The 10-11 May 2024 superstorm is the largest geomagnetic event since March 1989. This work focuses on the analysis of a severe negative ionospheric storm that occurred in American/Atlantic region on 11 May. The vertical total electron content (VTEC) dropped by 75 TECU below the quiet-time values, which represents extreme storm-time deviations. Our analysis shows that the May 2024 negative ionospheric storm was the most significant out of 6 strongest superstorms that occurred in 2000-2004. This also means that the 11 May negative storm was one of the strongest ever observed by the GPS/GNSS-sounding. The remarkable VTEC drops were produced by a combination of strong downward equatorial ExB drifts and decreases in the thermospheric composition. The recovery phase was also marked by the occurrence of vortex-like VTEC enhancements that repeated the O/N2 increases, however, the dynamics of the VTEC patches and vortices significantly differs from that of the O/N2 structures. Plain Language Summary On 10-11 May 2024, a major geomagnetic storm occurred on Earth. It significantly affected the dynamics of the Earth's atmosphere and ionosphere. In this work, we use measurements from ground-based GNSS receivers and we show that this geomagnetic storm caused extreme negative deviations in the ionospheric vertical total electron content (VTEC). The VTEC drops reached-75TECU, which is one of the strongest deviations ever observed since the beginning of the ionospheric GPS/GNSS era. Further analysis revealed that such a strong negative storm was caused by storm-time changes in the equatorial electrodynamics and that in the thermospheric composition. In addition to the extreme negative storm, we observed the occurrence of vortex-like and patchy VTEC enhancements that resembled the increases in the thermospheric O/N2 ratio. Further analysis showed that the lifetime of the thermospheric O/N2 and the corresponding VTEC structures is different: while the composition alters very slowly, the VTEC can changes very rapidly. Key-points:-on 11 May 2024, a spectacular dayside negative ionospheric storm occurred at middle and low-latitudes-the formation of major VTEC drops of-75 TECU is attributed to downward ExB drift and vortex-like decreases in the thermospheric O/N2 ratio-thermospheric composition changes are also responsible for the occurrence of vortexlike increases in the VTEC

We present a physical and computational analysis of the flocculation of suspended cohesive particles in turbulence by one-way coupling. Our numerical method can separately consider the cohesion, lubrication, and direct contact forces for each pair of particles, thereby allowing us to conduct a detailed analysis of their influence on the flocculation process in turbulence. We first test the numerical approach in the two-dimensional cellular flow which consists of Taylor-Green vortices and investigate the binary interaction of cohesive particles. Further, we numerically investigate the flocculation of suspended cohesive particles with significant surface roughness in homogeneous isotropic turbulence and analyze the temporal evolution of the average sizes. Stronger cohesion and weaker turbulent shear yield larger flocs. The increase of the Stokes number limits the growth of flocs. The influence of the particles' roughness on flocculation is compared. Larger roughness yields a smaller equilibrium floc size while it does not affect the flocculation rate.

 On October 8, 2023, between 18:50 and 22:00, a cluster of earthquakes occurred near Torishima Island, and a tsunami advisory was issued for the surrounding areas. Previous studies showed that the main source of this tsunami was an uplift near the Sofugan volcano and the tsunami could be simulated by the summation of the multiple sources over time. To clarify the seismic mechanism of this volcanic activity, we performed the seismic waveform inversion and cross-correlation analysis. We obtained the source time function of the 13 repeated earthquakes and found that the source mechanism of the tsunamigenic event was a force symmetric about the vertical axis, such as single-force, isotropic, or vertical CLVD mechanisms. We also found that there were low-frequency harmonic signals between earthquakes, which do not come with clear body waves. We interpreted these signals with a caldera collapse and resonance at the magma reservoir. The repeated earthquakes can be interpreted as the vertical movement of the rock column, supplying magma to the magma chamber and causing the uplift of the caldera floor that excited tsunamis. The harmonic signals between earthquakes may be the resonance at the magma reservoir associated with the magma migration. We assumed that the edifice subsided slowly between earthquakes and repeated this inflation-deflation cycle along with the earthquakes.

