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

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

Spatio-Temporal Characteristics of Heavy Precipitation Forecasts from ECMWF in Eastern China

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.

Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

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.

Time-lagged Effects of the Spring Atmospheric Heat Source over the Tibetan Plateau on Summer Precipitation in Northeast China during 1961–2020:Role of Soil Moisture

The spring atmospheric heat source(AHS)over the Tibetan Plateau(TP)has been suggested to affect the Asian summer monsoon and summer precipitation over South China.However,its influence on the summer precipitation in Northeast China(NEC)remains unknown.The connection between spring TP AHS and subsequent summer precipitation over NEC from 1961 to 2020 is analyzed in this study.Results illustrate that stronger spring TP AHS can enhance subsequent summer NEC precipitation,and higher soil moisture in the Yellow River Valley-North China region(YRVNC)acts as a bridge.During spring,the strong TP AHS could strengthen the transportation of water vapor to East China and lead to excessive rainfall in the YRVNC.Thus,soil moisture increases,which regulates local thermal conditions by decreasing local surface skin temperature and sensible heat.Owing to the memory of soil moisture,the lower spring sensible heat over the YRVNC can last until mid-summer,decrease the land–sea thermal contrast,and weaken the southerly winds over the East Asia–western Pacific region and convective activities over the South China Sea and tropical western Pacific.This modulates the East Asia–Pacific teleconnection pattern,which leads to a cyclonic anomaly and excessive summer precipitation over NEC.

The GNSS PWV retrieval using non-observation meteorological parameters based on ERA5 and its relation with precipitation

The pressure and temperature significantly influence precipitable water vapor(PWV) retrieval. Global Navigation Satellite System(GNSS) PWV retrieval is limited because the GNSS stations lack meteorological sensors. First, this article evaluated the accuracy of pressure and temperature in 68 radiosonde stations in China based on ERA5 Reanalysis data from 2015 to 2019 and compared them with GPT3model. Then, the accuracy of pressure and temperature calculated by ERA5 were estimated in 5 representative IGS stations in China. And the PWV calculated by these meteorological parameters from ERA5(ERA5-PWV) were analyzed. Finally, the relation between ERA5-PWV and precipitation was deeply explored using wavelet coherence analysis in IGS stations. These results indicate that the accuracy of pressure and temperature of ERA5 is better than the GPT3 model. In radiosonde stations, the mean BIAS and MAE of pressure and temperature in ERA5 are-0.41/1.15 hpa and-0.97/2.12 K. And the mean RMSEs are 1.35 hpa and 2.87 K, which improve 74.77% and 40.58% compared with GPT3 model. The errors of pressure and temperature of ERA5 are smaller than the GPT3 model in bjfs, hksl and wuh2, and the accuracy of ERA5-PWV is improved by 18.77% compared with the GPT3 model. In addition, there is a significant positive correlation between ERA5-PWV and precipitation. And precipitation is always associated with the sharp rise of ERA5-PWV, which provides important references for rainfall prediction.

A New Algorithm of Rain Type Classification for GPM Dual-Frequency Precipitation Radar in Summer Tibetan Plateau

In this study, a new rain type classification algorithm for the Dual-Frequency Precipitation Radar(DPR) suitable over the Tibetan Plateau(TP) was proposed by analyzing Global Precipitation Measurement(GPM) DPR Level-2 data in summer from 2014 to 2020. It was found that the DPR rain type classification algorithm(simply called DPR algorithm) has mis-identification problems in two aspects in summer TP. In the new algorithm of rain type classification in summer TP,four rain types are classified by using new thresholds, such as the maximum reflectivity factor, the difference between the maximum reflectivity factor and the background maximum reflectivity factor, and the echo top height. In the threshold of the maximum reflectivity factors, 30 d BZ and 18 d BZ are both thresholds to separate strong convective precipitation, weak convective precipitation and weak precipitation. The results illustrate obvious differences of radar reflectivity factor and vertical velocity among the three rain types in summer TP, such as the reflectivity factor of most strong convective precipitation distributes from 15 d BZ to near 35 d BZ from 4 km to 13 km, and increases almost linearly with the decrease in height. For most weak convective precipitation, the reflectivity factor distributes from 15 d BZ to 28 d BZ with the height from 4 km to 9 km. For weak precipitation, the reflectivity factor mainly distributes in range of 15–25 d BZ with height within 4–10 km. It is also shows that weak precipitation is the dominant rain type in summer TP, accounting for 40%–80%,followed by weak convective precipitation(25%–40%), and strong convective precipitation has the least proportion(less than 30%).

