Analysis of Short-term Heavy Precipitations in a Regional Heavy Rainstorm in Shannxi Province

[Objective] This study aimed to analyze the cause of the generation of short-term heavy precipitations in a regional heavy rainstorm in Shannxi Province. [Method] Taking a heavy rainstorm covering most parts of Shaanxi Province in late July 2010 as an example, data of five Doppler weather radars in Shaanxi Province were employed for a detailed analysis of the evolution of the heavy rainstorm pro- cess. [Result] Besides the good large-scale weather background conditions, the de- velopment and evolution of some mesoscale and small-scale weather systems direct- ly led to short-term heavy precipitations during the heavy rainstorm process, involv- ing the intrusion of moderate IS-scale weak cold air and presence of small-scale wind shear, convergence and adverse wind area. In addition, small-scale convection echoes were arranged in lines and formed a ＂train effect＂, which would also con- tribute to the generation of short-term heavy precipitation. [Conclusion] This study provided basic information for more clear and in-depth analysis of the formation mechanism of short-term heavy precipitations.

Multimodel Ensemble Forecasts for Precipitations in China in 1998

Different multimodel ensemble methods are used to forecast precipitations in China, 1998, and their forecast skills are compared with those of individual models. Datasets were obtained from monthly simulations of eight models during the period of January 1979 to December 1998 from the “Climate of the 20th Century Experiment” （20C3M） for the Fourth IPCC Assessment Report. Climate Research Unit （CRU） data were chosen for the observation analysis field. Root mean square （RMS） error and correlation coeffi-cients （R） are used to measure the forecast skills. In addition, superensemble forecasts based on different input data and weights are analyzed. Results show that for original data, superensemble forecasting based on multiple linear regression （MLR） performs best. However, for bias-corrected data, the superensemble based on singular value decomposition （SVD） produces a lower RMS error and a higher R than in the MLR superensemble. It is an interesting result that the SVD superensemble based on bias-corrected data performs better than the MLR superensemble, but that the SVD superensemble based on original data is inferior to the corresponding MLR superensemble. In addition, weights calculated by different data formats are shown to affect the forecast skills of the superensembles. In comparison with the MLR superensemble, a slightly significant effect is present in the SVD superensemble. However, both the SVD and MLR superensembles based on different weight formats outperform the ensemble mean of bias-corrected data.

Assessment of Intra-Seasonal Variability and Trends of Precipitations in a Climate Change Framework in West Africa

Climate change has led human beings to take an interest in the study of meteorological and climatic phenomena. In fact, the main impact of climate change on different sectors of society is caused by extreme events since the occurrence of extreme events leads to more impact related to change in mean climate. Unfortunately, the West African region is vulnerable to extreme rainfall impact because its economy is based on rain-fed agriculture. This study examined the seasonal variability of extreme rainfall in West Africa. Eight (8) climate indices were chosen from among the 27 defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). The nonparametric Mann-Kendall test was used to assess the seasonal trends. The indices of the same types (frequency or intensity) were compared to assess the intra-seasonal variation of extreme precipitation. The results indicate that, regardless of the season, the Gulf of Guinea receives more rainfall than the Sahel. This phenomenon is due to the fact that the coastal part of West Africa is under the influence of evaporation which is observed at the Atlantic Ocean and during the monsoon, while the other part is dominated by the desert. Mann-Kendall’s test revealed upward and downward trends during each season. The increase in extreme rainfall trends in the number of consecutive dry days suggests that droughts, due to global warming, could be observed and could have severe consequences in terms of water availability, energy supply, agricultural yields and ecosystems in West Africa. In addition, it can lead to the loss of biodiversity and health issues. It is therefore essential for policymakers or decisions makers to determine strategies and mitigation measures against climate change and its impacts on populations.

Thermodynamic re-assessment of the Mg-Gd-Y ternary system coupling with the driving forces for phase precipitations during aging process

