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.

Publisher’s Note:“Benchmark simulations of radiative transfer in participating binary stochastic mixtures in two dimensions”[Matter Radiat.Extremes 9, 067802 (2024)]

This article was originally published online on 30 August 2024.Due to a production error,as originally published the author list was not in its intended order.All online versions of this article were corrected on 9 September 2024 and it appears correctly in print.AIP Publishing apologizes for this error.

Nuclear Fusion Within Extremely Dense Plasma Enhanced by Quantum Particle Waves

Quantum effects play an enhancement role in p-p chain reactions occurring within stars. Such an enhancement is quantified by a wave penetration factor that is proportional to the density of the participating fuel particles. This leads to an innovative theory for dense plasma, and its result shows good agreement with independent data derived from the solar energy output. An analysis of the first Z-pinch machine in mankind＇s history exhibiting neutron emission leads to a derived deuterium plasma beam density greater than that of water, with plasma velocities exceeding 10000 km/s. Fusion power could be achieved by the intersection of four such pinched plasma beams with powerful head-on collisions in their common focal region due to the beam and target enhanced reaction.

Multi-model Projection of July–August Climate Extreme Changes over China under CO_2 Doubling. Part I: Precipitation

Potential changes in precipitation extremes in July–August over China in response to CO 2 doubling are analyzed based on the output of 24 coupled climate models from the Twentieth-Century Climate in Coupled Models （20C3M） experiment and the 1% per year CO 2 increase experiment （to doubling） （1pctto2x） of phase 3 of the Coupled Model Inter-comparison Project （CMIP3）. Evaluation of the models’ performance in simulating the mean state shows that the majority of models fairly reproduce the broad spatial pattern of observed precipitation. However, all the models underestimate extreme precipitation by ～50%. The spread among the models over the Tibetan Plateau is ～2–3 times larger than that over the other areas. Models with higher resolution generally perform better than those with lower resolutions in terms of spatial pattern and precipitation amount. Under the 1pctto2x scenario, the ratio between the absolute value of MME extreme precipitation change and model spread is larger than that of total precipitation, indicating a relatively robust change of extremes. The change of extreme precipitation is more homogeneous than the total precipitation. Analysis on the output of Geophysical Fluid Dynamics Laboratory coupled climate model version 2.1 （GFDL-CM2.1） indicates that the spatially consistent increase of surface temperature and water vapor content contribute to the large increase of extreme precipitation over contiguous China, which follows the Clausius–Clapeyron relationship. Whereas, the meridionally tri-polar pattern of mean precipitation change over eastern China is dominated by the change of water vapor convergence, which is determined by the response of monsoon circulation to global warming.

Multi-Model Projection of July–August Climate Extreme Changes over China under CO_2 Doubling. Part II: Temperature

This is the second part of the authors’ analysis on the output of 24 coupled climate models from the Twentieth-Century Climate in Coupled Models （20C3M） experiment and 1% per year CO 2 increase experiment （to doubling） （1pctto2x） of phase 3 of the Coupled Model Inter-comparison Project （CMIP3）. The study focuses on the potential changes of July–August temperature extremes over China. The pattern correlation coefficients of the simulated temperature with the observations are 0.6–0.9, which are higher than the results for precipitation. However, most models have cold bias compared to observation, with a larger cold bias over western China （5°C） than over eastern China （2°C）. The multi-model ensemble （MME） exhibits a significant increase of temperature under the 1pctto2x scenario. The amplitude of the MME warming shows a northwest–southeast decreasing gradient. The warming spread among the models （～1°C– 2°C） is less than MME warming （～2°C–4°C）, indicating a relatively robust temperature change under CO 2 doubling. Further analysis of Geophysical Fluid Dynamics Laboratory coupled climate model version 2.1 （GFDL-CM2.1） simulations suggests that the warming pattern may be related to heat transport by summer monsoons. The contrast of cloud effects also has contributions. The different vertical structures of warming over northwestern China and southeastern China may be attributed to the different natures of vertical circulations. The deep, moist convection over southeastern China is an effective mechanism for ＂transporting＂ the warming upward, leading to more upper-level warming. In northwestern China, the warming is more surface-orientated, possibly due to the shallow, dry convection.

