Satellite-based and reanalysis precipitation products provide valuable information for various applications.However,their performance varies widely across regions due to different data sources and production processes...Satellite-based and reanalysis precipitation products provide valuable information for various applications.However,their performance varies widely across regions due to different data sources and production processes.This paper evaluated the daily performance of four precipitation products(MSWEP,ERA5,PERSIANN,and TRMM)for seven regions of the Chinese mainland,using observations from 2462 ground stations across the country as a benchmark.We used four statistical and four classification indicators to describe their spatial and temporal accuracy,and capability to detect precipitation events while analyzing their applicability.The results show that according to the precipitation char-acteristics and accuracy of different types of precipitation products over the Chinese mainland,MSWEP was the most suitable product over the Chinese mainland,having the lowest root mean square error and mean absolute error,along with the highest coefficient of determination.It was followed by TRMM and ERA5,whereas PERSIANN lagged behind in terms of performance.In terms of different regions,MSWEP still performed well,especially in North China and East China.The accuracy of the four precipitation products was relatively low in the summer months,and they all overestimated in the northwest region.In other months,MSWEP and TRMM were better than PERSIANN and ERA5.The four precipitation products had good detection performance over the Chinese mainland,with probability of detection above 0.5.However,with the increase of precipitation threshold,the detection capability of the four products decreased,and MSWEP and ERA5 had good detection capability for moderate rain.TRMM’s detection capability for heavy rain and rainstorms was better than that of the other three products,and PERSIANN’s detection capability for moderate rain,heavy rain and rainstorms was relatively poor,with a large deviation.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
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
Due to its complex and diverse terrain,precipitation gauges in the Tibetan Plateau(TP)are sparse,making it difficult to obtain reliable precipitation data for environmental studies.Data merging is a method that can in...Due to its complex and diverse terrain,precipitation gauges in the Tibetan Plateau(TP)are sparse,making it difficult to obtain reliable precipitation data for environmental studies.Data merging is a method that can integrate precipitation data from multiple sources to generate high-precision precipitation data.However,the more commonly used methods,such as regression and machine learning,do not usually consider the local correlation of precipitation,so that the spatial pattern of precipitation cannot be reproduced,while deep learning methods do incorporate spatial correlation.To explore the ability of using deep learning methods in merging precipitation data for the TP,this study compared three methods:a deep learning method—a convolutional neural network(CNN)algorithm,a machine learning method—an artificial neural network(ANN)algorithm,and a statistical method based on Extended Triple Collocation(ETC)in merging precipitation from multiple sources(gauged,grid,satellite and dynamic downscaling)over the TP,as well as their performance for hydrological simulations.Dynamic downscaling data driven by global reanalysis data centered on the TP were introduced in the merging process to better reflect the spatial variability of precipitation.The results show that:(1)in terms of the meteorological metrics,the merged data perform better than the gauge interpolation data.By using data merging,the error between the raw multi-source and gauged precipitation can be reduced,and the precipitation detection capability can be greatly improved;(2)The merged precipitation data also perform well in the hydrological evaluation.The Xin’anjiang(XAJ)model parameter calibration experiments at the source of the Yangtze River(SYR)and the source of the Yellow River(SHR)were repeated 300 times to remove uncertainty in the model parameter results.The median Kling-Gupta Efficiency Coefficients(KGE)of simulated runoff from the merged data of the ANN,CNN and ETC methods for the SYR and the SHR are 0.859,0.864,0.838 and 0.835,0.835,0.789,respectively.Except for the ETC merging data at the SHR,the performance of other merged data was improved compared to the simulation results of the gauged precipitation(KGE=0.807 at the SYR,KGE=0.828 at the SHR);and(3)In contrast to the machine learning ANN method and the statistical ETC method,the deep learning method,CNN,consistently showed better performance.展开更多
Traditional hourly rain gauges and automatic weather stations rarely measure solid precipitation, except for those stations with weighing-type precipitation sensors. Microwave remote sensing has only a low ability to ...Traditional hourly rain gauges and automatic weather stations rarely measure solid precipitation, except for those stations with weighing-type precipitation sensors. Microwave remote sensing has only a low ability to retrieve solid precipitation. In addition, there are no long-term, high-quality precipitation data in China that can be used to drive land surface models. To address these issues, in the China Meteorological Administration(CMA) Land Data Assimilation System(CLDAS), we blended the Climate Prediction Center(CPC) morphing technique(CMORPH) and Modern-Era Retrospective analysis for Research and Applications version 2(MERRA2) precipitation datasets with observed temperature and precipitation data on various temporal scales using multigrid variational analysis and temporal downscaling to produce a multi-source precipitation fusion dataset for China(CLDAS-Prcp). This dataset covers all of China at a resolution of 6.25 km at hourly intervals from 1998 to 2018. We performed dependent and independent evaluations of the CLDAS-Prcp dataset from the perspectives of seasonal total precipitation and