Manganese is a major impurity in acidic vanadium-bearing leaching solutions,but its effects on vanadium precipitation via hydrolysis and acidic ammonium salts remain unclear.In this study,vanadium-bearing leachates wi...Manganese is a major impurity in acidic vanadium-bearing leaching solutions,but its effects on vanadium precipitation via hydrolysis and acidic ammonium salts remain unclear.In this study,vanadium-bearing leachates with varying manganese concentrations(VL-cMn)were prepared through calcium,a calcium-manganese composite,and manganese-based roasting of vanadium slag(VS)to investigate the influence of manganese on vanadium precipitation behavior during hydrolysis precipitation(HP)and ammonium salt precipitation(AP),as well as the microscopic characteristics and purity of the resulting V_(2)O_(5) products.The results showed that increasing the pH mitigated the negative effects of Mn on the V precipitation rate during HP.However,as the manganese concentration increased from 5.69 to 15.38 g/L,the V precipitation rate gradually declined at higher temperatures and longer reaction times.The precipitates exhibited increased microstructural density,which might had contributed to the formation of Mn-bearing phases.Additionally,the average grain size of V_(2)O_(5) was reduced and the particles were increasingly agglomerated,leading to a 2.55%decrease in product purity.For AP,as manganese concentration increased,raising the pH counteracted the negative impact of Mn on the V precipitation rate and reduced the required amount of ammonium sulfate.Moreover,Mn was unevenly adsorbed on the surface of the precipitates.Although V_(2)O_(5) grains gradually shrank and became denser,there was no significant effect on the final product purity,which remained above 99.3%.In conclusion,roasting with added manganese salts influenced the hydrolysis of vanadium but had no significant effect on acidic ammonium salt precipitation.展开更多
Precipitation events,which follow a life cycle of initiation,development,and decay,represent the fundamental form of precipitation.Comprehensive and accurate detection of these events is crucial for effective water re...Precipitation events,which follow a life cycle of initiation,development,and decay,represent the fundamental form of precipitation.Comprehensive and accurate detection of these events is crucial for effective water resource management and flood control.However,current investigations on their spatio-temporal patterns remain limited,largely because of the lack of systematic detection indices that are specifically designed for precipitation events,which constrains event-scale research.In this study,we defined a set of precipitation event detection indices(PEDI)that consists of five conventional and fourteen extreme indices to characterize precipitation events from the perspectives of intensity,duration,and frequency.Applications of the PEDI revealed the spatial patterns of hourly precipitation events in China and its first-and second-order river basins from 2008 to 2017.Both conventional and extreme precipitation events displayed spatial distribution patterns that gradually decreased in intensity,duration,and frequency from southeast to northwest China.Compared with those in northwest China,the average values of most PEDIs in southeast China were usually 2-10 times greater for first-order river basins and 3-15 times greater for second-order basins.The PEDI could serve as a reference method for investigating precipitation events at global,regional,and basin scales.展开更多
The water-quenched(WQ)2195 Al−Li alloy was subjected to stretching at different temperatures,from room temperature(RT)to−196℃(CT),to investigate the effect of cryogenic deformation on the aging precipitation behavior...The water-quenched(WQ)2195 Al−Li alloy was subjected to stretching at different temperatures,from room temperature(RT)to−196℃(CT),to investigate the effect of cryogenic deformation on the aging precipitation behaviors and mechanical properties.The precipitation kinetics of the T1 phase and the microstructures in peak aging state were investigated through the differential scanning calorimetric(DSC)tests and electron microscopy observation.The results show that−196℃deformation produces a high dislocation density,which promotes the precipitation of the T1 phase and refines its sizes significantly.In addition,the grain boundary precipitates(GBPs)of−196℃-stretched samples are suppressed considerably due to the high dislocation density in the grain interiors,which increases the ductility.In comparison,the strength remains nearly constant.Thus,it is indicated that cryogenic forming has the potential to provide the shape and property control for the manufacture of critical components of aluminum alloys.展开更多
China launched its first spaceborne Precipitation Measurement Radar(PMR)on the FY-3G satellite in April 2023.To achieve the scientific goal of measuring the three-dimensional precipitation structure,evaluating the qua...China launched its first spaceborne Precipitation Measurement Radar(PMR)on the FY-3G satellite in April 2023.To achieve the scientific goal of measuring the three-dimensional precipitation structure,evaluating the quantitative measurement ability of the PMR is critical.China operates more than 250 weather radars over the mainland.Consistency of the spaceborne radar with ground-based radars will enhance precipitation measurement ability,especially over oceans and mountains where observations are sparse.Additionally,the spaceborne radar can be used to evaluate the spatial and temporal homogeneity of the ground-based radar network.This paper focuses on comparing the PMR onboard the FY-3G satellite with S-band China New Generation Weather Radars(CINRADs).A comparison algorithm between the PMR and CINRADs has been developed,incorporating detailed quality control,attenuation correction,data optimization,spatiotemporal matching,non-uniform beam filling constraint,uniformity constraint,and frequency correction.The matched data in typical months of four seasons were selected to carry out the comparison.The data consistency between the PMR and CINRADs was analyzed.The correlation coefficient is 0.87,the deviation is 0.89 dB,and the standard deviation is 2.50 dB,based on 98226 matching samples.The results show the radar reflectivity of the PMR is quite comparable to that of the CINRADs,demonstrating that the PMR data quality is satisfactory and can be used to verify and correct data consistency among multiple ground-based radars.This work also paves the way for data fusion and joint application of satellite and ground radars in the future.展开更多
Based on reanalysis data from 1979 to 2021,this study explores the spatial distribution of the Southern Indian Ocean Dipole(SIOD)and its individual and synergistic effects with the El Niño-Southern Oscillation(EN...Based on reanalysis data from 1979 to 2021,this study explores the spatial distribution of the Southern Indian Ocean Dipole(SIOD)and its individual and synergistic effects with the El Niño-Southern Oscillation(ENSO)on summer precipitation in China.The inverse phase spatial distribution of sea surface temperature anomalies(SSTAs)in the southwest and northeast of the southern Indian Ocean is defined as the SIOD.Positive SIOD events(positive SSTAs in the southwest,negative SSTAs in the northeast)are associated with La Niña events(Central Pacific(CP)type),while negative SIOD events(negative SSTAs in the southwest,positive SSTAs in the northeast)are associated with El Niño events(Eastern Pacific(EP)type).Both SIOD and ENSO have certain impacts on summer precipitation in China.Precipitation in the Yangtze River basin decreases,while precipitation in southern China increases during pure positive SIOD(P_PSIOD)events.During pure negative SIOD(P_NSIOD)events,the changes in precipitation are exactly the opposite of those during P_PSIOD events,which may be due to differences in the cross-equatorial flow in the southern Indian Ocean,particularly in low-level Australian cross-equatorial flow.When positive SIOD and CP-type La Niña events occur simultaneously(PSIOD+La_Niña),precipitation increases in the Yangtze-Huaihe River basin,while it decreases in northern China.When negative SIOD and EP-type El Niño events occur simultaneously(NSIOD+El_Niño),precipitation in the Yangtze-Huaihe River basin is significantly lower than during P_NSIOD events.This is caused by differences in water vapor originating from the Pacific Ocean during different events.展开更多
