Extreme Storm Research Articles

Experimental Study Unraveling Flow Allocation Patterns at Crossroad Intersections During Urban Flooding

Urban roads can effectively handle peak flows during extreme storms by serving as surface flood passages, provided the flow remains within safety thresholds for vehicles and pedestrians. However, studies on flow allocation at crossroad intersections are limited. Previous research has overlooked important factors: road transverse slope and turning radius. This study built a “two in, two out” laboratory crossroad intersection to examine flow allocation patterns. Experiments explored the effects of road longitudinal slope, boundary conditions, and the combined influence of turning radius and side slope. The results indicated that at flatter slopes, flow allocation is more influenced by road slope, while at steeper slopes, the inflow Froude number ratio becomes more significant. The combined effect of the turning radius and side slope results in a flow allocation that differs by 44.3% compared to rectangular orthogonal channel intersections. A straightforward formula is proposed to calculate the flow allocation ratio based on experimental results and inflow power ratio. These findings could improve road intersection designs for better flood mitigation, offering a practical tool for planning flood-resilient road networks.

Unveiling key factors in solar eruptions leading to the solar superstorm in 2024 May

NOAA active region (AR) 13664/8 produced the most intense geomagnetic effects since the Halloween event of 2003. The resulting extreme solar storm is thought to be the consequence of multiple interacting coronal mass ejections (CMEs). Notably, this AR exhibits exceptionally rapid magnetic flux emergence. The eruptions on which we focus all occurred along collisional polarity inversion lines (PILs) through collisional shearing during a three-day period of extraordinarily high flux emergence (sim 1021 Mx hr$^ $). Our key findings reveal how photospheric magnetic configurations in eruption sources influence solar superstorm formation and geomagnetic responses, and link exceptionally strong flux emergence to sequential homologous eruptions: (1) We identified the source regions of seven halo CMEs that were distributed primarily along two distinct PILs. This distribution suggests two groups of homologous CMEs. (2) The variations in the magnetic flux emergence rates in the source regions are correlated with the CME intensities. This might explain the two contrasting cases of complex ejecta that are observed at Earth. (3) Our calculations of the magnetic field gradients around the CME source regions show strong correlations with eruptions. This provides crucial insights into solar eruption mechanisms and enhances our prediction capabilities for future events.

Enhancing Road Drainage Systems for Extreme Storms: Integration of a High-Precision Flow Diversion Module into SWMM Code

Enhancing Road Drainage Systems for Extreme Storms: Integration of a High-Precision Flow Diversion Module into SWMM Code

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.

Performance Assessment of Satellite-Based Precipitation Products in the 2023 Summer Extreme Precipitation Events over North China

In the summer of 2023, North China experienced a rare extreme precipitation storm due to Typhoons Doksuri and Khanun, leading to significant secondary disasters and highlighting the urgent need for accurate rainfall forecasting. Satellite-based quantitative precipitation estimation (QPE) products like Integrated Multi-Satellite Retrievals for GPM (IMERG) and Global Satellite Mapping of Precipitation (GSMaP) from the Global Precipitation Measurement (GPM) Mission have great potential for enhancing forecasts, necessitating a quantitative evaluation before deployment. This study uses a dense rain gauge as a benchmark to assess the accuracy and capability of the latest version 7B IMERG and version 8 GSMaP satellite-based QPE products for the 2023 summer extreme precipitation in North China. These satellite-based QPE products include four satellite-only products, namely IMERG early run (IMERG_ER) and IMERG late run (IMERG_LR), GSMaP near-real-time (GSMaP_NRT), and GSMaP microwave-infrared reanalyzed (GSMaP_MVK), along with two gauge-corrected products, namely IMERG final run (IMERG_FR) and GSMaP gauge adjusted (GSMaP_Gauge). The results show that (1) GSMaP_MVK, IMERG_LR, and IMERG_FR effectively capture the space distribution of the extreme rainfall, with relatively high correlation coefficients (CCs) of approximately 0.77, 0.75, and 0.79. The IMERG_ER, GSMaP_NRT, and GSMaP_Gauge products exhibit a less accurate spatial pattern capture (CCs about 0.66, 0.73, and 0.67, respectively). Each of the six QPE products tends to underestimate rainfall (RBs < 0%). (2) The IMERG products surpass the corresponding GSMaP products in serial rainfall measurement. IMERG_LR demonstrates superior performance with the lowest root-mean-square error (RMSE) (about 0.38 mm), the highest CC (0.97), and less underestimation (RB about −6.37%). (3) The IMERG products at rainfall rates ≥ 30 mm/h, GSMaP_NRT and GSMaP_MVK products at rainfall rates ≥ 55 mm/h, and GSMaP_Gauge products at ≥ 40 mm/h showed marked limitations in event detection, with a near-zero probability of detection (POD) and a nearly 100% false alarm ratio (FAR). In this extreme precipitation event, caution is needed when using the IMERG and GSMaP products.

