Storm Events Research Articles

The Impact of Geomagnetic Storms on the Ionospheric Critical Frequency in the Northern and Southern Mid-Latitude Hemisphere Regions

In this work, the impact of different geomagnetic storm events on the plasma-sphere layer (ionosphere layer) over the northern and southern hemisphere regions was investigated during solar cycle 23. To grasp the influence of geomagnetic storms on the behavior and variation of the critical frequency parameter of the F2 ionospheric layer (foF2), five geomagnetic storms (classified as great, severe, and strong), with Disturbance storm time (Dst) values <-100 nT were chosen. Four stations located in different mid-latitude regions in northern and southern hemispheres were designated, the northern stations are: Millstone Hill (42.6° N, 288.50° W) and Rome (41.90° N, 12.50° E) and the southern stations are: Port Stanley (-51.60° S, 302.10° W) and Grahamstown (-33.30° S, 26.50° E). The findings of this study showed that during events of 16 July 2000 and 24 August 2005, the negative storms cause a noticeable reduction in the values of the foF2 parameter at the northern hemisphere stations compared to those at the southern hemisphere. These outcomes are consistent with the results of the examining the variation of D(foF2) and the electron density depletion during the tested event times at all stations except in Rome, where minor enhancements in foF2 value were observed during the August 24 2005 storm. During equinox storm events occurring on March 31 and November 6 2001, a noticeable negative impact of storms was observed across all stations. However, at Millstone Hill and Port Stanley stations, the results showed a slight positive storm impact during the October 21, 2001event.

A Comparative Investigation of Different Ionospheric Models to Predict the MUF Parameter During Severe Geomagnetic Storm on 17th March 2015.

The present work aimed to make a comparative investigation between three different ionospheric models: IRI-2020, ASAPS and VOACAP. The purpose of the comparative study is to investigate the compatibility of predicting the Maximum Usable Frequency parameter (MUF) over mid-latitude region during the severe geomagnetic storm on 17 March 2015. Three stations distributed in the mid-latitudes were selected for study; these are (Athens (23.50o E, 38.00o N), Jeju (124.53o E, 33.6o N) and Pt. Arguello (239.50o W, 34.80o N). The daily MUF outcomes were calculated using the tested models for the three adopted sites, for a span of five-day (the day of the event and two days preceding and following the event day). The calculated datasets were compared for each location with the observed daily MUF values. In general, the findings show that the three investigated models gave good outcomes compared to the observed values for all selected stations. The comparative investigation results of the three tested models corresponding to the observed MUF values during the storm event revealed that the IRI -2020 Model indicate a clear impact of the geomagnetic storm on the predicted MUF values during the day of event. Similarly, for ASAPS Model, the storm's impact is clear on both the day of the event and the subsequent day, in contrast, the VOACAP model showed almost no impact of the geomagnetic storm on the observed MUF values throughout the entire study period for event 17 March 2015.

Vulnerability assessment of English and Welsh coastal areas

The escalating threat of climate change has placed global coastal communities at risk, with rising sea levels and intensified storm events presenting unprecedented challenges. Coastal vulnerability assessments, conducted every 3–5 years, are crucial. This empirical study assesses the Coastal Vulnerability Index (CVI) for the distinct coastal contexts of Dawlish, Happisburgh (England), and Aberystwyth (Wales). The CVI method consists of the Physical Coastal Vulnerability Index (PCVI) and the Economic Coastal Vulnerability Index (ECVI), which provide a multidimensional assessment of vulnerability for coastal zones. This integrated index allows for a nuanced evaluation of vulnerability, distinguishing between sites based on various factors. Additionally, this study conducted a correlation analysis to understand the associations between the parameters. The findings demonstrate that physical features like beach and dune widths significantly impact a location’s natural defences, and economic factors such as property values and population density are equally crucial in determining societal risks and potential financial repercussions. The Combined Coastal Vulnerability Index (CCVI) results confirm the effectiveness of incorporating a diverse range of variables. Despite its substantial economic value, it reveals that Dawlish requires targeted protective measures, whereas Happisburgh needs an increased focus on its most vulnerable sectors. Aberystwyth emerges as the area with the highest overall vulnerability, underscoring the need for comprehensive coastal management practices. The study’s conclusions emphasize the essential role of adaptive, integrated management strategies in enhancing coastal resilience against the complex threats posed by climate dynamics. Moving forward, the indices established herein advocate for their use in strategic planning and policymaking to strengthen coastal regions in the face of sea-level rise and climatic variability. This investigation lays the groundwork for future research, aimed at refining and expanding these methodologies, aspiring to develop a detailed national coastal vulnerability atlas, a critical tool for informed decision-making and safeguarding at-risk communities.

