Precipitation strengthening is a key strategy for improving the overall mechanical properties of Mg alloys. In Mg-Al alloys, basal precipitates are known to strengthen against twinning, resulting in an increase in the...Precipitation strengthening is a key strategy for improving the overall mechanical properties of Mg alloys. In Mg-Al alloys, basal precipitates are known to strengthen against twinning, resulting in an increase in the critical resolved shear stress(CRSS) necessary for continued deformation. Although several models have been proposed to quantify the influence of precipitate shape, size, and distribution on the CRSS, the accuracy, scope, and applicability of these models has not been fully assessed. Accordingly, the objectives of this study are:(i)to analyze the accuracy of analytical models proposed in the literature for precipitation strengthening against twin thickening and propagation(in Mg-Al alloys) using phase-field(PF) simulations,(ii) to propose modifications to these model forms to better capture the observed trends in the PF data, and(iii) to subsequently test the predictiveness of the extended models in extrapolating to experimental strengthening data.First, using an atomistically-informed phase-field method, the interactions between migrating twin boundaries(during the propagation and thickening stages) and basal plates are simulated for different precipitate sizes and arrangements. In general, comparison of the increase in CRSS determined from the PF simulations and the predictions from four precipitation strengthening models reveals that modifications are necessary to the model forms to extend their applicability to precipitation strengthening against both twin thickening and propagation. A subsequent comparison between predictions from the extended models and experimental strengthening data for peak age-hardened samples reveals that the(extended) single dislocation and dislocation wall models provide reasonably accurate values of the increase in CRSS.Ultimately, the results presented here help elucidate the fidelity and applicability of the various hardening models in predicting precipitation strenghtening effects in technologically important alloys.展开更多
Xinjiang Uygur Autonomous Region is a typical inland arid area in China with a sparse and uneven distribution of meteorological stations,limited access to precipitation data,and significant water scarcity.Evaluating a...Xinjiang Uygur Autonomous Region is a typical inland arid area in China with a sparse and uneven distribution of meteorological stations,limited access to precipitation data,and significant water scarcity.Evaluating and integrating precipitation datasets from different sources to accurately characterize precipitation patterns has become a challenge to provide more accurate and alternative precipitation information for the region,which can even improve the performance of hydrological modelling.This study evaluated the applicability of widely used five satellite-based precipitation products(Climate Hazards Group InfraRed Precipitation with Station(CHIRPS),China Meteorological Forcing Dataset(CMFD),Climate Prediction Center morphing method(CMORPH),Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record(PERSIANN-CDR),and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis(TMPA))and a reanalysis precipitation dataset(ECMWF Reanalysis v5-Land Dataset(ERA5-Land))in Xinjiang using ground-based observational precipitation data from a limited number of meteorological stations.Based on this assessment,we proposed a framework that integrated different precipitation datasets with varying spatial resolutions using a dynamic Bayesian model averaging(DBMA)approach,the expectation-maximization method,and the ordinary Kriging interpolation method.The daily precipitation data merged using the DBMA approach exhibited distinct spatiotemporal variability,with an outstanding performance,as indicated by low root mean square error(RMSE=1.40 mm/d)and high Person's correlation coefficient(CC=0.67).Compared with the traditional simple model averaging(SMA)and individual product data,although the DBMA-fused precipitation data were slightly lower than the best precipitation product(CMFD),the overall performance of DBMA was more robust.The error analysis between DBMA-fused precipitation dataset and the more advanced Integrated Multi-satellite Retrievals for Global Precipitation Measurement Final(IMERG-F)precipitation product,as well as hydrological simulations in the Ebinur Lake Basin,further demonstrated the superior performance of DBMA-fused precipitation dataset in the entire Xinjiang region.The proposed framework for solving the fusion problem of multi-source precipitation data with different spatial resolutions is feasible for application in inland arid areas,and aids in obtaining more accurate regional hydrological information and improving regional water resources management capabilities and meteorological research in these regions.展开更多
Understanding the structure of tropical cyclone(TC)hydrometeors is crucial for detecting the changes in the distribution and intensity of precipitation.In this study,the GMI brightness temperature and cloud-dependent ...Understanding the structure of tropical cyclone(TC)hydrometeors is crucial for detecting the changes in the distribution and intensity of precipitation.In this study,the GMI brightness temperature and cloud-dependent 1DVAR algorithm were used to retrieve the hydrometeor profiles and surface rain rate of TC Nanmadol(2022).The Advanced Radiative Transfer Modeling System(ARMS)was used to calculate the Jacobian and degrees of freedom(△DOF)of cloud water,rainwater,and graupel for different channels of GMI in convective conditions.The retrieval results were compared with the Dual-frequency Precipitation Radar(DPR),GMI 2A,and IMERG products.It is shown that from all channels of GMI,rain water has the highest△DOF,at 1.72.According to the radiance Jacobian to atmospheric state variables,cloud water emission dominates its scattering.For rain water,the emission of channels 1–4 dominates scattering.Compared with the GMI 2A precipitation product,the 1DVAR precipitation rate has a higher correlation coefficient(0.713)with the IMERG product and can better reflect the location of TC precipitation.Near the TC eyewall,the highest radar echo top indicates strong convection.Near the melting layer where Ka-band attenuation is strong,the double frequency difference of DPR data reflects the location of the melting.The DPR drop size distribution(DSD)product shows that there is a significant increase in particle size below the melting layer in the spiral rain band.Thus,the particle size may be one of the main reasons for the smaller rain water below the melting layer retrieved from 1DVAR.展开更多
Whether climate change or anthropogenic activities play a more pivotal role in regulating vegetation growth on the Tibetan Plateau is still controversial.A better understanding on grassland changes at a fine scale may...Whether climate change or anthropogenic activities play a more pivotal role in regulating vegetation growth on the Tibetan Plateau is still controversial.A better understanding on grassland changes at a fine scale may provide important guidance for local government policy and grassland management.Using two of the most reliable satellite NDVI products(MODIS NDVI and SPOT NDVI),we evaluated the dynamic of grasslands in the Zhegucuo valley on the southern Tibetan Plateau from 2000 to 2020,and analyzed its driving factors and relative influences of climate change and anthropogenic activities.Here,the key indicators of climate change were assumed to be precipitation and temperature.The main results were:(1)the grassland NDVI in Zhegucuo valley did not reflect a significant temporal change during the last 21 years.The variation of precipitation during the early growing season(GSP)resembled that of NDVI,and the GSP was positively correlated with NDVI.At the pixel level,the partial correlation analysis showed that 37.79%of the pixels depicted a positive relationship between GSP and NDVI,while 11.32%of the pixels showed a negative relationship between temperature during the early growing season(GST)and NDVI.(2)In view of the spatial distribution,the areas mainly controlled by GSP were generally distributed in the southern part,while those affected by GST stood in the eastern part,mainly around the Zhegucuo lake where most population in Cuomei County settled down.(3)Decreasing NDVI trends were mainly occurred in alpine steppe at lower elevations rather than alpine meadow at higher elevations.(4)The residual trend(RESTREND)analysis further indicated that the anthropogenic activities played a more pivotal role in regulating the annual changes of NDVI rather than climate factors in this area.Future studies should pay more attention on climate extremes rather than the simple temporal trends.Also,the influence of human activities on alpine grassland needs to be accessed and fully considered in future sustainable management.展开更多
By using the multi-taper method(MTM)of singular value decomposition(SVD),this study investigates the interdecadal evolution(10-to 30-year cycle)of precipitation over eastern China from 1951 to 2015 and its relationshi...By using the multi-taper method(MTM)of singular value decomposition(SVD),this study investigates the interdecadal evolution(10-to 30-year cycle)of precipitation over eastern China from 1951 to 2015 and its relationship with the North Pacific sea surface temperature(SST).Two significant interdecadal signals,one with an 11-year cycle and the other with a 23-year cycle,are identified in both the precipitation and SST fields.Results show that the North Pacific SST forcing modulates the precipitation distribution over China through the effects of the Pacific Decadal Oscillation(PDO)-related anomalous Aleutian low on the western Pacific subtropical high(WPSH)and Mongolia high(MH).During the development stage of the PDO cold phase associated with the 11-year cycle,a weakened WPSH and MH increased the precipitation over the Yangtze River Basin,whereas an intensified WPSH and MH caused the enhanced rain band to move northward to North China during the decay stage.During the development stage of the PDO cold phase associated with the 23-year cycle,a weakened WPSH and MH increased the precipitation over North China,whereas an intensified WPSH and the weakened MH increased the precipitation over South China during the decay stage.The 11-year and 23-year variabilities contribute differently to the precipitation variations in the different regions of China,as seen in the 1998flooding case.The 11-year cycle mainly accounts for precipitation increases over the Yangtze River Basin,while the 23-year cycle is responsible for the precipitation increase over Northeast China.These results have important implications for understanding how the PDO modulates the precipitation distribution over China,helping to improve interdecadal climate prediction.展开更多