Based on the available experimental phase equilibrium relations and aging precipitation sequences,the Mg–Gd–Y ternary system has been thermodynamically re-assessed by means of CALPHAD technique.To simulate the experimentally reported aging precipitation sequence,α(Mg)_(SS)(supersaturated)→GP zones(D019-type,metastable)→β’-Mg_(7)Gd(c-bco,metastable)→β_(1)-Mg_(3)Gd(fcc,metastable)→β-Mg_(5)Gd(fcc,stable)near the Mg–Gd side,andα(Mg)SS(supersaturated)→β’-Mg_(7)Y(c-bco,metastable)→β-Mg_(24)Y_(5)(bcc,stable)near the Mg–Y side,the effective nucleation driving forces obtained by deducting the nucleation resistances from the thermodynamic driving forces are calculated and analyzed.Two metastable components,GP zones(D019-type)andβ’(c-bco)ordered fromα(Mg)_(SS),do not exist in the stable equilibrium phase diagram but appear in the annealing process of typical alloys.The Redlich–Kister equations are adopted to describe three solution phases,Liquid,HCP_A3 and BCC_A2.The intermediate compounds Mg_(2)Y,Mg_(24)Y_(5),Mg_(2)Gd,Mg_(3)Gd and Mg_(5)Gd are expressed by the formulas of(Mg,Y)_(2/3)(Gd,Mg,Y)_(1/3),Mg_(24/29)(Gd,Mg,Y)_(4/29)Y1/29,(Gd,Mg)_(2/3)(Gd,Mg,Y)_(1/3),(Gd,Mg)_(3/4)(Gd,Mg,Y)_(1/4)and Mg_(5/6)(Gd,Mg,Y)_(1/6),respectively.In particular,the two-sublattice models(Gd,Mg,Y)_(1/2)(Gd,Mg,Y)_(1/2),(Gd,Mg,Y)_(3/4)(Gd,Mg,Y)_(1/4)and(Gd,Mg,Y)_(7/8)(Gd,Mg,Y)_(1/8)have been respectively used to describe the stable Mg(Gd,Y)(BCC_B2)alloy compound as well as the metastable GP zones(D019-type)andβ’(c-bco)phase,in order to cope with the order-disorder transitions.A set of self-consistent thermodynamic parameters has been obtained to ensure the thermodynamic calculations well consistent with the reported experimental data,containing not only the stable equilibrium phase diagram but also the aging precipitation sequence.

Oxygen Stable Isotopic Ratio in Precipitations in Niigata Prefecture, Japan

Time-course of oxygen stable isotopic ratios （i.e., δ^18O） as well as seasonal variation of δ^18O has been examined to investigate the characteristics, sources and the passing route of precipitations in Niigata Prefecture. The precipitation samples have been mainly collected with a filtrating bulk sampler at the rooftop of Niigata University. Furthermore, backward trajectories analyses have been also conducted for these samples taken sequentially for a short period. Consequently, the following features have been mainly clarified for the precipitations in Niigata Prefecture： （1） the δ^18O values varied between -14.57%o and -3.86%0 in the precipitations of Niigata University; （2） as for the comparison among sampling points, the mean value of δ^18O at seaside spots （i.e., Niigata City： -6.93%0） is larger than that of inland spots （Sanjyo City： -8.68%0）; （3） δ^18O value was generally small in the rainy or typhoon season, and relatively large in summer; （4） decreasing δ^18O content with time is a predominant feature of sequentially sampled rainfalls as predicted by Rayleigh models of atmospheric vapor condensation.

The Projected Changes of Precipitations over Niger Under the Scenarios RCP 4.5 and RCP 8.5

The socio-economic activities of Niger rely on agriculture which is strongly affected by changes in precipitation during the rainy season.The ultimate aim of this study is to assess the projected changes of precipitation over Niger under the Representative Concentration Pathways(RCP)scenarios 4.5(RCP 4.5)and RCP 8.5 using multi-RCM(Multi-Regional Climate)model approach.The observation data are from CHIRPS(Climate Hazards Group InfraRed Precipitation with Station)and the RCMs are from the SMHI(Swedish Meteorological and Hydrological Institute)model(RCA4)driven by ten(10)different GCMs(General Circulation Model)(e.g.,CCCma,CSIRO,ICHEC,IPSL,MIROC,MOHC-HadGEM2,MPI,NCC-NorESM1,NOOA,and NRCM)within the framework of CORDEX(Coordinated Regional Climate Downscaling Experiment)Africa experiment.The reference and projections periods in this study are respectively 1981-2005 for the present and 2011-2100 for the near,medium and far future divided into three periods,2011 to 2040(P1),2041 to 2070(P2)and 2071 to 2100(P3).The methodology used,consists of assessing the performance of the multi-RCMs of RCA4 model(with respect of CHIRPS)in simulating the precipitations changes by computing the spatial distribution and anomalies of precipitations;and their indices of RMSE(Root Mean Square Error),the bias,SPI(Standardized Precipitation Anomaly Index),correlation coefficient,statistical t-test,spatial evolution rate and the rate of temporal change.After the validation of the multi-RCMs RCA4 models,the ensemble mean of the models is used to assess the projected changes of precipitations over Niger in the future.The results show that most of the multi-RCMs capture the four climatic zone except for IPSL.While the ensemble mean of the models simulates(as compared to CHIRPS)more accurately the monthly,annual precipitations anomalies and their indices than individual’s models in the reference period,some RCMs(e.g.,CSIRO-IPSL and CCCma-HadGEM)poorly reproduce them.The projected changes of precipitations indicate for the scenario RCP 4.5 respectively a moderately surplus of precipitation years in the period P1 and moderately deficit years in the period P2 while the period P3 shows a small upward precipitation trend.In contrary,for the scenario RCP 8.5,all the three periods(P1,P2 and P3)indicate an intensification of precipitation leading to a longer wet period which may lead to extreme precipitations and flooding.Moreover,both scenarios have projected an increase of total monthly precipitation in May and September and a decrease in July and August respectively which will likely lead to an early onset and late cessation of the rainy season;and a shift of the peak of the rainy season.Therefore,this study shows the need of a monitoring system for the projected changes of precipitation in the near future to anticipate urgent action in wet/dry periods to adapt to a changing climate.

