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
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
Enzyme-Induced Carbonate Precipitation(EICP)is an innovative technique to improve soil strength and reduce permeability.However,the use of EICP for reinforcing underwater sand beds remains largely unexplored.To advanc...Enzyme-Induced Carbonate Precipitation(EICP)is an innovative technique to improve soil strength and reduce permeability.However,the use of EICP for reinforcing underwater sand beds remains largely unexplored.To advance EICP implementation in various geotechnical applications,this paper develops a model box system to investigate the effectiveness of the EICP technique in reinforcing underwater sand beds.An"injection-extraction"system is designed to facilitate the flow of the EICP solution through underwater sand layers.Key parameters,including conductivity,pH,and Ca^(2+)concentration of the solution,are measured and analyzed.Electrical resistivity tomography(ERT)is utilized to evaluate the reinforcement effect in the underwater sand bed.The permeability of the model is tested to verify the feasibility of EICP technology for strengthening underwater sands.Furthermore,scanning electron microscope(SEM)is performed to investigate the growth mechanisms of calcium carbonate(CaCO_(3))crystals.The results show that the permeability of the model decreases from 1.28×10^(-2)m/s to 9.66×10^(-5)m/s,representing a reduction of approximately three orders of magnitude.This verifies that the EICP technology can greatly reduce the permeability of underwater sand beds.With increasing grouting cycles,the resistivity of the underwater sand initially decreases and then increases.This variation in sand resistivity is significantly influenced by the ion concentration in the solution,resulting in marked differences in resistivity at various depths and positions within the sand.The findings from this study offer a theoretical basis for the application of EICP technology in reinforcing seabed foundations and supporting marine infrastructure such as offshore pipelines,wind turbines,and oil platforms.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
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
The northeastern permafrost region of China is one of the most vulnerable areas to climate warming in midlatitude areas.Despite this,the specific pathways of water vapor circulation and transport in this area remain p...The northeastern permafrost region of China is one of the most vulnerable areas to climate warming in midlatitude areas.Despite this,the specific pathways of water vapor circulation and transport in this area remain poorly understood.Additionally,there is ongoing debate on whether the oxygen isotope of precipitation(δ^(18)O_(p))is primarily influenced by the temperature or the precipitation amount effects.Tree-ring samples were collected from various sites and tree species across the region,and 12 stable oxygen isotopes(δ18Oc)series constructed to investigate the water vapor signals embedded within.Our findings revealed consistentδ18Oc variations across different sites and species,reflecting relative humidity signals during the growing season(June to September)(r=−0.764,P<0.001,n=40).By applying an improved model to simulateδ^(18)O_(p),a“temperature effect”was identified.Bothδ18Oc andδ^(18)O_(p) provided valuable insights into the regional water vapor circulation,withδ18Oc offering a stronger climate signal.A binary linear regression model further revealed thatδ^(18)O_(p) had a greater influence onδ18Oc than relative humidity.The regional climate is primarily driven by the East Asian summer monsoon and large-scale water vapor circulation associated with the El Niño-Southern Oscillation.Because of future warming and drying trends,trees in this region are expected to face increasing drought stress.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
Benthic habitat mapping is an emerging discipline in the international marine field in recent years,providing an effective tool for marine spatial planning,marine ecological management,and decision-making applications...Benthic habitat mapping is an emerging discipline in the international marine field in recent years,providing an effective tool for marine spatial planning,marine ecological management,and decision-making applications.Seabed sediment classification is one of the main contents of seabed habitat mapping.In response to the impact of remote sensing imaging quality and the limitations of acoustic measurement range,where a single data source does not fully reflect the substrate type,we proposed a high-precision seabed habitat sediment classification method that integrates data from multiple sources.Based on WorldView-2 multi-spectral remote sensing image data and multibeam bathymetry data,constructed a random forests(RF)classifier with optimal feature selection.A seabed sediment classification experiment integrating optical remote sensing and acoustic remote sensing data was carried out in the shallow water area of Wuzhizhou Island,Hainan,South China.Different seabed sediment types,such as sand,seagrass,and coral reefs were effectively identified,with an overall classification accuracy of 92%.Experimental results show that RF matrix optimized by fusing multi-source remote sensing data for feature selection were better than the classification results of simple combinations of data sources,which improved the accuracy of seabed sediment classification.Therefore,the method proposed in this paper can be effectively applied to high-precision seabed sediment classification and habitat mapping around islands and reefs.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