In order to obtain more accurate precipitation data and better simulate the precipitation on the Tibetan Plateau,the simulation capability of 14 Coupled Model Intercomparison Project Phase 6(CMIP6)models of historical...In order to obtain more accurate precipitation data and better simulate the precipitation on the Tibetan Plateau,the simulation capability of 14 Coupled Model Intercomparison Project Phase 6(CMIP6)models of historical precipitation(1982-2014)on the Qinghai-Tibetan Plateau was evaluated in this study.Results indicate that all models exhibit an overestimation of precipitation through the analysis of the Taylor index,temporal and spatial statistical parameters.To correct the overestimation,a fusion correction method combining the Backpropagation Neural Network Correction(BP)and Quantum Mapping(QM)correction,named BQ method,was proposed.With this method,the historical precipitation of each model was corrected in space and time,respectively.The correction results were then analyzed in time,space,and analysis of variance(ANOVA)with those corrected by the BP and QM methods,respectively.Finally,the fusion correction method results for each model were compared with the Climatic Research Unit(CRU)data for significance analysis to obtain the trends of precipitation increase and decrease for each model.The results show that the IPSL-CM6A-LR model is relatively good in simulating historical precipitation on the Qinghai-Tibetan Plateau(R=0.7,RSME=0.15)among the uncorrected data.In terms of time,the total precipitation corrected by the fusion method has the same interannual trend and the closest precipitation values to the CRU data;In terms of space,the annual average precipitation corrected by the fusion method has the smallest difference with the CRU data,and the total historical annual average precipitation is not significantly different from the CRU data,which is better than BP and QM.Therefore,the correction effect of the fusion method on the historical precipitation of each model is better than that of the QM and BP methods.The precipitation in the central and northeastern parts of the plateau shows a significant increasing trend.The correlation coefficients between monthly precipitation and site-detected precipitation for all models after BQ correction exceed 0.8.展开更多
Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss pos...Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.展开更多
This study examines the spatio-temporal characteristics of heavy precipitation forecasts in eastern China from the European Centre for Medium-Range Weather Forecasts(ECMWF) using the time-domain version of the Method ...This study examines the spatio-temporal characteristics of heavy precipitation forecasts in eastern China from the European Centre for Medium-Range Weather Forecasts(ECMWF) using the time-domain version of the Method for Object-based Diagnostic Evaluation(MODE-TD). A total of 23 heavy rainfall cases occurring between 2018 and 2021 are selected for analysis. Using Typhoon “Rumbia” as a case study, the paper illustrates how the MODE-TD method assesses the overall simulation capability of models for the life history of precipitation systems. The results of multiple tests with different parameter configurations reveal that the model underestimates the number of objects’ forecasted precipitation tracks, particularly at smaller radii. Additionally, the analysis based on centroid offset and area ratio tests for different classified precipitation objects indicates that the model performs better in predicting large-area, fast-moving, and longlifespan precipitation objects. Conversely, it tends to have less accurate predictions for small-area, slow-moving, and shortlifespan precipitation objects. In terms of temporal characteristics, the model overestimates the forecasted movement speed for precipitation objects with small-area, slow movement, or both long and short lifespans while underestimating it for precipitation with fast movement. In terms of temporal characteristics, the model tends to overestimate the forecasted movement speed for precipitation objects with small-area, slow movement, or both long and short lifespans while underestimating it for precipitation with fast movement. Overall, the model provides more accurate predictions for the duration and dissipation of precipitation objects with large-area or long-lifespan(such as typhoon precipitation) while having large prediction errors for precipitation objects with small-area or short-lifespan. Furthermore, the model’s simulation results regarding the generation of precipitation objects show that it performs relatively well in simulating the generation of large-area and fast-moving precipitation objects. However, there are significant differences in the forecasted generation of small-area and slow-moving precipitation objects after 9 hours.展开更多
Weather conditions play a pivotal role in embryo development and parental incubation costs,potentially impacting the clutch size and incubation behavior of birds.Understanding these effects is crucial for bird conserv...Weather conditions play a pivotal role in embryo development and parental incubation costs,potentially impacting the clutch size and incubation behavior of birds.Understanding these effects is crucial for bird conservation.Reeves’ s Pheasant(Syrmaticus reevesii) is a threatened species endemic to China,which is characterized by female-only incubation.However,there is a lack of information regarding the impact of weather conditions on clutch size and incubation behavior in this species.Using satellite tracking,we tracked 27 wild female Reeves’ s Pheasants from 2020 to 2023 in Hubei Province,China.We explored their clutch size and incubation behavior,as well as their responses to ambient temperature and precipitation.Clutch size averaged 7.75 ±1.36,had an association with average ambient temperature and average daily precipitation during the egglaying period,and was potentially linked to female breeding attempts.Throughout the incubation period,females took an average of 0.73 ±0.46 recesses every 24 h,with an average recess duration of 100.80 ±73.37 min and an average nest attendance of 92.98 ±5.27%.They showed a unimodal recess pattern in which nest departures peaked primarily between 13:00 and 16:00.Furthermore,females rarely left nests when daily precipitation was high.Recess duration and nest attendance were influenced by the interaction between daily mean ambient temperature and daily precipitation,as well as day of incubation.Additionally,there was a positive correlation between clutch size and recess duration.These results contribute valuable insights into the lifehistory features of this endangered species.展开更多
Landslides are highly dangerous phenomena that occur in different parts of the world and pose significant threats to human populations. Intense rainfall events are the main triggering process for landslides in urbaniz...Landslides are highly dangerous phenomena that occur in different parts of the world and pose significant threats to human populations. Intense rainfall events are the main triggering process for landslides in urbanized slope regions, especially those considered high-risk areas. Various other factors contribute to the process;thus, it is essential to analyze the causes of such incidents in all possible ways. Soil moisture plays a critical role in the Earth’s surface-atmosphere interaction systems;hence, measurements and their estimations are crucial for understanding all processes involved in the water balance, especially those related to landslides. Soil moisture can be estimated from in-situ measurements using different sensors and techniques, satellite remote sensing, hydrological modeling, and indicators to index moisture conditions. Antecedent soil moisture can significantly impact runoff for the same rainfall event in a watershed. The Antecedent Precipitation Index (API) or “retained rainfall,” along with the antecedent moisture condition from the Natural Resources Conservation Service, is generally applied to estimate runoff in watersheds where data is limited or unavailable. This work aims to explore API in estimating soil moisture and establish thresholds based on landslide occurrences. The estimated soil moisture will be compared and calibrated using measurements obtained through multisensor capacitance probes installed in a high-risk area located in the mountainous region of Campos do Jordão municipality, São Paulo, Brazil. The API used in the calculation has been modified, where the recession coefficient depends on air temperature variability as well as the climatological mean temperature, which can be considered as losses in the water balance due to evapotranspiration. Once the API is calibrated, it will be used to extrapolate to the entire watershed and consequently estimate soil moisture. By utilizing recorded mass movements and comparing them with API and soil moisture, it will be possible to determine thresholds, thus enabling anticipation of landslide occurrences.展开更多
