Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks:Climatology,Interannual Variability,and Extremes

Climate models are vital for understanding and projecting global climate change and its associated impacts.However,these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future projections.Addressing these challenges requires addressing internal variability,hindering the direct alignment between model simulations and observations,and thwarting conventional supervised learning methods.Here,we employ an unsupervised Cycle-consistent Generative Adversarial Network(CycleGAN),to correct daily Sea Surface Temperature(SST)simulations from the Community Earth System Model 2(CESM2).Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole mode,as well as SST extremes.Notably,it substantially corrects climatological SST biases,decreasing the globally averaged Root-Mean-Square Error(RMSE)by 58%.Intriguingly,the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies,a common issue in climate models that traditional methods,like quantile mapping,struggle to rectify.Additionally,it substantially improves the simulation of SST extremes,raising the pattern correlation coefficient(PCC)from 0.56 to 0.88 and lowering the RMSE from 0.5 to 0.32.This enhancement is attributed to better representations of interannual,intraseasonal,and synoptic scales variabilities.Our study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.

Assessment of the Southern Ocean Sea Surface Temperature Biases in CMIP5 and CMIP6 Models

This work evaluates the performances of climate models in simulating the Southern Ocean(SO)sea surface temperature(SST)by a large ensemble from phases 5 and 6 of the Coupled Model Intercomparison Project(CMIP5 and CMIP6).By combining models from the same community sharing highly similar SO SST biases and eliminating the effect of global-mean biases on local SST biases,the results reveal that the ensemble-mean SO SST bias at 70°-30°S decreases from 0.38℃ in CMIP5 to 0.28℃ in CMIP6,together with increased intermodel consistency.The dominant mode of the intermodel variations in the zonal-mean SST biases is characterized as a meridional uniform warm bias pattern,explaining 79.1% of the intermodel variance and exhibiting positive principal values for most models.The ocean mixed layer heat budget further demonstrates that the SST biases at 70°-50°S primarily result from the excessive summertime heating effect from surface net heat flux.The biases in surface net heat flux south of 50°S are largely impacted by surface shortwave radiation from cloud and clear sky components at different latitudes.North of 50°S,the underestimated westerlies reduce the northward Ekman transport and hence northward cold advection in models,leading to warm SST biases year-round.In addition,the westerly biases are primarily traced back to the atmosphere-alone model simulations forced by the observed SST and sea ice.These results disclose the thermal origin at the high latitude and dynamical origin at the low latitude of the SO SST biases and underscore the significance of the deficiencies of atmospheric models in producing the SO SST biases.

Publication behaviour and(dis)qualification of chief editors in Turkish national Social Sciences journals

Purpose:This study investigated the publication behaviour of 573 chief editors managing 432 Social Sciences journals in Turkey.Direct inquiries into editorial qualifications are rare,and this research aims to shed light on editors’scientific leadership capabilities.Design/methodology/approach:This study contrasts insider publication behaviour in national journals with international articles in journals indexed by the Web of Science(WOS)and Scopus.It argues that editors demonstrating a consistent ability to publish in competitive WOS and Scopus indexed journals signal high qualifications,while editors with persistent insider behaviour and strong local orientation signal low qualification.Scientific leadership capability is measured by first-authored publications.Correlation and various regression tests are conducted to identify significant determinants of publication behaviour.Findings:International publications are rare and concentrated on a few individuals,while insider publications are endemic and constitute nearly 40%of all national articles.Editors publish 3.2 insider papers and 8.1 national papers for every SSCI article.62%(58%)of the editors have no SSCI(Scopus)article,53%(63%)do not have a single lead-authored WOS(Scopus)article,and 89%publish at least one insider paper.Only a minority consistently publish in international journals;a fifth of the editors have three or more SSCI publications,and a quarter have three or more Scopus articles.Editors with foreign Ph.D.degrees are the most qualified and internationally oriented,whereas non-mobile editors are the most underqualified and underperform other editors by every measure.Illustrating the overall lack of qualification,nearly half of the professor editors and the majority of the WOS and Scopus indexed journal editors have no record of SSCI or Scopus publications.Research limitations:This research relies on local settings that encourage national publications at the expense of international journals.Findings should be evaluated in light of this setting and bearing in mind that narrow localities are more prone to peer favouritism.Practical implications:Incompetent and nepotistic editors pose an imminent threat to Turkish national literature.A lasting solution would likely include the dismissal and replacement of unqualified editors,as well as delisting and closure of dozens of journals that operate in questionable ways and serve little scientific purpose.Originality/value:To my knowledge,this is the first study to document the publication behaviour of national journal chief editors.

