permanent. These findings therefore show that zircon crystals with non-uniform distributions of U and Th can anneal to create long-lived damage zones at specific damage levels, which has implications for treating the zircon (U-Th)/He chronometer as a multi-domain diffusion system.

Kostinskiy et al. (2015a), using a high-speed infrared (2.5-5.5 μm) camera, discovered the so-called unusual plasma formations (UPFs) in artificial clouds of charged water droplets. UPFs had complex morphology including both streamer-like regions and hot channel segments. They were observed both in the presence and in the absence of hot leader channels developing from the grounded plane toward the cloud. In this paper, which is aimed at revealing the genesis of UPFs, we present two UPFs that occurred inside the initial corona streamer burst of positive polarity emitted from the grounded plane, prior to the formation (or in the absence) of associated hot leader channel. These streamer bursts developed at speeds of 5 to 7 x 10^5 m/s over 1 to 1.5 m in apparently clear air before entering the negatively-charged cloud and producing UPFs at its periphery. Hot channel segments within UPFs were formed in very short times of the order of 1 μs or less. It is not clear if the UPFs were caused solely by the enhanced electric field near the charged cloud boundary or other factors also played a role. Occurrence of UPFs may be a necessary component of any lightning initiation mechanism (Kostinskiy et al., 2020; Iudin et al., 2021).

On-site earthquake early warning techniques, which issue alerts based on seismic waves measured at a single station, are promising, and have performed quite successfully during some damaging earthquakes. Conventionally, most existing techniques extract several P-wave features from the first few seconds of seismic waves after the trigger to predict the intensity or destructiveness of an incoming earthquake. This type of technique neglects the behavior of temporal varying features within P waves. In other words, the characteristics of data sequences are not considered. In this study, a long short-term memory (LSTM) neural network, which was capable of learning order dependence in seismic waves, was employed to predict the PGA of the coming earthquake. A dense LSTM architecture was proposed and a large data set of earthquakes was used to train the LSTM model. The general performance of the LSTM model indicated that the predicted PGA values were quite promising but were generally overestimated. However, the predicted PGA of the Chi-Chi earthquake data set, whose fault rupture was complex and long, using the proposed LSTM model was more accurate than the PGA predicted in a previous study using a support vector regression approach. In addition, an alternative alert criterion, which issues alerts when the predicted PGA exceeds the threshold in successive time windows, is presented, and the performance of the proposed LSTM model when different PGA thresholds are considered is also discussed.

According to the different orientations of the interplanetary magnetic field (IMF), the planetary shock can be either quasi-parallel or quasi-perpendicular. Under quasi-parallel conditions a significant number of solar wind suprathermal particles are reflected from the shock and drift along IMF, forming an extended and highly turbulent region called the foreshock where various nonlinear plasma phenomena are observed. In this research, we perform a case study of the structures in the foreshock region at Mars observed by Mars Atmosphere and Volatile Evolution (MAVEN). We use data from plasma analyzer STATIC and magnetometer MAG to analyze ion beams angular spectrum and magnetic field dynamics. We show that the observed structures are consistent with Short Large-Amplitude Magnetic Structures (SLAMS), commonly detected in foreshock regions of magnetized and unmagnetized bodies throughout the Solar system. Finally, we calculate the magnetic Mach number to analyze the characteristics of the observed foreshock structures. The analysis shows, that SLAMS are formed by the resonance between plasma waves propagating along the IMF and the backstreaming scattered solar wind H+ and exospheric O+ and O2+ ions, with the dominant impact of O2+ ions.