land surface model simulation. Our results show that the CLDAS-Prcp dataset represents reasonably the spatial distribution of precipitation in China. The dependent evaluation indicates that the CLDAS-Prcp performs better than the MERRA2 precipitation, CMORPH precipitation, Global Land Data Assimilation System version 2(GLDAS-V2.1) precipitation,and CLDAS-V2.0 winter precipitation, as compared to the meteorological observational precipitation. The independent evaluation indicates that the CLDAS-Prcp dataset performs better than the Global Precipitation Measurement(GPM) precipitation dataset and is similar to the CLDAS-V2.0 summer precipitation dataset based on the hydrological observational precipitation. The simulated soil moisture content driven by CLDAS-Prcp is slightly better than that driven by the CLDAS-V2.0 precipitation, whereas the snow depth simulation driven by CLDAS-Prcp is much better than that driven by the CLDAS-V2.0 precipitation. This is because the CLDAS-Prcp data have included solid precipitation. Overall, the CLDAS-Prcp dataset can meet the needs of land surface and hydrological modeling studies.展开更多
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 int...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.展开更多
Precipitation is often used for the preparation of La(OH)_(3)with precipitants of liquid alkali and ammonia.To solve the problems of high cost and wastewater pollution caused by common precipitants,the active MgO synt...Precipitation is often used for the preparation of La(OH)_(3)with precipitants of liquid alkali and ammonia.To solve the problems of high cost and wastewater pollution caused by common precipitants,the active MgO synthesized by pyrolysis was used as the precipitant to prepare La(OH)_(3).The species distribution of LaCl_(3)and LaCl_(3)-MgCl_(2)mixed system solution was calculated,and the kinetic analysis of the precipi-tation process was carried out to confirm the key factors influencing the precipitation of La(OH)_(3).The results show that La(OH)_(3)with D_(50)of 5.57μm,a specific surface area of 25.70 m^(2)/g,a rod-like shape,and MgO content of 0.044 wt%,was successfully prepared by adding active MgO.The precipitation ratio of La reaches 99.92%.The La(OH)_(3)precipitation is controlled by the diffusion process.The activity of MgO has a significant influence on MgO content in the precipitate.The preparation of La(OH)_(3)by active MgO provides a potential way for an eco-friendly preparation method of rare earth.展开更多
This past year, 2024, is on track to be the warmest year, joining 2023 as the two hottest years on record. With the exceptional heat, weather and climate extremes were common across the world. In particular, 2024 has ...This past year, 2024, is on track to be the warmest year, joining 2023 as the two hottest years on record. With the exceptional heat, weather and climate extremes were common across the world. In particular, 2024 has seen a remarkable run of extreme precipitation events and resulting impacts. Here, we provide an overview of the most notable extreme events of the year, including extreme precipitation and floods, tropical cyclones, and droughts. The characteristics and impacts of these extreme events are summarized, followed by discussion on the physical drivers and the role of global warming.Finally, we also discuss the future prospects in extreme event studies, including impact-based perspectives, challenges in attribution of precipitation extremes, and the existing gap to minimize impacts from climate extremes.展开更多
Northern China is a prominent “hotspot” for land–atmosphere interactions, with substantial gradients in both moisture and thermal conditions. Previous studies have identified a link between land–atmosphere couplin...Northern China is a prominent “hotspot” for land–atmosphere interactions, with substantial gradients in both moisture and thermal conditions. Previous studies have identified a link between land–atmosphere coupling and the individual roles of each factor, but the synergistic effect of the two factors remains unclear. This study considers the covariation of evapotranspiration and precipitation to assess evapotranspiration–precipitation(ET–P) coupling across northern China,exploring its spatial variations and their linkage to water and heat factors. Our findings reveal a transition from strongly positive coupling in the northwest to weakly negative coupling in the southeast, peaking in spring. These spatial variations are attributable to water(soil moisture) and heat(air temperature), which explain 39% and 25% of the variability,respectively. The aridity index(AI), a water–heat synergy factor, is the dominant factor, explaining 66% of the spatial variation in ET–P coupling. As the AI increases, ET–P coupling shifts from strongly positive to weakly negative, with an AI around 0.7. This shift is determined by a shift in the evapotranspiration–lifting condensation level(LCL) coupling under an AI change. Regions with an AI below 0.7 experience water-limited evapotranspiration, where increased soil moisture enhances evapotranspiration, reduces sensible heat(H), and lowers the LCL, resulting in a negative ET–LCL coupling.Conversely, regions with an AI above 0.7 experience energy-limited evapotranspiration, where the positive ET–LCL coupling reflects a positive H–LCL coupling or a positive impact of the LCL on evapotranspiration. This analysis advances our understanding of the intricate influences of multifactor surface interactions on the spatial variations of land–atmosphere coupling.展开更多