NO_x emission model for coal-fired boilers using partial least squares and extreme learning machine

To implement a real-time reduction in NOx,a rapid and accurate model is required.A PLS-ELM model based on the combination of partial least squares(PLS)and the extreme learning machine(ELM)for the establishment of the NOx emission model of utility boilers is proposed.First,the initial input variables of the NOx emission model are determined according to the mechanism analysis.Then,the initial input data is extracted by PLS.Finally,the extracted information is used as the input of the ELM model.A large amount of real data was obtained from the distributed control system(DCS)historical database of a 1 000 MW power plant boiler to train and validate the PLS-ELM model.The modeling performance of the PLS-ELM was compared with that of the back propagation(BP)neural network,support vector machine(SVM)and ELM models.The mean relative errors(MRE)of the PLS-ELM model were 1.58%for the training dataset and 1.69%for the testing dataset.The prediction precision of the PLS-ELM model is higher than those of the BP,SVM and ELM models.The consumption time of the PLS-ELM model is also shorter than that of the BP,SVM and ELM models.

Impacts of Multi-Scale Solar Activity on Climate.Part Ⅰ:Atmospheric Circulation Patterns and Climate Extremes

The impacts of solar activity on climate are explored in this two-part study. Based on the principles of atmospheric dynamics, Part I propose an amplifying mechanism of solar impacts on winter climate extremes through changing the atmospheric circulation patterns. This mechanism is supported by data analysis of the sunspot number up to the predicted Solar Cycle 24, the historical surface temperature data, and atmospheric variables of NCEP/NCAR Reanalysis up to the February 2011 for the Northern Hemisphere winters. For low solar activity, the thermal contrast between the low- and high-latitudes is enhanced, so as the mid-latitude baroclinic ultra-long wave activity. The land-ocean thermal contrast is also enhanced, which amplifies the topographic waves. The enhanced mid-latitude waves in turn enhance the meridional heat transport from the low to high latitudes, making the atmospheric ＂heat engine＂ more efficient than normal. The jets shift southward and the polar vortex is weakened. The Northern Annular Mode （NAM） index tends to be negative. The mid-latitude surface exhibits large-scale convergence and updrafts, which favor extreme weather/climate events to occur. The thermally driven Siberian high is enhanced, which enhances the East Asian winter monsoon （EAWM）. For high solar activity, the mid-latitude circulation patterns are less wavy with less meridional transport. The NAM tends to be positive, and the Siberian high and the EAWM tend to be weaker than normal. Thus the extreme weather/climate events for high solar activity occur in different regions with different severity from those for low solar activity. The solar influence on the mid- to high-latitude surface temperature and circulations can stand out after removing the influence from the E1 Nifio-Southern Oscillation. The atmospheric amplifying mechanism indicates that the solar impacts on climate should not be simply estimated by the magnitude of the change in the solar radiation over solar cycles when it is compared with other external radiative forcings that do not influence the climate in the same way as the sun does.

HadISDH.extremes Part Ⅱ:Exploring Humid Heat Extremes Using Wet Bulb Temperature Indices