Microbially induced calcium carbonate precipitation(MICP)is an eco-friendly technology for soil improvement.Although numerous experiments have been conducted to solidify sand foundations using MICP,the mechanisms by w...Microbially induced calcium carbonate precipitation(MICP)is an eco-friendly technology for soil improvement.Although numerous experiments have been conducted to solidify sand foundations using MICP,the mechanisms by which grain interfacial morphologies influencethe MICP process remain unclear.This study utilized 3D-printed flowcells with different boundary morphologies to investigate the effects of interfacial morphologies on the MICP process.CaCO_(3)precipitation characteristics were investigated through microscopic observation and image quantificationanalysis.The results indicate that low flowvelocities near the interface promote bacterial accumulation due to reduced hydrodynamic shear forces.Rough interfaces,compared to smooth ones,enhance bacterial adsorption owing to the larger regions of low flowvelocity,increased surface area,and the formation of local eddies,which promote greater CaCO_(3)precipitation.Compared to the regions away from the interface,a higher abundance of small CaCO_(3)crystals is observed near the interface because of the high urease activity from bacteria and the reduced shear-induced entrainment due to the low flowvelocity.Besides,larger crystals also preferentially precipitate in proximity to interfaces as the low flowvelocity enhances crystal growth according to the particle attachment theory.The presence of rough interfaces further reduces flowvelocities,leading to the precipitation of larger and more densely packed CaCO_(3)crystals.Therefore,rough interfaces promote the microbially induced calcium carbonate precipitation.This work is expected to enhance the understanding of microbially induced calcium carbonate precipitation characteristics on solid surfaces such as soil grains and contribute to the optimization of MICP applications.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 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
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
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
Titanium alloys engineered in structural applications achieve ultrahigh strength primarily through precipitation strengthening of secondary α-phase(αs)during aging,while they often experience compromised ductility a...Titanium alloys engineered in structural applications achieve ultrahigh strength primarily through precipitation strengthening of secondary α-phase(αs)during aging,while they often experience compromised ductility and toughness due to traditional strength-toughness tradeoff.In this study,we propose a novel strategy to address this conflict by introducing deformation kinks prior to conventional cold rolling(CR)and aging processes.These kinks are produced by cold forging(CF)to create macroscopic lamellar structures in β-grains,which alter strain partitioning during subsequent CR and ultimately tailor α_(s)-precipitation upon aging.As a result,an ultrafine duplex(αe+β)-structure is formed within kink interi-ors,while hierarchicalαs-precipitates are generated in the external β-matrix.This unique microstructure effectively enhances dislocation activity,promotes uniform plastic strain distribution and impedes crack propagation.Consequently,a simple Ti-V binary titanium alloy exhibits exceptional properties with ultra-high strength∼1636 MPa,decent ductility∼5.4% and appreciable fracture toughness∼36.1 MPa m^(1/2).The synergetic properties surpass those obtained through traditional CR and aging processes for the alloy and even outperform numerous multielement engineering titanium alloys reported in literature.Our findings open up a new avenue for overcoming the strength-toughness tradeoffof ultrahigh-strength titanium alloys,and also offer a facile production route towards structural materials for advanced performance.展开更多
At present,the identification of tropical cyclone remote precipitation(TRP)requires subjective participation,leading to inconsistent results among different researchers despite adopting the same identification standar...At present,the identification of tropical cyclone remote precipitation(TRP)requires subjective participation,leading to inconsistent results among different researchers despite adopting the same identification standard.Thus,establishing an objective identification method is greatly important.In this study,an objective synoptic analysis technique for TRP(OSAT_TRP)is proposed to identify TRP using daily precipitation datasets,historical tropical cyclone(TC)track data,and the ERA5 reanalysis data.This method includes three steps:first,independent rain belts are separated,and those that might relate to TCs'remote effects are distinguished according to their distance from the TCs.Second,the strong water vapor transport belt from the TC is identified using integrated horizontal water vapor transport(IVT).Third,TRP is distinguished by connecting the first two steps.The TRP obtained through this method can satisfy three criteria,as follows:1)the precipitation occurs outside the circulation of TCs,2)the precipitation is affected by TCs,and 3)a gap exists between the TRP and TC rain belt.Case diagnosis analysis,compared with subjective TRP results and backward trajectory analyses using HYSPLIT,indicates that OSAT_TRP can distinguish TRP even when multiple TCs in the Northwest Pacific are involved.Then,we applied the OSAT_TRP to select typical TRPs and obtained the synoptic-scale environments of the TRP through composite analysis.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
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 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supported by the National Youth Top-notch Talent Support Program of China(Grant No.00389335)the National Natural Science Foundation of China(Grant No.52378392)+1 种基金the“Foal Eagle Program”Youth Top-notch Talent Project of Fujian Province(Grant No.00387088)supports are gratefully acknowledged.