First Results for the Influence of Two Geomagnetic Storms during 10-12 May 2024 On Mid-latitude Ionosphere

The main idea of this study is to analyze the ionospheric anomalies in selected points related to the extreme geomagnetic storm which occurred during the period 10–12 May 2024. In the present research, data of the critical frequency of the F2 region (foF2) from the vertical sounding of ionospheric station Rome (Italy) and foF2 data for the territory of Sofia (Bulgaria) obtained by empirical modelling were used. The selection of Rome ionospheric station is related to the fact that this ionosonde is located at the geographic latitude coinciding with the latitude of Sofia, which suggests similar characteristics of the ionosphere. In order to evaluate the type of response (positive or negative), the relative deviation of the values was used, taking into account the influence of the local time for the individual points (1 hour). The results of the of the ionospheric response analysis show a well expressed negative response, more significant at Rome station. Another interesting result related to the inertia of the ionosphere is expressed in the observed response delay depending on the onset of the geomagnetic storm. From the comparison of the measured data and those obtained through the empirical model it can be seen that for the purposes of ionospheric forecasting, the model is able to describe the behaviour of the ionosphere with sufficient accuracy. The ionospheric response is supported by an additional study of the behaviour of the Total Electron Content (TEC), which response is similar to that of foF2.

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.

Mangrove freeze resistance and resilience across a tropical‐temperate transitional zone

Abstract Freeze events govern the distribution and structure of mangrove ecosystems, especially in tropical‐temperate transitional zones. Understanding mangrove responses to freezing is crucial for predicting their poleward expansion under climate change. However, there is a need for field‐based measurements of mangrove freeze resistance and resilience. After an extreme winter storm in December 2022, we measured mangrove post‐freeze damage and recovery (January and November 2023), building on a pre‐freeze baseline assessment conducted in July 2022 across 12 sites along the temperature gradient of Florida's Gulf of Mexico coast (USA). Low‐temperature thresholds for leaf damage to Avicennia germinans, Rhizophora mangle and Laguncularia racemosa were quantified near −6, −4 and − 4°C, respectively. Thresholds for mortality were found to be near −6 to −7°C for A. germinans and −4 to −5°C for R. mangle. A threshold for loss of reproductivity in A. germinans was identified near −6 to −7°C. Resprouting was observed in all three species but limited to just one individual for R. mangle. Surviving A. germinans resprouted vigorously and had the greatest number of resprout branches, which was proportional to leaf damage. Tall A. germinans had a higher resprout percentage than short trees. Strata‐specific differences in freeze damage were most pronounced for R. mangle, with higher damage in tall versus short trees, while no difference was found between A. germinans strata. These results suggest that R. mangle population recovery may depend on the growth of short trees, while A. germinans can recover from all strata. Minimum air temperature was strongly correlated with mangrove height and above‐ground biomass. Projections of future minimum temperature and species‐specific freeze degree days predict warming winters, suggesting further mangrove development and range expansion under climate change. Synthesis: Collectively, our study advances understanding of mangrove responses to freezing and identifies low‐temperature thresholds for each species, aiding predictions of mangrove range expansion.