Although magnesium-aluminum alloys,such as AZ80 and AZ91 have promising application potential in automotive,high-speed train and aerospace fields,their age-hardening response is generally not very appreciable.In this ...Although magnesium-aluminum alloys,such as AZ80 and AZ91 have promising application potential in automotive,high-speed train and aerospace fields,their age-hardening response is generally not very appreciable.In this work,the aging-hardening response of AZ80 alloy was effectively enhanced by applying cold-rolling deformation before conducting conventional aging treatment at 200°C.Compared to the directly aged sample,the yield strength of the pre-rolling and aged sample was increased by 35 MPa.Electron microscope examination confirmed that profuse{10¯11}and{10¯11}-{10¯12}twins,consisting of high density of dislocations and stacking faults,were generated by cold rolling.Blocky or ellipsoidal Mg_(17)Al_(12)precipitates formed at the twin boundaries(TBs)during subsequent aging treatment.Crystallographic analysis indicated that the precipitates at{10¯11}TBs always held an identical Potter OR with both the matrix and twin,while the precipitates at{10¯11}-{10¯12}TBs exhibited three different ORs:Burgers OR,Potter OR and P-S OR with either the matrix or the twin.Moreover,recrystallized grains were found inside{10¯11}-{10¯12}double twins after peak-aging at 200°C,implying that precipitation and recrystallization might occur concurrently along TBs at a relatively low temperature.It was speculated that the highly stored energy inside twins and the high elastic energy between the precipitates and twins were driving factors for the occurrence of recrystallization.展开更多
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 cons...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.展开更多
This study investigates the development of novel high-entropy alloys(HEAs)with enhanced mechanical properties through an innovative fabrication method of direct energy deposition(DED).The focus is on the creation of m...This study investigates the development of novel high-entropy alloys(HEAs)with enhanced mechanical properties through an innovative fabrication method of direct energy deposition(DED).The focus is on the creation of metastable core-shell precipitation-strengthened HEAs that exhibit a unique multi-stage terrace-like slip wave toughening mechanism,a novel approach to improving both strength and ductility simultaneously.Mechanical testing reveals that the developed HEAs exhibit superior mechanical proper-ties,including high yield strength,ultimate tensile strength,and exceptional ductility.The improvement in these properties is attributed to the multi-stage terrace-like slip wave toughening mechanism activated by the unique microstructural features.This toughening mechanism involves the sequential activation of slip systems,facilitated by the stress concentration around the core-shell precipitates and the subsequent propagation of slip waves across the material.The terrace-like pattern of these slip waves enhances the material's ability to deform plastically,providing a significant toughening effect while maintaining high strength levels.Furthermore,the study delves into the fundamental interactions between the microstruc-tural elements and the deformation mechanisms.It elucidates how the core-shell precipitates and the matrix cooperate to distribute stress uniformly,delay the onset of necking,and prevent premature failure.This synergistic interaction between the microstructural features and the slip wave toughening mecha-nism is central to the remarkable balance of strength and ductility achieved in the HEAs.The introduction of a multi-stage terrace-like slip wave toughening mechanism offers a new pathway to designing HEAs with an exceptional amalgamation of strength and ductility.展开更多
Precipitation types primarily include rainfall,snowfall,and sleet,and the transformation of precipitation types has significant impacts on regional climate,ecosystems,and the land-atmosphere system.This study employs ...Precipitation types primarily include rainfall,snowfall,and sleet,and the transformation of precipitation types has significant impacts on regional climate,ecosystems,and the land-atmosphere system.This study employs the Ding method to separate precipitation types from three datasets(CMFD,ERA5_Land,and CN05.1).Using data from 26meteorological observation stations in the Chinese Tianshan Mountains Region(CTMR)of China as the validation dataset,the precipitation type separation accuracy of three datasets was evaluated.Additionally,the impacts of relative humidity,precipitation amount,and air temperature on the accuracy of precipitation type separation were analyzed.The results indicate that the CMFD dataset provides the highest separation accuracy,followed by CN05.1,with ERA5_Land showing the poorest performance.Spatial correlation analysis reveals that CMFD outperforms the other two datasets at both annual and monthly scales.Root Mean Square Error(RMSE)and Mean Deviation(MD)values suggest that CMFD is more consistent with the station observational data.The analysis further demonstrates that relative humidity and precipitation amount significantly affect separation accuracy.After bias correction,the correlation coefficients between CMFD,ERA5_Land,and station observational data improved to 0.85-0.94,while the RMSE was controlled within 2 mm.The study also revealed that the overestimation of precipitation was positively correlated with the overestimation of rainfall days,negatively correlated with the overestimation of snowfall days,and that underestimated air temperatures led to an increase in the misclassification of snowfall days.This research provides a basis for selecting climate change datasets and managing water resources in alpine regions.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