The distance over which planktonic larvae are dispersed and the variability within that dispersal distance are important for understanding gene flow and persistence of species with planktonic larvae in the coastal ocean. The breadth of spatial and temporal scales that can be important to dispersal in shelf seas makes direct observations of larvae, and thus these statistics difficult - instead, we often use numerical simulations of circulation to estimate the statistics of larval dispersal. However, meroplanktonic life histories are most common in coastal regions where drifter-based estimates of circulation are sparsely distributed, making validation of these numerical simulations quite difficult. We use a novel technique to validate climatological mean and standard deviation of dispersal distance at a global scale by drawing on the tens of thousands of sparsely distributed drifter observations on the shelf. Numerical dispersal estimates were made using Lagrangian particle trajectories calculated with circulation fields from a 1/12{degree sign} global physical model and were validated against drifter data from the Global Drifter Program (GDP). The median dispersal distance of a climatological ensemble of numerical drifters released from a single location were found to match GDP drifter estimates quite well (with a mean deviation of 0.2%), while model estimates of dispersal were shown to underestimate the diffusivity of GDP drifters by 30 to 50%. Our results indicate that while global numerical estimates of dispersal statistics provide a close approximation of median dispersal distance in the coastal ocean, these numerical simulations underestimate the overall variation present in the coastal ocean.

While melt-driven occurrence of supraglacial water is largely recognized, an essential but over-looked component of supraglacial water appearance is glacial dynamics and their interaction with hydrological drainage systems. ICESat-2 ATLAS data record returns from water features, which requires an automated method for detection and depth measurement. We introduce second-order Density-Dimension algorithms (DDA-ice) that facilitate detection of water in crevasses and melt features. Density characteristics from the DDA-ice allow identification of cryospheric material types such as snow, water-logged firn and water in crevasses. Application of the DDA-ice-2 to data from the surge of Negribreen, Svalbard, yields key informants on englacial hydrological changes that control the surge process, but are hard to detect other- wise. Analysis of melt ponds and streams on the Greenland Ice Sheet and the Amery Ice Shelf illustrate the capability of the DDA-bifurcate to extract complex morphological shapes, a characteristic that suggests application in morphogenesis of glacio-hydrological features.

This study presents first probability hazard maps of the areas potentially affected by ballistic fallout from major explosions and paroxysms at Stromboli (Italy), based on mathematical analyses of the extensive historical and recent records of its explosive activity. The novel approach develops and integrates three statistical models that describe ballistic fallout patterns under different assumptions and considering the associated uncertainty. Model 1 mirrors the areas observed to be affected in the past, with major explosions displaying NE and SE asymmetries, while paroxysms show NE and mostly WSW predominant dispersal. To address likely data under-sampling and morphological and dynamics changes, Models 2 and 3 assume independency between ballistic distance and dispersal direction. By combining these models, robust and conservative ballistic fallout hazard maps are produced for major explosions and paroxysms, considered as separated categories, as well as for the two categories combined together by assuming a relative proportion. The new combined maps allow highlighting the most exposed areas of the island and quantifying the probability to be affected in case of event. For instance, the NE trails at 600 m are affected with ≈25% probability and the viewpoints at 400 and 290 m a.s.l. on Labronzo trail with ≈8% and 5% probability, respectively. Remarkably, the entire village of Ginostra is affected with ≈3% probability. Notably, ballistic fallout probability contours are moderately influenced by mapping uncertainties and by the assumed proportion between major explosions and paroxysms. These findings open the way to individual and societal risk assessments for this phenomenon at Stromboli.

Previous assessments of Numerical Weather Prediction (NWP) systems have shown that reanalysis data sets exhibit consistency with the observed climate but tend to be biased, especially at a local scale. In this study, we present a thorough approach to assessing the accuracy of the European Center for Medium‐Range Weather Forecasts, Reanalysis 5 (ERA5) data set compared to low-cost weather stations (Meter ATMOS stations) deployed widely across Kenya as part of the TAHMO weather network.We compare ERA5's performance on temperature (in degrees Celsius) and precipitation (in millimetres) measurements to that of 62 low-cost stations in Kenya for the year 2023. Our assessment performs a detailed comparison of ERA5 reanalysis weather data to the quality-controlled ground truth data from the low-cost weather stations, focusing on error rates and distributions. The detailed data comparison examines the comparative performance of ERA5 and the low-cost stations categorised by distance from the WMO stations within the same climate zones.The Pearson correlation coefficient between the Mean Squared Error (MSE) and the distances is 0.43. An example of the MSE computed for one year on the ERA5 and low-cost station, TA00453, is 23.09 for temperature and 0.44 for precipitation. The moderate correlation between error and distance suggests that as the distance between the weather stations increases, the prediction error also tends to increase, but not in a strong or perfect linear relationship. This could imply that ERA5's accuracy decreases with increased distance from the WMO stations, but other factors could also contribute to the error.Exploring scenarios where low-cost stations complement ERA5 could potentially enhance local weather predictions. Integrating low-cost weather stations with large-scale NWP models like ERA5 can improve the granularity and accuracy of local weather predictions, addressing biases at a local scale and providing more reliable data for various applications.