Optimal Assimilation of Microwave Upper-Level Sounding Data in CMA-GFS

Various approaches have been proposed to minimize the upper-level systematic biases in global numerical weather prediction(NWP)models by using satellite upper-air sounding channels as anchors.However,since the China Meteorological Administration Global Forecast System(CMA-GFS)has a model top near 0.1 hPa(60 km),the upper-level temperature bias may exceed 4 K near 1 hPa and further extend to 5 hPa.In this study,channels 12–14 of the Advanced Microwave Sounding Unit A(AMSU-A)onboard five satellites of NOAA and METOP,whose weighting function peaks range from 10 to 2 hPa are all used as anchor observations in CMA-GFS.It is shown that the new“Anchor”approach can effectively reduce the biases near the model top and their downward propagation in three-month assimilation cycles.The bias growth rate of simulated upper-level channel observations is reduced to±0.001 K d^(–1),compared to–0.03 K d^(–1)derived from the current dynamic correction scheme.The relatively stable bias significantly improves the upper-level analysis field and leads to better global medium-range forecasts up to 10 days with significant reductions in the temperature and geopotential forecast error above 10 hPa.

AI Fairness-From Machine Learning to Federated Learning

This article reviews the theory of fairness in AI-frommachine learning to federated learning,where the constraints on precision AI fairness and perspective solutions are also discussed.For a reliable and quantitative evaluation of AI fairness,many associated concepts have been proposed,formulated and classified.However,the inexplicability of machine learning systems makes it almost impossible to include all necessary details in the modelling stage to ensure fairness.The privacy worries induce the data unfairness and hence,the biases in the datasets for evaluating AI fairness are unavoidable.The imbalance between algorithms’utility and humanization has further reinforced suchworries.Even for federated learning systems,these constraints on precision AI fairness still exist.Aperspective solution is to reconcile the federated learning processes and reduce biases and imbalances accordingly.

Performance analysis of the tight combination of GPS, BDS, GALILEO, and QzsS mixed frequencies signals

With the gradual development and modernization of satellite navigation systems,using observation information from multi-GNss has become one of the hot-spot issues in recent years.Multi-system loose combinations form double-difference observation equations within their respective systems,and the positioning effect is improved.However,the interchangeability and compatible interoperability between global navigation satellite systems(GNSS)cannot be truly realized.At the same time,when the number of visible satellites decreases abruptly,the positioning performance deteriorates sharply.This paper focuses on the GNsS multi-system tight combination relative positioning technique,gives a mathe-matical model of multi-system tight combination relative positioning considering differential inter-system bias(DISB),and analyzes the time-varying characteristics of DISB at overlapping and non-overlapping frequencies among GPS/Galileo,GPS/BDS,and GPS/QZSS in terms of receiver brand,tem-perature,and receiver restart.The GNsS tight combination relative positioning performance is verified by static data from Curtin University and dynamic data measured at Taiyuan University of Technology.The results show that compared with loose combination,the ambiguity-fixed rate increases from 62.18%to 97.60%for static data and from 74.97%to 99.53%for dynamic data when the elevation mask angle is 50°,resulting in a significant improvement in positioning performance.

Vibration and noise mechanism of a 110 kV transformer under DC bias based on finite element method

Global energy and environmental issues are becoming increasingly problematic,and the vibration and noise problem of 110 kV transformers,which are the most widely distributed,have attracted widespread attention from both inside and outside the industry.DC bias is one of the main contributing factors to vibration noise during the normal operation of transformers.To clarify the vibration and noise mechanism of a 110 kV transformer under a DC bias,a multi-field coupling model of a 110 kV transformer was established using the finite element method.The electromagnetic,vibration,and noise characteristics during the DC bias process were compared and quantified through field circuit coupling in parallel with the power frequency of AC,harmonic,and DC power sources.It was found that a DC bias can cause significant distortions in the magnetic flux density,force,and displacement distributions of the core and winding.The contributions of the DC bias effect to the core and winding are different at Kdc=0.85.At this point,the core approached saturation,and the increase in the core force and displacement slowed.However,the saturation of the core increased the leakage flux,and the stress and displacement of the winding increased faster.The sound field distribution characteristics of the 110 kV transformer under a DC bias are related to the force characteristics.When the DC bias coefficient was 1.25,the noise sound pressure level reached 73.6 dB.

Assessing the Performance of a Dynamical Downscaling Simulation Driven by a Bias-Corrected CMIP6 Dataset for Asian Climate

In this study,we aim to assess dynamical downscaling simulations by utilizing a novel bias-corrected global climate model(GCM)data to drive a regional climate model(RCM)over the Asia-western North Pacific region.Three simulations were conducted with a 25-km grid spacing for the period 1980–2014.The first simulation(WRF_ERA5)was driven by the European Centre for Medium-Range Weather Forecasts Reanalysis 5(ERA5)dataset and served as the validation dataset.The original GCM dataset(MPI-ESM1-2-HR model)was used to drive the second simulation(WRF_GCM),while the third simulation(WRF_GCMbc)was driven by the bias-corrected GCM dataset.The bias-corrected GCM data has an ERA5-based mean and interannual variance and long-term trends derived from the ensemble mean of 18 CMIP6 models.Results demonstrate that the WRF_GCMbc significantly reduced the root-mean-square errors(RMSEs)of the climatological mean of downscaled variables,including temperature,precipitation,snow,wind,relative humidity,and planetary boundary layer height by 50%–90%compared to the WRF_GCM.Similarly,the RMSEs of interannual-tointerdecadal variances of downscaled variables were reduced by 30%–60%.Furthermore,the WRF_GCMbc better captured the annual cycle of the monsoon circulation and intraseasonal and day-to-day variabilities.The leading empirical orthogonal function(EOF)shows a monopole precipitation mode in the WRF_GCM.In contrast,the WRF_GCMbc successfully reproduced the observed tri-pole mode of summer precipitation over eastern China.This improvement could be attributed to a better-simulated location of the western North Pacific subtropical high in the WRF_GCMbc after GCM bias correction.

