Para- and ferro-magnetic fabrics are known to provide essential clues for understanding impact cratering processes. However, research on the effects of shock waves on diamagnetic fabrics is lacking. We, therefore, conducted a hypervelocity impact experiment on a block of diamagnetic Taunus quartzite and studied the changes in diamagnetic fabrics. In the crater subsurface, the reorientation of the diamagnetic fabrics is concentrated in a zone of ~4 projectile diameters (25 mm) width directly below the point of impact. Higher reorientation in this zone indicates the concentration of damage. We argue that although the shockwaves traversed through the target with a hemi spherical wavefront, the damage was concentrated directly below the point of impact. Another important observation is that the weak shock waves have changed the diamagnetic parameters. The bulk susceptibility has increased overall, while the corrected degree of anisotropy (P’) and the shape parameter (T) have increased in the crater subsurface but have decreased at the target surface. We propose that the variable response of P’ and T could be due to the difference in incident angle subtended by the shock wave on the diamagnetic foliation at the target surface (c. 34°) and in the subsurface (c. 54°). These results, thus, show that the changes in diamagnetic fabrics can be used as a proxy for plastic deformation caused by shock waves at low peak pressures.

During intense geomagnetic storms, the magnetopause can move in as far as geosynchronous orbit, leaving the satellites in that orbit out in the magnetosheath. Spacecraft operators turn to numerical models to predict the response of the magnetopause to solar wind conditions, but the predictions of the models are not always accurate. This study investigates four storms with a magnetopause crossing by at least one GOES satellite, using four magnetohydrodynamic models at NASA’s Community Coordinated Modeling Center (CCMC) to simulate the events, and analyzes the results to investigate the reasons for errors in the predictions. Two main reasons can explain most of the erroneous predictions. Firstly, the solar wind input to the simulations often contains features measured near the L1 point that did not eventually arrive at Earth; incorrect predictions during such periods are not the fault of the models. Secondly, while the models do well when the primary driver of magnetopause motion is a variation in the solar wind density, they tend to overpredict or underpredict the Birkeland currents during times of strong negative IMF Bz, leading to poorer prediction capability. Coupling the MHD codes to a ring current model, when such a coupling is available, generally will improve the predictions but will not always entirely correct them. More work is needed to fully characterize the response of each code under strong southward IMF conditions as it relates to prediction of magnetopause location.

The eruption of the Hunga Tonga – Hunga Ha’apai (HTHH) volcano on January 15, 2022 injected large amounts of water vapor directly into the stratosphere. While normal background levels of stratospheric water vapor are not detectable in radio occultation (RO) measurements, effects of the HTHH eruption are clearly observed as anomalous refractivity profiles from COSMIC-2, suggesting the possibility of detecting the HTHH water vapor signal. To separate temperature vs. water vapor effects on refractivity, we use co-located temperature observations from the Microwave Limb Sounder (MLS) to constrain a simplified water vapor retrieval. Our results show enhancements of water vapor up to ~1500-2300 ppmv in the stratosphere (~29-33 km) in the days following the HTHH eruption, with propagating patterns that follow the dispersing volcanic plume. The stratospheric water vapor profiles derived from RO are in reasonable agreement with limited radiosonde observations over Australia.

Understanding drivers of cloud organization is crucial for accurately estimating clouds’ feedback to a warming climate. Shallow mesoscale circulations are thought to play an important role in cloud organization, but they have not been observed. Here, we present observational evidence for shallow mesoscale overturning circulations (SMOCs) from divergence measurements made during the EUREC4A field campaign in the north-Atlantic trades. Meteorological reanalyses reproduce the observed low-level divergence well and confirm SMOCs to be mesoscale features (ca. 200 km). Large mesoscale variability, five-fold the mean, is shown to be associated with the ubiquity of SMOCs. Furthermore, time-lag correlations suggest that SMOCs amplify mesoscale moisture variance at cloud-base and in the sub-cloud layer. Through their modulation of cloud-base moisture, SMOCs influence the drying efficiency of entrainment, thus yielding moist ascending branches and dry descending branches. The observed moisture variance differs from expectations from large-eddy simulations, which show largest variance near cloud top and negligible sub-cloud variance. The ubiquity of SMOCS and their coupling to moisture and cloud fields suggest that the strength and scale of mesoscale circulations are important in determining how clouds couple to climate, something which is not considered by present theories.