Small mountainous rivers are characterized by large instantaneous fluxes and susceptible to extreme weather events,which can rapidly transport materials into the sea and have a significant impact on the ecological env...Small mountainous rivers are characterized by large instantaneous fluxes and susceptible to extreme weather events,which can rapidly transport materials into the sea and have a significant impact on the ecological environment of estuaries and bays.In order to investigate the seasonal characteristics of nutrients in small mountainous rivers in the subtropical monsoon region and the output pattern to the sea during heavy precipitation,surveys on the mountainous rivers were carried out in Baixi watershed in August 2020(wet season),March 2021(dry season)and June 2021(Meiyu period).The results showed that the dissolved inorganic nitrogen(DIN)of the rivers has an average concentration of 752μg L^(−1)in the wet season and 1472μg L^(−1)in the dry season.The concentrations of dissolved inorganic phosphorus(DIP)in wet season and dry season were 63μg L^(−1)and 51μg L^(−1),respectively.Influenced by the changes of land use in sub-watersheds,DIN concentrations in the mainstream increased from 701μg L^(−1)in the upper reaches to 1284μg L^(−1)in the middle reaches.Two rainstorms during the Meiyu period in the watershed caused the pulse runoff in the river.The maximum daily runoff reached 70 times that before rains.The maximum daily fluxes of DIN and DIP were 109 and 247 times that before rains,respectively.In view that the watershed experienced several rainstorms in the wet season,the river,with pulse runoff,carries a large amount of nutrients into the sea in a short time,which will have a significant impact on the environment of Sanmen bay and its adjacent sea.展开更多
There are more uncertainties with ice hydrometeor representations and related processes than liquid hydrometeors within microphysics parameterization(MP)schemes because of their complicated geometries and physical pro...There are more uncertainties with ice hydrometeor representations and related processes than liquid hydrometeors within microphysics parameterization(MP)schemes because of their complicated geometries and physical properties.Idealized supercell simulations are produced using the WRF model coupled with“full”Hebrew University spectral bin MP(HU-SBM),and NSSL and Thompson bulk MP(BMP)schemes.HU-SBM downdrafts are typically weaker than those of the NSSL and Thompson simulations,accompanied by less rain evaporation.HU-SBM produces more cloud ice(plates),graupel,and hail than the BMPs,yet precipitates less at the surface.The limiting mass bins(and subsequently,particle size)of rimed ice in HU-SBM and slower rimed ice fall speeds lead to smaller melting-level net rimed ice fluxes than those of the BMPs.Aggregation from plates in HU-SBM,together with snow–graupel collisions,leads to a greater snow contribution to rain than those of the BMPs.Replacing HU-SBM’s fall speeds using the formulations of the BMPs after aggregating the discrete bin values to mass mixing ratios and total number concentrations increases net rain and rimed ice fluxes.Still,they are smaller in magnitude than bulk rain,NSSL hail,and Thompson graupel net fluxes near the surface.Conversely,the melting-layer net rimed ice fluxes are reduced when the fall speeds for the NSSL and Thompson simulations are calculated using HU-SBM fall speed formulations after discretizing the bulk particle size distributions(PSDs)into spectral bins.The results highlight precipitation sensitivity to storm dynamics,fall speed,hydrometeor evolution governed by process rates,and MP PSD design.展开更多
This study assesses the suitability of convolutional neural networks(CNNs) for downscaling precipitation over East Africa in the context of seasonal forecasting. To achieve this, we design a set of experiments that co...This study assesses the suitability of convolutional neural networks(CNNs) for downscaling precipitation over East Africa in the context of seasonal forecasting. To achieve this, we design a set of experiments that compare different CNN configurations and deployed the best-performing architecture to downscale one-month lead seasonal forecasts of June–July–August–September(JJAS) precipitation from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0(NUIST-CFS1.0) for 1982–2020. We also perform hyper-parameter optimization and introduce predictors over a larger area to include information about the main large-scale circulations that drive precipitation over the East Africa region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results show that the CNN-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme precipitation spatial patterns. Besides, CNN-based downscaling yields a much more accurate forecast of extreme and spell indicators and reduces the significant relative biases exhibited by the raw model predictions. Moreover, our results show that CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of East Africa. The results demonstrate the potential usefulness of CNN in downscaling seasonal precipitation predictions over East Africa,particularly in providing improved forecast products which are essential for end users.展开更多
Existing studies contend that latent heating(LH)will replace sensible heating(SH)to become the dominant factor affecting the development of the Tibetan Plateau vortex(TPV)after it moves off the Tibetan Plateau(TP).How...Existing studies contend that latent heating(LH)will replace sensible heating(SH)to become the dominant factor affecting the development of the Tibetan Plateau vortex(TPV)after it moves off the Tibetan Plateau(TP).However,in the process of the TPV moving off the TP requires that the airmass traverse the eastern slope of the Tibetan Plateau(ESTP)where the topography and diabatic heating(DH)conditions rapidly change.How LH gradually replaces SH to become the dominant factor in the development of the TPV over the ESTP is still not very clear.In this paper,an analysis of a typical case of a TPV with a long life history over the ESTP is performed by using multi-sourced meteorological data and model simulations.The results show that SH from the TP surface can change the TPV-associated precipitation distribution by temperature advection after the TPV moves off the TP.The LH can then directly promote the development of the TPV and has a certain guiding effect on the track of the TPV.The SH can control the active area of LH by changing the falling area of the TPV-associated precipitation,so it still plays a key role in the development and tracking of the TPV even though it has moved out of the main body of the TP.展开更多
Enzyme-induced carbonate precipitation(EICP)is an emanating,eco-friendly and potentially sound technique that has presented promise in various geotechnical applications.However,the durability and microscopic character...Enzyme-induced carbonate precipitation(EICP)is an emanating,eco-friendly and potentially sound technique that has presented promise in various geotechnical applications.However,the durability and microscopic characteristics of EICP-treated specimens against the impact of drying-wetting(D-W)cycles is under-explored yet.This study investigates the evolution of mechanical behavior and pore charac-teristics of EICP-treated sea sand subjected to D-W cycles.The uniaxial compressive strength(UCS)tests,synchrotron radiation micro-computed tomography(micro-CT),and three-dimensional(3D)recon-struction of CT images were performed to study the multiscale evolution characteristics of EICP-reinforced sea sand under the effect of D-W cycles.The potential correlations between microstructure characteristics and macro-mechanical property deterioration were investigated using gray relational analysis(GRA).Results showed that the UCS of EICP-treated specimens decreases by 63.7% after 15 D-W cycles.The proportion of mesopores gradually decreases whereas the proportion of macropores in-creases due to the exfoliated calcium carbonate with increasing number of D-W cycles.The micro-structure in EICP-reinforced sea sand was gradually disintegrated,resulting in increasing pore size and development of pore shape from ellipsoidal to columnar and branched.The gray relational degree suggested that the weight loss rate and UCS deterioration were attributed to the development of branched pores with a size of 100-1000 m m under the action of D-W cycles.Overall,the results in this study provide a useful guidancee for the long-term stability and evolution characteristics of EICP-reinforced sea sand under D-W weathering conditions.展开更多
The recent increase in blast/bombing incidents all over the world has pushed the development of effective strengthening approaches to enhance the blast resistance of existing civil infrastructures.Engineered geopolyme...The recent increase in blast/bombing incidents all over the world has pushed the development of effective strengthening approaches to enhance the blast resistance of existing civil infrastructures.Engineered geopolymer composite(EGC)is a promising material featured by eco-friendly,fast-setting and strain-hardening characteristics for emergent strengthening and construction.However,the fiber optimization for preparing EGC and its protective effect on structural elements under blast scenarios are uncertain.In this study,laboratory tests were firstly conducted to evaluate the effects of fiber types on the properties of EGC in terms of workability,dry shrinkage,and mechanical properties in compression,tension and flexure.The experimental results showed that EGC containing PE fiber exhibited suitable workability,acceptable dry shrinkage and superior mechanical properties compared with other types of fibers.After that,a series of field tests were carried out to evaluate the effectiveness of EGC retrofitting layer on the enhancement of blast performance of typical elements.The tests include autoclaved aerated concrete(AAC)masonry walls subjected to vented gas explosion,reinforced AAC panels subjected to TNT explosion and plain concrete slabs subjected to contact explosion.It was found that EGC could effectively enhance the blast resistance of structural elements in different scenarios.For AAC masonry walls and panels,with the existence of EGC,the integrity of specimens could be maintained,and their deflections and damage were significantly reduced.For plain concrete slabs,the EGC overlay could reduce the diameter and depth of the crater and spallation of specimens.展开更多