The sparsity of ground gauges poses a significant challenge for evaluating and merging satellite-based and reanalysis-based precipitation datasets in lake regions.While the standard triple collocation(TC)method offers...The sparsity of ground gauges poses a significant challenge for evaluating and merging satellite-based and reanalysis-based precipitation datasets in lake regions.While the standard triple collocation(TC)method offers a solution without access to ground-based observations,it fails to address rain/no-rain classification and its suitability for assessing and merging lake precipitation has not been explored.This study combines categorical triple collocation(CTC)with standard TC to create an integrated framework(CTC-TC)tailored to evaluate and merge global gridded precipitation products(GPPs).We assess the efficacy of CTC-TC using six GPPs(ERA5-Land,SM2 RAIN-ASCAT,IMERG-Early,IMERG-Late,GSMaPMVK,and PERSIANN-CCS)across the five largest freshwater lakes in China.CTC-TC effectively captures the spatial patterns of metrics for all GPPs,and precisely estimates the correlation coefficient and root mean square error for satellite-based datasets apart from SM2 RAIN-ASCAT,but overestimates the classification accuracy indicator V for all GPPs.Regarding multi-source fusion,CTC-TC leverages the strengths of individual products of triplets,resulting in significant improvements in the critical success index(CSI)by over 11.9%and the modified Kling-Gupta efficiency(KGE')by more than 13.3%.Compared to baseline models,including standard TC,simple model averaging,one outlier removal,and Bayesian model averaging,CTC-TC achieves gains in CSI and KGE'of no less than 24.7%and 3.6%,respectively.In conclusion,the CTC-TC framework offers a thorough evaluation and efficient fusion of GPPs,addressing both categorical and continuous accuracy in data-scarce regions such as lakes.展开更多
The effect of hot deformation onα-phase precipitation during the subsequent heat treatment,as well as the mechanical properties of TB18 Ti-alloy,was investigated.Results show that the round bar obtained by the dual-p...The effect of hot deformation onα-phase precipitation during the subsequent heat treatment,as well as the mechanical properties of TB18 Ti-alloy,was investigated.Results show that the round bar obtained by the dual-phase field forging of the cast ingot exhibits uniform composition distribution on its cross-section.However,various degrees of deformation are detected at different positions on the cross-section,which is attributed to the characteristics of the forging process.Under the forging condition,the microstructure is mainly composed ofβ-phase matrix and coarsened discontinuous primaryα-phases.After solution and following artificial aging treatment,the primaryα-phases disappear,while needle-like secondaryα-phases precipitate in the matrix.Additionally,dispersed white zones are observed in the samples after aging,which are analyzed to be the precipitation-free zones of secondaryα-phase.Despite a uniform compositional distribution among various regions,these dispersed white zones exhibit higher content and larger size in the positions that have undergone lower forging deformation.It indicates that the insufficient forging deformation inhibits the precipitation of the secondaryα-phase,ultimately resulting in the lower strengthening effect by heat treatment.Thus,consistent with the characteristics of the forging process,a periodic variation of sample in strength is detected along the circumferential direction of the forged round bar.展开更多
This study investigates trends in extreme precipitation events(EPEs)across Antarctica from 1979 to 2023,analyzing changes in EPE frequency,intensity,and the proportion of extreme to total precipitation.Using Self-Orga...This study investigates trends in extreme precipitation events(EPEs)across Antarctica from 1979 to 2023,analyzing changes in EPE frequency,intensity,and the proportion of extreme to total precipitation.Using Self-Organizing Map(SOM)techniques,the study distinguishes the contributions from thermodynamic,dynamic,and interaction components in explaining these trends.Positive EPE occurrence trends are observed across the Bellingshausen and Weddell Seas,Dronning Maud Land,and parts of the Southern Ocean,with declines limited to Queen Mary Land.Thermodynamic factors,responsible for 96.0%of the overall trend,are driven by increased water vapor content in polar air masses.Dynamic contributions,representing 10.8%,are linked to a strengthened Amundsen Sea Low(ASL)associated with the Southern Annular Mode(SAM)and Pacific South American(PSA)trends.Interaction effects make a slightly negative contribution(-6.8%)to the overall trend.Variations in water vapor transport and vertical velocity tied to annual 500-hPa geopotential height anomalies further explain EPE trends.These findings provide insight into the atmospheric processes that influence Antarctic EPEs,with implications for understanding the climatic impact on the polar environment.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
基金173 National Basic Research Program of China(2020-JCJQ-ZD-087-01)。
文摘Satellite-based and reanalysis precipitation products provide valuable information for various applications.However,their performance varies widely across regions due to different data sources and production processes.This paper evaluated the daily performance of four precipitation products(MSWEP,ERA5,PERSIANN,and TRMM)for seven regions of the Chinese mainland,using observations from 2462 ground stations across the country as a benchmark.We used four statistical and four classification indicators to describe their spatial and temporal accuracy,and capability to detect precipitation events while analyzing their applicability.The results show that according to the precipitation char-acteristics and accuracy of different types of precipitation products over the Chinese mainland,MSWEP was the most suitable product over the Chinese mainland,having the lowest root mean square error and mean absolute error,along with the highest coefficient of determination.It was followed by TRMM and ERA5,whereas PERSIANN lagged behind in terms of performance.In terms of different regions,MSWEP still performed well,especially in North China and East China.The accuracy of the four precipitation products was relatively low in the summer months,and they all overestimated in the northwest region.In other months,MSWEP and TRMM were better than PERSIANN and ERA5.The four precipitation products had good detection performance over the Chinese mainland,with probability of detection above 0.5.However,with the increase of precipitation threshold,the detection capability of the four products decreased,and MSWEP and ERA5 had good detection capability for moderate rain.TRMM’s detection capability for heavy rain and rainstorms was better than that of the other three products,and PERSIANN’s detection capability for moderate rain,heavy rain and rainstorms was relatively poor,with a large deviation.