Recent research has put in evidence the self-lofting capacity of smoke aerosols in the stratosphere and their self-confinement by persistent anticyclones, which prolongs their atmospheric residence time and radiative effects. By contrast, the volcanic aerosols-composed mostly of non-absorptive sulphuric acid droplets-were never reported to be subject of self-lofting nor of dynamical confinement. Here we use high-resolution satellite observations to show that the eruption of Raikoke volcano in June 2019 produced a long-lived stratospheric anticyclone containing 24% of the total erupted mass of sulphur dioxide. The anticyclone persisted for more than 3 months, circumnavigated the globe three times, and ascended diabatically to 27 km altitude through radiative heating of volcanic ash contained by the plume. The mechanism of dynamical confinement has important implications for the planetary-scale transport of volcanic emissions, their stratospheric residence time, and atmospheric radiation balance. It also provides a challenge or “out of sample test” for weather and climate models that should be capable of reproducing similar structures.

A set of LSE observations from field experiments were conducted on 16-18 Oct 2013 along a south/north desert road in the Taklimakan Desert (TD), China. The observed LSEs (EOBS) are thus used in this study as the reference to evaluate the quality of Combined ASTER MODIS Emissivity over Land (CAMEL). Analysis of these data shows four main results. Firstly, the CAMEL appears to capture the spatial variations of LSE from the oasis to the hinterland of TD well, especially in the quartz reststrahlen band 8.1 mm, 8.6 mm and 9.1 mm. From site 1 at the south edge of the TD to site 10 at the north edge, the EOBS and the corresponding CAMEL in the quartz reststrahlen band firstly decrease and reach their minimum around sites 4-6 at the hinterland of the TD. Then the LSE increases gradually and finally gets their maximum at site 10 with clay ground surface, which is higher at the edges of the desert and lower in the center. Second, the CAMEL at 8.3 mm has a Zonal distribution characteristic of northeast-southwest strike. Third, the unrealistic variation of original EOBS can be filtered out with useful signals remaining by the first 6 principal components from PCA upon the laboratory measured hyperspectral emissivity spectra (ELAB). Fourth, the CAMEL correlates well with the measured LSE at the ten observation sites, with the EOBS slightly smaller than CAMEL in general.

Physical interactions of microplastics within vegetation and turbulent flows of freshwater systems are poorly understood. An experimental study was conducted to investigate the underlying physical transport mechanisms of microplastics over submerged canopies across a range of flow conditions common in the natural environment. The effects of changing canopy heights were investigated by testing two model canopies of varying stem heights, simulating seasonal variation. This study determined and compared the mixing and dispersion processes for microplastics and solutes and proposed a hydrodynamic model for quantifying microplastic mixing in submerged canopies. Longitudinal dispersion coefficients for neutrally buoyant microplastics (polyethylene) and solutes were significantly correlated within submerged model vegetation irrespective of the complexity of the flow regime. Hydrodynamic and solute transport models were shown to be capable of robust predictions of mixing for neutrally buoyant microplastics in environmental flows over a canopy, facilitating a new approach to quantify microplastic transport and fate.

The analysis of drought onset and their potential relationship to drought severity (deficit volume) are critical for providing timely information for agricultural operations, such as cultivation planning and crop productivity monitoring. A coupling between drought timing and deficit volume can be used as a proxy for drought-related damage estimation and associated risks. Despite its high importance, so far little attention was paid to determine the timing of drought and its linkage with deficit volume for hydrological droughts. This study utilizes quality-controlled streamflow observations from 1965 to 2018 to unveil regional patterns of hydrological drought onset, trends in event-specific deficit volume, and nonlinear relationships between onset timing and deficit volume across 97 rain-dominated catchments in Peninsular India (8-24o N, 72-87o E). Our results show a shift towards earlier hydrological drought onset in conjunction with a decrease in deficit volume during the Indian monsoon (June-September) season, which is contrasted by a delayed onset in the pre-monsoon (March-May) and post-monsoon (October-February) seasons. Further, approximately one-third of the catchments show a significant nonlinear dependency between drought deficit volume and onset time. We find environmental controls, such as soil organic carbon, vertical distance to channel network, and soil wetness are dominant factors in influencing droughts. Our analysis provides new insights into the causal chain and physical processes linking climatic and physiographic controls on streamflow drought mechanisms, which can support drought forecasting and climate impact assessment studies.

