Strong Events Research Articles

Predicting the 2023/24 El Niño from a multi-scale and global perspective

The 2023/24 El Niño ranks as the second strongest event in the twenty-first century thus far. The event exhibited a two-step warming tendency and two warming centers, which could not be explained by the heat content buildup. Here, by conducting observational analysis and model experiments, we show that the record-breaking pantropical warming in 2023 mitigated this El Niño and confined the warming to the eastern basin, and that a series of westerly wind bursts induced another warming center in the central equatorial Pacific toward the end of 2023. Yet the effects of pantropical forcing and wind bursts coincidentally offset each other, leaving the heat content buildup appearing as the primary cause of the 2023/24 El Niño. Our results not only confirm the essential role of equatorial ocean heat recharge for El Niño development, but also demonstrate the necessity of accounting for multi-scale interactions from a global perspective to predict El Niño.

Exceptionally Strong Equatorial Intermediate Current Events in the Indian Ocean Associated with Climate Modes

Abstract Knowledge of the effects of climate modes on the equatorial intermediate current (EIC) remains limited. This paper investigates exceptional events of the EIC in the Indian Ocean and their relationships with climate modes at various time scales by using observations, reanalysis outputs, and a continuously stratified linear ocean model (LOM). A mooring at 80°E from 2015 to 2019 revealed four exceptionally strong EIC events, occurring in 2015 July–August (JA), 2016 January–February (JF), 2016 JA, and 2019 JF. Component analysis revealed that these exceptional events are attributed to the co-occurrence of the seasonal components peaking during JF and JA, as well as the larger current anomalies associated with intraseasonal and interannual components. In the intraseasonal band, the Madden–Julian oscillation (MJO) generates a significant EIC anomaly through a 40–50-day process involving equatorial waves. The MJO exerts a substantial effect when the amplitude of the MJO index exceeds 1 and the oscillation is in phase 4. In the interannual band, El Niño–Southern Oscillation and the Indian Ocean dipole (IOD) can each independently contribute to the EIC anomaly. This contribution initiates during the mature phase and persists throughout the subsequent year. Concurrent occurrences of these effects can lead to larger interannual anomalies. Notably, El Niño–positive IOD (El Niño–pIOD) and La Niña–negative IOD (La Niña–nIOD) synergies are most pronounced in August and in January of the following year. Significance Statement Four exceptional equatorial intermediate current (EIC) events characterized by strong eastward velocities are observed in the Indian Ocean during 2015–19. This study explored their underlying dynamics and their relationships with climate modes. Climatologically, the EIC has seasonal cycles with peaks in January–February and July–August, which is helpful in producing exceptional EIC events. However, the occurrence of these events is attributed to the intensity of the intraseasonal and interannual variability that occurs around the seasonal cycle peaks. This study revealed that climate modes, including the Madden–Julian oscillation (MJO), El Niño–Southern Oscillation (ENSO), and Indian Ocean dipole (IOD), contribute to exceptional EIC events in the intraseasonal and interannual bands. Notably, their influence is comparable, albeit contingent upon specific conditions.

The history of the El Niño–Southern Oscillation and sea surface salinity during 1376–1500 CE reconstructed by Porites coral δ18O from Huangyan Island, South China Sea

The El Niño–Southern Oscillation (ENSO) is the most influential climatic phenomenon affecting global ecosystems, water use, and agriculture on an interannual scale. However, limited instrumental records make it difficult to fully understand the characteristics of ENSO events. In this study, we used both monthly-resolved Porites coral δ18O records, i.e., living Porites corals of δ18O–HYDL4 (1992–2015) and subfossil Porites corals of δ18O–HYD3 (1376–1500 CE), from Huangyan Island in the South China Sea (SCS), to reconstruct the moderate intensity ENSO and sea surface salinity (SSS) during 1376–1500 CE. The results show that the SSS was higher but the frequency of moderate-to-high intensity ENSO events was lower than the present during 1376–1500 CE. ENSO activity was generally similar to or slightly lower than that of today, but it included several very strong ENSO events in the first substage of 1376–1450 CE, while it was relatively quiet in the second substage of 1451–1500 CE. More moderate-intensity ENSO events may have occurred in the relatively warm climate. The variation in coral δ18O was dominated by multiple factors in this region. SST, ENSO and the Pacific Decadal Oscillation (PDO) may be the dominant factors influencing the changes in coral δ18O at different timescales.