Effect of pre-deformation on precipitation behavior of AZ80 alloy:Comparison of slip-and twinning-dominant deformation

This study investigates the effect of the deformation mode on the precipitation behavior of an extruded Mg-8.0Al-0.5Zn-0.2Mn(AZ80)alloy.The alloy samples are compared after the application of 3.5%tension and 3.5%compression along the extrusion direction to induce slip-dominant and twinning-dominant deformation modes,respectively.The pre-compressed(PC)sample,which contained numerous{10-12}tension twins,has a reduced grain size and a higher internal strain than the pre-tensioned(PT)sample,which is attributed to the inherent internal strain that occurs during the formation and growth of the twins.As a result,the precipitation behavior of the PC sample is accelerated,leading to its short peak aging time of 32 h,which is lower than those of the PT and as-extruded samples(48 and 100 h,respectively).Furthermore,fine continuous precipitates(CPs)rapidly form within the{10-12}twins,contributing to the enhanced hardness.Discontinuous precipitates(DPs),which have a hardness comparable to the CP-containing twinned regions,in the PC sample experience less coarsening during aging than those in the PT sample due to growth inhibition by the{10-12}twins.Ultimately,the{10-12}twins generated under the twinning-dominant deformation condition lead to enhanced precipitation behaviors,including the preferential formation and refinement of CPs and the suppressed coarsening of DPs.Consequently,pre-deformation that occurs{10-12}twinning exhibits more pronounced effects on precipitation acceleration and microstructural modification than slip-inducing pre-deformation.

Cloud-Type-Dependent 1DVAR Algorithm for Retrieving Hydrometeors and Precipitation in Tropical Cyclone Nanmadol from GMI Data

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.

Synergistic Interdecadal Evolution of Precipitation over Eastern China and the Pacific Decadal Oscillation during 1951-2015

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.

Different ENSO Impacts on Eastern China Precipitation Patterns in Early and Late Winter Associated with Seasonally-Varying Kuroshio Anticyclonic Anomalies

Winter precipitation over eastern China displays remarkable interannual variability,which has been suggested to be closely related to El Niño-Southern Oscillation(ENSO).This study finds that ENSO impacts on eastern China precipitation patterns exhibit obvious differences in early(November-December)and late(January-February)winter.In early winter,precipitation anomalies associated with ENSO are characterized by a monopole spatial distribution over eastern China.In contrast,the precipitation anomaly pattern in late winter remarkably changes,manifesting as a dipole spatial distribution.The noteworthy change in precipitation responses from early to late winter can be largely attributed to the seasonally varying Kuroshio anticyclonic anomalies.During the early winter of El Niño years,anticyclonic circulation anomalies appear both over the Philippine Sea and Kuroshio region,enhancing water vapor transport to the entirety of eastern China,thus contributing to more precipitation there.During the late winter of El Niño years,the anticyclone over the Philippine Sea is further strengthened,while the one over the Kuroshio dissipates,which could result in differing water vapor transport between northern and southern parts of eastern China and thus a dipole precipitation distribution.Roughly the opposite anomalies of circulation and precipitation are displayed during La Niña winters.Further analysis suggests that the seasonally-varying Kuroshio anticyclonic anomalies are possibly related to the enhancement of ENSO-related tropical central-eastern Pacific convection from early to late winter.These results have important implications for the seasonal-tointerannual predictability of winter precipitation over eastern China.

Adaptation analysis and fusion correction method of CMIP6 precipitation simulation data on the Qinghai-Tibetan Plateau

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.