Microseismicity associated with fluid pressurization in the subsurface occurs during fluid injection but can also be triggered after injection shut-in. Understanding the extent and duration of the post-injection microseismicity is critical to limit the risk of fluid-induced seismicity and insure the safe utilization of the subsurface. Using theoretical and numerical techniques, we investigated how aseismic slip on a fault plane evolves and stops after a fluid pressurization event. We found that the locking mechanisms controlling the arrest of aseismic slip highly depend on the initial fault stress criticality and the pressurization duration. The absolute arrest time of fault aseismic slip after injection shut-in is proportional to the pressurization duration and increases significantly with the initial fault stress criticality. Given that microseismicity can be triggered by aseismic slip, these results provide insights into the mechanics controlling the arrest of microseismicity after fluid pressurization as a milestone towards induced seismicity mitigation strategies.

The concept of radial velocity is proposed for high frequency (HF) radar for sea surface current measurement. However, in a spaceborne synthetic aperture radar (SAR) system, the meaning of this concept has changed greatly. Through the evidence and analysis presented in this paper, the radial velocity of the sea surface observed via spaceborne SAR is revealed from the projection of the satellite’s velocity at different points along the range direction, and its distribution on the image presents a strip-like texture, which is very different from the central radial distribution on the velocity image measured via HF radar. The retrieved sea surface velocity field does not exhibit any radial characteristics, and its value is solely the magnitude of the sea surface velocity.

Species Distribution Modelling (SDM) is widely used by ecologists to monitor biodiversity and manage wildlife. In the last decades, Artificial Intelligence (AI) and Machine Learning (ML) techniques became popular and were successfully applied for different tasks, including SDM. The objective of this article was to evaluate Machine Learning models for Species Distribution Modeling in the Amazon Basin region near Manaus (AM), based on meteorological and aerosol data collected by the GoAmazon 2014/15 project. The techniques were evaluated regarding their accuracy and the Decision Tree Classifier and the Maximum Entropy Model obtained good predictive performances.

Near-term freshwater forecasts, defined as sub-daily to decadal future predictions of a freshwater variable with quantified uncertainty, are urgently needed to improve water quality management as freshwater ecosystems exhibit greater variability due to global change. Shifting baselines in freshwater ecosystems due to land use and climate change prevent managers from relying on historical averages for predicting future conditions, necessitating near-term forecasts to mitigate freshwater risks to human health and safety (e.g., flash floods, harmful algal blooms). To assess the current state of freshwater forecasting and identify opportunities for future progress, we synthesized freshwater forecasting papers published in the past five years. We found that freshwater forecasting is currently dominated by near-term forecasts of water quantity and that near-term water quality forecasts are fewer in number and in early stages of development (i.e., non-operational), despite their potential as important preemptive decision support tools. We contend that more freshwater quality forecasts are critically needed, and that near-term water quality forecasting is poised to make substantial advances based on examples of recent progress in forecasting methodology, workflows, and end user engagement. For example, current water quality forecasting systems can predict water temperature, dissolved oxygen, and algal bloom/toxin events five days ahead with reasonable accuracy. Continued progress in freshwater quality forecasting will be greatly accelerated by adapting tools and approaches from freshwater quantity forecasting (e.g., machine learning modeling methods). In addition, future development of effective operational freshwater quality forecasts necessitates substantive engagement of end users throughout the forecast process, funding, and training opportunities. Looking ahead, near-term forecasting provides a hopeful future for freshwater management in the face of increased variability and risk due to global change, and we encourage the freshwater scientific community to incorporate forecasting approaches in water quality research and management.

The variations of elastic parameters and attenuation of rock under deformation are of great importance for a number of geophysical problems. Here, we estimate elastic parameters and their evolutions during laboratory rock deformation experiments, while developing a Monte-Carlo full-waveform fitting method. The transducer-transducer one-source one-station active seismic data of dry and water-saturated samples are obtained from Zaima and Katayama (2018, https://doi.org/10.1029/2018JB016377). The synthetic seismic data are modeled using the spectral element method. We first performed a trial-and-error estimate of the boundary conditions in order to suppress its influence on waveform matching. The synthetic seismic data are generated using equivalent homogeneous models with different combinations of elastic and anelastic parameters. We then compared the synthetics with the laboratory experimental data. Based on these comparisons, we obtain the time-lapse variations of seismic velocities and attenuation of rock samples during deformation, which are then interpreted as crack development. Our simultaneous estimation of elastic and anelastic parameters allowed us to detail the dynamics prior to the rock failure.