Northeast China(NEC),a critical agricultural and ecological zone,has experienced intensified hydrological variability under global warming,with cascading impacts on food security and ecosystem resilience.This study ut...Northeast China(NEC),a critical agricultural and ecological zone,has experienced intensified hydrological variability under global warming,with cascading impacts on food security and ecosystem resilience.This study utilized observational data and two new generation reanalysis products(i.e.,the fifth major global reanalysis produced by ECMWF(ERA5)and the Japanese Reanalysis for Three Quarters of a Century(JRA-3Q))to investigate the shift changes in precipitation in NEC around 2000 and associated water vapor transport.The analysis identified a pivotal interdecadal shift in 1998/99,transitioning from moderate increases(17.5 mm/10 yr during 1980-1998)to accelerated but more variable precipitation growth(85.4 mm/10 yr post-1999).While the mean precipitation during the post-shift period decreased,enhanced anticyclonic circulation amplified moisture divergence over continental NEC,redirecting vapor flux toward coastal regions.Crucially,trajectory analysis demonstrated regime-dependent moisture sourcing:midlatitude westerlies dominated during wet extremes(44% of trajectories in 1998),whereas East Asian monsoon flows prevailed in drought years(36% of trajectories in 2007).The post-1998 period exhibited increased reliance on localized recycling(45%of mid-tropospheric trajectories),reflecting weakened monsoonal inflow.These findings highlight NEC’s growing vulnerability to competing moisture pathways and atmospheric blocking-a dual mechanism that explains rising extremes despite declining mean precipitation.By reconciling dataset discrepancies(ERA5 vs.JRA-3Q trends)and elucidating circulation-precipitation linkages,this work provides actionable insights for climate-resilient agriculture in NEC’s water-stressed ecosystems.展开更多
Using multi-source reanalysis data,this study examines the relationship between the tropical Pacific-Atlantic SST Dipole Mode(TPA-DM)and summer precipitation in North China(NCSP)on the interannual timescale during the...Using multi-source reanalysis data,this study examines the relationship between the tropical Pacific-Atlantic SST Dipole Mode(TPA-DM)and summer precipitation in North China(NCSP)on the interannual timescale during the period of 1979-2022.The results show that the TPA-DM,the dominant pattern of interannual variability in the tropical Pacific and Atlantic regions,exhibits a significant negative correlation with NCSP.The positive phase of TPA-DM induces subsidence over the Maritime Continent through a zonal circulation pattern,which initiates a Pacific-Japan-like wave train along the East Asian coast.The circulation anomalies lead to moisture deficits and convergence subsidence over North China,leading to below-normal rainfall.Further analysis reveals that cooler SST in the Southern Tropical Atlantic facilitates the persistence of the TPA-DM by stimulating the anomalous Walker circulation associated with wind-evaporation-SST-convection feedback.展开更多
Global land monsoon precipitation(GLMP)is highly sensitive to changes in interhemispheric thermal contrast(ITC).Amplified interhemispheric asymmetries of GLMP due to enhanced ITC driven by high-level anthropogenic emi...Global land monsoon precipitation(GLMP)is highly sensitive to changes in interhemispheric thermal contrast(ITC).Amplified interhemispheric asymmetries of GLMP due to enhanced ITC driven by high-level anthropogenic emissions are expected to simultaneously increase the probability of regional floods and droughts,threatening ecosystems within global terrestrial monsoon regions and the freshwater supply for billions of residents in these areas.In this study,the responses of GLMP to the evolution of ITC toward the carbon neutrality goal are assessed using multimodel outputs from a new model intercomparison project(CovidMIP).The results show that the Northern Hemisphere-Southern Hemisphere(NH-SH)asymmetry of GLMP in boreal summer weakens during the 2040s,as a persistent reduction in well-mixed greenhouse gas(WMGHG)emissions leads to a downward trend in the ITC after 2040.At the same time,the reduction in WMGHG emissions dampens the Eastern Hemisphere-Western Hemisphere(EH-WH)asymmetry of GLMP by inducing La Niña-like cooling and enhancing moisture transport to Inner America.The resulting increases in land monsoon precipitation(LMP)may alleviate drought under the global warming scenario by about 19%-25%and 7%-9%in the WH and SH monsoon regions,respectively.However,a persistent reduction in aerosol emissions in Asia will dominate the increases in LMP in this region until the mid-21st century,and these increases may be approximately 23%-60%of the growth under the global warming scenario.Our results highlight the different rates of response of aerosol and WMGHG concentrations to the carbon neutrality goal,leading to various changes in LMP at global and regional scales.展开更多
Northeast China serves as an important crop production region.Accurately forecasting summer precipitation in Northeast China(NEC-PR)has been a challenge due to its wide range of time scales influenced by varying clima...Northeast China serves as an important crop production region.Accurately forecasting summer precipitation in Northeast China(NEC-PR)has been a challenge due to its wide range of time scales influenced by varying climatic conditions.This study presents a scale separation hybrid statistical model with recurrent neural network(SS-RNN)to predict the summer monthly NEC-PR.The SS-RNN model decomposes the multiple scales of the NEC-PR into several spatiotemporal intrinsic mode functions covering annual to decadal time scales.This strategy provides a way to derive appropriate predictors and establish predictive models for the primary spatial modes of the NEC-PR at various time scales.Our results demonstrate substantial improvements by the SS-RNN model in predicting the summer monthly NEC-PR as compared with dynamic models,particularly in predicting the spatial pattern of the NEC-PR.In this paper we take August,the month of the highest NEC-PR,to assess our model skill.Independent forecasts of the August NEC-PR over the period 2021–24 achieve significant spatial anomaly correlation coefficients,reaching a maximum value of 0.83.Additional verifications by station observations show that the model hits most station anomalies,achieving a mean predictive skill score of 90.展开更多
Precipitation nowcasting is of great importance for disaster prevention and mitigation.However,precipitation is a complex spatio-temporal phenomenon influenced by various underlying physical factors.Even slight change...Precipitation nowcasting is of great importance for disaster prevention and mitigation.However,precipitation is a complex spatio-temporal phenomenon influenced by various underlying physical factors.Even slight changes in the initial precipitation field can have a significant impact on the future precipitation patterns,making the nowcasting of short-term high-resolution precipitation a major challenge.Traditional deep learning methods often have difficulty capturing the long-term spatial dependence of precipitation and are usually at a low resolution.To address these issues,based upon the Simpler yet Better Video Prediction(SimVP)framework,we proposed a deep generative neural network that incorporates the Simple Parameter-Free Attention Module(SimAM)and Generative Adversarial Networks(GANs)for short-term high-resolution precipitation event forecasting.Through an adversarial training strategy,critical precipitation features were extracted from complex radar echo images.During the adversarial learning process,the dynamic competition between the generator and the discriminator could continuously enhance the model in prediction accuracy and resolution for short-term precipitation.Experimental results demonstrate that the proposed method could effectively forecast short-term precipitation events on various scales and showed the best overall performance among existing methods.展开更多
Groundwater level(GWL)is a key indicator used to accurately assess groundwater resources and form the foundation for ef-fective groundwater management.This paper integrates a Gate Recurrent Unit(GRU)model with a Multi...Groundwater level(GWL)is a key indicator used to accurately assess groundwater resources and form the foundation for ef-fective groundwater management.This paper integrates a Gate Recurrent Unit(GRU)model with a Multi-head Self-attention mechan-ism(MSAM-GRU)to simulate GWLs in both confined and unconfined aquifers simultaneously.The model innovatively captures the lag times between GWLs in the unconfined aquifer and precipitation,as well as between GWLs in the confined aquifer and the upper aquifer.We have assessed the effectiveness of the proposed model using a case study in the Beijing Plain,China from January 2005 to December 2020.With the consideration of lag times,the results indicated that the MSAM-GRU model exhibits a maximum 67%and 73%reduction in RMSE compared to the Attention mechanism-GRU(AM-GRU)and GRU model,respectively.MSAM-GRU model exhibited a 31%reduction in RMSE and a 0.12 increase in R^(2) compared to the same model that do not account for lag time.In Region I,the shortest lag time of GWL in the unconfined aquifer was two months,while that in the confined aquifer was three months,indicating a longer delayed response in the confined aquifer.MSAM-GRU model considering lag time,was then applied to simulate the GWLs in the unconfined aquifer under different scenarios and to analyze whether GWL fluctuations affect subway operations.The simulation res-ults showed that under the scenario 1,the GWL in the unconfined aquifer would rise above the depth of subway station floor,threaten-ing the operation of subways.This study can provide reliable technical support for the accurate simulation of GWLs in multi-aquifer systems.展开更多