Winter Precipitations of Northern Part of Farming-Pastoral Zone and Hulunbuir Grassland

In January 2018, a high record of monthly total precipitation in northern China drew our attention. The precipitation amount is 4 times more than that in normal winters over the past 30 years. Up to now, many researches over the world focus on the intensity of precipitations or the number of intense precipitations, however, no sufficient study is investigated in the continuous moderate precipitations. The abnormal precipitation in January 2018 in northern China is a typical case of the continuous moderate precipitation. The research region is composed by the northern part of the farming-pastoral zone and the Hulunbuir Grassland. The main method in this study consists of analyzing the abnormal precipitation month by identifying the precipitation types and locations, and exploring the atmospheric circulations at the moment of typical precipitations. The research found that the continuity is the key point for high precipitation amount in January 2018 in Northern China. Besides, this continuity is caused by frequent appearance of cyclones in the vicinity.

Review of precipitation strengthening in ultrahigh-strength martensitic steel

Martensite is an important microstructure in ultrahigh-strength steels,and enhancing the strength of martensitic steels often involves the introduction of precipitated phases within the martensitic matrix.Despite considerable research efforts devoted to this area,a systematic summary of these advancements is lacking.This review focuses on the precipitates prevalent in ultrahigh-strength martensitic steel,primarily carbides(e.g.,MC,M_(2)C,and M_(3)C)and intermetallic compounds(e.g.,Ni Al,Ni_(3)X,and Fe_(2)Mo).The precipitation-strengthening effect of these precipitates on ultrahigh-strength martensitic steel is discussed from the aspects of heat treatment processes,microstructure of precipitate-strengthened martensite matrix,and mechanical performance.Finally,a perspective on the development of precipitation-strengthened martensitic steel is presented to contribute to the advancement of ultrahigh-strength martensitic steel.This review highlights significant findings,ongoing challenges,and opportunities in the development of ultrahigh-strength martensitic steel.

As-cast Ti_(x)(AlVCr)_(100−x)light-weight medium entropy alloys with high strength and uniform compressive plasticity

The effect of Ti content on the microstructure and mechanical properties of as-cast light-weight Ti_(x)(AlVCr)_(100−x)medium entropy alloys was studied by compressive tests,X-ray diffraction,scanning electron microscopy and transmission electron microscopy.The results suggest that yield strength increases and then decreases with the increment of Ti content.The Ti_(60)(AlVCr)_(40)alloy has the best combination of high strength of 1204 MPa and uniform plastic strain of 70%,possessing a high specific yield strength of 255 MPa·cm^(3)/g.The enhancement of strength is mainly attributed to the synergic effects of solid-solution and coherent nano-precipitation strengthening,while dislocation motion such as dislocation pinning,entanglement and dislocation cells significantly increases the strain-hardening capacity.

Improving the Seasonal Forecast of Summer Precipitation in Southeastern China Using a CycleGAN-based Deep Learning Bias Correction Method

Accurate seasonal precipitation forecasts,especially for extreme events,are crucial to preventing meteorological hazards and their potential impacts on national development,social activity,and security.However,the intensity of summer precipitation is often largely underestimated in many current dynamic models.This study uses a deep learning method called Cycle-Consistent Generative Adversarial Networks(CycleGAN)to improve the seasonal forecasts for June-JulyAugust precipitation in southeastern China by the Nanjing University of Information Science and Technology Climate Forecast System(NUIST-CFS 1.0).The results suggest that the CycleGAN-based model significantly improves the accuracy in predicting the spatiotemporal distribution of summer precipitation compared to the traditional quantile mapping(QM)method.Using the unpaired bias-correction model,we can also obtain advanced forecasts of the frequency,intensity,and duration of extreme precipitation events over the dynamic model predictions.This study expands the potential applications of deep learning models toward improving seasonal precipitation forecasts.