Application of the NRCS-curve number method in humid tropical basins of southeastern Nigeria: a statistical analysis

In the south-eastern region of Nigeria, the application of rainfall (P) and runoff (Q) data directly into the Natural Resources Conservation Service Curve Number (NRCS-CN) method hasn’t been thoroughly studied. This research aimed to determine representative values of the initial abstraction ratio (λ) and corresponding curve number (CN), fit the P and Q data using theoretical probability distributions, and establish confidence intervals for CN. The least squares minimization method and Kolmogorov-Smirnov test were employed on data from 129 sub-basins across 4 major basins. Findings revealed optimal initial abstraction ratio (λopt) = 0.24 and optimal CN (CNopt) = 80, with rainfall best fitted by Gamma, runoff by Weibull, and CN by Normal distributions. However, the study was limited to the available 8-year record period with 96 storm events. The 96 storm events over an 8-year period may seem limited for a humid tropical region, the available data were the most comprehensive and reliable dataset for this study area. Additional data collection over a longer time frame could enhance future studies. The localized CN value and associated confidence intervals can enhance runoff prediction accuracy for flood mitigation and water resources management in this humid tropical region, though further validation is recommended.

On the Influence of Beach Slope on Wave Non-Linearities on a Macrotidal Low-Tide Terrace Beach

This study examines the evolution of wave shapes as they propagate over a beach of varying morphology, information essential for understanding coastal dynamics and supporting coastal management. Our objective was to analyze the relationship between wave shape parameters and the local slope of the beach. To achieve this, we used data from pressure sensors and topographic measurements to evaluate the shape of waves on a cross-shore profile of a low-tide terrace beach. The analysis of wave conditions revealed a pronounced modulation of the tidal signal, which is augmented during storm events. Our findings demonstrate that the asymmetry and skewness parameters are more pronounced in the reflective zone of the beach. Considering these results, it can be concluded that the non-linearity of waves is significantly affected by the beach slope. The parameterization method employed in this study effectively incorporates this factor, offering improved accuracy in comparison to the existing approaches.

Re-processing Datawell Directional Waverider MkIII heave data affected by breaking waves

Observations of nearshore waves are essential for coastal management, planning and operations. However, shallow water deployments often encounter breaking waves, causing anomalous measurements that are rejected during quality control. A new methodology for re-processing wave data containing breaking waves has been developed, utilising data from the National Network of Regional Coastal Monitoring Programmes of England which operates 37 Datawell Directional Waverider MkIII buoys. Heave data affected by breaking waves is reviewed, anomalous heaves removed, and the remaining data re-processed. Validation through a two-stage process confirms that re-processed wave parameters closely match those derived from the established Datawell processing and ensures strong agreement between parameters derived from shorter re-processed records and full-length data. Applying this new approach to all measured storm wave data, 7.3% (928.5 hours) of storm wave data is recovered across the 37 sites. At some sites, the retention of additional storm wave data has considerable impacts on significant wave height (Hm0) return periods. At five sites, the 1 in 100 year return period increased by over one meter. The enhanced dataset now includes more individual storm events and more complete records of storm events, providing a more robust foundation for coastal management and planning.

Development and performance of a high-resolution surface wave and storm surge forecast model: application to a large lake

Abstract. A real-time forecast model of surface hydrodynamics in Lake Ontario (Coastlines-LO) was developed to automatically predict storm surges and surface waves. The system uses a dynamically coupled Delft3D–SWAN model with a structured grid to generate 48 h predictions for the lake that are updated every 6 h. The lake surface is forced with meteorological data from the High Resolution Deterministic Prediction System (HRDPS). The forecast model has been running since May 2021, capturing a wide variety of storm conditions. Good agreement between observations and modelled results is achieved, with root mean squared errors (RMSEs) for water levels and waves under 0.02 and 0.26 m, respectively. During storm events, the magnitude and timing of storm surges are accurately predicted at nine monitoring stations (RMSE <0.05 m), with model accuracy either improving or remaining consistent with decreasing forecast length. Forecast significant wave heights agree with observed data (1 %–12 % relative error for peak wave heights) at four wave buoys in the lake. Coastlines-LO forecasts for storm surge prediction for two consecutive storm events were compared to those from the Great Lakes Coastal Forecasting System (GLCFS) to further evaluate model performance. Both systems achieved comparable results with average RMSEs of 0.02 m. Coastlines-LO is an open-source wrapper code driven by open data and has relatively low computational requirements compared to GLCFS, making this approach suitable for forecasting marine conditions in other coastal regions.