The number of objects orbiting the Earth will significantly increase with the deployment of large constellations of small satellites, along with the launch infrastructure needed to support it. Upon reaching the end of service life, most satellites and upper stages of launch vehicles in low-Earth orbit (LEO) burn up during reentry in the mesosphere. This high-altitude influx of chemical species such as Aluminum, which is dominant in aerospace structures, raises questions about the long-term impacts of burning anthropogenic objects during atmospheric reentry. The polluting potential of the said activities encompasses fluctuations in radiative forcing, impacts in ice nucleation, cloud condensation, and stratospheric ozone concentrations. We present a methodology that resorts to large-scale Molecular Dynamics simulations to infer the behavior upon reentry of a typical small satellite with an Aluminum-rich structure. As a first-principle informed method for modelling physical and chemical interactions, it allows to preform simulations of increasingly larger domain sizes at atomic scale, emulating the behavior of up to hundreds of thousands of atoms to compute the oxidation yield and particle size distribution. The full-scale scenario results are inferred from the atomic scale, showing that the byproduct particle size follows a lognormal distribution centered in the nanoparticle regime (nucleation/Aitken mode).This tool can provide more accurate inputs to atmospheric models aiming at estimating the global impact of reentries from LEO in the atmosphere. The use-case is focused in the oxidation of Aluminum upon reentry, and forecasts are made and compared against the contribution from micrometeoroids entering atmosphere.

A document by Parnia Shokri. Click on the document to view its contents.

Enhanced rock weathering (ERW) is an innovative geoengineering approach that involves spreading finely crushed silicate minerals on agricultural lands to accelerate natural weathering processes, promoting the sequestration of atmospheric CO₂. ERW presents significant potential for CO2 removal (CDR), with proposed global estimates reaching gigatons of CO2 removed per year. For some soils, application of silicate minerals may improve soil fertility by releasing essential nutrients reducing chemical fertilizer expenses. Pulverized rock applications are predicted to enhance infiltration and water holding capacity of certain soils by modifying soil texture. Additionally, ERW is relatively simple to incorporate into typical agricultural operations, and examples of early adoption are increasing. Despite its promising potential, several challenges must be addressed to fully realize the benefits of ERW, particularly in irrigated systems in mediterranean, semi-arid climates such as California. Key concerns include environmental impacts of mining and processing minerals, transportation logistics, and the economic viability of large-scale implementation. Fundamental research is needed into ERW mechanics under varying soil, cropping system, irrigation and fertilizer use conditions, and we need robust, cost-effective measurement methods of ERW rates to validate CDR and ensure it significantly outweighs CO2 emissions incurred during production and transport. Furthermore, addressing uncertainties about impacts on critical soil quality parameters such as soil organic carbon, aggregate stability, and water availability is critical in semi-arid, carbon-poor soils such as those throughout California. Few field-scale ERW efforts have been reported to date, and mostly in humid, rainfed management systems; here we present implementation and evaluation lessons from a California-wide ERW research/pilot project and insights from recent efforts to formulate guidelines for ERW implementation.

We investigate the NW-SE basement trends of the U.S. Midcontinent, often cited as Proterozoic in age. From a reduced-to-pole magnetic anomaly map, we map basement lineaments over an area of ~1.48 million km2. We compile published Ediacaran-Ordovician radiometric dates of intrusive rocks that suggest a deep crustal/mantle magma source for this time. Dolomite from one core provides one higher precision U-Pb date of 462 {plus minus}15 Ma and several lower precision dates that overlap this age range. Fluid inclusion, carbon, oxygen, and strontium isotope data indicate hot fluids were injected from deep in the basement relatively early in the Paleozoic. Even though the area has been structurally overprinted by late Paleozoic and later deformation, compilation of regional stratigraphic and structural data points strongly to widespread deformation in the latest Proterozoic to early Paleozoic. Taken together, these data indicate that the NW-SE basement trends are long-lived leaky transform faults associated with Iapetan rifting during the Ediacaran-Ordovician. These transform faults are interpreted as transtensional in part and leaky with respect to both magmatic emplacement and hot fluids from deeper in the basement. Our findings suggest a new model for the tectonic evolution of the U.S. Midcontinent, based on changing stress fields as subduction progresses south into Iapetus. This has implications for the origin of zones of weakness that are reactivated later, the distribution of aulacogens versus transforms, and the tectonic underpinnings of ore minerals deposited concurrently with the active faulting as well as oil and mineral deposits formed during their later reactivation.

