Using a substorm onset list from the Imager for Magnetopause to Aurora Global Exploration (IMAGE) and Polar satellite images, we have constructed a new dataset of 63 substorm onsets observed in both hemispheres and their locations. We find that incorporating the history of the interplanetary magnetic field (IMF) improves the predictive power of IMF By in explaining conjugate displacement in Magnetic Local Time (MLT). Our dataset, approximately five times larger than in previous studies, enhances statistical power and focuses on the substorm onset feature. This allows for better correlation of IMF By with MLT conjugate displacement (ΔMLT), since it has been shown that IMF-induced By tends to diminish as substorms progress. In line with previous work, we find a linear relationship between IMF By and ΔMLT, though with a shallower gradient. Additionally, we analyse predictors of conjugate displacement in Magnetic Latitude (ΔMLat), showing that dipole tilt (ψ) is the strongest predictor. However, we find that this relationship is not strictly linear, and that a larger dataset and a better understanding of the physical mechanisms are needed to more accurately capture the exact functional relationship between ψ and ΔMLat.

This report highlights the complex interplay between cardiac func8on, metabolic disorders, and the impact of Oshtoran Syndrome on overall health. Par8cular emphasis is placed on the implica8ons of a le? ventricular ejec8on frac8on (LV-EF) decline, PDH cytopathy, and the resultant metabolic dysregula8on. Addi8onally, the cri8cal role of catecholamine suppression in preven8ng poten8ally life-threatening episodes is discussed. Introduc/on: Oshtoran Syndrome (H63D Syndrome Type-3) presents a mul8faceted clinical challenge, characterized by both cardiac and metabolic complica8ons. This report examines the deteriora8on in cardiac func8on, the metabolic impact of PDH cytopathy, and the systemic effects observed in a pa8ent with this syndrome, along with the essen8al role of catecholamine suppression. 1,4,5 Cardiac issues: Le? Ventricular Ejec8on Frac8on (LV-EF): The pa8ent's LV-EF has decreased from 63% to 49%, indica8ng a significant impairment in the heart's ability to pump blood and oxygen efficiently. This decline reflects a compromised cardiac func8on, likely contribu8ng to systemic hypoperfusion and metabolic stress. 9,10,11,12

A document by Jingwei ZHANG. Click on the document to view its contents.

Ocean-bottom seismic acquisitions are gaining widespread popularity for various subsurface applications. However, the high cost of these systems often necessitates receiver geometries with large intervals between ocean-bottom cables or nodes. The upside-down Rayleigh-Marchenko (UD-RM) method has been recently proposed as an effective solution for accurate redatuming and imaging of sparse seabed data. In this paper, we present the first successful application of the UD-RM method to field data. We demonstrate that in the presence of a shallow seabed, an improved data pre-processing workflow is necessary to generate more accurate input wavefields than those produced by the workflow in the original paper. To validate the proposed processing workflow, the UD-RM method is initially tested on a synthetic dataset mimicking the Volve field data, followed by its application to a 2D line of the Volve ocean-bottom cable dataset. Subsequently, the field dataset is subsampled by retaining only 25\% of the total receivers to numerically validate the UD-RM method’s capability to handle sparse receiver arrays. The resulting images reveal that the UD-RM method, when paired with our enhanced data processing workflow, can effectively handle surface-related multiples, internal multiples, and sparse receiver arrays, producing accurate imaging results without the need for costly and labor-intensive multiple removal processes. Finally, we provide theoretical insights and numerical evidence supporting the necessity of source-side deghosting prior to redatuming. While a pre-processing workflow that omits source-side deghosting can offers some practical advantages, we show that this ultimately produces blurrier images compared to those obtained using source-side deghosted input data.