The role of refractive indices in measuring mineral dust with high-spectral-resolution infrared satellite sounders: application to the Gobi Desert

Abstract. Mineral dust significantly influences the Earth's climate system by affecting the radiative balance through the emission, absorption and scattering of solar and terrestrial radiation. Estimating the dust radiative effect remains challenging due to the lack of detailed information on the physical and chemical properties of dust. High-spectral-resolution instruments in the infrared (IR) spectrum, such as the Infrared Atmospheric Sounding Instrument (IASI), have demonstrated the ability to quantify these aerosol properties. A crucial parameter for characterizing mineral dust from space is the complex refractive index (CRI), as it links the dust's physical and chemical properties to its optical properties. This paper examines the impact of six prior laboratory CRI datasets to improve the characterization of dust microphysical properties using IASI. The CRIs include older measurements obtained through the classical pellet method, commonly employed in mineral dust applications, as well as newer datasets that incorporate the latest advancements in laboratory measurement techniques for aerosol generation. These datasets are tested on IASI measurements during a dust storm event over the Gobi Desert in May 2017. We evaluate the sensitivity of IASI to different CRI datasets using the Atmospheric Radiation Algorithm for High-Spectral Resolution Measurements from Infrared Spectrometer (ARAHMIS) radiative transfer algorithm and explore the datasets' impact on retrieving size distribution parameters by mapping their spatial distributions. The results indicate that the laboratory CRI datasets decrease the total error in the covariance matrix by 30 %. In addition, we assess the ability to accurately reconstruct IASI detections and the extent to which we can retrieve the microphysical properties of dust particles. The choice of CRI significantly impacts the accuracy of dust detection and characterization from satellite observations. Notably, datasets that incorporate recent aerosol generation techniques with higher spectral resolution and samples from the case study region show improved compatibility with IASI observations. The outcomes of this research emphasize two key points: the crucial link between chemical composition of dust and its optical properties and the importance of considering the specific composition of the CRI dataset for improved retrieval of the microphysical parameters. Furthermore, this study highlights the critical role of ongoing enhancements in CRI measurement approaches, as well as the potential of high-spectral-resolution infrared sounders for aerosol atmospheric investigation and for understanding the radiative impacts of sounders.

Stable silicon isotope fractionation reflects the routing of water through a mesoscale hillslope

Concentration - isotope Ratio - Discharge (C-R-Q) relationships offer a promising means of disentangling the underlying hydrologic, geochemical, and ecological factors that produce variations in stream solute chemistry across a variety of critical zone systems. However, natural environments are both temporally and spatially complex, and prevailing interpretations of these C-R-Q patterns remain difficult to validate. Here we employ three replicate artificially constructed hillslopes at the Landscape Evolution Observatory (LEO) in Tucson, Arizona as simplified analogs to natural catchments. LEO allows us to record silicon stable isotope (δ30Si) signatures of fluid discharge under a controlled irrigation schedule in a system devoid of vegetation. This unique meso‑scale experiment enables, for the first time, evaluation of metalloid stable isotope signatures at the scale of natural hillslopes constrained to known fluid transit time distributions (TTDs) and limited to fractionation in association with secondary mineral formation. We report δ30Si in discharge samples collected over three randomized storm events of varying intensity. The data reflect consistent enrichment in the fluid phase between +1.00 and +2.07 ‰ across the three hillslopes, despite highly variable irrigation scenarios, reflecting substantial loss of SiO2 from solution due to secondary mineral precipitation. We compare results from an isotope-enabled Reactive Transport Model (RTM) and the discharge measurements from LEO to constrain the contributions of both characteristic watershed TTDs and fractionation pathways in emergent δ30Si signatures. Our study confirms and expands upon recent work in natural systems attributing intra-site variability in silicon stable isotope signatures to the routing of fluid through catchments.

