2023: Weather and Climate Extremes Hitting the Globe with Emerging Features

Globally,2023 was the warmest observed year on record since at least 1850 and,according to proxy evidence,possibly of the past 100000 years.As in recent years,the record warmth has again been accompanied with yet more extreme weather and climate events throughout the world.Here,we provide an overview of those of 2023,with details and key background causes to help build upon our understanding of the roles of internal climate variability and anthropogenic climate change.We also highlight emerging features associated with some of these extreme events.Hot extremes are occurring earlier in the year,and increasingly simultaneously in differing parts of the world(e.g.,the concurrent hot extremes in the Northern Hemisphere in July 2023).Intense cyclones are exacerbating precipitation extremes(e.g.,the North China flooding in July and the Libya flooding in September).Droughts in some regions(e.g.,California and the Horn of Africa)have transitioned into flood conditions.Climate extremes also show increasing interactions with ecosystems via wildfires(e.g.,those in Hawaii in August and in Canada from spring to autumn 2023)and sandstorms(e.g.,those in Mongolia in April 2023).Finally,we also consider the challenges to research that these emerging characteristics present for the strategy and practice of adaptation.

Assessment of the Spatio-Temporal Trends of Annual Extreme Temperature Indices over Tanzania during the Period of 1982-2022

Extreme weather and climatic phenomena, such as heatwaves, cold waves, floods and droughts, are expected to become more common and have a significant impact on ecosystems, biodiversity, and society. Devastating disasters are mostly caused by record-breaking extreme events, which are becoming more frequent throughout the world, including Tanzania. A clear global signal of an increase in warm days and nights and a decrease in cold days and nights has been observed. The present study assessed the trends of annual extreme temperature indices during the period of 1982 to 2022 from 29 meteorological stations in which the daily minimum and maximum data were obtained from NASA/POWER. The Mann-Kendall and Sen slope estimator were employed for trend analysis calculation over the study area. The analyzed data have indicated for the most parts, the country has an increase in warm days and nights, extreme warm days and nights and a decrease in cold days and nights, extreme cold days and nights. It has been disclosed that the number of warm nights and days is on the rise, with the number of warm nights trending significantly faster than the number of warm days. The percentile-based extreme temperature indices exhibited more noticeable changes than the absolute extreme temperature indices. Specifically, 66% and 97% of stations demonstrated positive increasing trends in warm days (TX90p) and nights (TN90p), respectively. Conversely, the cold indices demonstrated 41% and 97% negative decreasing trends in TX10p and TN10p, respectively. The results are seemingly consistent with the observed temperature extreme trends in various parts of the world as indicated in IPCC reports.

Extreme value theory applied to the auroral electrojet indices

The study of extreme weather and space events has gained paramount importance in modern society owing to rapid advances in high technology.Understanding and describing exceptional occurrences plays a crucial role in making decisive assessments of their potential impact on technical,economic,and social aspects in various fields.This research focuses on analyzing the hourly values of the auroral electrojet(AE)geomagnetic index from 1957 to 2019 by using the peak over threshold method in extreme value theory.By fitting the generalized Pareto distribution to extreme AE values,shape parameter indices were derived,revealing negative values that establish an upper bound for this time series.Consequently,it became evident that the AE values had reached a plateau,suggesting that extreme events exceeding the established upper limit are rare.As a result,although the need for diligent precautions to mitigate the consequences of such extreme events persists,surpassing the upper limit of AE values becomes increasingly challenging.It is also possible to observe an aurora in the middle-and low-latitude regions during the maximum period of the AE index.

Competitive oxidation behavior of Ni-based superalloy GH4738 at extreme temperature

A high thrust-to-weight ratio poses challenges to the high-temperature performance of Ni-based superalloys. The oxidation behavior of GH4738 at extreme temperatures has been investigated by isothermal and non-isothermal experiments. As a result of the competitive diffusion of alloying elements, the oxide scale included an outermost porous oxide layer (OOL), an inner relatively dense oxide layer (IOL), and an internal oxide zone (IOZ), depending on the temperature and time. A high temperature led to the formation of large voids at the IOL/IOZ interface. At 1200℃, the continuity of the Cr-rich oxide layer in the IOL was destroyed, and thus, spallation occurred. Extension of oxidation time contributed to the size of Al-rich oxide particles with the increase in the IOZ. Based on this finding,the oxidation kinetics of GH4738 was discussed, and the corresponding oxidation behavior at 900-1100℃ was predicted.