Heat events may be humid or dry.While several indices incorporate humidity,such combined indices obscure identification and exploration of heat events by their different humidity characteristics.The new HadISDH.extremes global gridded monitoring product uniquely provides a range of wet and dry bulb temperature extremes indices.Analysis of this new data product demonstrates its value as a tool for quantifying exposure to humid verses dry heat events.It also enables exploration into“stealth heat events”,where humidity is high,perhaps enough to affect productivity and health,while temperature remains moderate.Such events may not typically be identified as“heat events”by temperature-focused heat indices.Over 1973-2022,the peak magnitude of humid extremes(maximum daily wet bulb temperature over a month;T_(w)X)for the global annual mean increased significantly at 0.13±0.04℃(10 yr)^(−1),which is slightly slower than the global annual mean T_(w) increase of 0.22±0.04℃(10 yr)^(−1).The frequency of moderate humid extreme events per year(90th per-centile daily maxima wet bulb temperature exceedance;T_(w)X90p)also increased significantly at 4.61±1.07 d yr^(−1)(10 yr)^(−1).These rates were slower than for temperature extremes,TX and TX90p,which respectively increased significantly at 0.27±0.04℃(10 yr)^(−1) and 5.53±0.72 d yr^(−1)(10 yr)^(−1).Similarly,for the UK/Europe focus region,JJA-mean T_(w)X increased significantly,again at a slower rate than for TX and mean T_(w).HadISDH.extremes shows some evidence of“stealth heat events”occurring where humidity is high but temperature remains more moderate.

HadISDH.extremes Part Ⅰ:A Gridded Wet Bulb Temperature Extremes Index Product for Climate Monitoring

HadISDH.extremes is an annually updated global gridded monthly monitoring product of wet and dry bulb temperature–based extremes indices,from January 1973 to December 2022.Data quality,including spatial and temporal stability,is a key focus.The hourly data are quality controlled.Homogeneity is assessed on monthly means and used to score each gridbox according to its homogeneity rather than to apply adjustments.This enables user-specific screening for temporal stability and avoids errors from inferring adjustments from monthly means for the daily maximum values.For general use,a score(HQ Flag)of 0 to 6 is recommended.A range of indices are presented,aligning with existing standardised indices.Uniquely,provision of both wet and dry bulb indices allows exploration of heat event character—whether it is a“humid and hot”,“dry and hot”or“humid and warm”event.It is designed for analysis of long-term trends in regional features.HadISDH.extremes can be used to study local events,but given the greater vulnerability to errors of maximum compared to mean values,cross-validation with independent information is advised.

THE EXTREME POINTS OF A CLASS OF ANALYTIC FUNCTIONS WITH POSITIVE REAL PART AND A PRESCRIBED SET OF VALUES

Letζ =（0,z1,z2,···,zn） with ｜zj｜〈1for1≤j≤n,ω=（1,w1,w2,···,wn）,and P（ζ,ω） denote the set of functions p（z） that are analytic in D={z：｜z｜〈1} and satisfy Rep（z）〉0（｜z｜〈1）,p（0）=1,p（zj）=wj,j=1,2,···,n.In this article we investigate the extreme points of P（ζ,ω）.

Internet of things intrusion detection model and algorithm based on cloud computing and multi-feature extraction extreme learning machine

With the rapid development of the Internet of Things(IoT),there are several challenges pertaining to security in IoT applications.Compared with the characteristics of the traditional Internet,the IoT has many problems,such as large assets,complex and diverse structures,and lack of computing resources.Traditional network intrusion detection systems cannot meet the security needs of IoT applications.In view of this situation,this study applies cloud computing and machine learning to the intrusion detection system of IoT to improve detection performance.Usually,traditional intrusion detection algorithms require considerable time for training,and these intrusion detection algorithms are not suitable for cloud computing due to the limited computing power and storage capacity of cloud nodes;therefore,it is necessary to study intrusion detection algorithms with low weights,short training time,and high detection accuracy for deployment and application on cloud nodes.An appropriate classification algorithm is a primary factor for deploying cloud computing intrusion prevention systems and a prerequisite for the system to respond to intrusion and reduce intrusion threats.This paper discusses the problems related to IoT intrusion prevention in cloud computing environments.Based on the analysis of cloud computing security threats,this study extensively explores IoT intrusion detection,cloud node monitoring,and intrusion response in cloud computing environments by using cloud computing,an improved extreme learning machine,and other methods.We use the Multi-Feature Extraction Extreme Learning Machine(MFE-ELM)algorithm for cloud computing,which adds a multi-feature extraction process to cloud servers,and use the deployed MFE-ELM algorithm on cloud nodes to detect and discover network intrusions to cloud nodes.In our simulation experiments,a classical dataset for intrusion detection is selected as a test,and test steps such as data preprocessing,feature engineering,model training,and result analysis are performed.The experimental results show that the proposed algorithm can effectively detect and identify most network data packets with good model performance and achieve efficient intrusion detection for heterogeneous data of the IoT from cloud nodes.Furthermore,it can enable the cloud server to discover nodes with serious security threats in the cloud cluster in real time,so that further security protection measures can be taken to obtain the optimal intrusion response strategy for the cloud cluster.