The snow cover over the Taurus Mountains affects water supply, agriculture, and hydropower generation in the region. In this study, we analyzed the monthly Snow Cover Extent(SCE) from November to April in the Central ...The snow cover over the Taurus Mountains affects water supply, agriculture, and hydropower generation in the region. In this study, we analyzed the monthly Snow Cover Extent(SCE) from November to April in the Central Taurus Mountains(Bolkar, Aladaglar, Tahtali and Binboga Mountains) from 1981 to 2021. Linear trends of snow cover season(November to April) over the last 41 years showed decreases in SCE primarily at lower elevations. The downward trend in SCE was found to be more pronounced and statistically significant for only November and March. SCE in the Central Taurus Mountains has declined about-6.3% per decade for 2500-3000 m in November and about-6.0% per decade for 1000-1500 m and 3000+ m in March over the last 41 years. The loss of SCE has become evident since the 2000s, and the lowest negative anomalies in SCE have been observed in 2014, 2001, and 2007 in the last 41 years, which are consistent with an increase in air temperature and decreased precipitation. SCE was correlated with both mean temperature and precipitation, with temperature having a greater relative importance at all elevated gradients. Results showed that there is a strong linear relationship between SCE and the mean air temperature(r =-0.80) and precipitation(r = 0.44) for all elevated gradients during the snow season. The Arctic Oscillation(AO), the North Atlantic Oscillation(NAO), and the Mediterranean Oscillation(MO) winter indices were used to explain the year-to-year variability in SCE over the Central Taurus Mountains. The results showed that the inter-annual variability observed in the winter SCE on the Central Taurus Mountains was positively correlated with the phases of the winter AO, NAO and MO, especially below 2000 m elevation.展开更多
Based on the monitoring data of PM_(2.5) concentration in Bengbu Environmental Monitoring Station and precipitation observation data of Bengbu National Meteorological Observation Station from 2016 to 2019, the influen...Based on the monitoring data of PM_(2.5) concentration in Bengbu Environmental Monitoring Station and precipitation observation data of Bengbu National Meteorological Observation Station from 2016 to 2019, the influence of precipitation on PM_(2.5) mass concentration in Bengbu City was analyzed. The results show that precipitation had a washing and removal effect on PM_(2.5) in the air, and the removal effect was related to precipitation level, precipitation intensity, precipitation duration and PM_(2.5) concentration. The removal effect of precipitation on PM_(2.5) increased with the increase of precipitation level, and the seasonal difference was obvious. Precipitation intensity was positively correlated with the removal effect of PM_(2.5) , but the average removal rate began to decline when precipitation intensity exceeded 10 mm. With the increase of precipitation intensity, the proportion of positive removal showed an overall upward trend, but there was a low-value area as precipitation intensity was 3-10 mm. Precipitation duration was also positively correlated with the removal effect of PM_(2.5) , and there was a low-value area when precipitation duration was 10-15 h. When PM_(2.5) concentration was low before the precipitation process began, the removal effect was not good, and the average removal rate was negative. As PM_(2.5) concentration was high before the precipitation process started, the removal effect was obvious.展开更多
The purpose of this paper is to investigate the spatial interpolation of rainfall variability with deterministic and geostatic inspections in the Prefecture of Kilkis (Greece). The precipitation data where recorded fr...The purpose of this paper is to investigate the spatial interpolation of rainfall variability with deterministic and geostatic inspections in the Prefecture of Kilkis (Greece). The precipitation data where recorded from 12 meteorological stations in the Prefecture of Kilkis for 36 hydrological years (1973-2008). The cumulative monthly values of rainfall were studied on an annual and seasonal basis as well as during the arid-dry season. In the deterministic tests, the I.D.W. and R.B.F. checks were inspected, while in the geostatic tests, Ordinary Kriging and Universal Kriging respectively. The selection of the optimum method was made based on the least Root Mean Square Error (R.M.S.E.), as well as on the Mean Error (M.E.), as assessed by the cross validation analysis. The geostatical Kriging also considered the impact of isotropy and anisotropy across all time periods of data collection. Moreover, for Universal Kriging, the study explored spherical, exponential and Gaussian models in various combinations. Geostatistical techniques consistently demonstrated greater reliability than deterministic techniques across all time periods of data collection. Specifically, during the annual period, anisotropy was the prevailing characteristic in geostatistical techniques. Moreover, the results for the irrigation and seasonal periods were generally comparable, with few exceptions where isotropic methods yielded lower (R.M.S.E.) in some seasonal observations.展开更多
This study comprehensively examines the patterns and regional variation of severe rainfall across the African continent, employing a suite of eight extreme precipitation indices. The analysis extends to the assessment...This study comprehensively examines the patterns and regional variation of severe rainfall across the African continent, employing a suite of eight extreme precipitation indices. The analysis extends to the assessment of projected changes in precipitation extremes using five General Circulation Models (GCMs) from Coupled Model Intercomparison Project Phase 6 (CMIP6) under four Shared Socioeconomic Pathways (SSPs) scenarios at the long-term period (2081-2100) of the 21<sup>st</sup> century. Furthermore, the study investigates potential mechanisms influencing precipitation extremes by correlating extreme precipitation indices with oceanic system indices, specifically Ni?o 3.4 for El Ni?o-Southern Oscillation (ENSO) and Dipole Mode Index (DMI) for the Indian Ocean Dipole (IOD). The findings revealed distinct spatial distributions in mean trends of extreme precipitation indices, indicating a tendency toward decreased extreme precipitation in North Africa, Sahel region, Central Africa and the Western part of South Africa. Conversely, West Africa, East Africa and the Eastern part of South Africa exhibit an inclination toward increased extreme precipitation. The changes in precipitation extreme indices indicate a general rise in both the severity and occurrence of extreme precipitation events under all scenarios by the end of the 21<sup>st</sup> century. Notably, our analysis projects a decrease in consecutive wet days (CWD) in the far-future. Additionally, correlation analysis highlights significant correlation between above or below threshold rainfall fluctuation in East Africa and South Africa with oceanic systems, particularly ENSO and the IOD. Central Africa abnormal precipitation variability is also linked to ENSO with a significant negative correlation. These insights contribute valuable information for understanding and projecting the dynamics of precipitation extreme in Africa, providing a foundation for climate adaptation and mitigation efforts in the region.展开更多
基金fully funded by the U.S.Dept.of Energy,Office of Basic Energy Sciences Project FWP 06SCPE401supported by the U.S.Department of Energy National Nuclear Security Administration under Contract No.89233218CNA000001。
文摘Precipitation strengthening is a key strategy for improving the overall mechanical properties of Mg alloys. In Mg-Al alloys, basal precipitates are known to strengthen against twinning, resulting in an increase in the critical resolved shear stress(CRSS) necessary for continued deformation. Although several models have been proposed to quantify the influence of precipitate shape, size, and distribution on the CRSS, the accuracy, scope, and applicability of these models has not been fully assessed. Accordingly, the objectives of this study are:(i)to analyze the accuracy of analytical models proposed in the literature for precipitation strengthening against twin thickening and propagation(in Mg-Al alloys) using phase-field(PF) simulations,(ii) to propose modifications to these model forms to better capture the observed trends in the PF data, and(iii) to subsequently test the predictiveness of the extended models in extrapolating to experimental strengthening data.First, using an atomistically-informed phase-field method, the interactions between migrating twin boundaries(during the propagation and thickening stages) and basal plates are simulated for different precipitate sizes and arrangements. In general, comparison of the increase in CRSS determined from the PF simulations and the predictions from four precipitation strengthening models reveals that modifications are necessary to the model forms to extend their applicability to precipitation strengthening against both twin thickening and propagation. A subsequent comparison between predictions from the extended models and experimental strengthening data for peak age-hardened samples reveals that the(extended) single dislocation and dislocation wall models provide reasonably accurate values of the increase in CRSS.Ultimately, the results presented here help elucidate the fidelity and applicability of the various hardening models in predicting precipitation strenghtening effects in technologically important alloys.