Impacts of Future Changes in Heavy Precipitation and Extreme Drought on the Economy over South China and Indochina

Heavy precipitation and extreme drought have caused severe economic losses over South China and Indochina(INCSC)in recent decades.Given the areas with large gross domestic product(GDP)in the INCSC region are distributed along the coastline and greatly affected by global warming,understanding the possible economic impacts induced by future changes in the maximum consecutive 5-day precipitation(RX5day)and the maximum consecutive dry days(CDD)is critical for adaptation planning in this region.Based on the latest data released by phase 6 of the Coupled Model Intercomparison Project(CMIP6),future projections of precipitation extremes with bias correction and their impacts on GDP over the INCSC region under the fossil-fueled development Shared Socioeconomic Pathway(SSP5-8.5)are investigated.Results indicate that RX5day will intensify robustly throughout the INCSC region,while CDD will lengthen in most regions under global warming.The changes in climate consistently dominate the effect on GDP over the INCSC region,rather than the change of GDP.If only considering the effect of climate change on GDP,the changes in precipitation extremes bring a larger impact on the economy in the future to the provinces of Hunan,Jiangxi,Fujian,Guangdong,and Hainan in South China,as well as the Malay Peninsula and southern Cambodia in Indochina.Thus,timely regional adaptation strategies are urgent for these regions.Moreover,from the sub-regional average viewpoint,over two thirds of CMIP6 models agree that maintaining a lower global warming level will reduce the economic impacts from heavy precipitation over the INCSC region.

The 2022 Extreme Heatwave in Shanghai,Lower Reaches of the Yangtze River Valley:Combined Influences of Multiscale Variabilities

In the summer of 2022,China(especially the Yangtze River Valley,YRV)suffered its strongest heatwave(HW)event since 1961.In this study,we examined the influences of multiscale variabilities on the 2022 extreme HW in the lower reaches of the YRV,focusing on the city of Shanghai.We found that about 1/3 of the 2022 HW days in Shanghai can be attributed to the long-term warming trend of global warming.During mid-summer of 2022,an enhanced western Pacific subtropical high(WPSH)and anomalous double blockings over the Ural Mountains and Sea of Okhotsk,respectively,were associated with the persistently anomalous high pressure over the YRV,leading to the extreme HW.The Pacific Decadal Oscillation played a major role in the anomalous blocking pattern associated with the HW at the decadal time scale.Also,the positive phase of the Atlantic Multidecadal Oscillation may have contributed to regulating the formation of the double-blocking pattern.Anomalous warming of both the warm pool of the western Pacific and tropical North Atlantic at the interannual time scale may also have favored the persistency of the double blocking and the anomalously strong WPSH.At the subseasonal time scale,the anomalously frequent phases 2-5 of the canonical northward propagating variability of boreal summer intraseasonal oscillation associated with the anomalous propagation of a weak Madden-Julian Oscillation suppressed the convection over the YRV and also contributed to the HW.Therefore,the 2022 extreme HW originated from multiscale forcing including both the climate warming trend and air-sea interaction at multiple time scales.