Due to global warming, extreme weather and climate events are becoming more frequent, highlighting the need to explore the changing characteristics of precipitation in China, including extreme precipitation. A cluster...Due to global warming, extreme weather and climate events are becoming more frequent, highlighting the need to explore the changing characteristics of precipitation in China, including extreme precipitation. A clustering algorithm was developed to classify summer(June, July, and August) daily precipitation in China from 1961 to 2020, considering spatial distribution, standard deviations, and frequency of extreme precipitation events. The results reveal six distinct precipitation climate zones, a classification that differs from previous divisions. While overall precipitation has decreased in most regions, the frequency of extreme precipitation events has increased across all clusters, indicating a shift in precipitation distribution patterns. Analysis shows that the weakened Lake Baikal blocking high and strengthened Mongolian cyclone influence the arid region in northwest China(Cluster 1), which is characterized by the lowest precipitation.The transition zone between the monsoon and arid region(Cluster 2) is affected by the Mongolian cyclone, water vapor transport from the Indian Ocean, and shifts in the monsoon boundary. Clusters 3 and 4 represent areas associated with advancement and retreat of the summer monsoon. In the Meiyu region, two distinct subregions have been identified exist.Cluster 4 is primarily influenced by the East Asia-Pacific wave train. Despite sharing similar climate drivers and proximity,Clusters 4 and 5 differ significantly due to topographic variations and disparate levels of urbanization. Cluster 5 exhibits a higher average precipitation, greater variability, and more frequent extreme events. Cluster 6 exhibits the highest overall precipitation in the coastal areas of Guangdong and Guangxi, where abundant water vapor contributes to a higher frequency of extreme precipitation. In addition, anthropogenic activities and urbanization significantly influence precipitation in Beijing-Tianjin-Hebei and Yangtze River Delta regions. This research proposes a precipitation classification scheme integrating multiple precipitation parameters, providing support for risk management and mitigation strategies in the face of increasing extreme precipitation events.展开更多
The microstructural evolution of Cu−19Ni−6Cr−7Mn alloy during aging treatment was investigated.After aging for 120 min at 500℃,the alloy exhibited excellent mechanical properties,including a tensile strength of 978 M...The microstructural evolution of Cu−19Ni−6Cr−7Mn alloy during aging treatment was investigated.After aging for 120 min at 500℃,the alloy exhibited excellent mechanical properties,including a tensile strength of 978 MPa and an elastic modulus of 145.8 GPa.After aging for 240 min at 500℃,the elastic modulus of the alloy reached 149.5 GPa,which was among the highest values reported for Cu alloys.It was worth mentioning that the tensile strength increased rapidly from 740 to 934 MPa after aging for 5 min at 500℃,which was close to the maximum tensile strength(978 MPa).Analysis of the underlying strengthening mechanisms and phase transformation behavior revealed that the Cu−19Ni−6Cr−7Mn alloy underwent spinodal decomposition and DO_(22) ordering during the first 5 min of aging at 500℃,and L1_(2) ordered phases and bcc-Cr precipitates appeared.Therefore,the enhanced mechanical properties of the Cu−19Ni−6Cr−7Mn alloy can be attributed to the stress field generated by spinodal decomposition and the presence of nanoscale ordered phase and Cr precipitates.展开更多
[Objective]Precipitation events caused by Super Typhoon Doksuri in Fujian Province were simulated and evaluated based on the WRF model to provide a reference for typhoon precipitation simulation and forecasting in sou...[Objective]Precipitation events caused by Super Typhoon Doksuri in Fujian Province were simulated and evaluated based on the WRF model to provide a reference for typhoon precipitation simulation and forecasting in southeast coastal areas of China.[Methods]The next-generation mesoscale numerical weather prediction model WRF V4.3(The Weather Research and Forecasting Model)was used to simulate the precipitation caused by Typhoon Doksuri in Fujian Province in 2023.Observations from 86 meteorological stations with hourly rainfall records were used to evaluate the model’s performance.Six evaluation indices were used,including the correlation coefficient(R),root mean square error(RMSE),mean absolute error(MAE),equitable threat score(ETS),probability of detection(POD),and false alarm ratio(FAR).[Results](1)The temporal and spatial evolution of precipitation during Typhoon Doksuri was effectively captured by the WRF model.Precipitation intensity increased gradually from July 27 to 29,2023,with the heaviest rainfall concentrated in the northern and eastern coastal areas of Fujian Province.(2)Significant differences in model performance were observed in terms of R,RMSE,and MAE.The largest errors occurred in Putian City,while smaller errors were found in southwestern Fujian Province.The evaluation result of all six indices showed that the WRF model performed best in simulating daily precipitation compared to hourly,three-hourly,six-hourly,and twelve-hourly precipitation.(3)The R95p index indicated that the WRF model successfully captured the overall spatial distribution of extreme precipitation.However,extreme precipitation intensity was overestimated in certain coastal areas.(4)Despite accurately identifying the coastal regions of Fujian as being most affected,the WRF model failed to accurately simulate the spatial distribution and intensity of precipitation.The simulated precipitation centers showed discrepancies when compared with the observed centers.[Conclusion]Although the WRF model underestimated hourly precipitation,it successfully captured the temporal evolution and spatial distribution of rainfall caused by Typhoon Doksuri in Fujian Province.It reproduced the heavy rainfall centers in central Fujian Province,with daily precipitation peaks reaching up to 350 mm.This highlighted the severity of extreme rainfall caused by Typhoon Doksuri.展开更多
Cloud type profoundly affects precipitation,but few studies have explored its impact on precipitation scale height.The authors calculated the ratio of the volume of each cloud type to the total cloud volume and partit...Cloud type profoundly affects precipitation,but few studies have explored its impact on precipitation scale height.The authors calculated the ratio of the volume of each cloud type to the total cloud volume and partitioned the tropical region based on the dominant cloud types.Based on this,tropical regions were categorized into altocumulus control regions,stratocumulus control regions,deep convective cloud control regions,and transition regions.These regions exhibit unique characteristics:high precipitation scale heights and low surface precipitation rates in altocumulus control regions;low precipitation scale heights and low surface precipitation rates in stratocumulus control regions;and moderate precipitation scale heights with high surface precipitation rates in deep convective cloud regions.These features arise from differences in cloud characteristics,precipitation probability,and intensity,influenced by varying water vapor structures.In terms of physical mechanisms,altocumulus,stratocumulus,and deep convective cloud regions are characterized by total dryness,upper-level dryness with lower-level wetness,and total wetness,respectively.Upper-layer dryness leads to low cloud and precipitation structures,reducing the precipitation scale height,while lower-layer dryness increases it.Different humidity conditions in the upper and lower layers lead to variations in cloud type and volume distribution,ultimately affecting precipitation scale heights.This finding aids the mechanistic study of cloud precipitation physics in the tropics,providing valuable insights for developing numerical models and parameterizations.展开更多
Overcoming the tradeoffbetween mechanical strength and electrical conductivity is a long-standing chal-lenge in developing advanced copper alloys for industrial applications.Herein,we report a new strategy to obtain h...Overcoming the tradeoffbetween mechanical strength and electrical conductivity is a long-standing chal-lenge in developing advanced copper alloys for industrial applications.Herein,we report a new strategy to obtain high strength and good conductivity of Cu-Ni-Si-Ca alloy by introducing and regulating the discontinuous precipitation(DP)and continuous precipitation(CP)behaviors.The DP process combined with thermomechanical treatment was exploited to expedite the precipitation kinetics,whilst the com-petition between DP and CP was utilized to inhibit the nucleation and growth of continuous precipitation phase(CPP).The resultant copper alloy exhibits superior comprehensive properties with a yield strength of 956 MPa,fracture strength of 989 MPa,and electrical conductivity of 34.1%IACS.The improved elec-trical conductivity is attributed to the heterogeneous-nucleation dominant DP,while the high strength stems from the combination of strain hardening and precipitation strengthening of δ-Ni2 Si and t-Ni3 Si precipitates.Notably,the precipitation strengthening arises from both the dislocation passing and cutting mechanisms,with the strongly ordered DO22-type(t-Ni3 Si)phase contributing approximately 202 MPa to the overall strength through the cutting mechanism.This work offers a new pathway for alloy design of high-strength and high-electrical-conductivity copper alloys,by regulating coherent ordered nanoprecip-itates through DP and CP.展开更多