Flood early warning systems are crucial for disaster risk reduction strategies, enabling communities to take timely action against threats. However, the effectiveness of these systems depends on accurate and timely hydrological data, particularly river discharge and water level measurements. Unfortunately, many regions face significant challenges in obtaining hydrological data, especially discharge data, due to outdated rating curves, high equipment costs, and logistical constraints. In contrast, water-level measurements offer reduced uncertainty and are often more accessible, providing an alternative to hydrological modeling in data-scarce regions. To address these limitations, we developed and validated the Discharge-to-Water Level Transformation (DWLT) method, which uses the monthly duration curves to transform discharge simulations from the GEOGLOWS ECMWF Global Hydrological Model into water level predictions using data from over 19,000 ground- and satellite-based river gauge stations. The results indicate that the water levels generated by DWLT are closely aligned with the observed water levels, especially when using satellite measurements, which offer a valuable alternative when ground-based data are scarce. Despite quality issues such as spikes and zero-level inconsistencies in ground-based data and temporal limitations such as short monitoring periods and infrequent measurements in satellite-based data, the methodology shows promising potential for large-scale and local hydrological applications. This work supports future flood forecasting and water resource management efforts, highlighting water level as an effective variable in hydrological modeling.

Marine oxygen deficient zones (ODZs) play a major role in the Earth’s biogeochemical cycles and are responsible for nitrogen and sulfur removal from the oceans. Microbial-reducing reaction processes generate nitrite (NO2-) and sulfur compounds as intermediaries that may accumulate in these zones. Current assessments on microbial transformations inside ODZs are based on shipboard measurements, and there are no well-resolved seasonal to annual observations or high-resolution vertical sampling that would characterize variability. Here, we propose an alternative statistical approach to analyze the raw output of the nitrate sensor from BGC-Argo floats, with the ability to detect NO2- and thiosulfate (S2O32-) concentrations in addition to nitrate. The new approach provides data with great vertical and spatiotemporal resolution. The method can be applied to UV-spectrometer output data from SUNAs and ISUS nitrate sensors, commonly deployed on various observing platforms. We validated the technique in the field by matching shipboard NO2- bottle data with float data from the eastern tropical North Pacific (ETNP) and eastern tropical South Pacific (ETSP) ODZs. We then show a complete time series of three floats as study cases. The ability to detect NO2- and S2O32- concomitantly with other key chemical variables (i.e., oxygen, pH, and bio-optics) at such fine scale allows for novel insights into the nitrogen and sulfur cycling of ODZs and processes driving these cycles. This new approach will enable fine-scale remote quantification of NO2- and S2O32- to support a better understanding of the biogeochemical transformations happening inside these already-expanding deoxygenated regions.

The seasonal variability of phytoplankton vertical distribution is investigated in the South Pacific where observations are scarce and scattered. We used 13 BioGeoChemical-Argo floats deployed across diverse oceanic environments. The seasonal latitudinal displacement of the Tasman front induces transitions from mesotrophic to oligotrophic conditions. This shift results in Chlorophyll-a concentration vertical distribution changing from bloom types to Subsurface Chlorophyll Maxima (SCM) types, with intermediate hybrid types between these extremes. Such hybrid profiles frequently occur in the equatorial Pacific, highlighting a large-scale pattern rather than local island mass effect. In oligotrophic regions, seasonal variations of light availability and stratification dynamics below the mixed layer likely relate SCMs to an increase in carbon biomass or photoacclimation. A biomass increase is frequently observed, contrary to previously reported, suggesting that subsurface phytoplankton production may have been largely underestimated. This calls for further observations of the water column in these remote undersampled open ocean areas.

The GEO SERVICE program, supported by the NSF GEOPAths STEM Education Grant, aims to inspire and prepare the next generation of geoscientists through immersive, community-focused service-learning projects. Targeting 8th-12th grade and early undergraduate students, our program addresses local environmental issues such as coastal wetland loss and flooding in south Louisiana and along the Gulf Coast, fostering sustained interest in STEM careers through practical, career-relevant experiences. Central to our approach is the integration of hands-on learning with real-world applications. For instance, the "Rising Waters" summer workshop engages students in remote sensing and urbanization studies using kites, drones, and satellite imagery. Students develop digital Story Maps, honing skills in data interpretation, communication, and project planning. These activities enhance geoscience literacy and empower students to present their findings to peers and community members, reinforcing their understanding and engagement. The Regional Application Center’s Natural Disaster Geospatial Data Mining Workshop further supports our educational mission by promoting spatial literacy and workforce readiness. These workshops connect students with industry experts and provide hands-on training, eld experience, and internship placements, bridging the gap between academic learning and professional practice. Our outreach initiatives include interactive educational tools and activities, such as the NASA AEROKATS kite and STELLA program, which teach students about geoscience concepts through active learning and data collection. Programs like Fly High 4 Geo, tailored to diverse cultural and geographical contexts, further our goal of promoting geographic education. Through collaborations, we are able to offer personalized learning experiences, making geoscience relevant and engaging for students from various backgrounds. This presentation will highlight the structure, activities, and outcomes of our programs, demonstrating their impact on student recruitment and retention in geosciences. By addressing workforce needs and improving geoscience literacy, we aim to bridge the gap from education to careers in STEM elds, contributing to a more informed and skilled geoscience workforce.