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 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 No.52079093)the National Natural Science Foundation of Hubei Province of China(Grant No.2020CFA100)。
文摘Due to its complex and diverse terrain,precipitation gauges in the Tibetan Plateau(TP)are sparse,making it difficult to obtain reliable precipitation data for environmental studies.Data merging is a method that can integrate precipitation data from multiple sources to generate high-precision precipitation data.However,the more commonly used methods,such as regression and machine learning,do not usually consider the local correlation of precipitation,so that the spatial pattern of precipitation cannot be reproduced,while deep learning methods do incorporate spatial correlation.To explore the ability of using deep learning methods in merging precipitation data for the TP,this study compared three methods:a deep learning method—a convolutional neural network(CNN)algorithm,a machine learning method—an artificial neural network(ANN)algorithm,and a statistical method based on Extended Triple Collocation(ETC)in merging precipitation from multiple sources(gauged,grid,satellite and dynamic downscaling)over the TP,as well as their performance for hydrological simulations.Dynamic downscaling data driven by global reanalysis data centered on the TP were introduced in the merging process to better reflect the spatial variability of precipitation.The results show that:(1)in terms of the meteorological metrics,the merged data perform better than the gauge interpolation data.By using data merging,the error between the raw multi-source and gauged precipitation can be reduced,and the precipitation detection capability can be greatly improved;(2)The merged precipitation data also perform well in the hydrological evaluation.The Xin’anjiang(XAJ)model parameter calibration experiments at the source of the Yangtze River(SYR)and the source of the Yellow River(SHR)were repeated 300 times to remove uncertainty in the model parameter results.The median Kling-Gupta Efficiency Coefficients(KGE)of simulated runoff from the merged data of the ANN,CNN and ETC methods for the SYR and the SHR are 0.859,0.864,0.838 and 0.835,0.835,0.789,respectively.Except for the ETC merging data at the SHR,the performance of other merged data was improved compared to the simulation results of the gauged precipitation(KGE=0.807 at the SYR,KGE=0.828 at the SHR);and(3)In contrast to the machine learning ANN method and the statistical ETC method,the deep learning method,CNN,consistently showed better performance.
基金Supported by the National Key Research and Development Program of China(2018YFC1506601)National Natural Science Foundation of China(91437220)+1 种基金China Meteorological Administration Special Public Welfare Research Fund(GYHY201506002 and GYHY201206008)China Meteorological Administration“Meteorological Data Quality Control and Multi-source Data Fusion and Reanalysis”project。
文摘Traditional hourly rain gauges and automatic weather stations rarely measure solid precipitation, except for those stations with weighing-type precipitation sensors. Microwave remote sensing has only a low ability to retrieve solid precipitation. In addition, there are no long-term, high-quality precipitation data in China that can be used to drive land surface models. To address these issues, in the China Meteorological Administration(CMA) Land Data Assimilation System(CLDAS), we blended the Climate Prediction Center(CPC) morphing technique(CMORPH) and Modern-Era Retrospective analysis for Research and Applications version 2(MERRA2) precipitation datasets with observed temperature and precipitation data on various temporal scales using multigrid variational analysis and temporal downscaling to produce a multi-source precipitation fusion dataset for China(CLDAS-Prcp). This dataset covers all of China at a resolution of 6.25 km at hourly intervals from 1998 to 2018. We performed dependent and independent evaluations of the CLDAS-Prcp dataset from the perspectives of seasonal total precipitation and land surface model simulation. Our results show that the CLDAS-Prcp dataset represents reasonably the spatial distribution of precipitation in China. The dependent evaluation indicates that the CLDAS-Prcp performs better than the MERRA2 precipitation, CMORPH precipitation, Global Land Data Assimilation System version 2(GLDAS-V2.1) precipitation,and CLDAS-V2.0 winter precipitation, as compared to the meteorological observational precipitation. The independent evaluation indicates that the CLDAS-Prcp dataset performs better than the Global Precipitation Measurement(GPM) precipitation dataset and is similar to the CLDAS-V2.0 summer precipitation dataset based on the hydrological observational precipitation. The simulated soil moisture content driven by CLDAS-Prcp is slightly better than that driven by the CLDAS-V2.0 precipitation, whereas the snow depth simulation driven by CLDAS-Prcp is much better than that driven by the CLDAS-V2.0 precipitation. This is because the CLDAS-Prcp data have included solid precipitation. Overall, the CLDAS-Prcp dataset can meet the needs of land surface and hydrological modeling studies.