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.

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.

An Extreme Value Analysis of Wind Speed over the European and Siberian Parts of Arctic Region

Multiyear observed time series of wind speed for selected points of the Arctic region (data of station network from the Kola Peninsula to the Chukotka Peninsula) are used to highlight the important peculiarities of wind speed extreme statistics. How largest extremes could be simulated by climate model (the INM-CM4 model data from the Historical experiment of the CMIP5) is also discussed. Extreme value analysis yielded that a volume of observed samples of wind speeds are strictly divided into two sets of variables. Statistical properties of one population are sharply different from another. Because the common statistical conditions are the sign of identity of extreme events we therefore hypothesize that two groups of extreme wind events adhere to different circulation processes. A very important message is that the procedure of selection can be realized easily based on analysis of the cumulative distribution function. The authors estimate the properties of the modelled extremes and conclude that they consist of only the samples, adhering to one group. This evidence provides a clue that atmospheric model with a coarse spatial resolution does not simulate special mechanism responsible for appearance of largest wind speed extremes. Therefore, the tasks where extreme wind is needed cannot be explicitly solved using the output of climate model. The finding that global models are unable to capture the wind extremes is already well known, but information that they are members of group with the specific statistical conditions provides new knowledge. Generally, the implemented analytical approach allows us to detect that the extreme wind speed events adhere to different statistical models. Events located above the threshold value are much more pronounced than representatives of another group (located below the threshold value) predicted by the extrapolation of law distributions in their tail. The same situation is found in different areas of science where the data referring to the same nomenclature are adhering to different statistical models. This result motivates our interest on our ability to detect, analyze, and understand such different extremes.

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.

Extreme Antarctic Cold of Late Winter 2023

Extreme cold temperatures were observed in July and August 2023,coinciding with the WINFLY(winter fly-in)period of mid to late August into September 2023,meaning aircraft operations into McMurdo Station and Phoenix Airfield were adversely impacted.Specifically,with temperatures below−50℃,safe flight operation was not possible because of the risk of failing hydraulics and fuel turning to gel onboard the aircraft.The cold temperatures were measured across a broad area of the Antarctic,from East Antarctica toward the Ross Ice Shelf,and stretching across West Antarctica to the Antarctic Peninsula.A review of automatic weather station measurements and staffed station observations revealed a series of sites recording new record low temperatures.Four separate cold phases were identified,each a few days in duration and occurring from mid-July to the end of August 2023.A brief analysis of 500-hPa geopotential height anomalies shows how the mid-tropospheric atmospheric environment evolves in relation to these extreme cold temperatures.The monthly 500-hPa geopotential height anomalies show strong negative anomalies in August.Examination of composite geopotential height anomalies during each of the four cold phases suggests various factors leading to cold temperatures,including both southerly off-content flow and calm atmospheric conditions.Understanding the atmospheric environment that leads to such extreme cold temperatures can improve prediction of such events and benefit Antarctic operations and the study of Antarctic meteorology and climatology.