Artificial Intelligence-Based Precipitation Estimation Method Using Fengyun-4B Satellite Data

This paper proposes a novel precipitation estimation method based on FY-4B meteorological satellite data (FY-4B_AI). This method facilitates the spatiotemporal matching of 125 features derived from the multi-temporal and multi-channel data of the FY-4B satellite with precipitation data at stations. Subsequently, a precipitation model was constructed using the light gradient boosting machine (LGBM) algorithm. A comparative analysis of FY-4B_AI and GPM/IMERG-L products for over 450 million station cases throughout 2023 revealed the following: (1) The results demonstrate that FY-4B_AI is more accurate than GPM/IMERG-L. Six of the eight evaluation indices exhibit superior performance for FY-4B_AI in comparison to GPM/IMERG-L. These indices include the mean absolute error (MAE), root mean square error (RMSE), relative error (RE), correlation coefficient (CC), probability of detection (POD), and critical success index (CSI). As for the MAE, the results are 1.67 (FY-4B_AI) and 1.92 (GPM/IMERG-L), respectively. The RMSEs are 3.68 and 4.07, respectively. The REs are 17.72% and 26.28%, respectively. The CCs are 0.44 and 0.36, respectively. The PODs are 61.84% and 47.31%, respectively. The CSIs are 0.30 and 0.27, respectively. However, with regard to the mean errors (MEs) and false alarm rates (FARs), FY-4B_AI (−0.88 and 62.85%, respectively) displays a slight degree of inferiority in comparison to GPM/IMERG-L (−0.80 and 62.21%, respectively). (2) An evaluation of two strong weather events to represent the spatial distribution of precipitation in different climatic zones revealed that both FY-4B_AI and GPM/IMERG-L are equally capable of accurately representing these phenomena, irrespective of whether the region in question is humid, as is the case in the southeast, or dry, as is the case in the northwest.

Strong coupling between the East Asian summer monsoon and regional hydrological conditions as evidenced by multiproxy stalagmite records for the last deglaciation

Millennial-to centennial-scale abrupt climate events during the last glacial‒interglacial transition have significant relevance to modern-day extreme climate changes, which are occurring more frequently in the context of global warming. However, the regional expression of humidity conditions during the last deglaciation and their possible forcing mechanism in northern China are controversial. Here, combined with published δ18O data, we report 35-year-resolved δ13C and 76-year-resolved Mg/Ca and Sr/Ca records from a stalagmite from 15.3 to 10.9 ka BP from Lianhua Cave, northern China. The LH4 stalagmite δ18O record clearly records a weak monsoon event during the Younger Dryas (YD) from 12.8 to 11.6 ka BP and a strong monsoon event during the Bølling-Allerød (BA) from 14.6 to 12.8 ka BP. In addition, the δ13C and trace element ratio records, which represent local hydroclimatic changes, indicate wetter conditions during the BA and drier conditions during the YD, which appear to match well with the δ18O variations on the millennial timescale. A comparison of 28 records from 17 sites along the modern margin of the China summer monsoon revealed that the BA was characterized by wet conditions; inversely, the YD was characterized by dry conditions throughout northern China, which is obviously different from the consensus of the wet YD and the dry BA in northern northeastern China. The covariance in northern China suggests that the hydrological variation may be modulated by the advance and retreat of the large-scale East Asian summer monsoon (EASM) circulation. Further comparison revealed an anticorrelated relationship between millennial-scale precipitation changes in northern China and the middle‒lower reaches of the Yangtze River Valley during the last deglaciation. This correlation is analogous to the dipole precipitation mode at present, which is likely associated with the strength and position of the westerly jet and/or the western Pacific subtropical high, both of which play important roles in the spatial distribution of precipitation over eastern China.