Effect of lanthanum on microstructure of a nickel-based single crystal superalloy

To enhance the high-temperature oxidation resistance and mechanical properties of a secondgeneration nickel-based superalloy,various concentrations of lanthanum(La)ranging from 5.0×10^(-5)wt.%to 3.4×10^(-4)wt.%are added to the alloy.The microstructure of the nickel-based single crystal superalloy with trace of La was examined by means of SEM,EDS and TEM.Results show the addition of La decreases the segregation of elements and increases the amount ofγ/γ′eutectics of the as-cast alloy,and in the interdendritic region,the growth of eutectics is accompanied by the growth of strip clusters composed of Ni_(5)La and Ni_(3)Ta.As the La content in the alloy increases,the proportion of Ni_(5)La in the cluster increases.After heat treatment,incipient melting occurs in the cluster regions,leading to an increase in microporosity compared to the original as-cast samples.Furthermore,the heat treatment alters the shape of the clusters from a strip morphology to an elliptical one,and it changes their composition from Ni_(5)La and Ni_(3)Ta to a combination of Ni_(5)La,Ni_(3)Ta,and MC carbides.

A Machine Learning-Based Observational Constraint Correction Method for Seasonal Precipitation Prediction

Seasonal precipitation has always been a key focus of climate prediction.As a dynamic-statistical combined method,the existing observational constraint correction establishes a regression relationship between the numerical model outputs and historical observations,which can partly predict seasonal precipitation.However,solving a nonlinear problem through linear regression is significantly biased.This study implements a nonlinear optimization of an existing observational constrained correction model using a Light Gradient Boosting Machine(LightGBM)machine learning algorithm based on output from the Beijing National Climate Center Climate System Model(BCC-CSM)and station observations to improve the prediction of summer precipitation in China.The model was trained using a rolling approach,and LightGBM outperformed Linear Regression(LR),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost).Using parameter tuning to optimize the machine learning model and predict future summer precipitation using eight different predictors in BCC-CSM,the mean Anomaly Correlation Coefficient(ACC)score in the 2019–22 summer precipitation predictions was 0.17,and the mean Prediction Score(PS)reached 74.The PS score was improved by 7.87%and 6.63%compared with the BCC-CSM and the linear observational constraint approach,respectively.The observational constraint correction prediction strategy with LightGBM significantly and stably improved the prediction of summer precipitation in China compared to the previous linear observational constraint solution,providing a reference for flood control and drought relief during the flood season(summer)in China.

Spatiotemporal variations of tenebrionid beetles(Coleoptera:Tenebrionidae)in the Gobi desert,Northwest China

Tenebrionid beetles represent a crucial arthropod taxon in the Gobi desert ecosystems owing to their species richness and high biomass,both of which are essential for maintaining ecosystem health and stability.However,the spatiotemporal variations of tenebrionid beetle assemblages in the Gobi desert remain poorly understood.In this study,the monthly dynamics of tenebrionid beetles in the central part of the Hexi Corridor,Northwest China,a representative area of the Gobi desert ecosystems,were monitored using pitfall trapping during 2015-2020.The following results were showed:(1)monthly activity of tenebrionid beetles was observed from March to October,with monthly activity peaking in spring and summer,and monthly activity periods and peak of tenebrionid beetle species exhibited interspecific differences that varied from year to year;(2)spatial distribution of tenebrionid beetle community was influenced by structural factors.Specifically,at a spatial scale of 24.00 m,tenebrionid beetle community was strongly and positively correlated with the dominant species,with distinct spatial distribution patterns observed for Blaps gobiensis and Microdera kraatzi alashanica;(3)abundance of tenebrionid beetles was positively correlated with monthly mean precipitation and monthly mean temperature,whereas monthly abundance of B.gobiensis and M.kraatzi alashanica was positively correlated with monthly mean precipitation;and(4)the cover of Reaumuria soongarica(Pall.)Maxim.and Nitraria sphaerocarpa Maxim.had a positive influence on the number of tenebrionid beetles captured.In conclusion,monthly variation in precipitation significantly influences the community dynamic of tenebrionid beetles,with precipitation and shrub cover jointly determining the spatial distribution pattern of these beetles in the Gobi desert ecosystems.