Implications of the extremely hot summer of 2022 on urban ozone control in China

Frequent occurrences of extreme heat are causing severe ozone pollution over China.This study examined the driving factors of urban ozone pollution in China during the extremely hot summer of 2022 and the impact of emission control strategies using surface measurements and the GEOS-Chem model.The results show that ozone pollution was extremely severe in summer 2022,with a significant rebound by 12-15 ppbv in the North China Plain(NCP),Yangtze River Delta(YRD),and Sichuan basin(SCB),compared to 2021.Especially over the NCP,the MDA8(maximum daily 8-hourly average)ozone exceeded 160 ppbv,and the number of ozone exceedances was over 42 days.Based on an IPR(integrated process rate)analysis,the authors found that the net chemical production was the dominant factor contributing to the strong ozone increase in summer 2022.For example,in June over the NCP,the net chemical production resulted in an increase by 3.08 Gg d^(−1)(∼270%)in ozone mass change.Sensitivity simulations showed that both NO_(x)(nitrogen oxides)and VOC(volatile organic compound)reductions were important over the NCP,and NO_(x)reductions were more important than VOCs over southern China.To keep the ozone of 2022 at the same level as 2021,a joint reduction of NO_(x)and VOCs by at least 50%-60%would have been required.This study highlights the urgency to develop effective ozone management since extreme heat will become more frequent.

Research progress on the water vapor channel within the Yarlung Zsangbo Grand Canyon, China

The Second Tibetan Plateau Scientific Expedition and Research Program tasked a research team with the“Investigation of the water vapor channel of the Yarlung Zsangbo Grand Canyon(INVC)”in the southeastern Tibetan Plateau(TP).This paper summarizes the scientific achievements obtained from the data collected by the INVC observation network and highlights the progress in investigating the development of heavy rainfall events associated with water vapor changes.The rain gauge network of the INVC can represent the impacts of the Yarlung Zsangbo Grand Canyon(YGC)topography on precipitation at the hourly scale.The microphysical characteristics of the precipitation in the YGC are different than those in the lowland area.The GPM-IMERG(Integrated MultisatellitE Retrievals for Global Precipitation Measurement)satellite precipitation data for the YGC region should be calibrated before they are used.The meridional water vapor flux through the YGC is more important than the zonal flux for the precipitation over the southeastern TP.The decreased precipitation around the YGC region is partly due to the decreased meridional water vapor flux passing through the YGC.High-resolution numerical models can benefit precipitation forecasting in this region by using a combination of specific schemes that capture the valley wind and water vapor flux along the valley floor.

Projected changes in extreme snowfall events over the Tibetan Plateau based on a set of RCM simulations

Extreme snowfall events over the Tibetan Plateau(TP)cause considerable damage to local society and natural ecosystems.In this study,the authors investigate the projected changes in such events over the TP and its surrounding areas based on an ensemble of a set of 21st century climate change projections using a regional climate model,RegCM4.The model is driven by five CMIP5 global climate models at a grid spacing of 25 km,under the RCP4.5 and RCP8.5 pathways.Four modified ETCCDI extreme indices-namely,SNOWTOT,S1mm,S10mm,and Sx5day-are employed to characterize the extreme snowfall events.RegCM4 generally reproduces the spatial distribution of the indices over the region,although with a tendency of overestimation.For the projected changes,a general decrease in SNOWTOT is found over most of the TP,with greater magnitude and better cross-simulation agreement over the eastern part.All the simulations project an overall decrease in S1mm,ranging from a 25%decrease in the west and to a 50%decrease in the east of the TP.Both S10mm and Sx5day are projected to decrease over the eastern part and increase over the central and western parts of the TP.Notably,S10mm shows a marked increase(more than double)with high cross-simulation agreement over the central TP.Significant increases in all four indices are found over the Tarim and Qaidam basins,and northwestern China north of the TP.The projected changes show topographic dependence over the TP in the latitudinal direction,and tend to decrease/increase in low-/high-altitude areas.

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.