文摘Enzyme-Induced Carbonate Precipitation(EICP)is an innovative technique to improve soil strength and reduce permeability.However,the use of EICP for reinforcing underwater sand beds remains largely unexplored.To advance EICP implementation in various geotechnical applications,this paper develops a model box system to investigate the effectiveness of the EICP technique in reinforcing underwater sand beds.An"injection-extraction"system is designed to facilitate the flow of the EICP solution through underwater sand layers.Key parameters,including conductivity,pH,and Ca^(2+)concentration of the solution,are measured and analyzed.Electrical resistivity tomography(ERT)is utilized to evaluate the reinforcement effect in the underwater sand bed.The permeability of the model is tested to verify the feasibility of EICP technology for strengthening underwater sands.Furthermore,scanning electron microscope(SEM)is performed to investigate the growth mechanisms of calcium carbonate(CaCO_(3))crystals.The results show that the permeability of the model decreases from 1.28×10^(-2)m/s to 9.66×10^(-5)m/s,representing a reduction of approximately three orders of magnitude.This verifies that the EICP technology can greatly reduce the permeability of underwater sand beds.With increasing grouting cycles,the resistivity of the underwater sand initially decreases and then increases.This variation in sand resistivity is significantly influenced by the ion concentration in the solution,resulting in marked differences in resistivity at various depths and positions within the sand.The findings from this study offer a theoretical basis for the application of EICP technology in reinforcing seabed foundations and supporting marine infrastructure such as offshore pipelines,wind turbines,and oil platforms.
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supported by the National Natural Science Foundation of China(Grant Nos.42173080 and 42488201)the Chinese Academy of Sciences(Grant No.XDB40010300)the Young Talent Support Plan of Xi’an Jiaotong University.
文摘The northeastern permafrost region of China is one of the most vulnerable areas to climate warming in midlatitude areas.Despite this,the specific pathways of water vapor circulation and transport in this area remain poorly understood.Additionally,there is ongoing debate on whether the oxygen isotope of precipitation(δ^(18)O_(p))is primarily influenced by the temperature or the precipitation amount effects.Tree-ring samples were collected from various sites and tree species across the region,and 12 stable oxygen isotopes(δ18Oc)series constructed to investigate the water vapor signals embedded within.Our findings revealed consistentδ18Oc variations across different sites and species,reflecting relative humidity signals during the growing season(June to September)(r=−0.764,P<0.001,n=40).By applying an improved model to simulateδ^(18)O_(p),a“temperature effect”was identified.Bothδ18Oc andδ^(18)O_(p) provided valuable insights into the regional water vapor circulation,withδ18Oc offering a stronger climate signal.A binary linear regression model further revealed thatδ^(18)O_(p) had a greater influence onδ18Oc than relative humidity.The regional climate is primarily driven by the East Asian summer monsoon and large-scale water vapor circulation associated with the El Niño-Southern Oscillation.Because of future warming and drying trends,trees in this region are expected to face increasing drought stress.
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(Nos.42376185,41876111)the Shandong Provincial Natural Science Foundation(No.ZR2023MD073)。
文摘Benthic habitat mapping is an emerging discipline in the international marine field in recent years,providing an effective tool for marine spatial planning,marine ecological management,and decision-making applications.Seabed sediment classification is one of the main contents of seabed habitat mapping.In response to the impact of remote sensing imaging quality and the limitations of acoustic measurement range,where a single data source does not fully reflect the substrate type,we proposed a high-precision seabed habitat sediment classification method that integrates data from multiple sources.Based on WorldView-2 multi-spectral remote sensing image data and multibeam bathymetry data,constructed a random forests(RF)classifier with optimal feature selection.A seabed sediment classification experiment integrating optical remote sensing and acoustic remote sensing data was carried out in the shallow water area of Wuzhizhou Island,Hainan,South China.Different seabed sediment types,such as sand,seagrass,and coral reefs were effectively identified,with an overall classification accuracy of 92%.Experimental results show that RF matrix optimized by fusing multi-source remote sensing data for feature selection were better than the classification results of simple combinations of data sources,which improved the accuracy of seabed sediment classification.Therefore,the method proposed in this paper can be effectively applied to high-precision seabed sediment classification and habitat mapping around islands and reefs.
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supported by the National Key Research and Development Program of China(Grant No.2023YFC3707900)National Natural Science Foundation of China(Grant No.42230710,42525201)Key task project for joint research and development of the Yangtze River Delta Science and Technology Innovation Community(Grant No.2022CSJGG1200).