Predictability of the 2020 Strong Vortex in the Antarctic Stratosphere and the Role of Ozone

AbstractThe Antarctic vortex of October–December 2020 was the strongest on record in the satellite era for the season in the mid‐ to lower stratosphere. However, it was poorly predicted by the Australian Bureau of Meteorology's operational seasonal climate forecast system of that time, ACCESS‐S1, even at a short lead time of a month. Using the current operational forecast system, ACCESS‐S2, we have, therefore, tried to find a primary cause of the limited predictability of this event and conducted forecast sensitivity experiments to understand the potential role of ozone in the event and its associated anomalies of the Southern Annular Mode (SAM) and rainfall over south–eastern Australia and western Patagonia. Here, we show that the 2020 strong vortex event did not follow the canonical dynamical evolution seen in previous strong vortex events in spring but suddenly appeared as a result of the record‐low upward propagating wave activity in September 2020. The ACCESS‐S2 forecasts significantly underestimated the negative wave forcing in September even at zero lead time, irrespective of the ozone configuration, therefore falling short in predicting the record strength of the polar vortex in late spring 2020. Nevertheless, ACCESS‐S2 with prescribed realistic ozone that had large anomalies in the Antarctic stratosphere significantly better predicted the strong vortex and the subsequent positive SAM and related rainfall anomalies over south–eastern Australia and western Patagonia in the austral summer of 2020–21. This highlights the potentially important role of ozone variations for seasonal climate forecasting as a source of long‐lead predictability.

Analysis of the interrelationship between precipitation and confirmed dengue cases in the city of Recife (Brazil) covering climate and public health information.

Large-scale epidemics of arboviruses, such as dengue, have heightened societal awareness regarding the necessity of combating the primary transmission vectors. Equally critical is the identification of environmental conditions and variables that influence vector population dynamics. Aedes aegypti, the primary vector of arboviruses such as dengue and Zika in Brazil, is closely associated with the climatic and geographical conditions of urban environments. This study examines the relationship between precipitation and confirmed dengue cases in Recife (Brazil), employing regression and quantile analyses to evaluate the influence of meteorological conditions on the disease's spread. The findings reveal a direct correlation between monthly averages of precipitation and confirmed cases, although this is apparent only when excluding years of epidemic peaks. The highest number of cases generally aligns with the rainy season, and the lowest with the dry season, with weak, moderate and strong precipitation events being closely linked to increased dengue incidence. However, notable discrepancies were identified: four out of six major outbreaks occurred in drier months, challenging the assumption of a straightforward relationship between rainfall and dengue incidence. These findings underscore the multifaceted nature of dengue dynamics, suggesting that while precipitation plays a significant role, other factors, including serotype circulation and broader climatic phenomena, are equally critical in driving outbreaks. This complexity highlights the need for a more comprehensive understanding of the mechanisms influencing dengue epidemics.

Analyzing the seismic hazard of Jishishan earthquake based on multi-source data

Abstract. An Ms6.2 earthquake occurred in Jishishan County, Linxia Hui Autonomous Prefecture, Gansu Province on December 18, 2023, which is another strong earthquake event that occurred in the eastern and northeast margin of the Qinghai-Tibet Plateau after the Ms6.8 Luding earthquake in 2022. To determine the spatial characteristics and human casualties of the earthquake, this paper obtains the seismic spatial information based on remote sensing data. The results show that the earthquake has thrust characteristics and is a thrust-type earthquake, in which the line-of-sight deformation of the lifting and falling rail coseismic deformation fields are mainly uplifted, 7.51cm, and 7.91cm respectively. At the same time, the PSO-BiLSTM-Attention population casualty model is proposed, and 149 people are predicted to die, which is 2 people less than the actual 151 people, indicating that the model can well estimate the post-disaster death toll and can be used for the post-disaster death population assessment.