Positive effect of Mo on mechanical properties of a Ni-42W-10Co-xMo medium heavy alloy

In this study,a novel Ni-W-Co-Mo medium heavy alloy(MHA)was designed to improve its mechanical strength via Mo doping.In the Ni-42W-10Co-x Mo alloy series,where x represents the weight percent of Mo and varies between 0,1,2,5,and 10,the microstructure transitions from a dendritic structure to a hypo-eutectic structure as the Mo content increases from 0 to 5wt.%.Moreover,as the Mo content increases from 0 to 10wt.%,the distribution of theμ-phase shifts from being individually dispersed to forming aggregates,and its volume fraction rises from 0.5%to 7.9%.Notably,theμ-phase evolves into an eutectic microstructure,which helps in minimizing the segregation of elements.This change is accompanied by a substantial enhancement in mechanical properties;specifically,the compressive yield strength at room temperature increases from 350 MPa to 646 MPa,indicating a significant 85%increase.Similarly,the microhardness increases from 230 HV to 304 HV.Molecular dynamics simulations further reveal that the strengthening mechanism of Ni-42W-10Co-x Mo alloys is Mo-induced solid solution strengthening and precipitation strengthening.

Effects of bacterial strains on undrained cyclic behavior of bio-cemented sand considering wetting and drying cycles

The microbial-induced calcite precipitation(MICP)technique has been developed as a sustainable methodology for the improvement of the engineering characteristics of sandy soils.However,the efficiency of MICP-treated sand has not been well established in the literature considering cyclic loading under undrained conditions.Furthermore,the efficacy of different bacterial strains in enhancing the cyclic properties of MICP-treated sand has not been sufficiently documented.Moreover,the effect of wetting-drying(WD)cycles on the cyclic characteristics of MICP-treated sand is not readily available,which may contribute to the limited adoption of MICP treatment in field applications.In this study,strain-controlled consolidated undrained(CU)cyclic triaxial testing was conducted to evaluate the effects of MICP treatment on standard Ennore sand from India with two bacterial strains:Sporosarcina pasteurii and Bacillus subtilis.The treatment durations of 7 d and 14 d were considered,with an interval of 12 h between treatments.The cyclic characteristics,such as the shear modulus and damping ratio,of the MICP-treated sand with the different bacterial strains have been estimated and compared.Furthermore,the effect of WD cycles on the cyclic characteristics of MICP-treated sand has been evaluated considering 5–15 cycles and aging of samples up to three months.The findings of this study may be helpful in assessing the cyclic characteristics of MICP-treated sand,considering the influence of different bacterial strains,treatment duration,and WD cycles.

Assessment of ecological geological vulnerability in Mu Us Sandy Land based on GIS and suggestions of ecological protection and restoration

Eco-geological vulnerability assessment is a significant research topic within the field of eco-geology,but it remains poorly studied.The Mu Us Sandy Land,located in the central part of the farming-pastoral ecotone in northern China,plays a critical role in maintaining the ecological security pattern in this region.However,this sandy land also faces severe sandy desertification and ecological degradation.This study conducted a regional eco-geological vulnerability assessment of the Mu Us Sandy Land using a comprehensive index evaluation method based on eco-geological theories and survey results.To construct an appropriate index system for the eco-geological vulnerability assessment of the Mu Us Sandy Land,the study considered the sandy land’s unique characteristics and identified 15 factors of five categories,namely geology,meteorology,soil,topography,and vegetation.The paper calculated the comprehensive weights of all the indices using the analytic hierarchy process(AHP)and the entropy weight method(EWM).Furthermore,it established the eco-geological vulnerability index(EGVI)and obtained the assessment results.The results showed that the eco-geological vulnerability of the Mu Us Sandy Land gradually intensifies from east to west,manifested as vulnerable eco-geological conditions overall.Specifically,extremely vulnerable zones are found in the northwestern and southeastern parts of the study area,highly vulnerable zones in the western and southern parts,moderately vulnerable zones in the central part,and slightly and potentially vulnerable zones in the eastern and southern parts.Areas with high spatial autocorrelations include the northern Uxin Banner-Otog Banner-Angsu Town area,the surrounding areas of Hongdunjie Town in the southeastern part of the study area,the Hongshiqiao Township-Xiaohaotu Township area,Otog Front Banner,and Bainijing Town,which should be prioritized in the ecological conservation and restoration.Additionally,the paper proposed suggestions for the ecological conservation and restoration of county-level administrative areas in the study area.Overall,the findings provide a valuable reference for the ecological conservation and restoration of the Mu Us Sandy Land and other desert areas in arid and semi-arid regions.