基金supported by The Technology Innovation Team(Tianshan Innovation Team),Innovative Team for Efficient Utilization of Water Resources in Arid Regions(2022TSYCTD0001)the National Natural Science Foundation of China(42171269)the Xinjiang Academician Workstation Cooperative Research Project(2020.B-001).
文摘Xinjiang Uygur Autonomous Region is a typical inland arid area in China with a sparse and uneven distribution of meteorological stations,limited access to precipitation data,and significant water scarcity.Evaluating and integrating precipitation datasets from different sources to accurately characterize precipitation patterns has become a challenge to provide more accurate and alternative precipitation information for the region,which can even improve the performance of hydrological modelling.This study evaluated the applicability of widely used five satellite-based precipitation products(Climate Hazards Group InfraRed Precipitation with Station(CHIRPS),China Meteorological Forcing Dataset(CMFD),Climate Prediction Center morphing method(CMORPH),Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record(PERSIANN-CDR),and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis(TMPA))and a reanalysis precipitation dataset(ECMWF Reanalysis v5-Land Dataset(ERA5-Land))in Xinjiang using ground-based observational precipitation data from a limited number of meteorological stations.Based on this assessment,we proposed a framework that integrated different precipitation datasets with varying spatial resolutions using a dynamic Bayesian model averaging(DBMA)approach,the expectation-maximization method,and the ordinary Kriging interpolation method.The daily precipitation data merged using the DBMA approach exhibited distinct spatiotemporal variability,with an outstanding performance,as indicated by low root mean square error(RMSE=1.40 mm/d)and high Person's correlation coefficient(CC=0.67).Compared with the traditional simple model averaging(SMA)and individual product data,although the DBMA-fused precipitation data were slightly lower than the best precipitation product(CMFD),the overall performance of DBMA was more robust.The error analysis between DBMA-fused precipitation dataset and the more advanced Integrated Multi-satellite Retrievals for Global Precipitation Measurement Final(IMERG-F)precipitation product,as well as hydrological simulations in the Ebinur Lake Basin,further demonstrated the superior performance of DBMA-fused precipitation dataset in the entire Xinjiang region.The proposed framework for solving the fusion problem of multi-source precipitation data with different spatial resolutions is feasible for application in inland arid areas,and aids in obtaining more accurate regional hydrological information and improving regional water resources management capabilities and meteorological research in these regions.
基金funded by the National Key Research and Development Program of China(Grant No.2022YFC3004202)the National Natural Science Foundation of China(Grant Nos.U2142212 and 42105136)。
文摘Understanding the structure of tropical cyclone(TC)hydrometeors is crucial for detecting the changes in the distribution and intensity of precipitation.In this study,the GMI brightness temperature and cloud-dependent 1DVAR algorithm were used to retrieve the hydrometeor profiles and surface rain rate of TC Nanmadol(2022).The Advanced Radiative Transfer Modeling System(ARMS)was used to calculate the Jacobian and degrees of freedom(△DOF)of cloud water,rainwater,and graupel for different channels of GMI in convective conditions.The retrieval results were compared with the Dual-frequency Precipitation Radar(DPR),GMI 2A,and IMERG products.It is shown that from all channels of GMI,rain water has the highest△DOF,at 1.72.According to the radiance Jacobian to atmospheric state variables,cloud water emission dominates its scattering.For rain water,the emission of channels 1–4 dominates scattering.Compared with the GMI 2A precipitation product,the 1DVAR precipitation rate has a higher correlation coefficient(0.713)with the IMERG product and can better reflect the location of TC precipitation.Near the TC eyewall,the highest radar echo top indicates strong convection.Near the melting layer where Ka-band attenuation is strong,the double frequency difference of DPR data reflects the location of the melting.The DPR drop size distribution(DSD)product shows that there is a significant increase in particle size below the melting layer in the spiral rain band.Thus,the particle size may be one of the main reasons for the smaller rain water below the melting layer retrieved from 1DVAR.
基金funded by the Second Tibetan Plateau Scientific Expedition and Research program(2019QZKK0301)the Natural Science Foundation of Xizang Autonomous Region(XZ202301ZR0027G).
文摘Whether climate change or anthropogenic activities play a more pivotal role in regulating vegetation growth on the Tibetan Plateau is still controversial.A better understanding on grassland changes at a fine scale may provide important guidance for local government policy and grassland management.Using two of the most reliable satellite NDVI products(MODIS NDVI and SPOT NDVI),we evaluated the dynamic of grasslands in the Zhegucuo valley on the southern Tibetan Plateau from 2000 to 2020,and analyzed its driving factors and relative influences of climate change and anthropogenic activities.Here,the key indicators of climate change were assumed to be precipitation and temperature.The main results were:(1)the grassland NDVI in Zhegucuo valley did not reflect a significant temporal change during the last 21 years.The variation of precipitation during the early growing season(GSP)resembled that of NDVI,and the GSP was positively correlated with NDVI.At the pixel level,the partial correlation analysis showed that 37.79%of the pixels depicted a positive relationship between GSP and NDVI,while 11.32%of the pixels showed a negative relationship between temperature during the early growing season(GST)and NDVI.(2)In view of the spatial distribution,the areas mainly controlled by GSP were generally distributed in the southern part,while those affected by GST stood in the eastern part,mainly around the Zhegucuo lake where most population in Cuomei County settled down.(3)Decreasing NDVI trends were mainly occurred in alpine steppe at lower elevations rather than alpine meadow at higher elevations.(4)The residual trend(RESTREND)analysis further indicated that the anthropogenic activities played a more pivotal role in regulating the annual changes of NDVI rather than climate factors in this area.Future studies should pay more attention on climate extremes rather than the simple temporal trends.Also,the influence of human activities on alpine grassland needs to be accessed and fully considered in future sustainable management.