Spatially seamless and temporally continuous assessment on compound flood risk in Hong Kong

Compound flooding results from the simultaneous occurrence of extreme storm surges, sea level rise, and heavy rainfall. These events often lead to impacts significantly more severe than those caused by any individual flood-inducing factor alone. However, the limited and sparse data from tidal gauges hampers precise risk assessment at ungauged sites in coastal cities. Our study addresses this gap by integrating ensemble machine learning with Bayesian inference, offering a comprehensive spatial–temporal analysis of compound flood risk from 1979 to 2022 in Hong Kong. We developed an ensemble machine learning approach within the Bayesian hierarchical modeling framework to achieve spatial–temporal continuity in the estimation of extreme storm surges and mean sea level at sites without tidal gauge stations. Results show a significant yearly increase in maximum storm surge levels by 3 mm and a significant rise in mean sea level of 25 mm per decade in Hong Kong. Our analysis also indicates a significant increase in daily heavy rainfall intensity. Furthermore, in 14.54 % of cases, extreme storm surges coincided with heavy rainfall, while 13.69 % of heavy rainfall events occurred alongside extreme sea level conditions. The copula-based joint analysis reveals significant positive correlations among these extreme events. Our findings further reveal that the return level for a 100-year heavy rainfall event increases dramatically from 126.36 mm in the univariate case to 261.16 mm in the trivariate scenario, underlining the escalated risk associated with compound flooding. Similarly, for storm surge extremes, trivariate analysis reveals elevated risk during compound flood events, with the return level rising from 1.18 m (univariate scenario) to 1.40 m (trivariate scenario) for a 100-year return period. These spatial–temporal maps and comprehensive compound flood risk assessments offer crucial insights for addressing the multi-hazard flood risk in coastal urban areas.

Imaging the May 2024 Extreme Aurora With Ionospheric Total Electron Content

AbstractThe continental United States is well instrumented with facilities for mid‐latitude upper atmosphere research that operate on a continuous basis. In addition, citizen scientists provide a wealth of information when unusual events occur. We combine ionospheric total electron content (TEC) data from distributed arrays of GNSS receivers, magnetometer chains, and auroral observations obtained by citizen scientists, to provide a detailed view of the intense auroral breakup and westward surge occurring at the peak of the 10–11 May 2024 extreme geomagnetic storm. Over a 20‐min interval, vertical TEC (vTEC) increased at unusually low latitude (∼45°) and rapidly expanded azimuthally across the continent. Individual receiver/satellite data sets indicate sharp bursts of greatly elevated of vTEC (∼50 TECu). Intense red aurora was co‐located with the leading edge of the equatorward and westward TEC enhancements, indicating that the large TEC enhancement was created by extremely intense low‐energy precipitation during the rapid substorm breakup.

An Evaluation of the Sediment Reduction Benefits of Soil and Water Conservation Measures under Extreme Rainfall Conditions in the Loess Plateau in China Based on a Distributed Soil Erosion Model

Since the 1970s, comprehensive control measures on soil erosion in the headwater region of the Loess Plateau have been carried out. Quantitative evaluation of the benefits of soil and water conservation measures during extreme rainstorms is of great significance for the comprehensive management of the catchments. In this study, a systematic modeling methodology for evaluating the effects of soil and water conservation measures on sediment reduction was developed based on a distributed soil erosion model (DSEM). Taking the Chabagou basin in the Loess Plateau as the study area, the tested DSEM was used to simulate soil erosion and sediment yield during an extreme rainstorm under two scenarios, the uncontrolled condition and the controlled condition with soil and water conservation measures implemented. The results showed that DSEM could successfully simulate soil and water losses and evaluate the effects of soil and water conservation measures during extreme storm events. The evaluated results showed that each soil and water conservation measure had the specific function of sediment reduction. And under rainstorm conditions, the effect of engineering measures on sediment reduction was greater than that of forest and grass measures.