The lithospheric architecture of passive margins is crucial for understanding the tectonic processes that caused the break-up of Gondwana. We highlight the evolution of the South Atlantic passive margins by a simple thermal lithosphere-asthenosphere-boundary (LAB) model based on rifting time, crustal thickness, and stretching factors. We simulate the different rifting stages that caused the opening of the South Atlantic Ocean and pick the LAB as the T=1330 °C isotherm, which is calculated by 1D advection and diffusion. In a synthetic example, we demonstrate that the initial crustal thickness has the largest effect on the thermal LAB. For the South American passive margin, our modeled LAB shows a deep and smooth structure between 110-150 km depth at equatorial latitudes and a more variable LAB between 50-200 km along the southern part. This division reflects different stages of the South Atlantic opening: initial opening of the southern South Atlantic causing substantial lithospheric thinning, followed by rather oblique opening of the equatorial South Atlantic accompanied by severe thinning. The modeled LAB reflects a high variability associated with tectonic features on a small scale. Comparing the LAB of the conjugate South American and African passive margins in a Gondwana framework reveals a variable lithospheric architecture for the southern conjugate margins. Along selected conjugate margin segments stark differences up to 80 km of the LAB depths correlate with strong gradients in margin width. This mutual asymmetry suggests highly asymmetric melting and lithospheric thinning prior to rifting.

We measured COs-1 which corresponds to a growing season estimate of 0.04 to 0.16 g CH4 m-2. We find that this moss tundra emits about 60 gCO2-equivalents m-2 yr-1 of which CH4 is responsible for 7%. Air temperature, soil moisture and greenness index contributed significantly to explain the variation in ecosystem respiration (Reco) while active layer depth, soil moisture and greenness index best explained CH4 emissions. Estimate of temperature sensitivity of Reco and gross primary productivity showed that a modest increase in air temperature of 1 degree did not significantly change the NEE during the growing season but that the annual NEE would be even more positive adding another 8.5 gC m-2 to the atmosphere. We tentatively suggest that the warming of the Arctic that has already taken place is partly responsible for the fact that the moist moss tundra now is a source of CO2 to the atmosphere.

Using the CAM-chem Model, we simulate the response of chemical species in the free troposphere to changes in emissions of primary pollutants during the COVID-19 pandemic. Zonally averaged ozone concentrations in the free troposphere during Northern Hemisphere spring and summer were 5 to 15 % lower than 19-year climatological values, in good quantitative agreement with ozone observations. About one third of this anomaly is attributed to the drastic reduction in air traffic during the pandemic, another third to reductions in surface emissions, the remainder to 2020 meteorological conditions, including the exceptional springtime Arctic stratospheric ozone depletion. The overall COVID-19 reduction in mean northern hemisphere tropospheric ozone in June is less than 5 ppb below 400 hPa, but reaches 8 ppb at 250 hPa. In the Southern Hemisphere, COVID-19 related ozone reductions by 4 to 6% were masked by comparable ozone increases due to other changes in 2020.

Progress in fundamental understanding of atmospheric chemistry in the past decades has enabled the development of advanced environmental predictive capability. Accurate chemical weather forecasts and source attribution information can play a decisive role in mitigating the exposure of the public to acute air pollution episodes in the short-term. Chemical climate projections will allow investigation of the long-term consequences of human choices and their impact on the future evolution of the Earth system. This commentary stresses the importance of integrating atmospheric chemistry in operational environmental prediction and projection systems.

Lithospheric slab breakoff can occur in various styles including a horizontal ‘tearing’, where an initial weakness develops into tearing and laterally propagates along the slab. Slab tearing has been invoked to explain changes in plate kinematics in the Western Mediterranean and the tectonic uplift that led to the Messinian Salinity Crisis. However, this process remains debated regarding its surface signature and the physical parameters controlling its initiation and dynamics. Here, we use 3D thermo-mechanical modelling to investigate geodynamic parameters affecting the slab-tearing initiation and its lateral propagation, and to quantify the corresponding surface vertical motions. We find that an oblique convergence introduces an asymmetry that favors the initiation of one-sided slab tearing. The tectonic configuration of the overriding plate has little effect on the trench migration rate, and slab tearing can results purely from the negative buoyancy of the subducted slab. This force and the slab retreat it causes are enough to generate an arcuate plan-view shape to the orogen. The slab-tear propagation rate varies from 37-67 cm/yr. During propagation, the slab tearing depth increases along the subducting slab, with a shallow initial tear (80-150 km) and a deeper tear (170-200 km) on the opposite end. The time needed for the slab to detach completely is geologically fast (<2 Myr). The slab tearing can cause a prominent surface uplift of 0.5-1.5 km throughout the forearc region with an uplift rate of 0.23-2.16 mm/yr, which is consistent with the situation during the first stage of the Messinian Salinity Crisis.