基金supported by the National Natural Science Foundation of China(Grant No.42030410)Laoshan Laboratory(No.LSKJ202202403-2)+1 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB40000000)the Startup Foundation for Introducing Talent of NUIST。
文摘By using the multi-taper method(MTM)of singular value decomposition(SVD),this study investigates the interdecadal evolution(10-to 30-year cycle)of precipitation over eastern China from 1951 to 2015 and its relationship with the North Pacific sea surface temperature(SST).Two significant interdecadal signals,one with an 11-year cycle and the other with a 23-year cycle,are identified in both the precipitation and SST fields.Results show that the North Pacific SST forcing modulates the precipitation distribution over China through the effects of the Pacific Decadal Oscillation(PDO)-related anomalous Aleutian low on the western Pacific subtropical high(WPSH)and Mongolia high(MH).During the development stage of the PDO cold phase associated with the 11-year cycle,a weakened WPSH and MH increased the precipitation over the Yangtze River Basin,whereas an intensified WPSH and MH caused the enhanced rain band to move northward to North China during the decay stage.During the development stage of the PDO cold phase associated with the 23-year cycle,a weakened WPSH and MH increased the precipitation over North China,whereas an intensified WPSH and the weakened MH increased the precipitation over South China during the decay stage.The 11-year and 23-year variabilities contribute differently to the precipitation variations in the different regions of China,as seen in the 1998flooding case.The 11-year cycle mainly accounts for precipitation increases over the Yangtze River Basin,while the 23-year cycle is responsible for the precipitation increase over Northeast China.These results have important implications for understanding how the PDO modulates the precipitation distribution over China,helping to improve interdecadal climate prediction.
文摘In order to obtain more accurate precipitation data and better simulate the precipitation on the Tibetan Plateau,the simulation capability of 14 Coupled Model Intercomparison Project Phase 6(CMIP6)models of historical precipitation(1982-2014)on the Qinghai-Tibetan Plateau was evaluated in this study.Results indicate that all models exhibit an overestimation of precipitation through the analysis of the Taylor index,temporal and spatial statistical parameters.To correct the overestimation,a fusion correction method combining the Backpropagation Neural Network Correction(BP)and Quantum Mapping(QM)correction,named BQ method,was proposed.With this method,the historical precipitation of each model was corrected in space and time,respectively.The correction results were then analyzed in time,space,and analysis of variance(ANOVA)with those corrected by the BP and QM methods,respectively.Finally,the fusion correction method results for each model were compared with the Climatic Research Unit(CRU)data for significance analysis to obtain the trends of precipitation increase and decrease for each model.The results show that the IPSL-CM6A-LR model is relatively good in simulating historical precipitation on the Qinghai-Tibetan Plateau(R=0.7,RSME=0.15)among the uncorrected data.In terms of time,the total precipitation corrected by the fusion method has the same interannual trend and the closest precipitation values to the CRU data;In terms of space,the annual average precipitation corrected by the fusion method has the smallest difference with the CRU data,and the total historical annual average precipitation is not significantly different from the CRU data,which is better than BP and QM.Therefore,the correction effect of the fusion method on the historical precipitation of each model is better than that of the QM and BP methods.The precipitation in the central and northeastern parts of the plateau shows a significant increasing trend.The correlation coefficients between monthly precipitation and site-detected precipitation for all models after BQ correction exceed 0.8.
文摘Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.
基金National Key Research and Development Program of China (2021YFC3000802)National Natural Science Foundation of China (41875059)The Open Research Program of the State Key Laboratory of Severe Weather (2021LASW-A04)。
文摘This study examines the spatio-temporal characteristics of heavy precipitation forecasts in eastern China from the European Centre for Medium-Range Weather Forecasts(ECMWF) using the time-domain version of the Method for Object-based Diagnostic Evaluation(MODE-TD). A total of 23 heavy rainfall cases occurring between 2018 and 2021 are selected for analysis. Using Typhoon “Rumbia” as a case study, the paper illustrates how the MODE-TD method assesses the overall simulation capability of models for the life history of precipitation systems. The results of multiple tests with different parameter configurations reveal that the model underestimates the number of objects’ forecasted precipitation tracks, particularly at smaller radii. Additionally, the analysis based on centroid offset and area ratio tests for different classified precipitation objects indicates that the model performs better in predicting large-area, fast-moving, and longlifespan precipitation objects. Conversely, it tends to have less accurate predictions for small-area, slow-moving, and shortlifespan precipitation objects. In terms of temporal characteristics, the model overestimates the forecasted movement speed for precipitation objects with small-area, slow movement, or both long and short lifespans while underestimating it for precipitation with fast movement. In terms of temporal characteristics, the model tends to overestimate the forecasted movement speed for precipitation objects with small-area, slow movement, or both long and short lifespans while underestimating it for precipitation with fast movement. Overall, the model provides more accurate predictions for the duration and dissipation of precipitation objects with large-area or long-lifespan(such as typhoon precipitation) while having large prediction errors for precipitation objects with small-area or short-lifespan. Furthermore, the model’s simulation results regarding the generation of precipitation objects show that it performs relatively well in simulating the generation of large-area and fast-moving precipitation objects. However, there are significant differences in the forecasted generation of small-area and slow-moving precipitation objects after 9 hours.
基金supported by the National Natural Science Foundation of China (grant number 31872240)。
文摘Weather conditions play a pivotal role in embryo development and parental incubation costs,potentially impacting the clutch size and incubation behavior of birds.Understanding these effects is crucial for bird conservation.Reeves’ s Pheasant(Syrmaticus reevesii) is a threatened species endemic to China,which is characterized by female-only incubation.However,there is a lack of information regarding the impact of weather conditions on clutch size and incubation behavior in this species.Using satellite tracking,we tracked 27 wild female Reeves’ s Pheasants from 2020 to 2023 in Hubei Province,China.We explored their clutch size and incubation behavior,as well as their responses to ambient temperature and precipitation.Clutch size averaged 7.75 ±1.36,had an association with average ambient temperature and average daily precipitation during the egglaying period,and was potentially linked to female breeding attempts.Throughout the incubation period,females took an average of 0.73 ±0.46 recesses every 24 h,with an average recess duration of 100.80 ±73.37 min and an average nest attendance of 92.98 ±5.27%.They showed a unimodal recess pattern in which nest departures peaked primarily between 13:00 and 16:00.Furthermore,females rarely left nests when daily precipitation was high.Recess duration and nest attendance were influenced by the interaction between daily mean ambient temperature and daily precipitation,as well as day of incubation.Additionally,there was a positive correlation between clutch size and recess duration.These results contribute valuable insights into the lifehistory features of this endangered species.