Extreme drought with seasonal timing consistently promotes CH_(4) uptake through inconsistent pathways in a temperate grassland, China

Methane(CH_(4))is a potent greenhouse gas that has a substantial impact on global warming due to its substantial influence on the greenhouse effect.Increasing extreme precipitation events,such as drought,attributable to global warming that caused by greenhouse gases,exert a profound impact on the intricate biological processes associated with CH_(4) uptake.Notably,the timing of extreme drought occurrence emerges as a pivotal factor influencing CH_(4) uptake,even when the degree of drought remains constant.However,it is still unclear how the growing season regulates the response of CH_(4) uptake to extreme drought.In an effort to bridge this knowledge gap,we conducted a field manipulative experiment to evaluate the impact of extreme drought on CH_(4) uptake during early,middle,and late growing stages in a temperate steppe of Inner Mongolia Autonomous Region,China.The result showed that all extreme drought consistently exerted positive effects on CH_(4) uptake regardless of seasonal timing.However,the magnitude of this effect varied depending on the timing of season,as evidenced by a stronger effect in early growing stage than in middle and late growing stages.Besides,the pathways of CH_(4) uptake were different from seasonal timing.Extreme drought affected soil physical-chemical properties and aboveground biomass(AGB),consequently leading to changes in CH_(4) uptake.The structural equation model showed that drought both in the early and middle growing stages enhanced CH_(4) uptake due to reduced soil water content(SWC),leading to a decrease in NO_(3)–-N and an increase in pmoA abundance.However,drought in late growing stage primarily enhanced CH_(4) uptake only by decreasing SWC.Our results suggested that seasonal timing significantly contributed to regulate the impacts of extreme drought pathways and magnitudes on CH_(4) uptake.The findings can provide substantial implications for understanding how extreme droughts affect CH_(4) uptake and improve the prediction of potential ecological consequence under future climate change.

Multiple mixed state variable incremental integration for reconstructing extreme multistability in a novel memristive hyperchaotic jerk system with multiple cubic nonlinearity

Memristor-based chaotic systems with infinite equilibria are interesting because they generate extreme multistability.Their initial state-dependent dynamics can be explained in a reduced-dimension model by converting the incremental integration of the state variables into system parameters.However,this approach cannot solve memristive systems in the presence of nonlinear terms other than the memristor term.In addition,the converted state variables may suffer from a degree of divergence.To allow simpler mechanistic analysis and physical implementation of extreme multistability phenomena,this paper uses a multiple mixed state variable incremental integration(MMSVII)method,which successfully reconstructs a four-dimensional hyperchaotic jerk system with multiple cubic nonlinearities except for the memristor term in a three-dimensional model using a clever linear state variable mapping that eliminates the divergence of the state variables.Finally,the simulation circuit of the reduced-dimension system is constructed using Multisim simulation software and the simulation results are consistent with the MATLAB numerical simulation results.The results show that the method of MMSVII proposed in this paper is useful for analyzing extreme multistable systems with multiple higher-order nonlinear terms.

αDecay in extreme laser fields within a deformed Gamow-like model

In this study, the effect of extreme laser fields on the α decay process of ground-state even–even nuclei was investigated.Using the deformed Gamow-like model, we found that state-of-the-art lasers can cause a slight change in the α decay penetration probability of most nuclei. In addition, we studied the correlation between the rate of change of the α decay penetration probability and angle between the directions of the laser electric field and α particle emission for different nuclei. Based on this correlation, the average effect of extreme laser fields on the half-life of many nuclei with arbitrary α particle emission angles was calculated. The calculations show that the laser suppression and promotion effects on the α decay penetration probability of the nuclei population with completely random α particle-emission directions are not completely canceled.The remainder led to a change in the average penetration probability of the nuclei. Furthermore, the possibility of achieving a higher average rate of change by altering the spatial shape of the laser is explored. We conclude that circularly polarized lasers may be helpful in future experiments to achieve a more significant average rate of change of the α decay half-life of the nuclei population.

Highly Thermally Conductive and Structurally Ultra‑Stable Graphitic Films with Seamless Heterointerfaces for Extreme Thermal Management

Highly thermally conductive graphitic film(GF)materials have become a competitive solution for the thermal management of high-power electronic devices.However,their catastrophic structural failure under extreme alternating thermal/cold shock poses a significant challenge to reliability and safety.Here,we present the first investigation into the structural failure mechanism of GF during cyclic liquid nitrogen shocks(LNS),which reveals a bubbling process characterized by“permeation-diffusion-deformation”phenomenon.To overcome this long-standing structural weakness,a novel metal-nanoarmor strategy is proposed to construct a Cu-modified graphitic film(GF@Cu)with seamless heterointerface.This well-designed interface ensures superior structural stability for GF@Cu after hundreds of LNS cycles from 77 to 300 K.Moreover,GF@Cu maintains high thermal conductivity up to 1088 W m^(−1)K^(−1)with degradation of less than 5%even after 150 LNS cycles,superior to that of pure GF(50%degradation).Our work not only offers an opportunity to improve the robustness of graphitic films by the rational structural design but also facilitates the applications of thermally conductive carbon-based materials for future extreme thermal management in complex aerospace electronics.