Storm resilience of subtidal soft‐bottom mussel beds: Mechanistic insights, threshold quantification and management implications

AbstractWith the projected escalation of extreme storm events, coastal ecosystems risk undergoing catastrophic shifts and losing essential ecosystem services. Subtidal soft‐bottom mussel beds, vital components of these ecosystems, are particularly vulnerable to hydrodynamically‐induced dislodgement (i.e., detachment of mussel clumps from the bed), especially during storms. However, the mechanisms underlying the resilience—comprising both resistance and recovery—of these beds to storms remain unclear, despite being essential for informed management.This study addresses this knowledge gap regarding subtidal soft‐bottom mussel beds by: (i) quantifying their dislodgement threshold (i.e., the hydrodynamics causing widespread dislodgement of mussel clumps) using novel in situ monitoring methodologies in a representative region, namely the Dutch Wadden Sea; (ii) unveiling the influence of prior life history (here, wave exposure extent) and storm durations on their dislodgement thresholds through a flume study; and (iii) assessing the impacts of repeated storms and prior life histories (here, wave exposure extent and substrate types) on their recovery (i.e. mussel re‐aggregation) through mesocosm experiments.Integrated experimental evidence indicates that: (i) hydrodynamic‐induced dislodgement is a sudden process characterized by distinct near‐bed orbital velocity thresholds, which were identified at our study site to be between 0.45 and 0.50 m s−1; (ii) peak storm intensity, rather than storm duration, primarily drives the dislodgement of subtidal soft‐bottom mussel beds, and prior wave exposure extent regulates the dislodgement threshold; (iii) repeated storms do not seem to affect the recovery of these beds following storm‐related disturbances when the conditions between storms are conducive to mussel re‐aggregation, whereas substrate type significantly impacts recovery.Synthesis and applications. Overall, concerns regarding subtidal soft‐bottom mussel beds degradation primarily stem from increasing storm intensity and their limited resistance to such events. The methodology we developed enables low‐cost quantification of mussel resistance thresholds across broad spatiotemporal scales, facilitating the pinpointing of vulnerable areas. Our findings inform strategic management by highlighting the influential role of prior life histories in shaping mussel bed resistance and the potential to accelerate mussel bed recovery through substrate modification (e.g., shell additions). Both our methodology and findings hold promise for application in comparable ecosystems, such as oyster and coral reefs.

A Tale of Two Storms: Inter‐Storm Variability of Stable Water Isotopes in a Solute Transport Model

ABSTRACTStable isotopic methods in hydroclimate monitoring are powerful for improving water resources management, but applications are limited, especially in semi‐arid regions where such management is needed most. Here, we show that we can address shortcomings related to the lack of a seasonal signal using stable water isotopic signatures measured in precipitation over the East San Francisco Bay area, California, during two contrasting events sampled at more than 20 locations in the winter of 2023. The observed range in δ18O in the rain samples is similar for both storms. However, the distributions do not overlap—the mean air temperature and δ18O during Winter Storm Olive (February 2023) were 2°C and − 12‰, respectively, while a warm atmospheric river event (March 2023) had a mean temperature of 9°C and δ18O of −6‰, close to the long‐term average δ18O measured in local precipitation. The Winter Storm showed expected trends in δ18O related to geography (i.e., lower with greater distance inland and elevation), while the atmospheric river δ18O pattern was more spatially uniform. We use hydrometric data from a gaged watershed in the study area and isotopic signatures of rain sampled during the two storm events and apply a solute transport model (StorAge selection) with a travel‐time approach to examine predicted watershed responses and potential water tracing applications. In this virtual experiment, we find that event size exerts a strong control on the relative amounts of runoff versus pre‐event water in the stream, while uncertainty in stream hydrograph separation is related to the degree of contrast between precipitation/runoff and pre‐event water. Key to flood prediction, adaptation, and mitigation, especially in coastal urban areas, is knowledge of the contributing water sources and timing of stream flow. The strong contrast in stable isotopes between these two events, close in time and over the same area, illustrates the potential to use stable isotope signatures to track the transport and mixing of events through natural and engineered watersheds that are threatened by climate whiplash events.