Strengthening effect of prefabrication(10-12)tensile twinning on AZ80+0.4%Ce magnesium alloy and inhibition mechanism of discontinuous precipitation

This paper provided an effective method to further improve the mechanical properties of the AZ80+0.4%Ce magnesium alloy wheel spoke.The effect of high strength and ductility was obtained with a yield strength of 295.36 MPa,an elongation of 10%,by the combination of pre-deformation(7%deformation)and two-stage aging treatment(120℃/9 h+175℃/24 h).The evolution of the microstructure and properties of the alloy was explored under the coupling conditions of different pre-deformation degrees and multi-stage aging.The results show that,pre-deformation introduced a large number of(1012)tensile twinning and dislocations,which greatly promoted the probability of continuous precipitates(CPs)appearing.On the contrary,the discontinuous precipitates(DPs)were limited by the vertical and horizontal twin structure.As a result,the pre-nucleation method of two-stage aging increased the proportion of CPs by 34%-38%.Owing to the DPs was effectively suppressed,the alloy's yield strength has been greatly improved.Besides,under multi-stage aging,the twin boundaries induce protruding nucleation to form static recrystallization by hindering the migration of dislocations,and the matrix swallows the twins,then the texture gradually tilts from the two poles to the basal plane.As an important supplement,the grain refinement and oblique texture promoted the improvement of the yield strength of the component.

Assessing the Applicability of Multi-Source Precipitation Products over the Chinese Mainland and Its Seven Regions

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.

Revealing precipitation behavior and mechanical response of wire-arc directed energy deposited Mg-Gd-Y-Zr alloy by tailoring aging procedures

Mg-Gd-Y-Zr alloy,as a typical magnesium rare-earth(Mg-RE)alloy,is gaining popularity in the advanced equipment manufacturing fields owing to its noticeable age-hardening properties and high specific strength.However,it is extremely challenging to prepare wrought components with large dimensions and complex shapes because of the poor room-temperature processability of Mg-Gd-Y-Zr alloy.Herein,we report a wire-arc directed energy deposited(DED)Mg-10.45Gd-2.27Y-0.52Zr(wt.%,GW102K)alloy with high RE content presenting a prominent combination of strength and ductility,realized by tailored nanoprecipitates through an optimized heat treatment procedure.Specifically,the solution-treated sample exhibits excellent ductility with an elongation(EL)of(14.6±0.1)%,while the aging-treated sample at 200°C for 58 h achieves an ultra-high ultimate tensile strength(UTS)of(371±1.5)MPa.Besides,the aging-treated sample at 250°C for 16 h attains a good strength-ductility synergy with a UTS of(316±2.1)MPa and a EL of(8.5±0.1)%.Particularly,the evolution mechanisms of precipitation response induced by various aging parameters and deformation behavior caused by nanoprecipitates type were also systematically revealed.The excellent ductility resulted from coordinating localized strains facilitated by active slip activity.And the ultra-high strength should be ascribed to the dense nano-β'hampering dislocation motion.Additionally,the shearable nano-β1 contributed to the good strength-ductility synergy.This work thus offers insightful understanding into the nanoprecipitates manipulation and performance tailoring for the wire-arc DED preparation of large-sized Mg-Gd-Y-Zr components with complex geometries.

Flow-Slip Stability Behavior of Calcareous Sand Treated by Microbially Induced Carbonate Precipitation Technology

Flow-slip damage commonly destabilizes coastal slopes.Finding a slope stabilization method for calcareous sands in the South China Sea is crucial.Microbially induced calcite precipitation is a promising,eco-friendly method for soil stabilization.This study investigates the effect of microbial treatments,initial relative density,initial cell pressure,and initial stress ratio on the flow-slip stability of calcareous sand specimens by using constant shear drained tests.These tests lay the foundation to study the mechanical instability of sand slopes.Results show that the microbial-treated specimens maintain stable stresses longer,take longer to reach the instability,and withstand larger volumetric strains.Microbial treatment effectively enhances sand stability under constant shear drainage,with improvements amplified by higher initial relative density and initial cell pressure.In addition,a smaller initial stress ratio reduces shear effects on the specimen and increases resistance to flow slides.Microanalysis reveals that the flow-slip stability of calcareous sand slopes is enhanced by contact cementation,particle coating,void filling,and mutual embedment of calcium carbonate crystals.