Fine particulate matter (PM2.5), with a diameter of 2.5 micrometers or smaller, presents a significant health risk due to its ability to penetrate deeply into the lungs and enter the bloodstream. Conventional exposure assessments often overlook critical factors such as individual movement patterns and spatial variability in pollution, leading to less accurate exposure estimates and masking disparities in vulnerable populations. This study introduces an innovative spatial-temporal agent-based modeling (ABM) approach to capture detailed exposure dynamics within urban airsheds, using the Pleasant Run Airshed in Indianapolis, IN, as a case study. By integrating data from 23 PM2.5 sensors, meteorological variables, and land use data, we modeled PM2.5 concentrations over 50 weeks and simulated exposure for 10,000 virtual agents grouped by susceptibility, reflecting varying levels of health vulnerability. Our results reveal marked exposure disparities across sociodemographic groups, with high-susceptibility agents experiencing significantly greater health impacts. The spatial analysis identifies high-exposure zones near industrial areas and transportation corridors, underscoring the urgent need for targeted environmental justice interventions. This study demonstrates ABM’s potential to capture spatial-temporal exposure variability and illuminate inequities in pollutant exposure, offering critical insights for public health policy to reduce environmental health risks. Future research should explore combining ABM with multi-pollutant analysis to comprehensively address complex urban air quality challenges and promote equitable health outcomes.

Campylobacter is the most common bacterial cause of foodborne illness globally. Both symptomatic and asymptomatic infections with Campylobacter species have been associated with growth faltering of children in low-resource settings, while previous prevalence studies primarily focused on diarrheal disease in children. Here, we leverage the data collected from the Campylobacter Genomics and Environmental Enteric Dysfunction (CAGED) project to characterize the spatial patterns of Campylobacter infections among infants with or without diarrhea in rural Eastern Ethiopia. Randomly enrolled infants (n = 106) were followed from birth to around 13 months, with fecal samples collected monthly. Livestock, drinking water, and soil samples were collected biannually. Campylobacter was detected and quantified using genus-specific PCR and species-specific PCR for four species. We employed a spatial filtering approach using genus-specific data to generate smoothed prevalence surfaces by month and age group. Temporally, an upward trend of prevalence was observed as the children grew older. Spatially, high-prevalence areas were distributed across the whole study area. To relate disease risk to environmental conditions, we used ecological niche modeling with MaxEnt to estimate habitat suitability of the genus Campylobacter and two dominant species identified by PCR results. Elevation, vegetation index, and slope were the most important contributors, and all distribution models suggested areas in the north were more likely to support the pathogen. These results inform Campylobacter infection patterns and identify target areas with higher risk of Campylobacter in low-resource settings. This further contributes to developing effective intervention strategies in the future.

A document by Hirohiko Masunaga. Click on the document to view its contents.

High-latitude frozen soils contain a vast store of organic matter, a potential source of greenhouse gases due to permafrost thaw. Understanding natural carbon cycle responses to climate change is crucial for emission reduction strategies. We use the Max Planck Institute Earth System Model, driven by the Adaptive Emission Reduction Approach (AERA) and accounting for the impact of frozen soil carbon (FSC), to assess emission pathways and remaining emissions budgets for limiting global warming to 2°C and 3°C relative to preindustrial levels. We found that thawing FSC adds 122 PgC under 2°C and 229 PgC under 3°C warming, available for decomposition in active layer, with about 75% reaching the atmosphere as carbon-dioxide by 2300. Emission pathways that include the release of FSC diverge from their respective reference simulations without permafrost by the middle and end of the current century. By 2300, remaining budgets are reduced by ~13% (115 PgC) for 2°C and ~11% (156 PgC) for 3°C stabilization levels. Annual permafrost emissions average ~0.7 PgC/yr for 3°C and ~0.3 PgC/yr for 2°C scenarios. However, temporary emission peaks reaching half of present-day annual fossil fuel emissions (~5 PgC) are possible. Surprisingly, while negative emissions are required for both reference simulations, only the simulation for the 3°C warming, accounting for FSC, requires negative fossil fuel emissions. This occurs because the FSC release causes an earlier initiation of emission reduction by AERA, resulting in a smoother emission curve. These findings underscore the importance of factoring in permafrost thaw in mitigation action.

Geocoronal Solar Wind Charge Exchange (SWCX) is the process by which heavy ions from the solar wind undergo charge exchange with neutral hydrogen atoms from the Earth’s exosphere, releasing photons at discrete energies characteristic of the solar wind ions. This paper investigates the solar wind types driving geocoronal SWCX. We find that during periods of time-variable SWCX, higher fractions of every ion species are recorded by ACE compared to the averages. Notably, a subset of the slow solar wind characterised by a systematic lower temperature and higher proton flux is surprisingly effective for producing SWCX. Given the degradation of the solar wind composition spectrometer on ACE in 2011, we explore the capabilities of XMM-Newton as an alternative sensor to monitor heavy ion composition in the solar wind. Unlike the distributions of other ion line fluxes analysed, only OVIII, extracted via spectral analysis of XMM-Newton observations, display patterns similar to the corresponding parent ion abundances from ACE (O8+/p). Finally, we employ a Random Forest Classifier model to predict solar wind types based on literature results. When combining proton data with XMM-Newton features, the model performance improves significantly, achieving a macro-averaged F1-score of 0.80 (with a standard deviation of 0.06).