Exploring Storm Intensities and the Implications on Green Stormwater Infrastructure Design

ABSTRACTThe peak intensity that occurs during a storm event can drive the performance of a green stormwater infrastructure (GSI), which may or may not align with the expected performance of the GSI. Both the peak intensity volume and where it occurs within an event are found to influence the GSI response. The design criteria set the expectation of how well a GSI will manage stormwater within a watershed. The Villanova University bioinfiltration rain garden (BRG) has been monitored since 2003, providing a long hydrological data record that is used to study local and observed rainfall patterns in comparison to design criteria to understand the impact of storm intensity on GSI performance. Intensities for all the storms recorded at the site were assessed at different timesteps and compared to the intensities typically used by the design storm approach in meeting regulatory criteria. There were 1482 storm events analysed and for all timesteps, the values commonly used for meeting design regulations were seen to be well above what was observed at the BRG, with 98% of the storms occurring below these values. Out of the 1482 storms, only 46 storms (3%) had effective durations longer than 10 h and no storm observed had an effective duration longer than 22 h, yet their peak intensities were still below the peak intensity associated with design regulations. This finding highlights the difference in the duration these sites are designed to manage (typically 24 h), in comparison to the ones experienced by the systems. The peak intensity analysis done at the different timesteps shows that for the storms recorded at the BRG, the intensities vary with changing time intervals and events. Of all the assessed events, only two events recorded larger intensities than the regionally specified NOAA C design storm, demonstrating the skewness of the approach. There was no trend in peak rain intensities over the 20‐year rainfall record. This study concludes that due to their dynamic performance, vegetated GSI have a natural resilience to a variety of precipitation patterns and climate changes that may be compromised when designing to a static value set through design storms.

Tree Trimming Effects on 3-Dimensional Crown Structure and Tree Biomechanics: A Pilot Project

AbstractBackgroundAlong electric distribution corridors in urban-exurban landscapes, forest edges are susceptible to damage associated with storm events. Disturbances and management interventions designed to preempt their effects (e.g., tree trimming) alter characteristics of tree structure and morphology (e.g., branch and crown structure), which may be associated with tree failure and likelihood of associated infrastructure damage. This study assessed the relationship between 3-dimensional tree crown structure and tree biomechanics and characterized the effect of utility tree trimming on tree sway dynamics using terrestrial laser scanning (TLS).MethodsIn this study we extracted and analyzed measures of crown structure (i.e., crown asymmetry, crown area, total volume, crown diameter to height ratio, and crown evenness) for individual trees during leaf-off conditions before and after implementation of tree trimming and linked these measures to tree biomechanics data, to evaluate how commonly implemented trimming practices affect both tree sway frequency and displacement—important indicators of tree stability.ResultsResults illustrated the effects of common tree trimming practices on tree crown structure, but there were not consistent changes to tree movement characteristics directly following tree trimming across our 24 study trees. However, we found that the associated changes in crown structure through tree trimming affected tree displacement in moderate wind conditions. Additionally, we found there were no significant differences between frequencies across treatment types.ConclusionsThis pilot project lays the foundation for understanding the intricate relationship between 3-dimensional crown structure and tree biomechanics following roadside tree trimming.

Dynamics of Barred Coast at Different Temporal Scales (by the Example of Vistula Spit in the Baltic Sea)

According to fundamental concepts, the morphodynamic system of an accumulative sandy coast with underwater bars exhibits cyclic behavior across various time scales. This raises the question: which factor is more significant for the dynamics of a given coast—individual storms or seasonal changes in wave activity? While observations and studies addressing this issue have primarily been conducted on oceanic coasts, there is a lack of comparable data for fetch-limited areas. Monitoring of the bottom topography along the west coast of Vistula Spit (Baltic Sea) revealed a cyclic behavior in morphology, transitioning from a straightened external bar to its connection with the shore. Analysis of field measurement results indicated that seasonal variations in wave intensity do not significantly impact coastal relief. Furthermore, it was found that the complete cycle of underwater bar evolution lasts approximately two years, during which the coast profile maintains a stable shape at the stage of the straightened external bar. The identification of the primary factor influencing coastal evolution can be characterized by the Dean number (Ω), which combines wave parameters (wave height and period) with sediment fall velocity. Utilizing ERA5 wave reanalysis data, we compared the variability of Ω values on both annual and monthly scales. The analysis revealed that for the section of the coast under consideration, there is no clearly dominant evolutionary factor; rather, the coast is influenced approximately equally by individual storm events and seasonal fluctuations in wave energy. Modeling storm-induced bed profile deformations using the CROSS-PB model demonstrated that the position of the external underwater bar remains nearly constant even during intense and prolonged storms. It is concluded that under specific conditions—determined by a combination of sediment size, coastal slope, and wave regime characteristics—the coast can remain stable, exhibiting minimal response to relatively strong storms and seasonal variations in wave energy. Such coasts are characterized by an absence of a dominant evolutionary factor as indicated by fluctuations in the Dean parameter, allowing their morphodynamic cycles to span several seasons. This type of morphodynamics in coastal accumulative relief appears to be typical for conditions found in fetch-limited areas, such as regional and semi-closed seas.