文摘Microbially induced calcium carbonate precipitation(MICP)is an eco-friendly technology for soil improvement.Although numerous experiments have been conducted to solidify sand foundations using MICP,the mechanisms by which grain interfacial morphologies influencethe MICP process remain unclear.This study utilized 3D-printed flowcells with different boundary morphologies to investigate the effects of interfacial morphologies on the MICP process.CaCO_(3)precipitation characteristics were investigated through microscopic observation and image quantificationanalysis.The results indicate that low flowvelocities near the interface promote bacterial accumulation due to reduced hydrodynamic shear forces.Rough interfaces,compared to smooth ones,enhance bacterial adsorption owing to the larger regions of low flowvelocity,increased surface area,and the formation of local eddies,which promote greater CaCO_(3)precipitation.Compared to the regions away from the interface,a higher abundance of small CaCO_(3)crystals is observed near the interface because of the high urease activity from bacteria and the reduced shear-induced entrainment due to the low flowvelocity.Besides,larger crystals also preferentially precipitate in proximity to interfaces as the low flowvelocity enhances crystal growth according to the particle attachment theory.The presence of rough interfaces further reduces flowvelocities,leading to the precipitation of larger and more densely packed CaCO_(3)crystals.Therefore,rough interfaces promote the microbially induced calcium carbonate precipitation.This work is expected to enhance the understanding of microbially induced calcium carbonate precipitation characteristics on solid surfaces such as soil grains and contribute to the optimization of MICP applications.
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supported by the National Natural Science Foundation of China(Nos.52271113,92163201)Jinyu Zhang is grateful for the Shaanxi Province Youth Innovation Team(No.22JP042)Shaanxi Province Innovation Team Project(2024RS-CXTD-58).
文摘Titanium alloys engineered in structural applications achieve ultrahigh strength primarily through precipitation strengthening of secondary α-phase(αs)during aging,while they often experience compromised ductility and toughness due to traditional strength-toughness tradeoff.In this study,we propose a novel strategy to address this conflict by introducing deformation kinks prior to conventional cold rolling(CR)and aging processes.These kinks are produced by cold forging(CF)to create macroscopic lamellar structures in β-grains,which alter strain partitioning during subsequent CR and ultimately tailor α_(s)-precipitation upon aging.As a result,an ultrafine duplex(αe+β)-structure is formed within kink interi-ors,while hierarchicalαs-precipitates are generated in the external β-matrix.This unique microstructure effectively enhances dislocation activity,promotes uniform plastic strain distribution and impedes crack propagation.Consequently,a simple Ti-V binary titanium alloy exhibits exceptional properties with ultra-high strength∼1636 MPa,decent ductility∼5.4% and appreciable fracture toughness∼36.1 MPa m^(1/2).The synergetic properties surpass those obtained through traditional CR and aging processes for the alloy and even outperform numerous multielement engineering titanium alloys reported in literature.Our findings open up a new avenue for overcoming the strength-toughness tradeoffof ultrahigh-strength titanium alloys,and also offer a facile production route towards structural materials for advanced performance.
基金supported by the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX22_1136)the National Natural Scientific Foundation of China(No.42275037)+2 种基金the Basic Research Fund of CAMS(No.2023Z016)the Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province(No.SCSF202202)supported by the Jiangsu Collaborative Innovation Center for Climate Change。
文摘At present,the identification of tropical cyclone remote precipitation(TRP)requires subjective participation,leading to inconsistent results among different researchers despite adopting the same identification standard.Thus,establishing an objective identification method is greatly important.In this study,an objective synoptic analysis technique for TRP(OSAT_TRP)is proposed to identify TRP using daily precipitation datasets,historical tropical cyclone(TC)track data,and the ERA5 reanalysis data.This method includes three steps:first,independent rain belts are separated,and those that might relate to TCs'remote effects are distinguished according to their distance from the TCs.Second,the strong water vapor transport belt from the TC is identified using integrated horizontal water vapor transport(IVT).Third,TRP is distinguished by connecting the first two steps.The TRP obtained through this method can satisfy three criteria,as follows:1)the precipitation occurs outside the circulation of TCs,2)the precipitation is affected by TCs,and 3)a gap exists between the TRP and TC rain belt.Case diagnosis analysis,compared with subjective TRP results and backward trajectory analyses using HYSPLIT,indicates that OSAT_TRP can distinguish TRP even when multiple TCs in the Northwest Pacific are involved.Then,we applied the OSAT_TRP to select typical TRPs and obtained the synoptic-scale environments of the TRP through composite analysis.
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.