Study of the dynamic response of an offshore continuous beam bridge under nonlinear wave and scour

The study highlights the critical factors and findings regarding bridge damage susceptibility during typhoons and hurricanes, primarily due to extreme waves, scour, and storm surges. While existing research has extensively studied bridges' responses to either extreme waves or scour individually, their combined effects have not been sufficiently explored. Experiments were conducted on a scaled two-span bridge to examine its behavior under simultaneous wave and scour conditions. Results from these experiments indicate that as scour depth increases, there is a corresponding escalation in displacement of the bridge pier, acceleration of the bearing platform, and strain along the pile foundation. To further investigate these dynamics, fluid-structure interaction analysis was employed, revealing significant insights. Notably, the study found that wave height exerts a substantial influence on wave load. For instance, at a wave height of 6 m, the average peak horizontal wave load on bridge piers was 2.48 times higher than at 3 m wave height. Moreover, local scour was identified as a critical factor reducing the bearing capacity of pile foundations, thereby significantly impacting the bridge's dynamic response to nonlinear waves. Under identical wave conditions, varying scour depths (3 m, 6 m, 9 m, and 12 m) resulted in increases in peak lateral displacements at the pier top compared to non-scouring conditions. The study concludes by emphasizing the increasing risk posed to pile foundations with deeper scour depths, particularly under stronger wave conditions. Consequently, there is a crucial need to enhance the resilience of offshore bridges against these dual hazards through advanced design and protective measures.

Projected changes of thermal, rainfall and drought indices in Morocco from high resolution climate models

Abstract Over the past decade, global changes in temperature, average and extreme precipitation have been observed many times. The increase in temperature or even the change in precipitation systems is directly affect extreme weather events, for example, heat waves, heavy rainfall, storms, and droughts are becoming more frequent and more powerful worldwide due to climate change caused by several factors including human activity. This is why there is a necessity to monitor future changes in climate extremes. The objective of this paper is to evaluate the future changes in thermal and rainfall extremes projected by the four climate models over time horizon 2041-2060 relative to the 1981-2010 reference period, based on the 5 climate indices, including Tmm, Tx90p, WSDI, PRCPTOT and SPI. The projections are given under the RCP 4.5 medium scenario. The analysis in thermal aspect shows that Morocco could experience by 2041-2060, a significant warming, has manifested by an increase in average temperature. Future changes in rainfall indices show that the spatial distribution of rainfall in Morocco could change significantly by 2041-2060 compared to the reference period 1971-2010. The four climate models agree on a decrease in annual precipitation that could affect most of the Kingdom. In the same way to dryness, the future changes of the SPI index that characterizes the drought, indicates a move to a dry climate.

Impact of climate change on child outcomes: an evidence gap map review

BackgroundClimate change and extreme weather events significantly threaten neonatal and child health. This review aims to provide a comprehensive overview of the current evidence on the impact of climate change...

Predicting storm surge extremes on the Southeast Brazilian Coast: Long-term projections with neural networks

Extreme sea level events, resulting from the confluence of tides and storm surges, pose a significant threat to coastal populations and economies. The escalating risks associated with these events are exacerbated by climate change, manifesting in heightened storm intensity, increased frequency, and rising sea levels. Precise estimation of the probability of extreme storm surges is crucial for effective coastal management and adaptation. However, utilizing historical storm data is challenging due to data scarcity and the imperative to consider potential non-stationarity induced by climate change in predicting such events. This study addresses these challenges by introducing two neural network-based machine learning systems: a Multilayer Perceptron (MLP) and a Long Short-Term Memory (LSTM). Leveraging local and remote atmospheric and oceanic conditions, these systems project storm surges until 2060, incorporating climate projections. Trained and evaluated using sea level data from Imbetiba Port in Macaé, Rio de Janeiro, Brazil, the models utilize dynamic regionalization data from the RegCM4 and WW3 models, forced by HadGEM2-ES and MPI climate models. Both neural network models exhibited similar performance patterns, demonstrating high agreement in predicting storm surge heights with a 100-year return value, based on Imbetiba Port data. Projections utilized peaks-over-threshold (POT) methods, and extremes were calculated using a generalized Pareto distribution (GPD). Long-term projections indicated a 28 % increase (MLP ANN) and a substantial 70 % increase (LSTM RNN) in estimating extreme values, surpassing the observed storm surge of 0.67 m. Projected mean values were 0.86 m for the MLP network and 1.15 m for the LSTM network, providing valuable insights into the potential amplification of extreme sea level events in the studied region.