Weathering the storm: Extreme weather events and their association with PED and PRRS occurrence

Porcine epidemic diarrhea (PED) and Porcine reproductive and respiratory syndrome (PRRS) are viral diseases that continue to challenge the US swine industry. Despite many known risk factors, unusual circumstances associated with their occurrence continues to be poorly explained. We investigated if extreme weather events (flood, heavy rain, high wind and tornadoes, measured at a county-level) are associated with the occurrence of both diseases up to ten weeks after the occurrence of the weather event using a case control study and logistic regression modeling to control for covariates. We obtained weekly farm-level disease occurrence information from the Morrison Swine Health Monitoring Project (MSHMP) and county-level weather events occurrence information from the National Oceanic and Atmospheric Administration (NOAA) storm events database. Our findings indicate that farms in counties exposed to floods had between two to three times higher odds of experiencing a PED outbreak between four to eight weeks after the event than control farms. However, we did not observe significant associations between other weather events and PED or PRRS occurrences. Even though the absolute risk these events pose to swine herds may be small, we suggest that companies should develop biosecurity protocols that consider the impact of extreme weather events in order to mitigate the risks posed to their herds.

Dust event identification and characterization with one-year online observations in Beijing.

Dust storms have a profound impact on air quality, atmospheric chemistry, and human well-being by carrying vast amounts of particles over distances of thousands of kilometers. However, the overall characteristics of these dust events and their influence on secondary pollution in the northern China region are not yet well understood, due to a lack of long-term, comprehensive observations and objective identification techniques. Based on principal component analysis combined with high-time-resolution observations of particulate matter components, here we developed a robust method to identify dust storm events and identified 14 dust events in Beijing in 2019. We further classified these 14 events into two distinct types using Lagrangian particle dispersion models and backward trajectory analysis. The first type (Type I, 9 cases) is characterized by synoptic patterns in Mongolia, originating from the north and directly impacting the Beijing area. The second type (Type II, 5 cases) involves air masses from the north or northwest that temporarily pass through polluted regions south of Beijing before being carried back into the city. Consistently, during Type I dust events, we observed a sharp decrease in secondary inorganic aerosols (SIA) from 65 % to 7 %, as well as in the sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR) (from 0.52 to 0.19, and 0.27 to 0.018 respectively). In contrast, during Type II dust events, SIA concentrations increased by 91 %, along with an increase in SOR (1.7 %), NOR (69 %), and f44/f43 (3.0 %), suggesting an enhancement of secondary aerosol formation resulting from the interaction between dust aerosols and gaseous anthropogenic pollutants. Our results demonstrate that dust events and the sub-type of dust events can be identified in an objective manner using the protocol developed in this study and the dynamics should be considered when discussing impacts of dust events on atmospheric chemistry.

Temporal and Spatial Variations in Microplastic Concentrations in Small Headwater Basins in the Southern Blue Ridge Mountains, North Carolina, USA

Microplastics (MPs) are ubiquitous contaminants of emerging concern that require additional study in freshwater streams. We examined the spatial-temporal variations in MP concentrations and characteristics within two headwater basins in the Southern Appalachian Mountains of western North Carolina over ~1 year. Atmospheric samples were also collected to determine the significance of atmospheric MP deposition to these relatively small streams. MP concentrations in both basins were within the upper quartile of those reported globally, reaching maximum values of 65.1 MPs/L. Approximately 90% of MPs were fibers. MP composition was dominated by polystyrene, polyamides, and polyethylene terephthalate. Spatially, concentrations were highly variable and increased with development, indicating anthropogenic inputs from urbanized areas. MP concentrations were also elevated in forested tributary subbasins with limited anthropogenic activity, suggesting atmospheric deposition was an important MPs source. Significant atmospheric inputs are supported by high atmospheric depositional rates (ranging between 7.6 and 449.8 MPs/m2/day across our study sites) and similarities in morphology, color, and composition between atmospheric and water samples. Temporally, MP concentrations during storm events increased, decreased, or remained the same in comparison to base flows, depending on the site. The observed spatial and temporal variations in concentrations appear to be related to the complex interplay between precipitation and runoff intensities, channel transport characteristics, and MP source locations and contributions.