We present an initial assessment of using tomography on single-spacecraft images to reconstruct 3D X-ray emissions from the Earth’s magnetosheath. 3D structures in the Earth’s magnetosphere have been studied using superposed epoch techniques with single-point single-spacecraft observations. They have yielded great insights, but some studies are observation starved, particularly for infrequent solar wind conditions. Global imaging data have provided more insight about these structures, but are 2D projections of 3D structures. We explore the use of tomographic reconstruction techniques to understand what can be extracted from global images from a single spacecraft. The Solar wind Magnetosphere Ionosphere Link Explorer (SMILE) mission, due to launch in 2024 on a 3-year mission, will carry a soft X-ray imager which will capture emissions from portions of the magnetosheath and upstream solar wind. We already demonstrated that the 3D shape of the magnetopause and the bow shock can be extracted from such images with suitable assumptions. The next step is to examine whether full 3D reconstructions of the emissions are possible. We explore the limited range of viewing angles, which affect the accuracy of the reconstructions and introduce artifacts in some cases, and the low count-rates in the images which introduce noise in the reconstructions which must be filtered out. Despite these limitations we show that it is possible to reconstruct some aspects of the magnetosheath global morphology using single-spacecraft soft X-ray imaging. Plans for similar missions which overlap with SMILE, open the possibility of multi-spacecraft tomography, to be addressed in a separate paper.

Hydraulic conductivity curves (HCCs) are important parameters in land surface modeling. The general way for predicting HCC from soil water retention curve (SWRC) requires an additional input of the saturated hydraulic conductivity. The time-consuming in measurement and more importantly, the macro-effect near saturation, however, often result in difficulty and poor performance in predicting the conductivity. In this study, we provided a physically based method for predicting the HCC fully from SWRC requiring no additional parameters. This is achieved by applying an estimated conductivity (from SWRC) in the dry range as new matching point, in together with modifying the HCC model developed by Wang et al. (2018) that accounts for both capillarity and adsorption forces. Testing with a total of 159 soil samples yielded that the new model significantly improved the predictions of HCC, with R2 being 0.74 and root mean value being 0.84 cm d−1, nearly double and half of the value predicted with the input of the saturated hydraulic conductivity, respectively. The abrupt drop near saturation of the HCC model that provided by Wang et al. (2018) for soils with small n values close to 1, a parameter in shaping the SWRC, was also overcome by introducing a non-zero air-entry value.

A substantial amount of dust aerosol was transported to the central Himalayas during the multiple dust storm event that occurred from 12 to 15 June 2018 in the Thar desert, northwestern India. In this study, we implemented a cloud-resolving Weather Research and Forecasting model coupled with chemistry (WRF-Chem) to assess the impact of transported Thar-related dust aerosols on precipitation processes over the central Himalayas. We isolated the effect of the transported dust on the precipitation distribution by zeroing out dust aerosols from lateral boundary condition and keeping other species of aerosols. Results show the noticeable impacts of transported dust aerosols on regional precipitation and cloud properties over the central Himalayas. When transported dust is included, spatially averaged (25°N-31°N and 78°E-89°E) AOD increases by 0.36. Over the Himalayas foothills with the dust, precipitation is enhanced by 7.5% (0.63mm), while surface temperature is reduced. The presence of mineral dust aerosols increased the cloud droplets and ice crystal number concentration, which is further facilitated by the mountainous terrain by orographic lifting, leading to enhanced precipitation. We diagnosed the role of cloud microphysics and that of the cloud dynamics in the simulated precipitation sensitivity. This study highlights the effect of remote dust aerosol on the perturbation of cloud microphysical properties, which can significantly influence precipitation over the Himalayas and impact the regional hydrology.

We image the rupture process of the 2021 Mw 7.4 Maduo, Tibet earthquake using slowness-enhanced back-projection and joint finite fault inversion, which combines teleseismic broadband body waves, long-period (166-333 s) seismic waves, and 3D ground displacements from radar satellites. The results reveal a left-lateral strike-slip rupture, propagating bilaterally on a 160-km-long north-dipping sub-vertical fault system that bifurcates near its east end. About 80% of the total seismic moment occurs on the asperities shallower than 10 km, with a peak slip of 5.7 m. To simultaneously match the observed long-period seismic waves and static displacements, notable deep slip is required, despite a tradeoff with the rigidity of the shallow crust. This coseismic deep slip within the ductile middle crust could result from strain localization and dynamic weakening. Local crustal structure and synthetic long-period Earth response for Tibet earthquakes thus deserve further investigation. The WNW branch ruptures ~75 km at ~2.7 km/s, while the ESE branch ruptures ~85 km at ~3 km/s, though super-shear rupture propagation possibly occurs during the ESE propagation from 12 s to 20 s. Synthetic back-projection tests confirm overall sub-shear rupture speeds and reveal a previously undocumented limitation caused by the signal interference between two bilateral branches. The stress analysis on the forks of the fault demonstrates that the pre-compression inclination, rupture speed, and branching angle could explain the branching behavior on the eastern fork.