Design and optimization of fluid lubricated bearings operated with extreme working performances——a comprehensive review

Fluid lubricated bearings have been widely adopted as support components for high-end equipment in metrology,semiconductor devices,aviation,strategic defense,ultraprecision manufacturing,medical treatment,and power generation.In all these applications,the equipment must deliver extreme working performances such as ultraprecise movement,ultrahigh rotation speed,ultraheavy bearing loads,ultrahigh environmental temperatures,strong radiation resistance,and high vacuum operation,which have challenged the design and optimization of reliable fluid lubricated bearings.Breakthrough of any related bottlenecks will promote the development course of high-end equipment.To promote the advancement of high-end equipment,this paper reviews the design and optimization of fluid lubricated bearings operated at typical extreme working performances,targeting the realization of extreme working performances,current challenges and solutions,underlying deficiencies,and promising developmental directions.This paper can guide the selection of suitable fluid lubricated bearings and optimize their structures to meet their required working performances.

Improved PSO-Extreme Learning Machine Algorithm for Indoor Localization

Wi Fi and fingerprinting localization method have been a hot topic in indoor positioning because of their universality and location-related features.The basic assumption of fingerprinting localization is that the received signal strength indication(RSSI)distance is accord with the location distance.Therefore,how to efficiently match the current RSSI of the user with the RSSI in the fingerprint database is the key to achieve high-accuracy localization.In this paper,a particle swarm optimization-extreme learning machine(PSO-ELM)algorithm is proposed on the basis of the original fingerprinting localization.Firstly,we collect the RSSI of the experimental area to construct the fingerprint database,and the ELM algorithm is applied to the online stages to determine the corresponding relation between the location of the terminal and the RSSI it receives.Secondly,PSO algorithm is used to improve the bias and weight of ELM neural network,and the global optimal results are obtained.Finally,extensive simulation results are presented.It is shown that the proposed algorithm can effectively reduce mean error of localization and improve positioning accuracy when compared with K-Nearest Neighbor(KNN),Kmeans and Back-propagation(BP)algorithms.

Long-Term Extreme Wave Characteristics in the Water Adjacent to China Based on ERA5 Reanalysis Data

Extreme waves have a profound impact on coastal infrastructure;thus,understanding the variation law of risky analysis and disaster prevention in coastal zones is necessary.This paper analyzed the spatiotemporal characteristics of extreme wave heights adjacent to China from 1979 to 2018 based on the ERA5 datasets.Nonstationary extreme value analysis is undertaken in eight repre-sentative points to investigate the trends in the values of 50-and 100-year wave heights.Results show that the mean value of extreme waves is the largest in the eastern part of Taiwan Island and the smallest in the Bohai Sea from 1979 to 2018.Only the extreme wave height in the northeastern part of Taiwan Island shows a significant increase trend in the study area.Nonstationary analysis shows remarkable variations in the values of 50-and 100-year significant wave heights in eight points.Considering the annual mean change,E1,E2,S1,and S2 present an increasing trend,while S3 shows a decreasing trend.Most points for the seasonal mean change demon-strate an increasing trend in spring and winter,while other points show a decreasing trend in summer and autumn.Notably,the E1 point growth rate is large in autumn,which is related to the change in typhoon intensity and the northward movement of the typhoon path.