文摘Landslides are highly dangerous phenomena that occur in different parts of the world and pose significant threats to human populations. Intense rainfall events are the main triggering process for landslides in urbanized slope regions, especially those considered high-risk areas. Various other factors contribute to the process;thus, it is essential to analyze the causes of such incidents in all possible ways. Soil moisture plays a critical role in the Earth’s surface-atmosphere interaction systems;hence, measurements and their estimations are crucial for understanding all processes involved in the water balance, especially those related to landslides. Soil moisture can be estimated from in-situ measurements using different sensors and techniques, satellite remote sensing, hydrological modeling, and indicators to index moisture conditions. Antecedent soil moisture can significantly impact runoff for the same rainfall event in a watershed. The Antecedent Precipitation Index (API) or “retained rainfall,” along with the antecedent moisture condition from the Natural Resources Conservation Service, is generally applied to estimate runoff in watersheds where data is limited or unavailable. This work aims to explore API in estimating soil moisture and establish thresholds based on landslide occurrences. The estimated soil moisture will be compared and calibrated using measurements obtained through multisensor capacitance probes installed in a high-risk area located in the mountainous region of Campos do Jordão municipality, São Paulo, Brazil. The API used in the calculation has been modified, where the recession coefficient depends on air temperature variability as well as the climatological mean temperature, which can be considered as losses in the water balance due to evapotranspiration. Once the API is calibrated, it will be used to extrapolate to the entire watershed and consequently estimate soil moisture. By utilizing recorded mass movements and comparing them with API and soil moisture, it will be possible to determine thresholds, thus enabling anticipation of landslide occurrences.
基金financially supported by the Postdoctoral Foundation of Qingdao(Pb Isotopes of Oujiang River to Quantitatively Identify Sediment Provenance in Oujiang Estuary and Adjacent Area)the China Geological Survey Project(No.DD20190276)the Fund of Ministry of Science and Technology(Nos.2013FY112200 and 2019YFE0127200).
文摘Small mountainous rivers are characterized by large instantaneous fluxes and susceptible to extreme weather events,which can rapidly transport materials into the sea and have a significant impact on the ecological environment of estuaries and bays.In order to investigate the seasonal characteristics of nutrients in small mountainous rivers in the subtropical monsoon region and the output pattern to the sea during heavy precipitation,surveys on the mountainous rivers were carried out in Baixi watershed in August 2020(wet season),March 2021(dry season)and June 2021(Meiyu period).The results showed that the dissolved inorganic nitrogen(DIN)of the rivers has an average concentration of 752μg L^(−1)in the wet season and 1472μg L^(−1)in the dry season.The concentrations of dissolved inorganic phosphorus(DIP)in wet season and dry season were 63μg L^(−1)and 51μg L^(−1),respectively.Influenced by the changes of land use in sub-watersheds,DIN concentrations in the mainstream increased from 701μg L^(−1)in the upper reaches to 1284μg L^(−1)in the middle reaches.Two rainstorms during the Meiyu period in the watershed caused the pulse runoff in the river.The maximum daily runoff reached 70 times that before rains.The maximum daily fluxes of DIN and DIP were 109 and 247 times that before rains,respectively.In view that the watershed experienced several rainstorms in the wet season,the river,with pulse runoff,carries a large amount of nutrients into the sea in a short time,which will have a significant impact on the environment of Sanmen bay and its adjacent sea.
基金This research was primarily supported by a NOAA Warn-on-Forecast(WoF)grant(Grant No.NA16OAR4320115).
文摘There are more uncertainties with ice hydrometeor representations and related processes than liquid hydrometeors within microphysics parameterization(MP)schemes because of their complicated geometries and physical properties.Idealized supercell simulations are produced using the WRF model coupled with“full”Hebrew University spectral bin MP(HU-SBM),and NSSL and Thompson bulk MP(BMP)schemes.HU-SBM downdrafts are typically weaker than those of the NSSL and Thompson simulations,accompanied by less rain evaporation.HU-SBM produces more cloud ice(plates),graupel,and hail than the BMPs,yet precipitates less at the surface.The limiting mass bins(and subsequently,particle size)of rimed ice in HU-SBM and slower rimed ice fall speeds lead to smaller melting-level net rimed ice fluxes than those of the BMPs.Aggregation from plates in HU-SBM,together with snow–graupel collisions,leads to a greater snow contribution to rain than those of the BMPs.Replacing HU-SBM’s fall speeds using the formulations of the BMPs after aggregating the discrete bin values to mass mixing ratios and total number concentrations increases net rain and rimed ice fluxes.Still,they are smaller in magnitude than bulk rain,NSSL hail,and Thompson graupel net fluxes near the surface.Conversely,the melting-layer net rimed ice fluxes are reduced when the fall speeds for the NSSL and Thompson simulations are calculated using HU-SBM fall speed formulations after discretizing the bulk particle size distributions(PSDs)into spectral bins.The results highlight precipitation sensitivity to storm dynamics,fall speed,hydrometeor evolution governed by process rates,and MP PSD design.
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)the High-Performance Computing of Nanjing University of Information Science&Technology for their support of this work。
文摘This study assesses the suitability of convolutional neural networks(CNNs) for downscaling precipitation over East Africa in the context of seasonal forecasting. To achieve this, we design a set of experiments that compare different CNN configurations and deployed the best-performing architecture to downscale one-month lead seasonal forecasts of June–July–August–September(JJAS) precipitation from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0(NUIST-CFS1.0) for 1982–2020. We also perform hyper-parameter optimization and introduce predictors over a larger area to include information about the main large-scale circulations that drive precipitation over the East Africa region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results show that the CNN-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme precipitation spatial patterns. Besides, CNN-based downscaling yields a much more accurate forecast of extreme and spell indicators and reduces the significant relative biases exhibited by the raw model predictions. Moreover, our results show that CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of East Africa. The results demonstrate the potential usefulness of CNN in downscaling seasonal precipitation predictions over East Africa,particularly in providing improved forecast products which are essential for end users.
基金supported by the National Natural Science Foundation of China(Grant Nos.42175002,42030611,42075013)the Natural Science Foundation of Sichuan,China(Grant No.2023NSFSC0242)the Innovation Team Fund of Southwest Regional Meteorological Center,China Meteorological Administration(Grant No.XNQYCXTD-202202)。
文摘Existing studies contend that latent heating(LH)will replace sensible heating(SH)to become the dominant factor affecting the development of the Tibetan Plateau vortex(TPV)after it moves off the Tibetan Plateau(TP).However,in the process of the TPV moving off the TP requires that the airmass traverse the eastern slope of the Tibetan Plateau(ESTP)where the topography and diabatic heating(DH)conditions rapidly change.How LH gradually replaces SH to become the dominant factor in the development of the TPV over the ESTP is still not very clear.In this paper,an analysis of a typical case of a TPV with a long life history over the ESTP is performed by using multi-sourced meteorological data and model simulations.The results show that SH from the TP surface can change the TPV-associated precipitation distribution by temperature advection after the TPV moves off the TP.The LH can then directly promote the development of the TPV and has a certain guiding effect on the track of the TPV.The SH can control the active area of LH by changing the falling area of the TPV-associated precipitation,so it still plays a key role in the development and tracking of the TPV even though it has moved out of the main body of the TP.
基金The authors gratefully acknowledge the financial support of National NaturalScience Foundation of China(Grant No.41972276)Natural Science Foundation of Fujian Province,China(Grant No.2020J06013)"Foal Eagle Program"Youth Top-notch Talent Project of Fujian Province,China(Grant No.00387088).
文摘Enzyme-induced carbonate precipitation(EICP)is an emanating,eco-friendly and potentially sound technique that has presented promise in various geotechnical applications.However,the durability and microscopic characteristics of EICP-treated specimens against the impact of drying-wetting(D-W)cycles is under-explored yet.This study investigates the evolution of mechanical behavior and pore charac-teristics of EICP-treated sea sand subjected to D-W cycles.The uniaxial compressive strength(UCS)tests,synchrotron radiation micro-computed tomography(micro-CT),and three-dimensional(3D)recon-struction of CT images were performed to study the multiscale evolution characteristics of EICP-reinforced sea sand under the effect of D-W cycles.The potential correlations between microstructure characteristics and macro-mechanical property deterioration were investigated using gray relational analysis(GRA).Results showed that the UCS of EICP-treated specimens decreases by 63.7% after 15 D-W cycles.The proportion of mesopores gradually decreases whereas the proportion of macropores in-creases due to the exfoliated calcium carbonate with increasing number of D-W cycles.The micro-structure in EICP-reinforced sea sand was gradually disintegrated,resulting in increasing pore size and development of pore shape from ellipsoidal to columnar and branched.The gray relational degree suggested that the weight loss rate and UCS deterioration were attributed to the development of branched pores with a size of 100-1000 m m under the action of D-W cycles.Overall,the results in this study provide a useful guidancee for the long-term stability and evolution characteristics of EICP-reinforced sea sand under D-W weathering conditions.