Climate patterns in the agricultural zones of the Indus basin are predicted to undergo undesirable changes in the hydrological cycle. These changes are a threat to the widespread agricultural activity and associated livelihoods of the underlying population. Livestock, an essential sector for human sustenance in the basin, is also a major source of greenhouse gas emissions thereby contributing towards climate change. However, it is also a recipient of climate impacts, thus introducing feedbacks and uncertainties that are further accentuated by the Water-Energy-Food Nexus. Here we model and simulate the farm-level dairy operations of a single dairy farm by introducing informatics-driven precision measurements of water, energy, food, and carbon emissions in a system dynamics framework. We analyze the simulated trajectories for energy, water, and waste fluxes to under different interventive scenarios to identify actions that enhance productivity and minimize environmental impact. The model is constructed based on data gathered from two dairy farms located in rural Punjab, Pakistan. The farms have a livestock capacity of 300 and 134 animals respectively, with data related to water, energy, food, and climate gathered over a duration of two years. The simulated results may be used to uncover structural changes in dairy-farm operations which improve the economic structure of the farm while remining within the thresholds defined by Sustainable Development Goals (SDG) 3, 7 and 13 set by the United Nations. The model itself also helps in unravelling the complex interactions among water-energy-food flows along with their coupling to land-climate interactions in context of the dairy farm operations. Beyond the climate change adaptation measures extracted from this study, the system dynamics model that we construct in the process, can help develop economic tools that leverage the advantages of water/climate informatics driven data services and decisions under large variabilities to devise sound agricultural policy.

Inverse thermal history modeling is an effective tool to explore plausible time-temperature (t-T) histories that can be used to describe the geologic history of a sample. Although in some inverse modeling exercises the input thermochronology data is consistent with a single set of t-T histories with similar heating and cooling trends, more commonly inverse models identify a range of paths with different and distinct heating and cooling histories but similarly good fits to the data. Each set of these “path families” typically requires a different geologic interpretation to explain the observed heating and cooling trend, so it is important to identify and consider all possible path families consistent with the regional geology that fit the modelled dataset before selecting a preferred geologic interpretation. Although the inverse model results are always consistent with measured data, a model’s ability to detect all possible path families is partly controlled by the model design – for example the choice of initial conditions, monotonicity settings, and forced time-temperature windows. In this exercise using the thermal history modeling program HeFTy, we illustrate the effects of model design on the inverse model results of a set of multi-chronometer datasets from the southern Patagonian Andes. We use model design to maximize the number of path families identified through inverse modeling. Once individual paths are classified according to path families, we use independently constrained regional geology to discriminate among the diverse plausible set of path families and evaluate different available geologic scenarios. Our exercise illustrates that models restricting exploration of all path families may not identify the true cooling history of the sample. Initially, it may appear challenging to interpret inverse model results that include multiple path families, but we argue that iterating between independent geologic data and modeling provides an effective tool to test the geologic plausibility of alternative heating and cooling histories. Although this exercise is executed using HeFTy, maximizing the identification of all possible path families should be an important component of model design in inverse modeling exercises using all inverse modeling programs.

Turbulent plasmas such as the solar wind and magnetosheath exhibit an energy cascade which is present across a broad range of scales, from the stirring scale at which energy is injected, down to the smallest scales where energy is dissipated through processes such as reconnection and wave-particle interactions. Recent observations of Earth's bow shock reveal a disordered or turbulent transition region which exhibits features of turbulent dissipation, such as reconnecting current sheets. We have used observations from Magnetospheric Multiscale (MMS) over four separate bow shock crossings of varying θBn to characterise turbulence in the shock transition region and how it evolves towards the magnetosheath. We observe the magnetic spectrum evolving by fitting power laws over many short intervals and find that the power-law index in the shock transition region is separable from that of the upstream and downstream plasma, for both quasi-perpendicular and quasi-parallel shocks. Across the shock, we see a change in the breakpoint location between inertial and ion power-law slopes. We also observe the evolution of scale-independent kurtosis of magnetic fluctuations across the shock, finding a reduction of high kurtosis intervals downstream of the shock, which is more apparent in the quasi-perpendicular case. Finally, we adapt a method for calculating correlation length to include a high-pass filter, allowing estimates for changes in correlation length across Earth's bow shock. In a quasi-perpendicular shock, we find the correlation length to be significantly smaller in the magnetosheath than in the solar wind, however the opposite can occur for quasi-parallel shocks.