Prediction of lime utilization ratio of dephosphorization in BOF steelmaking based on online sequential extreme learning machine with forgetting mechanism

The machine learning models of multiple linear regression(MLR),support vector regression(SVR),and extreme learning ma-chine(ELM)and the proposed ELM models of online sequential ELM(OS-ELM)and OS-ELM with forgetting mechanism(FOS-ELM)are applied in the prediction of the lime utilization ratio of dephosphorization in the basic oxygen furnace steelmaking process.The ELM model exhibites the best performance compared with the models of MLR and SVR.OS-ELM and FOS-ELM are applied for sequential learning and model updating.The optimal number of samples in validity term of the FOS-ELM model is determined to be 1500,with the smallest population mean absolute relative error(MARE)value of 0.058226 for the population.The variable importance analysis reveals lime weight,initial P content,and hot metal weight as the most important variables for the lime utilization ratio.The lime utilization ratio increases with the decrease in lime weight and the increases in the initial P content and hot metal weight.A prediction system based on FOS-ELM is applied in actual industrial production for one month.The hit ratios of the predicted lime utilization ratio in the error ranges of±1%,±3%,and±5%are 61.16%,90.63%,and 94.11%,respectively.The coefficient of determination,MARE,and root mean square error are 0.8670,0.06823,and 1.4265,respectively.The system exhibits desirable performance for applications in actual industrial pro-duction.

Health Effects of Extreme Low Temperatures and Cold Waves on Respiratory Diseases

Climate change is the most significant threat to public health and exerts myriad influences on health,including the occurrence of extreme temperature events.Studies have demonstrated that populations will experience significantly severe cold waves in the future^([1]),increasing the risk of respiratory diseases.

Optimization of extreme ultraviolet vortex beam based on high harmonic generation

In high harmonic generation(HHG),Laguerre–Gaussian(LG) beams are used to generate extreme ultraviolet(XUV)vortices with well-defined orbital angular momentum(OAM),which have potential applications in fields such as microscopy and spectroscopy.An experimental study on the HHG driven by vortex and Gaussian beams is conducted in this work.It is found that the intensity of vortex harmonics is positively correlated with the laser energy and gas pressure.The structure and intensity distribution of the vortex harmonics exhibit significant dependence on the relative position between the gas jet and the laser focus.The ring-like structures observed in the vortex harmonics,and the interference of quantum paths provide an explanation for the distinct structural characteristics.Moreover,by adjusting the relative position between the jet and laser focus,it is possible to discern the contributions from different quantum paths.The optimization of the HH vortex field is applicable to the XUV,which opens up a new way for exploiting the potential in optical spin or manipulating electrons by using the photon with tunable orbital angular momentum.

Diagnosis of the Kinetic Energy of the“21·7”Extreme Torrential Rainfall Event in Henan Province,China

An extreme torrential rain(ETR)event occurred in Henan Province,China,during 18-21 July 2021.Based on hourly rain-gauge observations and ERA5 reanalysis data,the ETR was studied from the perspective of kinetic energy(K),which can be divided into rotational wind(V_(R))kinetic energy(K_(R)),divergent wind kinetic energy(K_(D)),and the kinetic energy of the interaction between the divergent and rotational winds(K_(RD)).According to the hourly precipitation intensity variability,the ETR process was divided into an initial stage,a rapid increase stage,and maintenance stage.Results showed that the intensification and maintenance of ETR were closely related to the upper-level K,and most closely related to the upperlevel K_(R),with a correlation coefficient of up to 0.9.In particular,the peak value of hourly rainfall intensity lagged behind the K_(R) by 8 h.Furthermore,diagnosis showed that K transformation from unresolvable to resolvable scales made the ETR increase slowly.The meridional rotational wind(u_(R))and meridional gradient of the geopotential(φ)jointly determined the conversion of available potential energy(APE)to K_(R) through the barotropic process,which dominated the rapid enhancement of K_(R) and then caused the rapid increase in ETR.The transportation of K by rotational wind consumed K_(R),and basically offset the K_(R) produced by the barotropic process,which basically kept K_(R) stable at a high value,thus maintaining the ETR.