基金supported by the National Key Research and Development Program of China(Grant No.2020YFA0608000)the National Natural Science Foundation of China(Grant No.42030605)+1 种基金CAAI-MindSpore Academic Fund Research Projects(CAAIXSJLJJ2023MindSpore11)the program of China Scholarships Council(No.CXXM2101180001)。
文摘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.
基金the National Key Research and Development Program of China(2022YFB3504503)the National Natural Science Foundation of China(52274355)the Gansu Province Science and Technology Major Special Project,China(22ZD6GD061).
文摘Precipitation is often used for the preparation of La(OH)_(3)with precipitants of liquid alkali and ammonia.To solve the problems of high cost and wastewater pollution caused by common precipitants,the active MgO synthesized by pyrolysis was used as the precipitant to prepare La(OH)_(3).The species distribution of LaCl_(3)and LaCl_(3)-MgCl_(2)mixed system solution was calculated,and the kinetic analysis of the precipi-tation process was carried out to confirm the key factors influencing the precipitation of La(OH)_(3).The results show that La(OH)_(3)with D_(50)of 5.57μm,a specific surface area of 25.70 m^(2)/g,a rod-like shape,and MgO content of 0.044 wt%,was successfully prepared by adding active MgO.The precipitation ratio of La reaches 99.92%.The La(OH)_(3)precipitation is controlled by the diffusion process.The activity of MgO has a significant influence on MgO content in the precipitate.The preparation of La(OH)_(3)by active MgO provides a potential way for an eco-friendly preparation method of rare earth.
基金jointly supported by the National Natural Science Foundation of China (Grant Nos.42422502 and 42275038)the China Meteorological Administration Climate Change Special Program (Grant No.QBZ202306)funded by the Met Office Climate Science for Service Partnership (CSSP) China project under the International Science Partnerships Fund (ISPF)。
文摘This past year, 2024, is on track to be the warmest year, joining 2023 as the two hottest years on record. With the exceptional heat, weather and climate extremes were common across the world. In particular, 2024 has seen a remarkable run of extreme precipitation events and resulting impacts. Here, we provide an overview of the most notable extreme events of the year, including extreme precipitation and floods, tropical cyclones, and droughts. The characteristics and impacts of these extreme events are summarized, followed by discussion on the physical drivers and the role of global warming.Finally, we also discuss the future prospects in extreme event studies, including impact-based perspectives, challenges in attribution of precipitation extremes, and the existing gap to minimize impacts from climate extremes.
基金jointly supported by the National Science Foundation of China (Grant No.42230611)the Meteorological Joint Fund (Grant No.U2142208)+2 种基金the Second Tibetan Plateau Scientific Expedition and Research (STEP) program (grant no.2019QZKK0102)the National Science Foundation of China (Grant No.42005071)the Gansu Province Key Talent Project (Grant No.2023RCXM37)。
文摘Northern China is a prominent “hotspot” for land–atmosphere interactions, with substantial gradients in both moisture and thermal conditions. Previous studies have identified a link between land–atmosphere coupling and the individual roles of each factor, but the synergistic effect of the two factors remains unclear. This study considers the covariation of evapotranspiration and precipitation to assess evapotranspiration–precipitation(ET–P) coupling across northern China,exploring its spatial variations and their linkage to water and heat factors. Our findings reveal a transition from strongly positive coupling in the northwest to weakly negative coupling in the southeast, peaking in spring. These spatial variations are attributable to water(soil moisture) and heat(air temperature), which explain 39% and 25% of the variability,respectively. The aridity index(AI), a water–heat synergy factor, is the dominant factor, explaining 66% of the spatial variation in ET–P coupling. As the AI increases, ET–P coupling shifts from strongly positive to weakly negative, with an AI around 0.7. This shift is determined by a shift in the evapotranspiration–lifting condensation level(LCL) coupling under an AI change. Regions with an AI below 0.7 experience water-limited evapotranspiration, where increased soil moisture enhances evapotranspiration, reduces sensible heat(H), and lowers the LCL, resulting in a negative ET–LCL coupling.Conversely, regions with an AI above 0.7 experience energy-limited evapotranspiration, where the positive ET–LCL coupling reflects a positive H–LCL coupling or a positive impact of the LCL on evapotranspiration. This analysis advances our understanding of the intricate influences of multifactor surface interactions on the spatial variations of land–atmosphere coupling.