Our solar system is filled with meteoric particles, or cosmic dust, which is either interplanetary or interstellar in origin. Interstellar dust (ISD) enters the heliosphere due to the relative motion of the sun and the interstellar flow. Interplanetary dust (IPD) comes primarily from asteroid collisions or comet sublimation, and comprises the bulk of material entering Earth’s atmosphere. This study examines variations in ISD and the IPD flux at Earth using observations from three different satellite techniques. First are size-resolved in situ meteoroid detections by the Ulysses spacecraft, and second are in situ indirect dust observations by Wind. Third are measurements of meteoric smoke in the mesosphere by the Solar Occultation For Ice Experiment (SOFIE). Wind observations are sorted into the interstellar and interplanetary components. Wind ISD show the anticipated correlation to the 22-yr. solar magnetic cycle, and are consistent with model predictions of ISD. Because Wind does not discriminate particle size, the IPD measurements were interpreted using meteoric mass distributions from Ulysses observations and from different models. Wind observations during 2007-2020 indicate a total meteoric influx at Earth of 22 metric tons per day (t d-1), in reasonable agreement with long-term averages from SOFIE (25 t d-1) and Ulysses (32 t d-1). The SOFIE and Wind influx time series both show an unexpected correlation to the 22-yr. solar cycle. This relationship could be an artifact, or may indicate that IPD responds to changes in the solar magnetic field.

Simulating the evolution of a coagulating aerosol or cloud of droplets in a key problem in atmospheric science. We present a proof of concept for modeling coagulation processes using a novel combinatorally-invariant neural network (CiNN) architecture. Using two types of data from a high-detail particle-resolved aerosol simulation, we show that CiNN models outperform standard neural networks and are competitive in accuracy with traditional stateof-the-art sectional models. These CiNN models could have application in learning coarsegrained coagulation models for multi-species aerosols and for learning coagulation models from observed size-distribution data.

The chemical evolution of an exoplanetary Venus-like atmosphere is dependent upon the ultraviolet to near ultraviolet (FUV-NUV) radiation ratio from the parent star, the balance between CO2 photolysis and recombination via reactions that depend on the water abundance, and various catalytic chemical cycles. In this study, we use a three-dimensional (3-D) model to simulate conditions for a Venus-like exoplanet orbiting the M-dwarf type star GJ436 by varying the star/planet distance and considering the resultant effects on heating/cooling and dynamics. The simulation includes the middle and upper atmosphere (<40 mbar). Overall, these model comparisons reveal that the impact of extreme ultraviolet to ultraviolet (EUV-UV) heating on the energy balance shows both radiative and dynamical processes are responsible for driving significant variations in zonal winds and global temperature profiles at < 10-5 mbar. More specifically, CO2 15-μm cooling balances EUV/UV and Near InfraRed (NIR) heating at altitudes below 10-7 mbar pressure with a strong maximum balance for pressures at ~10-5 mbar, thus explaining the invariance of the temperature distribution at altitudes below 10-5 mbar pressure for all cases. Our model comparisons also show that moderate changes in NIR heating result in relatively small changes in neutral temperature in the upper atmosphere, and virtually no change in the middle atmosphere. However, with larger changes in the NIR heating profile, much greater changes in neutral temperature occur in the entire upper and middle atmosphere studied.