Deforestation has a significant influence on the hydrological cycle.Understanding the impact of deforestation on precipitation extremes is crucial for addressing global environmental challenges.This study investigates...Deforestation has a significant influence on the hydrological cycle.Understanding the impact of deforestation on precipitation extremes is crucial for addressing global environmental challenges.This study investigates the impact of deforestation on precipitation extremes(R95p index,which represents the total amount of precipitation exceeding the 95th percentile of the reference period)in China,using outputs from three earth system models(CanESM5,IPSL-CM6A-LR,and MIROC-ES2L).All models,along with their multimodel mean,indicate a general decrease in R95p in Northeast China and southern China,and changes in Northwest China and the Tibetan Plateau are minimal.In contrast,the responses are model-dependent in the Huanghuai and Jianghuai regions.The overall nationwide multimodel mean suggests an annual R95p decrease of 10.7 mm,with individual model variations ranging from-28.0 to 2.0 mm.Further analysis using precipitation extremes scaling reveals a high spatial correlation with direct precipitation extremes changes on both annual and seasonal scales,albeit with slightly smaller magnitudes.Decomposing the response into dynamic and thermodynamic scaling,the authors find that dynamic contributions predominantly drive the changes in precipitation extremes on both annual and seasonal scales.The authors findings highlight the substantial role of dynamic processes in modulating the response of precipitation extremes to deforestation in China.展开更多
Microbially induced calcite precipitation(MICP)and Enzyme induced calcite precipitation(EICP)techniques were implemented to reinforce the large-scale calcareous sand in this study.Then a coupled numerical model to pre...Microbially induced calcite precipitation(MICP)and Enzyme induced calcite precipitation(EICP)techniques were implemented to reinforce the large-scale calcareous sand in this study.Then a coupled numerical model to predict the biochemical reactions and hydraulic characteristics of MICP and EICP reactions was proposed and verified by physical experiments.Results showed that:This model could describe the variations of bacteria,calcium,calcite,permeability over time reasonably.It is necessary to consider the influence of the calculation domain scale when simulating the convection-diffusionreaction in the multi-process of MICP and EICP reactions.The numerical and experimental values of calcite content are 0.841 g/cm^(3) and 0.861 g/cm^(3) for MICP-reinforced sand,0.263 g/cm^(3) and 0.227 g/cm^(3) for EICP-reinforced sand after 192 h of reaction.The reaction rate k_(rea) is an important parameter to control the calcite content.Accordingly,the permeability coefficient of MICP and EICP reinforced calcareous sand decreases by 32%and 18%.Due to the influence of substance transportation and calcite precipitation,the calcite shows a trend of decreasing firstly and then increasing with the enhancing of the initial permeability coefficient in biochemical reactions.The optimal injecting ratio q11:q12 in this study is 100:300 mL/min.The process for the application of MICP and EICP coupled numerical model is also recommended,which provides reference for engineering projects in ground improvement.展开更多
The intensification of extreme precipitation(EP)under global warming presents a substantial risk to human safety and societal progress.Studying the specific impacts of global warming on rare EP events in China not onl...The intensification of extreme precipitation(EP)under global warming presents a substantial risk to human safety and societal progress.Studying the specific impacts of global warming on rare EP events in China not only enhances the comprehension of these shifts,but also paves the way for the development of proactive strategies to alleviate associated damages.Results from large-ensemble simulation data demonstrate that global warming has led to an enhancement in once-in-a-decade EP events in parts of western and central China over the past few decades,with the strengthening of the South Asia high(SAH)caused by global warming playing a dominant role.The strengthening of the SAH corresponds to an intensification and westward extension of the western Pacific subtropical high in the lower troposphere.The region between these two systems experiences enhanced upward motion and increased southwesterly water vapor transport,leading to a rise in climatological precipitation in western and central China,thereby raising the threshold for once-in-a-decade EP events.展开更多
Satellite Precipitation Products(SPPs) face challenges in detecting Extreme Precipitation Events(EPEs). Hence, the primary objective of this research is to introduce a novel framework termed Machine-Learning Clusterin...Satellite Precipitation Products(SPPs) face challenges in detecting Extreme Precipitation Events(EPEs). Hence, the primary objective of this research is to introduce a novel framework termed Machine-Learning Clustering-Merging Algorithms(ML-CMAs) to evaluate EPEs using SPPs and Auxiliary Data(AD). Daily precipitation measurements were utilized for training and evaluating EPE estimates over Iran, which is comprised of arid and semi-arid regions. Statistical analysis and evaluation of five SPPs demonstrated that during EPE occurrences, all products face challenges in precipitation estimation, and using these products individually is not recommended. Among the SPPs, Multi-Source Weighted-Ensemble Precipitation(MSWEP) performed best for heavy(>20 mm d–1) and extreme(>40 mm d–1)precipitation events, followed by Global Satellite Mapping of Precipitation(GSMa P), Integrated Multi-Satellite Retrievals for Global Precipitation Measurement(IMERG), Climate Prediction Center morphing technique(CMORPH), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Dynamic Infrared-Rain Rate(PERSIANN-PDIR). The findings indicate that all proposed methods based on ML-CMAs could estimate precipitation rates more accurately than SPPs and improve statistical indices. The seasonal assessment and spatial analysis of statistical metrics of the overall daily precipitation results for all periods and climates revealed that all methods based on ML-CMAs performed well in all seasons and at nearly all measurement stations. Using unsupervised K-means++ classification for clustering EPEs and Deep Neural Network(DNN) and Convolutional Neural Network(CNN) methods for merging the MLCMAs reduced the error rate of SPPs in EPE estimation by approximately 50%. Therefore, incorporating ML-CMAs along with PWV as AD can significantly improve the performance of SPPs in evaluating EPEs over the study region.展开更多
基金supported by National Natural Science Foundation of China(Nos.52204309,52174277 and 52374300)Fundamental Funds for the Central Universities(No.N2425026)。
文摘Manganese is a major impurity in acidic vanadium-bearing leaching solutions,but its effects on vanadium precipitation via hydrolysis and acidic ammonium salts remain unclear.In this study,vanadium-bearing leachates with varying manganese concentrations(VL-cMn)were prepared through calcium,a calcium-manganese composite,and manganese-based roasting of vanadium slag(VS)to investigate the influence of manganese on vanadium precipitation behavior during hydrolysis precipitation(HP)and ammonium salt precipitation(AP),as well as the microscopic characteristics and purity of the resulting V_(2)O_(5) products.The results showed that increasing the pH mitigated the negative effects of Mn on the V precipitation rate during HP.However,as the manganese concentration increased from 5.69 to 15.38 g/L,the V precipitation rate gradually declined at higher temperatures and longer reaction times.The precipitates exhibited increased microstructural density,which might had contributed to the formation of Mn-bearing phases.Additionally,the average grain size of V_(2)O_(5) was reduced and the particles were increasingly agglomerated,leading to a 2.55%decrease in product purity.For AP,as manganese concentration increased,raising the pH counteracted the negative impact of Mn on the V precipitation rate and reduced the required amount of ammonium sulfate.Moreover,Mn was unevenly adsorbed on the surface of the precipitates.Although V_(2)O_(5) grains gradually shrank and became denser,there was no significant effect on the final product purity,which remained above 99.3%.In conclusion,roasting with added manganese salts influenced the hydrolysis of vanadium but had no significant effect on acidic ammonium salt precipitation.