During the Asian Summer Monsoon Chemical and Climate Impact Project (ACCLIP), National Aeronautics and Space Administration (NASA) WB-57 high altitude research aircraft observed strong turbulence at an altitude of 15 to 18 km near the outflow of the Super Typhoon Hinnamnor in the Northwest Pacific. Our analyses based on the trial version of the “RRJ-ClimCORE” mesoscale reanalysis have revealed that a thin layer of strong vertical wind shear (VWS) extending just below the tropopause along the upper surface of the outflow from the typhoon eyewall provides favorable conditions for shear instability. Further analyses of the mesoscale background conditions based on RRJ-ClimCORE as well as the geostationary satellite Himawari-8 cloud imagery suggest that the convolution of such small-scale processes as convectively generated concentric gravity waves and shallow convection appearing as radially-banded cirrus clouds may have further increased the potential for turbulence generation. Absolute vorticity analysis suggests the occurrence of inertial instability to the north of the typhoon, which explains the development of radially-banded cirrus clouds as well as the layer of strong VWS around the flight altitudes. The present study thus demonstrates the advantages of the hourly output of RRJ-ClimCORE over 3-hourly output operational mesoscale analysis for investigating source mechanisms of turbulence in the upper-troposphere and lower-stratosphere.

The forward simulation of radar reflectivity requires details of clouds and precipitation from general circulation models (GCMs). But such details are represented as sub-grid processes that involve parameterizations and assumptions about the spatial coverage and thus depend on the GCM. In this research, we propose the use of a statistical method to generate sub-grid precipitation for generic use. In addition, the proposed method can be used to provide uncertainty estimates on the signals. The sub-grid variability is obtained from simulation with a global storm-resolving model called NICAM (non-hydrostatic icosahedral atmospheric model). The proposed method first generates precipitation probabilities for the possible scenarios and then sub-grid precipitation rates are generated from the generalized gamma distribution for the given cloud fraction and grid-scale precipitation rates. Compared to the standard method (which neglects the probabilities) that overestimates the precipitation fraction, our method well reproduces the NICAM dataset profiles of both the precipitation fraction and the radar-based cloud fraction. The in-cloud signal frequencies are also reproduced, although less accurately over a tropical region. Inclusion of sub-grid variability in precipitation rates was particularly important for the tropical region to obtain agreement of the precipitation fraction. Application of the two methods to a GCM shows it to have a robust bias for low-level liquid clouds. The proposed method can be used to identify uncertainty in the signals associated with sub-grid variability in the precipitation processes, indicating an effective way to use a global storm-resolving model to evaluate conventional GCMs.

The knowledge of the composition and dynamics of eruption columns is very important because tephra dispersal strongly depends on it. Few measurements on the vertical distribution of volcanic particles within the eruption column are available. In this work, we analyze data from the X-band radar that were located 75 km far from the crater of Grímsvötn (Iceland) during the eruption in 2011 and propose a first attempt to characterize how the mass eruption rate and the particle size are distributed within the eruption column. We find that both quantities are not uniformly distributed along it. In particular, a greater percentage of particle size and mass eruption rate is confined in the convective region with respect to the umbrella region. We think that this work can make new advancements in the characterization and dispersal of explosive eruptions.

There is a lack of consensus on how tropical cyclone outer winds may change, if at all, due to extratropical transition. Hence, this study examines changes in North Atlantic tropical cyclone outer size and structure using a large, multidecadal sample of cases from reanalysis data. These results suggest that tropical cyclone outer size and structure typically remain unchanged until after extratropical transition end. In those minority of cases with strong outer size growth during extratropical transition, increases in tropical cyclone outer winds begin first in the lower troposphere during ET and build upwards over time. This broadening of the azimuthal-mean outer winds is also associated with an increasingly asymmetric outer wind field with the strongest winds concentrated downstream of the tropical cyclone. These storms that grow most strongly during transition are typically smaller at transition start and eventually become embedded in more strongly baroclinic environments before extratropical transition end.