Knowledge of soil thermal conductivity is critical for understanding geophysical and biogeochemical processes in the subsurface. This study describes and evaluates a new measurement technique that provides rapid, depth-resolved measurements of soil thermal conductivity without digging a soil pit. Quick thermal profiling (QTP) interprets the passive thermal equilibration of a temperature probe after it is inserted in soil. Temperature is recorded simultaneously at 5-centimeter depth intervals down to 75 centimeters, providing vertically resolved data. Soil thermal properties are probabilistically estimated using a finite volume model simulating heat transfer and a gridded search inversion method. The use of prior soil properties measurements to constrain the inversion is also assessed. Field tests on the Seward Peninsula (Alaska, USA) indicate that the QTP estimates of thermal conductivity correlate significantly with in-situ measurements using a thermal properties analyzer (R2 = 0.56, n = 22). In addition, the vertical change in thermal conductivity enables estimates of peat layer thickness that correlate with visual observation from soil pits (R2 = 0.76, n = 10). QTP tends to underestimate thermal conductivity compared against a thermal analyzer (slope = 0.633), though estimates in peat soil layers are more accurate than those in a deeper silty mineral soil layer. The uncertainty of QTP conductivity estimates is found to arise from non-uniqueness in the solution space, as well as from discrepancies between field conditions and the heat transfer model. Overall, QTP presents a promising pathway for the future development of quick, depth-resolved soil thermal conductivity measurement techniques.

Ocean eddies are crucial around the Antarctic margin and there is evidence that they facilitate cross-slope flow of warm water, potentially contributing to ice shelf melt and accelerating sea level rise. However, because eddies around Antarctica are smaller than in other parts of the ocean, these eddies are also more difficult to observe and model. Here we compare the representation of eddies around the Antarctic continental margin in ocean-sea ice models at two different resolutions (1/10⁰ and 1/20⁰), and examine their link to local circulation features. Compared to the 1/20⁰ model, the 1/10⁰ resolution model has stronger shelf currents, especially in East Antarctica, but lower eddy kinetic energy (EKE). On a seasonal timescale, sea ice, EKE and current strength co-vary, with strong correlations on the shelf between current strength and EKE. Current strength and EKE both exhibit prominent seasonal hysteresis, where winter sea ice growth precedes a decline in EKE and current strength, and springtime sea ice decline leads an increase in EKE and current strength. The seasonal link between eddy energy, sea ice and current strength is stronger on the continental shelf than on the slope, and is amplified under higher model resolution. Given how strongly sea ice modulates eddy growth in higher resolution models, a decline in sea ice extent under climate change could greatly increase the projected EKE in models, which could have implications on cross-slope heat transport and thus Antarctic ice shelf melting.

Ocean ventilation, or the transfer of tracers from the surface boundary layer into the ocean interior, is a critical process in biogeochemical cycles and the climate system. Here, we assess steady-state ventilation patterns and timescales in three models of ocean transport: a 1º global configuration of the Nucleus for European Modelling of the Ocean (NEMO), a recent 2º solution of the Ocean Circulation Inverse Model (OCIM), and a 2º solution of the Total Matrix Intercomparison (TMI). We release artificial dyes in six surface regions of each model and compare equilibrium dye distributions as well as ideal age distributions. We find good qualitative agreement in large-scale dye distributions across the three models. However, the distributions indicate that TMI and OCIM are more diffusive than NEMO. A shallow bias of North Atlantic ventilation in NEMO contributes to a stronger presence of the North Atlantic dye in the mid-depth Southern Ocean and Pacific. This isopycnal communication between the North Atlantic surface and the mid-depth Pacific is very slow, however, and NEMO simulates a maximum age in the North Pacific about 900 years higher than the data-constrained models. Overly slow North Pacific ventilation persists across NEMO sensitivity experiments encompassing our current best knowledge of diapycnal and isopycnal mixing, pointing to biases in subarctic Pacific dynamics. This study provides a synoptic picture of global ocean ventilation and a framework for assessing its representation in general circulation models.