基金National Key Research and Development Program of China,No.2023YFC3206605,No.2021YFC3201102National Natural Science Foundation of China,No.41971035。
文摘Precipitation events,which follow a life cycle of initiation,development,and decay,represent the fundamental form of precipitation.Comprehensive and accurate detection of these events is crucial for effective water resource management and flood control.However,current investigations on their spatio-temporal patterns remain limited,largely because of the lack of systematic detection indices that are specifically designed for precipitation events,which constrains event-scale research.In this study,we defined a set of precipitation event detection indices(PEDI)that consists of five conventional and fourteen extreme indices to characterize precipitation events from the perspectives of intensity,duration,and frequency.Applications of the PEDI revealed the spatial patterns of hourly precipitation events in China and its first-and second-order river basins from 2008 to 2017.Both conventional and extreme precipitation events displayed spatial distribution patterns that gradually decreased in intensity,duration,and frequency from southeast to northwest China.Compared with those in northwest China,the average values of most PEDIs in southeast China were usually 2-10 times greater for first-order river basins and 3-15 times greater for second-order basins.The PEDI could serve as a reference method for investigating precipitation events at global,regional,and basin scales.
基金financially supported by the National Key Research and Development Program of China (No. 2019YFA0708801)the National Natural Science Foundation of China (No. 51875125)。
文摘The water-quenched(WQ)2195 Al−Li alloy was subjected to stretching at different temperatures,from room temperature(RT)to−196℃(CT),to investigate the effect of cryogenic deformation on the aging precipitation behaviors and mechanical properties.The precipitation kinetics of the T1 phase and the microstructures in peak aging state were investigated through the differential scanning calorimetric(DSC)tests and electron microscopy observation.The results show that−196℃deformation produces a high dislocation density,which promotes the precipitation of the T1 phase and refines its sizes significantly.In addition,the grain boundary precipitates(GBPs)of−196℃-stretched samples are suppressed considerably due to the high dislocation density in the grain interiors,which increases the ductility.In comparison,the strength remains nearly constant.Thus,it is indicated that cryogenic forming has the potential to provide the shape and property control for the manufacture of critical components of aluminum alloys.
基金jointly supported by the National Natural Science Foundation of China(Grant U2442214)the China Meteorological Administration Youth Innovation Team(Grant No.CMA2024QN10)+1 种基金the National Defense Science and Technology Bureau’s 14th Five-Year Civil Aerospace Preresearch Project(Grant Nos.D030303 and D040204)the International Space Water Cycle Observation Constellation Program(Grant No.183311KYSB20200015).
文摘China launched its first spaceborne Precipitation Measurement Radar(PMR)on the FY-3G satellite in April 2023.To achieve the scientific goal of measuring the three-dimensional precipitation structure,evaluating the quantitative measurement ability of the PMR is critical.China operates more than 250 weather radars over the mainland.Consistency of the spaceborne radar with ground-based radars will enhance precipitation measurement ability,especially over oceans and mountains where observations are sparse.Additionally,the spaceborne radar can be used to evaluate the spatial and temporal homogeneity of the ground-based radar network.This paper focuses on comparing the PMR onboard the FY-3G satellite with S-band China New Generation Weather Radars(CINRADs).A comparison algorithm between the PMR and CINRADs has been developed,incorporating detailed quality control,attenuation correction,data optimization,spatiotemporal matching,non-uniform beam filling constraint,uniformity constraint,and frequency correction.The matched data in typical months of four seasons were selected to carry out the comparison.The data consistency between the PMR and CINRADs was analyzed.The correlation coefficient is 0.87,the deviation is 0.89 dB,and the standard deviation is 2.50 dB,based on 98226 matching samples.The results show the radar reflectivity of the PMR is quite comparable to that of the CINRADs,demonstrating that the PMR data quality is satisfactory and can be used to verify and correct data consistency among multiple ground-based radars.This work also paves the way for data fusion and joint application of satellite and ground radars in the future.
基金supported by the National Natural Science Foundation of China[grant numbers 41975087,U2242212,and 41975085]supported by the National Natural Science Foundation of China[grant number U2242212]。
文摘Based on reanalysis data from 1979 to 2021,this study explores the spatial distribution of the Southern Indian Ocean Dipole(SIOD)and its individual and synergistic effects with the El Niño-Southern Oscillation(ENSO)on summer precipitation in China.The inverse phase spatial distribution of sea surface temperature anomalies(SSTAs)in the southwest and northeast of the southern Indian Ocean is defined as the SIOD.Positive SIOD events(positive SSTAs in the southwest,negative SSTAs in the northeast)are associated with La Niña events(Central Pacific(CP)type),while negative SIOD events(negative SSTAs in the southwest,positive SSTAs in the northeast)are associated with El Niño events(Eastern Pacific(EP)type).Both SIOD and ENSO have certain impacts on summer precipitation in China.Precipitation in the Yangtze River basin decreases,while precipitation in southern China increases during pure positive SIOD(P_PSIOD)events.During pure negative SIOD(P_NSIOD)events,the changes in precipitation are exactly the opposite of those during P_PSIOD events,which may be due to differences in the cross-equatorial flow in the southern Indian Ocean,particularly in low-level Australian cross-equatorial flow.When positive SIOD and CP-type La Niña events occur simultaneously(PSIOD+La_Niña),precipitation increases in the Yangtze-Huaihe River basin,while it decreases in northern China.When negative SIOD and EP-type El Niño events occur simultaneously(NSIOD+El_Niño),precipitation in the Yangtze-Huaihe River basin is significantly lower than during P_NSIOD events.This is caused by differences in water vapor originating from the Pacific Ocean during different events.