基金National Natural Science Foundation of China(Grant Nos.51908188 and 51938011).
文摘The recent increase in blast/bombing incidents all over the world has pushed the development of effective strengthening approaches to enhance the blast resistance of existing civil infrastructures.Engineered geopolymer composite(EGC)is a promising material featured by eco-friendly,fast-setting and strain-hardening characteristics for emergent strengthening and construction.However,the fiber optimization for preparing EGC and its protective effect on structural elements under blast scenarios are uncertain.In this study,laboratory tests were firstly conducted to evaluate the effects of fiber types on the properties of EGC in terms of workability,dry shrinkage,and mechanical properties in compression,tension and flexure.The experimental results showed that EGC containing PE fiber exhibited suitable workability,acceptable dry shrinkage and superior mechanical properties compared with other types of fibers.After that,a series of field tests were carried out to evaluate the effectiveness of EGC retrofitting layer on the enhancement of blast performance of typical elements.The tests include autoclaved aerated concrete(AAC)masonry walls subjected to vented gas explosion,reinforced AAC panels subjected to TNT explosion and plain concrete slabs subjected to contact explosion.It was found that EGC could effectively enhance the blast resistance of structural elements in different scenarios.For AAC masonry walls and panels,with the existence of EGC,the integrity of specimens could be maintained,and their deflections and damage were significantly reduced.For plain concrete slabs,the EGC overlay could reduce the diameter and depth of the crater and spallation of specimens.
文摘The snow cover over the Taurus Mountains affects water supply, agriculture, and hydropower generation in the region. In this study, we analyzed the monthly Snow Cover Extent(SCE) from November to April in the Central Taurus Mountains(Bolkar, Aladaglar, Tahtali and Binboga Mountains) from 1981 to 2021. Linear trends of snow cover season(November to April) over the last 41 years showed decreases in SCE primarily at lower elevations. The downward trend in SCE was found to be more pronounced and statistically significant for only November and March. SCE in the Central Taurus Mountains has declined about-6.3% per decade for 2500-3000 m in November and about-6.0% per decade for 1000-1500 m and 3000+ m in March over the last 41 years. The loss of SCE has become evident since the 2000s, and the lowest negative anomalies in SCE have been observed in 2014, 2001, and 2007 in the last 41 years, which are consistent with an increase in air temperature and decreased precipitation. SCE was correlated with both mean temperature and precipitation, with temperature having a greater relative importance at all elevated gradients. Results showed that there is a strong linear relationship between SCE and the mean air temperature(r =-0.80) and precipitation(r = 0.44) for all elevated gradients during the snow season. The Arctic Oscillation(AO), the North Atlantic Oscillation(NAO), and the Mediterranean Oscillation(MO) winter indices were used to explain the year-to-year variability in SCE over the Central Taurus Mountains. The results showed that the inter-annual variability observed in the winter SCE on the Central Taurus Mountains was positively correlated with the phases of the winter AO, NAO and MO, especially below 2000 m elevation.
文摘Based on the monitoring data of PM_(2.5) concentration in Bengbu Environmental Monitoring Station and precipitation observation data of Bengbu National Meteorological Observation Station from 2016 to 2019, the influence of precipitation on PM_(2.5) mass concentration in Bengbu City was analyzed. The results show that precipitation had a washing and removal effect on PM_(2.5) in the air, and the removal effect was related to precipitation level, precipitation intensity, precipitation duration and PM_(2.5) concentration. The removal effect of precipitation on PM_(2.5) increased with the increase of precipitation level, and the seasonal difference was obvious. Precipitation intensity was positively correlated with the removal effect of PM_(2.5) , but the average removal rate began to decline when precipitation intensity exceeded 10 mm. With the increase of precipitation intensity, the proportion of positive removal showed an overall upward trend, but there was a low-value area as precipitation intensity was 3-10 mm. Precipitation duration was also positively correlated with the removal effect of PM_(2.5) , and there was a low-value area when precipitation duration was 10-15 h. When PM_(2.5) concentration was low before the precipitation process began, the removal effect was not good, and the average removal rate was negative. As PM_(2.5) concentration was high before the precipitation process started, the removal effect was obvious.
文摘The purpose of this paper is to investigate the spatial interpolation of rainfall variability with deterministic and geostatic inspections in the Prefecture of Kilkis (Greece). The precipitation data where recorded from 12 meteorological stations in the Prefecture of Kilkis for 36 hydrological years (1973-2008). The cumulative monthly values of rainfall were studied on an annual and seasonal basis as well as during the arid-dry season. In the deterministic tests, the I.D.W. and R.B.F. checks were inspected, while in the geostatic tests, Ordinary Kriging and Universal Kriging respectively. The selection of the optimum method was made based on the least Root Mean Square Error (R.M.S.E.), as well as on the Mean Error (M.E.), as assessed by the cross validation analysis. The geostatical Kriging also considered the impact of isotropy and anisotropy across all time periods of data collection. Moreover, for Universal Kriging, the study explored spherical, exponential and Gaussian models in various combinations. Geostatistical techniques consistently demonstrated greater reliability than deterministic techniques across all time periods of data collection. Specifically, during the annual period, anisotropy was the prevailing characteristic in geostatistical techniques. Moreover, the results for the irrigation and seasonal periods were generally comparable, with few exceptions where isotropic methods yielded lower (R.M.S.E.) in some seasonal observations.
文摘This study comprehensively examines the patterns and regional variation of severe rainfall across the African continent, employing a suite of eight extreme precipitation indices. The analysis extends to the assessment of projected changes in precipitation extremes using five General Circulation Models (GCMs) from Coupled Model Intercomparison Project Phase 6 (CMIP6) under four Shared Socioeconomic Pathways (SSPs) scenarios at the long-term period (2081-2100) of the 21<sup>st</sup> century. Furthermore, the study investigates potential mechanisms influencing precipitation extremes by correlating extreme precipitation indices with oceanic system indices, specifically Ni?o 3.4 for El Ni?o-Southern Oscillation (ENSO) and Dipole Mode Index (DMI) for the Indian Ocean Dipole (IOD). The findings revealed distinct spatial distributions in mean trends of extreme precipitation indices, indicating a tendency toward decreased extreme precipitation in North Africa, Sahel region, Central Africa and the Western part of South Africa. Conversely, West Africa, East Africa and the Eastern part of South Africa exhibit an inclination toward increased extreme precipitation. The changes in precipitation extreme indices indicate a general rise in both the severity and occurrence of extreme precipitation events under all scenarios by the end of the 21<sup>st</sup> century. Notably, our analysis projects a decrease in consecutive wet days (CWD) in the far-future. Additionally, correlation analysis highlights significant correlation between above or below threshold rainfall fluctuation in East Africa and South Africa with oceanic systems, particularly ENSO and the IOD. Central Africa abnormal precipitation variability is also linked to ENSO with a significant negative correlation. These insights contribute valuable information for understanding and projecting the dynamics of precipitation extreme in Africa, providing a foundation for climate adaptation and mitigation efforts in the region.