During the summer of 2022, a record-breaking heatwave-drought (DH2022) hit southern China, especially in the middle and lower reaches of the Yangtze River basin (MLYR). However, its impact on regional carbon budget remains unclear. Here, we assessed the response of regional terrestrial carbon fluxes to DH2022 using Global Carbon Assimilation System (GCASv2) by assimilating OCO-2 XCO2 retrievals. Our results show that compared to 2015-2021, MLYR experienced a clear reduction in carbon uptake by 45.8 TgC (44.1%) during July-September in 2022. However, the total annual carbon sink in southern China increased by 42.8 TgC. This is due to a warm and wet spring, leading to an increase in carbon sink by 50.8 TgC and greatly compensating for the carbon losses. Our study provides a comprehensive assessment of land carbon dynamics in southern China under the influence of DH2022, enhancing understanding of the impacts of climate extremes on the regional carbon cycle.

The assessment of volcanic hazards is crucial to develop effective emergency plans, especially for volcanoes close to urban centers or under air traffic routes. Impact assessment relies on underlying numerical codes that require eruptive source parameters as input and forecasts drastically depend on their robust reconstruction during ongoing events. We apply a novel deposit inversion workflow built on ensemble methods and data assimilation techniques to reconstruct the explosive events that occurred at Mt Etna, Italy, between 3 and 5 December 2015. Based on results from previous studies, we reconstruct this eruption using the Gaussian with Non-negative Constraints data assimilation method. Results agree well with independent observations and highlight the potential for automatized procedures in volcanic hazard assessment.

Mirror mode structures are born from a plasma instability driven by a large temperature anisotropy and appear downstream of planetary and interplanetary shocks, in their magnetosheath. As magnetic bottles imprisoning dense and hot plasma, they are usually observed downstream of their region of formation, where the anisotropy is large and free energy is available, implying that they are advected with the plasma flow to the detection region. At Earth and other planets, the quasi-perpendicular shock provides the plasma with the necessary heating along the perpendicular direction to the local magnetic field. At Mars, which boasts an extended exosphere, an additional source of temperature anisotropy exists, through unstable ring-beam velocity distributions, that is, through ions locally ionised and subsequently picked up by the local electric fields. We report here for the first time an example of near locally-generated mirror mode structures at Mars using the full plasma instrument suite on board the Mars Atmosphere and Volatile EvolutioN (MAVEN) mission. We present three events in quasi-perpendicular and quasi-parallel shock conditions with a variable exosphere, discuss the locality of the mirror modes excited and show that, in addition to the classic quasi-perpendicular source of anisotropy, another source exists, that is, unstable pickup protons. The existence at Mars of this extra ion anisotropy-generating mechanism is reminiscent of comets.

Sub-Antarctic Mode Waters (SAMWs) form to the north of the Antarctic Circumpolar Current (ACC) in the Indo-Pacific Ocean, whence they ventilate the ocean’s lower pycnocline and play an important role in the climate system. With a backward Lagrangian particle-tracking experiment in a data-assimilative model of the Southern Ocean (B-SOSE), we address the long-standing question of whether SAMWs originate from densification of southward-flowing subtropical waters, or lightening of northward-flowing Antarctic waters sourced by Circumpolar Deep Water (CDW) upwelling. Our analysis evidences the co-occurrence of both sources of SAMWs in all formation areas, and strong inter-basin contrasts in their relative contributions. Subtropical waters are the main precursor of Indian Ocean SAMWs (70-75% of particles) but contribute a smaller amount ($<$40%) to Pacific SAMWs, which are mainly sourced by CDW. By tracking property changes along particle trajectories, we show that SAMW formation from northern and southern sources involves contrasting drivers: subtropical source waters are cooled and densified by surface heat fluxes, and freshened by ocean mixing. Southern source waters are warmed and lightened by surface heat and freshwater fluxes, and they are made either saltier by mixing in the case of Indian SAMWs, or fresher by surface fluxes in the case of Pacific SAMWs. Our results underscore the distinct climatic impact of Indian and Pacific SAMWs, as net sources of atmospheric heat and net sinks of freshwater, respectively; a role that is conferred by the relative contributions of subtropical and Antarctic sources to their formation.

A document by Daniel Matthiä. Click on the document to view its contents.