基金financially supported by the National Natural Science Foundation of China(No.52071040 and 51871036)Natural Science Foundation of Shandong Province,China(No.ZR2022QE008)China Postdoctoral Science Foundation(No.2022M712984)。
文摘Although magnesium-aluminum alloys,such as AZ80 and AZ91 have promising application potential in automotive,high-speed train and aerospace fields,their age-hardening response is generally not very appreciable.In this work,the aging-hardening response of AZ80 alloy was effectively enhanced by applying cold-rolling deformation before conducting conventional aging treatment at 200°C.Compared to the directly aged sample,the yield strength of the pre-rolling and aged sample was increased by 35 MPa.Electron microscope examination confirmed that profuse{10¯11}and{10¯11}-{10¯12}twins,consisting of high density of dislocations and stacking faults,were generated by cold rolling.Blocky or ellipsoidal Mg_(17)Al_(12)precipitates formed at the twin boundaries(TBs)during subsequent aging treatment.Crystallographic analysis indicated that the precipitates at{10¯11}TBs always held an identical Potter OR with both the matrix and twin,while the precipitates at{10¯11}-{10¯12}TBs exhibited three different ORs:Burgers OR,Potter OR and P-S OR with either the matrix or the twin.Moreover,recrystallized grains were found inside{10¯11}-{10¯12}double twins after peak-aging at 200°C,implying that precipitation and recrystallization might occur concurrently along TBs at a relatively low temperature.It was speculated that the highly stored energy inside twins and the high elastic energy between the precipitates and twins were driving factors for the occurrence of recrystallization.
基金supported by the National Natural Science Foundation of China(Nos.52122408 and 52071023)financial support from the Fundamental Research Funds for the Central Universities(University of Science and Technology Beijing,No.FRF-TP-2021-04C1,and 06500135)。
文摘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.
文摘This study investigates the development of novel high-entropy alloys(HEAs)with enhanced mechanical properties through an innovative fabrication method of direct energy deposition(DED).The focus is on the creation of metastable core-shell precipitation-strengthened HEAs that exhibit a unique multi-stage terrace-like slip wave toughening mechanism,a novel approach to improving both strength and ductility simultaneously.Mechanical testing reveals that the developed HEAs exhibit superior mechanical proper-ties,including high yield strength,ultimate tensile strength,and exceptional ductility.The improvement in these properties is attributed to the multi-stage terrace-like slip wave toughening mechanism activated by the unique microstructural features.This toughening mechanism involves the sequential activation of slip systems,facilitated by the stress concentration around the core-shell precipitates and the subsequent propagation of slip waves across the material.The terrace-like pattern of these slip waves enhances the material's ability to deform plastically,providing a significant toughening effect while maintaining high strength levels.Furthermore,the study delves into the fundamental interactions between the microstruc-tural elements and the deformation mechanisms.It elucidates how the core-shell precipitates and the matrix cooperate to distribute stress uniformly,delay the onset of necking,and prevent premature failure.This synergistic interaction between the microstructural features and the slip wave toughening mecha-nism is central to the remarkable balance of strength and ductility achieved in the HEAs.The introduction of a multi-stage terrace-like slip wave toughening mechanism offers a new pathway to designing HEAs with an exceptional amalgamation of strength and ductility.
基金financial support from the National Natural Sciences Foundation of China(42261026,and 42161025)the Open Foundation of Xinjiang Key Laboratory of Water Cycle and Utilization in Arid Zone(XJYS0907-2023-01)。
文摘Precipitation types primarily include rainfall,snowfall,and sleet,and the transformation of precipitation types has significant impacts on regional climate,ecosystems,and the land-atmosphere system.This study employs the Ding method to separate precipitation types from three datasets(CMFD,ERA5_Land,and CN05.1).Using data from 26meteorological observation stations in the Chinese Tianshan Mountains Region(CTMR)of China as the validation dataset,the precipitation type separation accuracy of three datasets was evaluated.Additionally,the impacts of relative humidity,precipitation amount,and air temperature on the accuracy of precipitation type separation were analyzed.The results indicate that the CMFD dataset provides the highest separation accuracy,followed by CN05.1,with ERA5_Land showing the poorest performance.Spatial correlation analysis reveals that CMFD outperforms the other two datasets at both annual and monthly scales.Root Mean Square Error(RMSE)and Mean Deviation(MD)values suggest that CMFD is more consistent with the station observational data.The analysis further demonstrates that relative humidity and precipitation amount significantly affect separation accuracy.After bias correction,the correlation coefficients between CMFD,ERA5_Land,and station observational data improved to 0.85-0.94,while the RMSE was controlled within 2 mm.The study also revealed that the overestimation of precipitation was positively correlated with the overestimation of rainfall days,negatively correlated with the overestimation of snowfall days,and that underestimated air temperatures led to an increase in the misclassification of snowfall days.This research provides a basis for selecting climate change datasets and managing water resources in alpine regions.