A Hybrid Approach for Predicting the Remaining Useful Life of Bearings Based on the RReliefF Algorithm and Extreme Learning Machine

Accurately predicting the remaining useful life(RUL)of bearings in mining rotating equipment is vital for mining enterprises.This research aims to distinguish the features associated with the RUL of bearings and propose a prediction model based on these selected features.This study proposes a hybrid predictive model to assess the RUL of rolling element bearings.The proposed model begins with the pre-processing of bearing vibration signals to reconstruct sixty time-domain features.The hybrid model selects relevant features from the sixty time-domain features of the vibration signal by adopting the RReliefF feature selection algorithm.Subsequently,the extreme learning machine(ELM)approach is applied to develop a predictive model of RUL based on the optimal features.The model is trained by optimizing its parameters via the grid search approach.The training datasets are adjusted to make them most suitable for the regression model using the cross-validation method.The proposed hybrid model is analyzed and validated using the vibration data taken from the public XJTU-SY rolling element-bearing database.The comparison is constructed with other traditional models.The experimental test results demonstrated that the proposed approach can predict the RUL of bearings with a reliable degree of accuracy.

Extreme massive hydraulic fracturing in deep coalbed methane horizontal wells:A case study of the Linxing Block,eastern Ordos Basin,NW China

Deep coal seams show low permeability,low elastic modulus,high Poisson’s ratio,strong plasticity,high fracture initiation pressure,difficulty in fracture extension,and difficulty in proppants addition.We proposed the concept of large-scale stimulation by fracture network,balanced propagation and effective support of fracture network in fracturing design and developed the extreme massive hydraulic fracturing technique for deep coalbed methane(CBM)horizontal wells.This technique involves massive injection with high pumping rate+high-intensity proppant injection+perforation with equal apertures and limited flow+temporary plugging and diverting fractures+slick water with integrated variable viscosity+graded proppants with multiple sizes.The technique was applied in the pioneering test of a multi-stage fracturing horizontal well in deep CBM of Linxing Block,eastern margin of the Ordos Basin.The injection flow rate is 18 m^(3)/min,proppant intensity is 2.1 m^(3)/m,and fracturing fluid intensity is 16.5 m^(3)/m.After fracturing,a complex fracture network was formed,with an average fracture length of 205 m.The stimulated reservoir volume was 1987×10^(4)m^(3),and the peak gas production rate reached 6.0×10^(4)m^(3)/d,which achieved efficient development of deep CBM.

Spatio-temporal Variation Characteristics of Extreme Climate Events and Their Teleconnections to Large-scale Ocean-atmospheric Circulation Patterns in Huaihe River Basin,China During 1959–2019

Huaihe River Basin(HRB) is located in China’s north-south climatic transition zone,which is very sensitive to global climate change.Based on the daily maximum temperature,minimum temperature,and precipitation data of 40 meteorological stations and nine monthly large-scale ocean-atmospheric circulation indices data during 1959–2019,we present an assessment of the spatial and temporal variations of extreme temperature and precipitation events in the HRB using nine extreme climate indices,and analyze the teleconnection relationship between extreme climate indices and large-scale ocean-atmospheric circulation indices.The results show that warm extreme indices show a significant(P < 0.05) increasing trend,while cold extreme indices(except for cold spell duration) and diurnal temperature range(DTR) show a significant decreasing trend.Furthermore,all extreme temperature indices show significant mutations during 1959-2019.Spatially,a stronger warming trend occurs in eastern HRB than western HRB,while maximum 5-d precipitation(Rx5day) and rainstorm days(R25) show an increasing trend in the southern,central,and northwestern regions of HRB.Arctic oscillation(AO),Atlantic multidecadal oscillation(AMO),and East Atlantic/Western Russia(EA/WR) have a stronger correlation with extreme climate indices compared to other circulation indices.AO and AMO(EA/WR) exhibit a significant(P < 0.05) negative(positive)correlation with frost days and diurnal temperature range.Extreme warm events are strongly correlated with the variability of AMO and EA/WR in most parts of HRB,while extreme cold events are closely related to the variability of AO and AMO in eastern HRB.In contrast,AMO,AO,and EA/WR show limited impacts on extreme precipitation events in most parts of HRB.