The recent spacecraft observations by MMS and Van Allen Probes associated with electromagnetic ion cyclotron waves (EMIC) in the Earth magnetosphere emphasize the important role of multi-ion plasma composition for generation and characteristics of these emissions. We show that the main properties of EMIC waves can be explained with the concept of ‘multi-ion oscillitons’ (Sauer et al., 2001). In a plasma with two types of ions of different masses (e.g. protons and oxygen ions), oscillitons arise from the exchange of momentum and energy between the two ion components, with the electromagnetic field acting as a mediator. At frequencies near cross-over frequencies of different wave modes in the multi-ion plasma the nonlinear resonance which strongly amplifies the seed unstable mode can be excited. A small phase difference in oscillations of different ion species leads to a nonlinear wave beating and generation of wave packets. The ‘resonance ‘ frequency is characterized by a local maximum of the phase velocity and the coincidence of phase and group velocity. The generation of coherent waves by oscillitons is of a general nature and may contribute to understand the manifold of phenomena in other space plasma environments in which the dynamics of minor ion admixtures cannot be neglected, as alpha particles in the solar wind and heavy ions around active comets. The concept of oscillitons also applies to the momentum exchange between different particle groups of the same mass. On this way, whistler oscillitons may arise in two-temperature electron plasmas.

Gas hydrates have been reported to exist in marine sediments from various parts of the world ocean. The hydrates start decomposing soon after recovery of the sediments through coring operations due to changes in ambient pressure and temperature. This decomposition leads to changes in sedimentary structures, and thus complicates physical property related measurements of the sediments by conventional methods. In this study, we used a medical X-ray CT scanner to quickly scan the recovered cores, and then used raw data from the CT, and thus avoided image processing steps, to estimate porosity and density of the sediments. The raw data were in terms of CT numbers, which were obtained by drawing a circular region of interest (ROI) to cover most of the sediments visible in a cross section XCT image of the sediments. The data were weighted for relative contribution of liquid and solid in sediments before estimating porosity. On the other hand, density was estimated by using an average CT number that was automatically calculated by the Osirix software used for drawing the ROI on an XCT image, and by using a calibration equation based on a set of standards. Although some uncertainty in estimation of relative volumes of solid, liquid and gas could not be avoided, the results obtained by this new procedure were in good agreement with those obtained by conventional methods. Since porosity and density estimates by the new procedure can be made in a matter of minutes after core recovery, it can guide progress of coring operation and further processing of hydrate-bearing sediments.

Non-hydrostatic km-scale weather and climate models show significant improvements in simulating clouds, especially convective ones. However, even km-scale models need to parameterize some physical processes and are thus subject to the corresponding uncertainty of parameters. Systematic calibration has the advantage of improving model performance with transparency and reproducibility, thus benefiting model intercomparison projects, process studies, and climate-change scenario simulations. In this paper, the regional atmospheric climate model COSMO v6 is systematically calibrated over the Tropical South Atlantic. First, the parameters’ sensitivities are evaluated with respect to a set of validation fields. Five of the most sensitive parameters are chosen for calibration. The objective calibration then closely follows a methodology extensively used for regional climate simulations. This includes simulations considering the interaction of all pairs of parameters, and the exploitation of a quadratic-form metamodel to emulate the simulations. In the current set-up with 5 parameters, 51 simulations are required to build the metamodel. The model is calibrated for the year 2016 and validated in two different years using slightly different model setups (domain and resolution). Both years demonstrate significant improvements, in particular for outgoing shortwave radiation, with reductions of the bias by a factor of 3 to 4. The results thus show that parameter calibration is a useful and efficient tool for model improvement. Calibrating over a larger domain might help improve the overall performance, but could potentially also lead to compromises among different regions and variables, and require more computational resources.

An interplanetary shock can abruptly compress the magnetosphere, excite magnetospheric waves and field-aligned currents, and cause a ground magnetic response known as a sudden commencement (SC). However, the transient (<~1 min) response of the ionosphere-thermosphere system during an SC has been little studied due to limited temporal resolution in previous investigations. Here, we report observations of a global reversal of ionospheric vertical plasma motion during an SC on 24 October 2011 using ~6 s resolution SuperDARN ground scatter data. The dayside ionosphere suddenly moved downward during the magnetospheric compression due to the SC, lasting for only ~1 min before moving upward. By contrast, the post-midnight ionosphere briefly moved upward then moved downward during the SC. Simulations with a coupled geospace model suggest that the reversed E X B vertical drift is caused by a global reversal of ionospheric zonal electric field induced by magnetospheric compression during the SC.