K-means for earthquakes: disaggregation analyses of small events by considering wave components and soil types

In this paper, k-means algorithm has been used to disaggregate seismic parameters to evaluate their inter-correlations. A goal is to quantify in a disaggregated way the weights and effects of each parameter with respect to other ones. From the database, about 4900.0 data, divided into 22.0 categories, have been collected. The main divisions regard the wave components in horizontal and vertical axis and the soil characteristics. The studied seismic zone is the “Norpirenaica oriental,” placed in the Pyrenees area between Spain and France, classified as a very high seismic hazard. Numerical and analytical analyses have been carried out to implement the algorithm. Preliminary analyses and results would quantify the role of the sand horizontal stratigraphy, the non-linear effects, the elasticity of the soil, and the energy damping phenomenon. Curves are plotted in stochastic distributions and elastic spectra accelerations. Results show good prediction for vertical spectral accelerations and for far and relative strong events. Rigorously, results are valid only for the studied seismogenic zone under predefined constrictions and ranges.

Opportunities and barriers for skillful sub-seasonal prediction of East Asian summer precipitation

Abstract Accurate sub-seasonal (2-8 weeks) prediction of monsoon precipitation is crucial for mitigating flood and heatwave disasters caused by intra-seasonal variability (ISV). However, current state-of-the-art sub-seasonal-to-seasonal (S2S) models have limited prediction skills beyond one week when predicting weekly precipitation. Our findings suggest that predictability primarily arises from strong ISV events, and the prediction skills for ISV events depend on the propagation stability of preceding signals, regardless of models. This allows us to identify opportunities and barriers (OBs) within S2S models, clarifying what the models can and cannot achieve in ISV event prediction. Focusing on the complex East Asian summer monsoon (EASM), we discover that stable propagation of Eurasian and tropical atmospheric wave trains towards East Asia serves as an opportunity. This opportunity offers a one-week leading prediction skill of up to 0.85 and skillful prediction up to 13 days ahead for 43% of all ISV events. However, the Tibetan Plateau barrier highlights the limitation of EASM predictability. Identifying these OBs will help us gain confidence in making more accurate sub-seasonal prediction.

Forecasting strong subsequent events in the Italian territory: a national and regional application for NESTOREv1.0

AbstractThe Italian territory is one of the most seismically active areas in Europe, where Strong Subsequent Events (SSEs), in combination with the strong mainshock effects, can lead to the collapse of already weakened buildings and to further loss of lives. In the last few years, the machine learning-based algorithm NESTORE (Next STrOng Related Earthquake) was proposed and used to forecast clusters in which the mainshock is followed by a SSE of similar magnitude. Recently, a first new version of a MATLAB package based on this algorithm (NESTOREv1.0) has been developed and the code has been further improved. In our analysis, we considered a nationwide and a regional catalogue for Italy to study the seismicity recorded over the last 40 years in two areas covering most of the Italian territory and northeastern Italy, respectively. For both applications, we obtained statistical information about the clusters in terms of duration, productivity and release of seismic moment. We trained NESTOREv1.0 on the clusters occurring approximately in the first 30 years of catalogues and we evaluated its performance on the last 10 years. The results showed that 1 day after the mainshock occurrence the rate of correct SSE forecasting is larger than 85% in both areas, supporting the application of NESTOREv1.0 in the Italian territory. Furthermore, by training the software on the entire period available for the two catalogues, we obtained good results in terms of near-real-time class forecasting for clusters recorded from 2021 onward.

Precise and Accurate Short-term Forecasting of Solar Energetic Particle Events with Multivariate Time-series Classifiers

Solar energetic particle (SEP) events are one of the most crucial aspects of space weather that require continuous monitoring and forecasting using robust methods. We demonstrate a proof of concept of using a data-driven supervised classification framework on a multivariate time-series data set covering solar cycles 22, 23, and 24. We implement ensemble modeling that merges the results from three proton channels (E ≥ 10 MeV, 50 MeV, and 100 MeV) and the long-band X-ray flux (1–8 Å) channel from the Geostationary Operational Environmental Satellite missions. Our task is binary classification, such that the aim of the model is to distinguish strong SEP events from nonevents. Here, strong SEP events are those crossing the Space Weather Prediction Center’s “S1” threshold of solar radiation storm and proton fluxes below that threshold are weak SEP events. In addition, we consider periods of nonoccurrence of SEPs following a flare with magnitudes ≥C6.0 to maintain a natural imbalance of sample distribution. In our data set, there are 244 strong SEP events comprising the positive class. There are 189 weak events and 2460 “SEP-quiet” periods for the negative class. We experiment with summary statistic, one-nearest neighbor, and supervised time-series forest (STSF) classifiers and compare their performance to validate our methods for prediction windows from 5 minutes up to 60 minutes. We find the STSF model to perform better under all circumstances. For an optimal classification threshold of ≈0.3 and a 60 minutes prediction window, we obtain a true skill statistic TSS = 0.850, Heidke skill score HSS = 0.878, and Gilbert skill score GSS = 0.783.