The State of Solar Wind Heavy Ions in Interplanetary Coronal Mass Ejection–Driven Geomagnetic Storms

During geomagnetic storms, which are the primary periods for heavy ions from the solar wind to enter Earth’s magnetospheric space, the charge state of solar wind heavy ions during these storms has significant implications for studying the distribution and effects of heavy ions in the magnetosphere. We analyzed the states and variations of heavy ions during 158 interplanetary coronal mass ejection (ICME)–driven geomagnetic storm events using data from the Advanced Composition Explorer satellite and examined four of these events in detail. We found that the increase in the average charge state of heavy ions such as O, Mg, Si, and Fe is positively correlated with the intensity of the geomagnetic storm. Regarding the abundance ratio of heavy ions such as Ne, Mg, Si, and Fe relative to oxygen ions, the rate and magnitude of increase in abundance ratios during extreme geomagnetic storms (Kp = 9) triggered by ICME events are significantly higher than those during other levels of geomagnetic storms. Additionally, we observed that although the average charge states of heavy ions such as O and Fe are correlated with the geomagnetic storm intensity induced by ICMEs, there are significant individual differences in the charge state variations of heavy ions.

Wave–Tide–Surge Interaction Modulates Storm Waves in the Bohai Sea

Typhoons, extratropical cyclones, and cold fronts cause strong winds leading to storm surges and waves in the Bohai Sea. A wave–flow coupled numerical model is established for storm events observed in 2022 caused by three weather systems, to investigate how storm waves are modulated by wave–tide–surge interaction (WTSI). Wave response is basically controlled by water level change in coastal areas, where bottom friction or breaking dominates the energy dissipation, and determined by the current field in deep water by altering whitecapping. Wave height increases/decreases are induced by positive/negative water level or obtuse/acute wave–current interaction angle, leading to six types of field patterns for significant wave height (Hs) responses. For the three storm events, Hs basically changed within ±5% in central deep water, while the maximum increase/decrease reached 160%/−60% in the coastal area of Laizhou Bay/Liaodong Bay. Based on maximum Hs and its occurrence time, WTSI modulation is manifested as the superposition effect of wave–tide and wave–surge interactions in both space and time scales, and occurrence time depends more on tide than surge for all three storms. The enhancement/abatement of WTSI modulation happens for consistent/opposite changing trends of wave–tide and wave–surge interaction, with the ultimate result showing the side with a higher effect.

The Evolution of Earth's Outer Radiation Belt Over Geomagnetic Storm Phase in Van Allen Probe Era

AbstractEarth's outer radiation belts are highly dynamic during geomagnetic storms. Using electron flux data from 226 keV to 2.6 MeV measured by the Van Allen Probes, we statistically analyzed the peak flux position and inner boundary position of the outer radiation belt across different storm phases: pre‐storm quiet time, main phase, early recovery phase, and later recovery phase. This analysis covered 196 geomagnetic storm events from October 2012 to September 2019. Our results indicate that: (a) During the pre‐storm, decreases with increasing energy. From the pre‐storm to the early recovery phase, shifts inward for energies below 1 MeV and outward for energies above 1 MeV. For all energies, converges to approximately L = 4.3–4.6 in the early recovery phase. (b) Below approximately 1 MeV, generally move inward from the main phase to the early recovery phase. Above 1 MeV, remains nearly unchanged across different storm phases. (c) The half‐width (−) of the outer belt decreases during the main phase for energies below 1 MeV and increases during the recovery phase for energies above 1.5 MeV. (d) In the early recovery phase, and at 593–742 keV show a moderate correlation with storm intensity (CC 0.7–0.8), while and at energies greater than 1.1 MeV exhibit low correlations (CC0.4) during each phase. These results confirm the complex, energy‐dependent morphology of the outer radiation belt throughout geomagnetic storm phases.