Thermospheric Neutral Density Data Assimilation System Based on the Whole Atmosphere Model During the November 2003 Storm

AbstractThe Iterative Driver Estimation and Assimilation (IDEA) data assimilation technique was used with the Whole Atmosphere Model (WAM) to improve neutral density specification in the upper thermosphere. Two different neutral density data sources were examined to enhance the capability of simulating the global thermospheric state. The first were accelerometer estimates of neutral density from the Challenging Mini‐Satellite Payload (CHAMP) satellite. The second were neutral density estimates from the Global Ultraviolet Imager (GUVI) limb‐scan airglow observations aboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite. Due to the intensity of the November 2003 storm, two changes were necessary in WAM. The first was allowing the Kp geomagnetic index to exceed 9 and the second was changing the relationship between Kp and the solar wind parameters used to drive the model. With these changes, results show that IDEA effectively captures the thermospheric neutral density at the CHAMP satellite altitude and follows the time‐dependence through the November 2003 storm period. Furthermore, a cross‐comparison was conducted with the GUVI dayside limb scan measurements. GUVI neutral densities within 270–320 km show the closest agreement with WAM when CHAMP data was assimilated by IDEA. We speculate on the potential for observations from GUVI at 300 km to be used as a data source in the IDEA‐WAM simulations. These simulations demonstrate the utility of the IDEA data assimilation technique with physical models and that using either accelerometer observations or ultraviolet airglow limb measurement during extreme storm periods could be used.

Prototype data analysis of the dynamics of the Venice gate-barriers during an extreme storm event

The MoSE barriers system was designed and constructed at the inlets of the Venice Lagoon (Italy) in order to limit and tame the flooding events in the Lagoon areas and in the City. The success of the design and operation of the system has been demonstrated by the significant reduction in the number and intensity of floods in the lagoon since its beginning of operations in 2020. In this study, we investigate the dynamical behavior of the MoSE system at full-scale by analyzing the barriers behavior during the severe storm event of November 22nd, 2022. In particular, the dynamical response of the Chioggia barrier to waves and storm surge is studied in detail. Spectral analysis of field records, barrier and inlet modal analyses and Empirical Orthogonal Functions (EOF) techniques are applied to provide a key for interpreting the actual behavior of such a complex system during a storm event, highlighting dominant frequencies and checking for the occurrence of resonance phenomena. First, a brief review of the experimental and theoretical studies carried out over the past forty years is given. Modal patterns of gates oscillations detected via EOF analysis confirm the presence of the eigenmodes of both the barrier and the inlet; however, the gates oscillations during the considered event are mild and the hydraulic performances of the system are satisfactory for the severe event studied. Further field measurements and future severe events should be studied to reach extended conclusions.

Unveiling the Evolution of Extreme Rainfall Storm Structure Across Space and Time in a Warming Climate