On the low-latitude ionospheric irregularities under geomagnetically active and quiet conditions using NavIC observables: A spectral analysis approach

Ionospheric irregularities and associated scintillations under geomagnetically active/quiet conditions have detrimental effects on the reliability and performance of space- and ground-based navigation satellite systems, especially over the low-latitude region. The current work investigates the low-latitude ionospheric irregularities using the phase screen theory and the corresponding temporal Power Spectral Density (PSD) analysis to present an estimate of the outer irregularity scale sizes over these locations. The study uses simultaneous L5 signal C/No observations of NavIC (a set of GEO and GSO navigation satellite systems) near the northern crest of EIA (Indore: 22.52∘N, 75.92∘E, dip: 32.23∘N) and in between the crest and the dip equator (Hyderabad: 17.42∘N, 78.55∘E, dip: 21.69∘N). The study period (2017–2018) covers disturbed and quiet-time conditions in the declining phase of the solar cycle 24. The PSD analysis brings forward the presence of irregularities, of the order of a few hundred meters during weak-to-moderate and quiet-time conditions and up to a few km during the strong event, over both locations. The ROTI values validate the presence of such structures in the Indian region. Furthermore, only for the strong event, a time delay of scintillation occurrence over Indore, with values of 36 min and 50 min for NavIC satellites (PRNs) 5 and 6, respectively, from scintillation occurrence at Hyderabad is observed, suggesting a poleward evolution of irregularity structures. Further observations show a westward propagation of these structures on this day. This study brings forward the advantage of utilizing continuous data from the GEO and GSO satellite systems in understanding the evolution and propagation of the ionospheric irregularities over the low-latitude region.

Intercomparison of WRF-chem aerosol schemes during a dry Saharan dust outbreak in Southern Iberian Peninsula

The Iberian Peninsula (IP), where this study is conducted, has experienced an increase of the frequency and intensity of Saharan aerosol dust outbreaks over the latest decades, which may have an impact on its regional climate. The Weather Research and Forecasting model coupled with chemistry (WRF-chem) has been used worldwide to simulate dust outbreaks and can support the analysis of such potential impacts. However, it includes multiple alternative aerosol parameterization choices that have not been conveniently evaluated in the study region yet. Here, three of the most popular WRF-chem aerosol parameterization schemes, namely, the Goddard Chemistry Aerosol Radiation and Transport (GOCART), the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) and the Modal Aerosol Dynamics Model for Europe (MADE) schemes, are inter-compared during a strong and dry dust outbreak on July 2021 in southern IP. The results show that the three schemes predict qualitatively similar dust intrusion patterns that are consistent with ground observations and have inter-model dust loading differences smaller than 4%. However, their average dust size distributions differ notably. While GOCART is reasonably consistent with observations, MOSAIC underpredicts the amount of dust particles with sub-micron diameters and overpredicts that of large particles and MADE does the opposite. This is found to have a strong detrimental impact on the prediction performance of dust optical properties in MOSAIC and MADE, which is related, at least partially, with issues in the required inter-sectional redistribution of dust parameters during the dust emission and calculation of optical properties. Overall, GOCART generally appears a better choice for strong and dry dust outbreak events in southern IP. It remains to be evaluated during wet dust outbreaks, which is a work underway.