基金supported by the National Natural Science Foundation of China[grant numbers 42275185 and 42205032]the Fundamental Research Funds for the Central Universities[grant number B250201118]。
文摘Northeast China(NEC),a critical agricultural and ecological zone,has experienced intensified hydrological variability under global warming,with cascading impacts on food security and ecosystem resilience.This study utilized observational data and two new generation reanalysis products(i.e.,the fifth major global reanalysis produced by ECMWF(ERA5)and the Japanese Reanalysis for Three Quarters of a Century(JRA-3Q))to investigate the shift changes in precipitation in NEC around 2000 and associated water vapor transport.The analysis identified a pivotal interdecadal shift in 1998/99,transitioning from moderate increases(17.5 mm/10 yr during 1980-1998)to accelerated but more variable precipitation growth(85.4 mm/10 yr post-1999).While the mean precipitation during the post-shift period decreased,enhanced anticyclonic circulation amplified moisture divergence over continental NEC,redirecting vapor flux toward coastal regions.Crucially,trajectory analysis demonstrated regime-dependent moisture sourcing:midlatitude westerlies dominated during wet extremes(44% of trajectories in 1998),whereas East Asian monsoon flows prevailed in drought years(36% of trajectories in 2007).The post-1998 period exhibited increased reliance on localized recycling(45%of mid-tropospheric trajectories),reflecting weakened monsoonal inflow.These findings highlight NEC’s growing vulnerability to competing moisture pathways and atmospheric blocking-a dual mechanism that explains rising extremes despite declining mean precipitation.By reconciling dataset discrepancies(ERA5 vs.JRA-3Q trends)and elucidating circulation-precipitation linkages,this work provides actionable insights for climate-resilient agriculture in NEC’s water-stressed ecosystems.
基金jointly supported by the Second Tibetan Plateau Scientific Expedition and Research Program[grant number-ber 2019QZKK0103]the National Natural Science Foundation of China[grant number 42293294]the China Meteorological Admin-istration Climate Change Special Program[grant number QBZ202303]。
文摘Using multi-source reanalysis data,this study examines the relationship between the tropical Pacific-Atlantic SST Dipole Mode(TPA-DM)and summer precipitation in North China(NCSP)on the interannual timescale during the period of 1979-2022.The results show that the TPA-DM,the dominant pattern of interannual variability in the tropical Pacific and Atlantic regions,exhibits a significant negative correlation with NCSP.The positive phase of TPA-DM induces subsidence over the Maritime Continent through a zonal circulation pattern,which initiates a Pacific-Japan-like wave train along the East Asian coast.The circulation anomalies lead to moisture deficits and convergence subsidence over North China,leading to below-normal rainfall.Further analysis reveals that cooler SST in the Southern Tropical Atlantic facilitates the persistence of the TPA-DM by stimulating the anomalous Walker circulation associated with wind-evaporation-SST-convection feedback.
基金funded by the National Natural Science Foundation of China(Grant No.42275039)the Meteorological Joint Fund by NSF and CMA(Grant No.U2342224)+1 种基金the National Key R&D Program of China(Grant No.2022YFC3701202)the S&T Development Fund of CAMS(Grant No.2024KJ019)。
文摘Global land monsoon precipitation(GLMP)is highly sensitive to changes in interhemispheric thermal contrast(ITC).Amplified interhemispheric asymmetries of GLMP due to enhanced ITC driven by high-level anthropogenic emissions are expected to simultaneously increase the probability of regional floods and droughts,threatening ecosystems within global terrestrial monsoon regions and the freshwater supply for billions of residents in these areas.In this study,the responses of GLMP to the evolution of ITC toward the carbon neutrality goal are assessed using multimodel outputs from a new model intercomparison project(CovidMIP).The results show that the Northern Hemisphere-Southern Hemisphere(NH-SH)asymmetry of GLMP in boreal summer weakens during the 2040s,as a persistent reduction in well-mixed greenhouse gas(WMGHG)emissions leads to a downward trend in the ITC after 2040.At the same time,the reduction in WMGHG emissions dampens the Eastern Hemisphere-Western Hemisphere(EH-WH)asymmetry of GLMP by inducing La Niña-like cooling and enhancing moisture transport to Inner America.The resulting increases in land monsoon precipitation(LMP)may alleviate drought under the global warming scenario by about 19%-25%and 7%-9%in the WH and SH monsoon regions,respectively.However,a persistent reduction in aerosol emissions in Asia will dominate the increases in LMP in this region until the mid-21st century,and these increases may be approximately 23%-60%of the growth under the global warming scenario.Our results highlight the different rates of response of aerosol and WMGHG concentrations to the carbon neutrality goal,leading to various changes in LMP at global and regional scales.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFC3002803)the National Key Research and Development Program of China(Grant No.2024YFF0808402)the National Natural Science Foundation of China(Grant No.42375169)。
文摘Northeast China serves as an important crop production region.Accurately forecasting summer precipitation in Northeast China(NEC-PR)has been a challenge due to its wide range of time scales influenced by varying climatic conditions.This study presents a scale separation hybrid statistical model with recurrent neural network(SS-RNN)to predict the summer monthly NEC-PR.The SS-RNN model decomposes the multiple scales of the NEC-PR into several spatiotemporal intrinsic mode functions covering annual to decadal time scales.This strategy provides a way to derive appropriate predictors and establish predictive models for the primary spatial modes of the NEC-PR at various time scales.Our results demonstrate substantial improvements by the SS-RNN model in predicting the summer monthly NEC-PR as compared with dynamic models,particularly in predicting the spatial pattern of the NEC-PR.In this paper we take August,the month of the highest NEC-PR,to assess our model skill.Independent forecasts of the August NEC-PR over the period 2021–24 achieve significant spatial anomaly correlation coefficients,reaching a maximum value of 0.83.Additional verifications by station observations show that the model hits most station anomalies,achieving a mean predictive skill score of 90.
基金Supported by the National Natural Science Foundation of China(No.42306214)the Postdoctoral Innovative Talents Support Program of Shandong Province(No.SDBX2022026)+1 种基金the China Postdoctoral Science Foundation(No.2023M733533)the Special Research Assistant Project of the Chinese Academy of Sciences in 2022。
文摘Precipitation nowcasting is of great importance for disaster prevention and mitigation.However,precipitation is a complex spatio-temporal phenomenon influenced by various underlying physical factors.Even slight changes in the initial precipitation field can have a significant impact on the future precipitation patterns,making the nowcasting of short-term high-resolution precipitation a major challenge.Traditional deep learning methods often have difficulty capturing the long-term spatial dependence of precipitation and are usually at a low resolution.To address these issues,based upon the Simpler yet Better Video Prediction(SimVP)framework,we proposed a deep generative neural network that incorporates the Simple Parameter-Free Attention Module(SimAM)and Generative Adversarial Networks(GANs)for short-term high-resolution precipitation event forecasting.Through an adversarial training strategy,critical precipitation features were extracted from complex radar echo images.During the adversarial learning process,the dynamic competition between the generator and the discriminator could continuously enhance the model in prediction accuracy and resolution for short-term precipitation.Experimental results demonstrate that the proposed method could effectively forecast short-term precipitation events on various scales and showed the best overall performance among existing methods.