AbstractClimate change induces significant changes in storm characteristics, particularly for short‐duration extreme storms (heavy rain features), impacting their intensity and spatio‐temporal distribution. Although alterations in precipitation intensity are well documented, past studies examining changes in spatio‐temporal distribution of storms (storm rainrates) were region‐specific and focused on isolated aspects of change in space or time, eluding a comprehensive understanding of the precise nature and extent of these changes. Bridging this gap, this study introduces a novel grid‐based measure of storm homogeneity, “spatio‐temporal homogeneity” metric and investigates the global patterns of change in combined spatio‐temporal characteristics of extreme storms. Analyzing the 30 min × 0.1° × 0.1° resolution Global Precipitation Measurements, the study finds that extreme storms are shrinking in both space and time due to rising surface air temperatures, predominantly in tropics. In contrast, temperate regions experience expanded extreme storms with increasing temperatures. The study also identifies a global trend toward more front‐loading in storms with rising temperatures, driven by a substantial increase in tropics and southern temperate regions. Conversely, storms in northern temperate regions become slightly more rear‐loaded as temperature increases. Furthermore, the study finds that characteristics of short–duration storms (6–12 hr) are more sensitive to temperature changes. Overall, this study contributes valuable insights into the global spatio‐temporal changes of extreme storms, highlighting regions most susceptible to alterations in storm patterns due to climate change. These findings are essential for developing effective adaptation strategies and flood management practices to cope with the changing nature of extreme storms in a warming climate.

Observational Overview of the May 2024 G5-Level Geomagnetic Storm: From Solar Eruptions to Terrestrial Consequences

This study reports comprehensive observations for the G5-level geomagnetic storm that occurred from May 10 to 12, 2024, the most intense event since the 2003 Halloween storm. The storm was triggered by a series of coronal mass ejections (CMEs) originating from the merging of two active regions 13664/13668, which formed a large and complex photospheric magnetic configuration and produced X-class flares in early May 2024. Among the events, the most significant CME, driven by an X2.2 flare on May 9, caught up with and merged with a preceding slower CME associated with an X-class flare on May 8. These combined CMEs reached 1 AU simultaneously, resulting in an extreme geomagnetic storm. Geostationary satellite observations revealed changes in Earth’s magnetosphere due to solar wind impacts, increased fluxes of high-energy particles, and periodic magnetic field fluctuations accompanied by particle injections. Extreme geomagnetic storms resulting from the interaction of the solar wind with the Earth’s magnetosphere caused significant energy influx into Earth’s upper atmosphere over the polar regions, leading to thermospheric heating and changes in the global atmospheric composition and ionosphere. As part of this global disturbance, significant disruptions were also observed in the East Asian sector, including the Korean Peninsula. Ground-based observations show strong negative storm effects in the ionosphere, which are associated with thermospheric heating and resulting in decreases in the oxygen-to-nitrogen ratio (O/N2) in high-latitude regions. Global responses of storm-time prompt penetration electric fields were also observed from magnetometers over the East-Asian longitudinal sector. We also briefly report storm-time responses of aurora and cosmic rays using all-sky cameras and neutron monitors operated by the Korea Astronomy and Space Science Institute (KASI). The extensive observations of the G5-level storm offer crucial insights into Sun-Earth interactions during extreme space weather events and may help establish better preparation for future space weather challenges.

Reconstruction of ionospheric VTEC using empirical orthogonal function and its performance during extreme geomagnetic storm

This paper demonstrates that the spatial distribution of the ionospheric TEC over the Indian region can be reconstructed with appreciable accuracy using minimal numbers of empirical orthogonal functions as a basis. These basis functions were derived using the Singular Value Decomposition of a matrix composed of pragmatic vertical Total Electron Content (VTEC) values collected across varied ionospheric conditions and measured over the region of interest. The reconstruction was achieved by linearly combining the appropriately chosen significant bases with corresponding weight factors. The reconstruction accuracy of the algorithm was found to be better than 4 TECU (TECU = 1016 electrons/m2) for more than 99.9 % of the time when tested over the complete year of 2016 with only eight basis vectors. The containment factor, defined here, indicates the goodness of the chosen bases in representing the arbitrary VTEC distributions and is found to remain typically high, aiding in improved algorithm performance. The performance, however, was found to be sensitive to the seasons and geomagnetic conditions. Deteriorated performance was observed when tested for the St. Patrick's Day storm data. The deterioration was attributed to the structural alteration of the ionospheric plasma density and the presence of atypical modes during the storm. The results ascertain the prospect of a faithful representation of the spatial distribution of the ionospheric VTEC using limited parametric variables, which may find utility in navigation, radar, and various other applications.