Climatology Comparison Studies of Precipitations Between GPCP and Rain Gauges in China

The Global Precipitation Climatology Project （GPCP） monthly rainfall data and the rainfall records observed by 740 rain gauges in the mainland of China are used to analyze similarities and differences of the precipitation in China in the period from January 1980 to December 2000. Results expose significantly consistent rainfall distributions between the both data in multi-year mean, multi-year seasonal mean, and multi-year monthly mean. Departures of monthly rainfall for each dataset also show a high correlation with an over 0.8 correlation coefficient. Analysis indicates small differences of both datasets during autumn, winter, and spring, but relative large ones in summer. Generally, the GPCP has trend of overestimating the rainfall rate. Based on above good relationship of both datasets, the GPCP data, are used to represent distributions and variations of precipitation in the Tibetan Plateau and Northwest China. Results indicate positive departures of precipitation in summer in the west part of Tibetan Plateau in the 1980s and negative departures after the 1980s. For the west part of Northwest China, analysis illustrates precipitation decreases a little, but no clear variation tendency.

Accelerating matrix/boundary precipitations to explore high-strength and high-ductile Co_(34)Cr_(32)Ni_(27)Al_(3.5)Ti_(3.5) multicomponent alloys through hot extrusion and annealing

Annealing-regulated precipitation strengthening combined with cold-working is one of the most efficient strategies for resolving the conflict between strength and ductility in metals and alloys.However,precipitation control and grain refinement are mutually contradictory due to the excellent phase stability of multicomponent alloys.This work utilizes the high-temperature extrusion and annealing to optimize the microstructures and mechanical properties of the Co_(34)Cr_(32)Ni_(27)Al_(3.5)Ti_(3.5) multicomponent alloy.Hot extrusion effectively reduces grain sizes and simultaneously accelerates the precipitation of coherent L12 nanoparticles inside the face-centered cubic(FCC)matrix and grain boundary precipitations(i.e.,submicron Cr-rich particles and L12-Ni 3(Ti,Al)precipitates),resulting in strongly reciprocal interaction between dislocation slip and hierarchical-scale precipitates.Subsequent annealing regulates grain sizes,dislocations,twins,and precipitates,further allowing to tailor mechanical properties.The high yield strength is attributed to the coupled precipitation strengthening effects from nanoscale coherent L12 particles inside grains and submicron grain boundary precipitates under the support of pre-existing dislocations.The excellent ductility results from the synergistic activation of dislocations,stacking faults,and twins during plastic deformation.The present study provides a promising approach for regulat-ing microstructures,especially defects,and enhancing the mechanical properties of multicomponent alloys.

Effect of drying-wetting cycles on pore characteristics and mechanical properties of enzyme-induced carbonate precipitation-reinforced sea sand

Enzyme-induced carbonate precipitation(EICP)is an emanating,eco-friendly and potentially sound technique that has presented promise in various geotechnical applications.However,the durability and microscopic characteristics of EICP-treated specimens against the impact of drying-wetting(D-W)cycles is under-explored yet.This study investigates the evolution of mechanical behavior and pore charac-teristics of EICP-treated sea sand subjected to D-W cycles.The uniaxial compressive strength(UCS)tests,synchrotron radiation micro-computed tomography(micro-CT),and three-dimensional(3D)recon-struction of CT images were performed to study the multiscale evolution characteristics of EICP-reinforced sea sand under the effect of D-W cycles.The potential correlations between microstructure characteristics and macro-mechanical property deterioration were investigated using gray relational analysis(GRA).Results showed that the UCS of EICP-treated specimens decreases by 63.7% after 15 D-W cycles.The proportion of mesopores gradually decreases whereas the proportion of macropores in-creases due to the exfoliated calcium carbonate with increasing number of D-W cycles.The micro-structure in EICP-reinforced sea sand was gradually disintegrated,resulting in increasing pore size and development of pore shape from ellipsoidal to columnar and branched.The gray relational degree suggested that the weight loss rate and UCS deterioration were attributed to the development of branched pores with a size of 100-1000 m m under the action of D-W cycles.Overall,the results in this study provide a useful guidancee for the long-term stability and evolution characteristics of EICP-reinforced sea sand under D-W weathering conditions.

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.