The Impact of the 8–10 March 2012 Geomagnetic Storm on Inner Zone Protons as Measured by Van Allen Probes

AbstractThe Relativistic Electron Proton Telescope (REPT) instrument on the Van Allen Probes observed a double‐peaked inner zone proton population throughout the 7 year lifetime of the mission. M. Hudson et al. (2023) showed that a strong SEP event accompanied by a CME‐shock in early March 2012 provided the Solar Energetic Proton (SEP) source for the higher L trapped proton population, which then diffused radially inward to be observed by REPT at . The study followed trajectories of SEP protons launched isotropically from a sphere at 7 Re for 2.5 hr in fields calculated by the LFM‐RCM global MHD model, which includes electric fields needed to model the transport and trapping of the protons by the shock, and then a radial diffusion simulation was run for 2 years using the result from the test‐particle simulation as the initial condition. The simulation result was compared with REPT measurement in November 2013 and showed reasonable agreement. However, the simulation overestimated the Phase Space Density by a factor of four due to lack of field line curvature scattering during the storm in the model. In this study, a test‐particle simulation is performed for 2 days following the injection and trapping of protons in March 2012 using TS05 fields to simulate the field line curvature scattering of the trapped SEP due to the buildup of the ring current during the geomagnetic storm. The resulting sample distribution was then weighted using the flux at the end of the two‐hour MHD‐test particle simulation. A radial diffusion simulation is then run using the initial profile that included the loss effect, with improved comparison with REPT measurements after 2 years.

Exploring the integration of InSAR data into climate‐driven creep models to assess slow‐moving landslide dynamics

AbstractThe deformation behavior of slow‐moving large landslides is often governed by rainfall characteristics. Based on observational data such as precipitation, deformation measurement, and pore water pressure measurements in the slip zone, in many cases a strong correlation between strong rainfall events, a time‐delayed increase of pore water pressures in the slip zone, and, simultaneously to this, an increase of the deformation rate of the landslide can be found. Based on such detailed data, calculation models, which couples the relation between rainfall characteristics and the development of pore water pressures in the slip zone on one hand and the deformation behavior of the slope on the other, can be developed and be used for a better understanding and a prediction of deformation behavior of such slow‐moving landslides. Climate change issues will lead to a change in rainfall frequency and magnitude and annual temperature distribution characteristics in several regions worldwide, which will also lead to changes in the deformation behavior of such large landslides. In this contribution, satellite‐based interferometric synthetic aperture radar (InSAR) data are discussed to be used as source for deformation measurements as bases for prediction models describing the rainfall‐triggered deformation behavior of slow‐moving landslides.

Do coastal or equatorial wind anomalies drive the Indian Ocean Dipole?

Based on first scientific principles, this study shows that both equatorial and coastal wind anomalies influence the development of positive phases of the Indian Ocean Dipole (IOD) in the south-east tropical Indian Ocean (SETIO). While southeasterly winds are favorable for upwelling along Sumatra's southwest coast, zonal equatorial wind anomalies are the main control of IOD variability given that the resultant Kelvin wave enhances or suppresses the Sumatran upwelling. Many previous studies have argued that easterly equatorial wind anomalies in the SETIO are essential for triggering the positive Bjerknes feedback, and thereby, the development of positive IOD (pIOD) events. With a focus on the particularly strong pIOD event of 2019, here we show that pIOD events can also evolve in the absence of zonal equatorial wind anomalies. Hence, it is possible that the Bjerknes feedback along the equator is less involved in IOD variability than previously thought.

Geomagnetic and ionospheric effects two consecutive strong earthquakes in Morocco on september 08, 2023

The geophysical effects of a strong seismic event in the form of two earthquakes of magnitude 6.8 and 4.9 that occurred on September 08, 2023 in Morocco at close times 22:11 and 22:30 UTC with an epicentral distance between the foci of ~ 4 km are considered. We used data from a number of observatories of the INTERMAGNET network and the results of magnetic registration at the Mikhnevo Geophysical Observatory of IDG RAS. It was shown that in the absence of significant global disturbances of the Earth’s magnetic field, earthquakes were accompanied by a series of three positive bay-shaped geomagnetic variations with maximum amplitudes from ~1 to ~10 nT, following each other after ~60 min. The maxima of the induced magnetic field variations were observed almost synchronously at distances from ~800 to ~10000 km. The delay time of the magnetic effect relative to the main shock of the first earthquake was ~70 min. Taking into account the almost planetary nature and high synchronicity of the magnetic field disturbances caused over a significant range of distances, as well as time delays corresponding in order of magnitude to the travel time of the seismic signal of a distance multiple of the size of the Earth, it is suggested that the magnetic effect of the seismic event in question was caused by a global source, which can serve as an excited geodynamo. The ionospheric effect of the seismic event under consideration is presented in the form of variations of the critical frequency f0F2 calculated from the data of the ground-based sounding station of the del Ebre Observatory.