基金Under the auspices of the National Key Research and Development Program of China(No.2024YFC3713102)。
文摘Groundwater level(GWL)is a key indicator used to accurately assess groundwater resources and form the foundation for ef-fective groundwater management.This paper integrates a Gate Recurrent Unit(GRU)model with a Multi-head Self-attention mechan-ism(MSAM-GRU)to simulate GWLs in both confined and unconfined aquifers simultaneously.The model innovatively captures the lag times between GWLs in the unconfined aquifer and precipitation,as well as between GWLs in the confined aquifer and the upper aquifer.We have assessed the effectiveness of the proposed model using a case study in the Beijing Plain,China from January 2005 to December 2020.With the consideration of lag times,the results indicated that the MSAM-GRU model exhibits a maximum 67%and 73%reduction in RMSE compared to the Attention mechanism-GRU(AM-GRU)and GRU model,respectively.MSAM-GRU model exhibited a 31%reduction in RMSE and a 0.12 increase in R^(2) compared to the same model that do not account for lag time.In Region I,the shortest lag time of GWL in the unconfined aquifer was two months,while that in the confined aquifer was three months,indicating a longer delayed response in the confined aquifer.MSAM-GRU model considering lag time,was then applied to simulate the GWLs in the unconfined aquifer under different scenarios and to analyze whether GWL fluctuations affect subway operations.The simulation res-ults showed that under the scenario 1,the GWL in the unconfined aquifer would rise above the depth of subway station floor,threaten-ing the operation of subways.This study can provide reliable technical support for the accurate simulation of GWLs in multi-aquifer systems.
基金National Natural Science Foundation of China(U2442202, 42274217, 62441501)Key Innovation Team of China Meteorological Administration (CMA2024ZD01)Scientific Research Foundation of CUIT (376278, KYTZ202158)。
文摘Due to global warming, extreme weather and climate events are becoming more frequent, highlighting the need to explore the changing characteristics of precipitation in China, including extreme precipitation. A clustering algorithm was developed to classify summer(June, July, and August) daily precipitation in China from 1961 to 2020, considering spatial distribution, standard deviations, and frequency of extreme precipitation events. The results reveal six distinct precipitation climate zones, a classification that differs from previous divisions. While overall precipitation has decreased in most regions, the frequency of extreme precipitation events has increased across all clusters, indicating a shift in precipitation distribution patterns. Analysis shows that the weakened Lake Baikal blocking high and strengthened Mongolian cyclone influence the arid region in northwest China(Cluster 1), which is characterized by the lowest precipitation.The transition zone between the monsoon and arid region(Cluster 2) is affected by the Mongolian cyclone, water vapor transport from the Indian Ocean, and shifts in the monsoon boundary. Clusters 3 and 4 represent areas associated with advancement and retreat of the summer monsoon. In the Meiyu region, two distinct subregions have been identified exist.Cluster 4 is primarily influenced by the East Asia-Pacific wave train. Despite sharing similar climate drivers and proximity,Clusters 4 and 5 differ significantly due to topographic variations and disparate levels of urbanization. Cluster 5 exhibits a higher average precipitation, greater variability, and more frequent extreme events. Cluster 6 exhibits the highest overall precipitation in the coastal areas of Guangdong and Guangxi, where abundant water vapor contributes to a higher frequency of extreme precipitation. In addition, anthropogenic activities and urbanization significantly influence precipitation in Beijing-Tianjin-Hebei and Yangtze River Delta regions. This research proposes a precipitation classification scheme integrating multiple precipitation parameters, providing support for risk management and mitigation strategies in the face of increasing extreme precipitation events.
基金supported by the National Key R&D Program of China (No. 2021YFB3700700)the Henan Province Top Talent Training Program Project, China (No. 244500510020)the High-level Talent Research Start-up Project Funding of Henan Academy of Sciences, China (No. 242017001)。
文摘The microstructural evolution of Cu−19Ni−6Cr−7Mn alloy during aging treatment was investigated.After aging for 120 min at 500℃,the alloy exhibited excellent mechanical properties,including a tensile strength of 978 MPa and an elastic modulus of 145.8 GPa.After aging for 240 min at 500℃,the elastic modulus of the alloy reached 149.5 GPa,which was among the highest values reported for Cu alloys.It was worth mentioning that the tensile strength increased rapidly from 740 to 934 MPa after aging for 5 min at 500℃,which was close to the maximum tensile strength(978 MPa).Analysis of the underlying strengthening mechanisms and phase transformation behavior revealed that the Cu−19Ni−6Cr−7Mn alloy underwent spinodal decomposition and DO_(22) ordering during the first 5 min of aging at 500℃,and L1_(2) ordered phases and bcc-Cr precipitates appeared.Therefore,the enhanced mechanical properties of the Cu−19Ni−6Cr−7Mn alloy can be attributed to the stress field generated by spinodal decomposition and the presence of nanoscale ordered phase and Cr precipitates.
文摘[Objective]Precipitation events caused by Super Typhoon Doksuri in Fujian Province were simulated and evaluated based on the WRF model to provide a reference for typhoon precipitation simulation and forecasting in southeast coastal areas of China.[Methods]The next-generation mesoscale numerical weather prediction model WRF V4.3(The Weather Research and Forecasting Model)was used to simulate the precipitation caused by Typhoon Doksuri in Fujian Province in 2023.Observations from 86 meteorological stations with hourly rainfall records were used to evaluate the model’s performance.Six evaluation indices were used,including the correlation coefficient(R),root mean square error(RMSE),mean absolute error(MAE),equitable threat score(ETS),probability of detection(POD),and false alarm ratio(FAR).[Results](1)The temporal and spatial evolution of precipitation during Typhoon Doksuri was effectively captured by the WRF model.Precipitation intensity increased gradually from July 27 to 29,2023,with the heaviest rainfall concentrated in the northern and eastern coastal areas of Fujian Province.(2)Significant differences in model performance were observed in terms of R,RMSE,and MAE.The largest errors occurred in Putian City,while smaller errors were found in southwestern Fujian Province.The evaluation result of all six indices showed that the WRF model performed best in simulating daily precipitation compared to hourly,three-hourly,six-hourly,and twelve-hourly precipitation.(3)The R95p index indicated that the WRF model successfully captured the overall spatial distribution of extreme precipitation.However,extreme precipitation intensity was overestimated in certain coastal areas.(4)Despite accurately identifying the coastal regions of Fujian as being most affected,the WRF model failed to accurately simulate the spatial distribution and intensity of precipitation.The simulated precipitation centers showed discrepancies when compared with the observed centers.[Conclusion]Although the WRF model underestimated hourly precipitation,it successfully captured the temporal evolution and spatial distribution of rainfall caused by Typhoon Doksuri in Fujian Province.It reproduced the heavy rainfall centers in central Fujian Province,with daily precipitation peaks reaching up to 350 mm.This highlighted the severity of extreme rainfall caused by Typhoon Doksuri.
基金supported by the National Natural Science Foundation of China[grant numbers 42175099 and 42027804]The appointment of Chunsong Lu at Nanjing University of Information Science&Technology was partially supported by the Jiangsu Specially-Appointed Professor[grant number R2024T01].
文摘Cloud type profoundly affects precipitation,but few studies have explored its impact on precipitation scale height.The authors calculated the ratio of the volume of each cloud type to the total cloud volume and partitioned the tropical region based on the dominant cloud types.Based on this,tropical regions were categorized into altocumulus control regions,stratocumulus control regions,deep convective cloud control regions,and transition regions.These regions exhibit unique characteristics:high precipitation scale heights and low surface precipitation rates in altocumulus control regions;low precipitation scale heights and low surface precipitation rates in stratocumulus control regions;and moderate precipitation scale heights with high surface precipitation rates in deep convective cloud regions.These features arise from differences in cloud characteristics,precipitation probability,and intensity,influenced by varying water vapor structures.In terms of physical mechanisms,altocumulus,stratocumulus,and deep convective cloud regions are characterized by total dryness,upper-level dryness with lower-level wetness,and total wetness,respectively.Upper-layer dryness leads to low cloud and precipitation structures,reducing the precipitation scale height,while lower-layer dryness increases it.Different humidity conditions in the upper and lower layers lead to variations in cloud type and volume distribution,ultimately affecting precipitation scale heights.This finding aids the mechanistic study of cloud precipitation physics in the tropics,providing valuable insights for developing numerical models and parameterizations.