Comparison of a Spectral Bin and Two Multi-Moment Bulk Microphysics Schemes for Supercell Simulation:Investigation into Key Processes Responsible for Hydrometeor Distributions and Precipitation

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.

Improving the Short-Range Precipitation Forecast of Numerical Weather Prediction through a Deep Learning-Based Mask Approach

Due to various technical issues,existing numerical weather prediction(NWP)models often perform poorly at forecasting rainfall in the first several hours.To correct the bias of an NWP model and improve the accuracy of short-range precipitation forecasting,we propose a deep learning-based approach called UNet Mask,which combines NWP forecasts with the output of a convolutional neural network called UNet.The UNet Mask involves training the UNet on historical data from the NWP model and gridded rainfall observations for 6-hour precipitation forecasting.The overlap of the UNet output and the NWP forecasts at the same rainfall threshold yields a mask.The UNet Mask blends the UNet output and the NWP forecasts by taking the maximum between them and passing through the mask,which provides the corrected 6-hour rainfall forecasts.We evaluated UNet Mask on a test set and in real-time verification.The results showed that UNet Mask outperforms the NWP model in 6-hour precipitation prediction by reducing the FAR and improving CSI scores.Sensitivity tests also showed that different small rainfall thresholds applied to the UNet and the NWP model have different effects on UNet Mask's forecast performance.This study shows that UNet Mask is a promising approach for improving rainfall forecasting of NWP models.

Advances in Deep-Learning-based Precipitation Nowcasting Techniques

Precipitation nowcasting,as a crucial component of weather forecasting,focuses on predicting very short-range precipitation,typically within six hours.This approach relies heavily on real-time observations rather than numerical weather models.The core concept involves the spatio-temporal extrapolation of current precipitation fields derived from ground radar echoes and/or satellite images,which was generally actualized by employing computer image or vision techniques.Recently,with stirring breakthroughs in artificial intelligence(AI)techniques,deep learning(DL)methods have been used as the basis for developing novel approaches to precipitation nowcasting.Notable progress has been obtained in recent years,manifesting the strong potential of DL-based nowcasting models for their advantages in both prediction accuracy and computational cost.This paper provides an overview of these precipitation nowcasting approaches,from which two stages along the advancing in this field emerge.Classic models that were established on an elementary neural network dominated in the first stage,while large meteorological models that were based on complex network architectures prevailed in the second.In particular,the nowcasting accuracy of such data-driven models has been greatly increased by imposing suitable physical constraints.The integration of AI models and physical models seems to be a promising way to improve precipitation nowcasting techniques further.

Improved Diurnal Cycle of Precipitation on Land in a Global Non-Hydrostatic Model Using a Revised NSAS Deep Convective Scheme

In relatively coarse-resolution atmospheric models,cumulus parameterization helps account for the effect of subgridscale convection,which produces supplemental rainfall to the grid-scale precipitation and impacts the diurnal cycle of precipitation.In this study,the diurnal cycle of precipitation was studied using the new simplified Arakawa-Schubert scheme in a global non-hydrostatic atmospheric model,i.e.,the Yin-Yang-grid Unified Model for the Atmosphere.Two new diagnostic closures and a convective trigger function were suggested to emphasize the job of the cloud work function corresponding to the free tropospheric large-scale forcing.Numerical results of the 0.25-degree model in 3-month batched real-case simulations revealed an improvement in the diurnal precipitation variation by using a revised trigger function with an enhanced dynamical constraint on the convective initiation and a suitable threshold of the trigger.By reducing the occurrence of convection during peak solar radiation hours,the revised scheme was shown to be effective in delaying the appearance of early-afternoon rainfall peaks over most land areas and accentuating the nocturnal peaks that were wrongly concealed by the more substantial afternoon peak.In addition,the revised scheme enhanced the simulation capability of the precipitation probability density function,such as increasing the extremely low-and high-intensity precipitation events and decreasing small and moderate rainfall events,which contributed to the reduction of precipitation bias over mid-latitude and tropical land areas.

Spatial Variation and Trend of Extreme Precipitation in Africa during 1981-2019 and Its Projected Changes at the End of 21st Century

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 21st 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 21st 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.