Revisiting empirical solar energetic particle scaling relations

Aims. The space radiation environment conditions and the maximum expected coronal mass ejection (CME) speed are assessed by investigating scaling laws between the peak proton flux and fluence of solar energetic particle (SEP) events with the speed of the CMEs. Methods. We used a complete catalog of SEP events, covering the last ∼25 years of CME observations (i.e., 1997–2017). We calculated the peak proton fluxes and integrated event fluences for events that reached an integral energy of up to E > 100 MeV. For a sample of 38 strong SEP events, we first investigated the statistical relations between the recorded peak proton fluxes (IP) and fluences (FP) at a set of integral energies of E > 10 MeV, E > 30 MeV, E > 60 MeV, and E > 100 MeV versus the projected CME speed near the Sun (VCME) obtained by the Solar and Heliospheric Observatory/Large Angle and Spectrometric Coronagraph (SOHO/LASCO). Based on the inferred relations, we further calculated the integrated energy dependence of both IP and FP, assuming that they follow an inverse power law with respect to energy. By making use of simple physical assumptions, we combined our derived scaling laws to estimate the upper limits for VCME, IP, and FP by focusing on two cases of known extreme SEP events that occurred on 23 February 1956, (GLE05) and in AD774/775, respectively. Based on the physical constraints and assumptions, several options for the upper limit VCME associated with these events were investigated. Results. A scaling law relating IP and FP to the CME speed as VCME5 for CMEs ranging between ∼3400–5400 km/s is consistent with values of FP inferred for the cosmogenic nuclide event of AD774/775. At the same time, the upper CME speed that the current Sun can provide possibly falls within an upper limit of VCME ≤ 5500 km/s.

Association between compound extreme weather event types and the spectrum of emergency ambulance calls: A metropolitan study in Shenzhen

Compound extreme weather events, a combination of weather and climate drivers that lead to potentially high-impact events, are becoming more frequent with climate change. The number of emergency ambulance calls (EACs) is expected to increase during compound extreme weather events. However, the extent of these increases and the trends over time have not been fully assessed. We obtained 242,165 EAC records for Shenzhen from January 1, 2020, to June 30, 2023. A compound extreme weather event was defined as the occurrence of at least two extreme weather events on the same day. A distributed lag non-linear model was used to explore the exposure-response and lag-response relationships between various compound extreme weather events and all-cause and specific-cause EACs. Compound Cold & Strong Monsoon events had more significant impacts on EACs for all causes and endocrine diseases, with the cumulative relative risk (CRR) of 1.401 (95% confidence interval (CI):1.290-1.522) and 1.641 (95% CI:1.279-2.105). Compound Heat Wave & Lightning events had more obvious impacts on digestive disease and endocrine disease EACs, with the CRRs of 1.185 (95% CI:1.041-1.348) and 1.278 (95% CI:0.954-1.711), respectively. Compound Rainstorm & Lightning & Heat Wave events also led to increased RRs of EACs for all causes (CRR: 1.168, 95% CI:1.012-1.348), cardiovascular diseases (CRR: 1.221, 95% CI:0.917-1.624), digestive diseases (CRR: 1.395, 95% CI:1.130-1.721), and endocrine diseases (CRR: 1.972, 95% CI:1.235-3.149). There was no increased RR in the compound Rainstorm & Lightning events for all types of EACs. Our study explored the relationship between EACs and compound extreme weather events, suggesting that compound extreme weather events are associated with the acute onset of cardiovascular diseases, digestive diseases, and endocrine diseases, increasing the burden on emergency ambulance resources for both all causes and specific diseases mentioned above.