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National Key R&D Program of China,No.2022YFC3202802National Natural Science Foundation of China,No.52009081,No.52121006,No.52279071Special Funded Project for Basic Scientific Research Operation Expenses of the Central Public Welfare Scientific Research Institutes of China,No.Y524017。
文摘The sparsity of ground gauges poses a significant challenge for evaluating and merging satellite-based and reanalysis-based precipitation datasets in lake regions.While the standard triple collocation(TC)method offers a solution without access to ground-based observations,it fails to address rain/no-rain classification and its suitability for assessing and merging lake precipitation has not been explored.This study combines categorical triple collocation(CTC)with standard TC to create an integrated framework(CTC-TC)tailored to evaluate and merge global gridded precipitation products(GPPs).We assess the efficacy of CTC-TC using six GPPs(ERA5-Land,SM2 RAIN-ASCAT,IMERG-Early,IMERG-Late,GSMaPMVK,and PERSIANN-CCS)across the five largest freshwater lakes in China.CTC-TC effectively captures the spatial patterns of metrics for all GPPs,and precisely estimates the correlation coefficient and root mean square error for satellite-based datasets apart from SM2 RAIN-ASCAT,but overestimates the classification accuracy indicator V for all GPPs.Regarding multi-source fusion,CTC-TC leverages the strengths of individual products of triplets,resulting in significant improvements in the critical success index(CSI)by over 11.9%and the modified Kling-Gupta efficiency(KGE')by more than 13.3%.Compared to baseline models,including standard TC,simple model averaging,one outlier removal,and Bayesian model averaging,CTC-TC achieves gains in CSI and KGE'of no less than 24.7%and 3.6%,respectively.In conclusion,the CTC-TC framework offers a thorough evaluation and efficient fusion of GPPs,addressing both categorical and continuous accuracy in data-scarce regions such as lakes.
基金Qin Chuangyuan Cites High-Level Innovation,Entrepreneurship Talent Project(QCYRCXM-2023-003)Innovation Capability Support Program of Shaanxi(2022KJXX-84)。
文摘The effect of hot deformation onα-phase precipitation during the subsequent heat treatment,as well as the mechanical properties of TB18 Ti-alloy,was investigated.Results show that the round bar obtained by the dual-phase field forging of the cast ingot exhibits uniform composition distribution on its cross-section.However,various degrees of deformation are detected at different positions on the cross-section,which is attributed to the characteristics of the forging process.Under the forging condition,the microstructure is mainly composed ofβ-phase matrix and coarsened discontinuous primaryα-phases.After solution and following artificial aging treatment,the primaryα-phases disappear,while needle-like secondaryα-phases precipitate in the matrix.Additionally,dispersed white zones are observed in the samples after aging,which are analyzed to be the precipitation-free zones of secondaryα-phase.Despite a uniform compositional distribution among various regions,these dispersed white zones exhibit higher content and larger size in the positions that have undergone lower forging deformation.It indicates that the insufficient forging deformation inhibits the precipitation of the secondaryα-phase,ultimately resulting in the lower strengthening effect by heat treatment.Thus,consistent with the characteristics of the forging process,a periodic variation of sample in strength is detected along the circumferential direction of the forged round bar.
基金supported by the National Key R&D Program of China(2022YFE0106300)Norges Forskningsråd(328886).
文摘This study investigates trends in extreme precipitation events(EPEs)across Antarctica from 1979 to 2023,analyzing changes in EPE frequency,intensity,and the proportion of extreme to total precipitation.Using Self-Organizing Map(SOM)techniques,the study distinguishes the contributions from thermodynamic,dynamic,and interaction components in explaining these trends.Positive EPE occurrence trends are observed across the Bellingshausen and Weddell Seas,Dronning Maud Land,and parts of the Southern Ocean,with declines limited to Queen Mary Land.Thermodynamic factors,responsible for 96.0%of the overall trend,are driven by increased water vapor content in polar air masses.Dynamic contributions,representing 10.8%,are linked to a strengthened Amundsen Sea Low(ASL)associated with the Southern Annular Mode(SAM)and Pacific South American(PSA)trends.Interaction effects make a slightly negative contribution(-6.8%)to the overall trend.Variations in water vapor transport and vertical velocity tied to annual 500-hPa geopotential height anomalies further explain EPE trends.These findings provide insight into the atmospheric processes that influence Antarctic EPEs,with implications for understanding the climatic impact on the polar environment.
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.