基金supported by the Funds for Cre-ative Research Groups of China(No.51921001)the National Natural Science Foundation of China Major Research Program Integration Project(No.92266301)+2 种基金the Natural Science Foundation for Distinguished Young Scholars of China(No.51925401)the National Key Research and Development Programme of China(No.2023YFB3812601)the Youth Foundation of National Natural Science Foundation China(No.52001020).
文摘Overcoming the tradeoffbetween mechanical strength and electrical conductivity is a long-standing chal-lenge in developing advanced copper alloys for industrial applications.Herein,we report a new strategy to obtain high strength and good conductivity of Cu-Ni-Si-Ca alloy by introducing and regulating the discontinuous precipitation(DP)and continuous precipitation(CP)behaviors.The DP process combined with thermomechanical treatment was exploited to expedite the precipitation kinetics,whilst the com-petition between DP and CP was utilized to inhibit the nucleation and growth of continuous precipitation phase(CPP).The resultant copper alloy exhibits superior comprehensive properties with a yield strength of 956 MPa,fracture strength of 989 MPa,and electrical conductivity of 34.1%IACS.The improved elec-trical conductivity is attributed to the heterogeneous-nucleation dominant DP,while the high strength stems from the combination of strain hardening and precipitation strengthening of δ-Ni2 Si and t-Ni3 Si precipitates.Notably,the precipitation strengthening arises from both the dislocation passing and cutting mechanisms,with the strongly ordered DO22-type(t-Ni3 Si)phase contributing approximately 202 MPa to the overall strength through the cutting mechanism.This work offers a new pathway for alloy design of high-strength and high-electrical-conductivity copper alloys,by regulating coherent ordered nanoprecip-itates through DP and CP.
基金supported by National Natural Science Foundation of China[grant number 42305041].
文摘Deforestation has a significant influence on the hydrological cycle.Understanding the impact of deforestation on precipitation extremes is crucial for addressing global environmental challenges.This study investigates the impact of deforestation on precipitation extremes(R95p index,which represents the total amount of precipitation exceeding the 95th percentile of the reference period)in China,using outputs from three earth system models(CanESM5,IPSL-CM6A-LR,and MIROC-ES2L).All models,along with their multimodel mean,indicate a general decrease in R95p in Northeast China and southern China,and changes in Northwest China and the Tibetan Plateau are minimal.In contrast,the responses are model-dependent in the Huanghuai and Jianghuai regions.The overall nationwide multimodel mean suggests an annual R95p decrease of 10.7 mm,with individual model variations ranging from-28.0 to 2.0 mm.Further analysis using precipitation extremes scaling reveals a high spatial correlation with direct precipitation extremes changes on both annual and seasonal scales,albeit with slightly smaller magnitudes.Decomposing the response into dynamic and thermodynamic scaling,the authors find that dynamic contributions predominantly drive the changes in precipitation extremes on both annual and seasonal scales.The authors findings highlight the substantial role of dynamic processes in modulating the response of precipitation extremes to deforestation in China.
基金supports from the National Key R&D Program of China(Grant No.2023YFB4203301)National Natural Science Foundation of China(Grant No.52238008)Postdoctoral Fellowship Program of CPSF(Grant No.GZC20241516).
文摘Microbially induced calcite precipitation(MICP)and Enzyme induced calcite precipitation(EICP)techniques were implemented to reinforce the large-scale calcareous sand in this study.Then a coupled numerical model to predict the biochemical reactions and hydraulic characteristics of MICP and EICP reactions was proposed and verified by physical experiments.Results showed that:This model could describe the variations of bacteria,calcium,calcite,permeability over time reasonably.It is necessary to consider the influence of the calculation domain scale when simulating the convection-diffusionreaction in the multi-process of MICP and EICP reactions.The numerical and experimental values of calcite content are 0.841 g/cm^(3) and 0.861 g/cm^(3) for MICP-reinforced sand,0.263 g/cm^(3) and 0.227 g/cm^(3) for EICP-reinforced sand after 192 h of reaction.The reaction rate k_(rea) is an important parameter to control the calcite content.Accordingly,the permeability coefficient of MICP and EICP reinforced calcareous sand decreases by 32%and 18%.Due to the influence of substance transportation and calcite precipitation,the calcite shows a trend of decreasing firstly and then increasing with the enhancing of the initial permeability coefficient in biochemical reactions.The optimal injecting ratio q11:q12 in this study is 100:300 mL/min.The process for the application of MICP and EICP coupled numerical model is also recommended,which provides reference for engineering projects in ground improvement.
基金supported by the National Natural Science Foundation of China[grant number 42088101]the National Key Research and Development Program of China[grant number 2022YFF0801702]。
文摘The intensification of extreme precipitation(EP)under global warming presents a substantial risk to human safety and societal progress.Studying the specific impacts of global warming on rare EP events in China not only enhances the comprehension of these shifts,but also paves the way for the development of proactive strategies to alleviate associated damages.Results from large-ensemble simulation data demonstrate that global warming has led to an enhancement in once-in-a-decade EP events in parts of western and central China over the past few decades,with the strengthening of the South Asia high(SAH)caused by global warming playing a dominant role.The strengthening of the SAH corresponds to an intensification and westward extension of the western Pacific subtropical high in the lower troposphere.The region between these two systems experiences enhanced upward motion and increased southwesterly water vapor transport,leading to a rise in climatological precipitation in western and central China,thereby raising the threshold for once-in-a-decade EP events.
文摘Satellite Precipitation Products(SPPs) face challenges in detecting Extreme Precipitation Events(EPEs). Hence, the primary objective of this research is to introduce a novel framework termed Machine-Learning Clustering-Merging Algorithms(ML-CMAs) to evaluate EPEs using SPPs and Auxiliary Data(AD). Daily precipitation measurements were utilized for training and evaluating EPE estimates over Iran, which is comprised of arid and semi-arid regions. Statistical analysis and evaluation of five SPPs demonstrated that during EPE occurrences, all products face challenges in precipitation estimation, and using these products individually is not recommended. Among the SPPs, Multi-Source Weighted-Ensemble Precipitation(MSWEP) performed best for heavy(>20 mm d–1) and extreme(>40 mm d–1)precipitation events, followed by Global Satellite Mapping of Precipitation(GSMa P), Integrated Multi-Satellite Retrievals for Global Precipitation Measurement(IMERG), Climate Prediction Center morphing technique(CMORPH), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Dynamic Infrared-Rain Rate(PERSIANN-PDIR). The findings indicate that all proposed methods based on ML-CMAs could estimate precipitation rates more accurately than SPPs and improve statistical indices. The seasonal assessment and spatial analysis of statistical metrics of the overall daily precipitation results for all periods and climates revealed that all methods based on ML-CMAs performed well in all seasons and at nearly all measurement stations. Using unsupervised K-means++ classification for clustering EPEs and Deep Neural Network(DNN) and Convolutional Neural Network(CNN) methods for merging the MLCMAs reduced the error rate of SPPs in EPE estimation by approximately 50%. Therefore, incorporating ML-CMAs along with PWV as AD can significantly improve the performance of SPPs in evaluating EPEs over the study region.