Stable photocurrent-voltage characteristics of perovskite single crystal detectors obtained by pulsed bias

Photocurrent-voltage characterization is a crucial method for assessing key parameters in x-ray or y-ray semiconductor detectors,especially the carrier mobility lifetime product.However,the high biases during photocurrent measurements tend to cause severe ion migration,which can lead to the instability and inaccuracy of the test results.Given the mixed electronic-ionic charac teristics,it is imperative to devise novel methods capable of precisely measuring photocurrentvoltage characteristics under high bias conditions,free from interference caused by ion migration.In this paper,pulsed bias is employed to explore the photocurrent-voltage characteristics of MAPbBr_(3) single crystals.The method yields stable photocurrent-voltage characteristics at a pulsed bias of up to 30 V,proving to be effective in mitigating ion migration.Through fitting the modified Hecht equation,we determined the mobility lifetime products of 1.0×10^(2) cm^(2)·V^(-1)for hole and 2.78×10~(-3)cm^(2)·V^(-1)for electron.This approach offers a promising solution for accurately measuring the transport properties of carriers in perovskite.

Influence of exchange bias on spin torque ferromagnetic resonance for quantification of spin–orbit torque efficiency

Antiferromagnet(AFM)/ferromagnet(FM)heterostructure is a popular system for studying the spin–orbit torque(SOT)of AFMs.However,the interfacial exchange bias field induces that the magnetization in FM layer is noncollinear to the external magnetic field,namely the magnetic moment drag effect,which further influences the characteristic of SOT efficiency.In this work,we study the SOT efficiencies of IrMn/NiFe bilayers with strong interfacial exchange bias by using spin-torque ferromagnetic resonance(ST-FMR)method.A full analysis on the AFM/FM systems with exchange bias is performed,and the angular dependence of magnetization on external magnetic field is determined through the minimum rule of free energy.The ST-FMR results can be well fitted by this model.We obtained the relative accurate SOT efficiencyξ_(DL)=0.058 for the IrMn film.This work provides a useful method to analyze the angular dependence of ST-FMR results and facilitates the accurate measurement of SOT efficiency for the AFM/FM heterostructures with strong exchange bias.

Differential colour-ring loss among Dalmatian Pelican(Pelecanus crispus) colonies and its consequence on survival estimates

The analysis of bird ringing data often comes with some potential sources of error and bias,as ring wear and/or loss could affect mark-recapture analyses and produce erroneous estimates of survival.Furthermore,ring wear and loss rates may differ between and within species based on the habitat they use or the species’ life-history traits and behaviour as well as the type of the ring.In this study we use resighting data from a long-term double marking experiment to directly estimate the rate of colour-ring loss among different Dalmatian Pelican colonies over time,evaluate any possible factors that could contribute to differential ring loss and assess how it may bias the results of mark-resighting analyses.Based on 14,849 resightings from 1275 individuals and using multi-state continuous-time hidden Markov models(HMMs) we showed that probability of ring loss was markedly different among colonies,ranging from 0.10 to 0.42 within the first year of marking,whereas the cumulative probability of losing a ring after ten years ranged 0.64 to 0.99.These rates are among the highest estimated when compared to previous studies in waterbirds.Our approach assessing the intra-specific variance in ring loss provided several factors potentially involved,such as the use of glue and the fledgling age accuracy and we could further hypothesise the effect of environmental factors.Finally,our results showed that ring loss can be a significant challenge for the assessment of the species’ population dynamics using mark-recapture methods as survival was consistently underestimated when not accounting for ring loss and varied significantly among different colonies.

Epidemiological Surveillance: Genetic Diversity of Rotavirus Group A in the Pearl River Delta, Guangdong, China in 2019

Objective This study aimed to understand the epidemic status and phylogenetic relationships of rotavirus group A(RVA)in the Pearl River Delta region of Guangdong Province,China.Methods This study included individuals aged 28 days–85 years.A total of 706 stool samples from patients with acute gastroenteritis collected between January 2019 and January 2020 were analyzed for 17 causative pathogens,including RVA,using a Gastrointestinal Pathogen Panel,followed by genotyping,virus isolation,and complete sequencing to assess the genetic diversity of RVA.Results The overall RVA infection rate was 14.59%(103/706),with an irregular epidemiological pattern.The proportion of co-infection with RVA and other pathogens was 39.81%(41/103).Acute gastroenteritis is highly prevalent in young children aged 0–1 year,and RVA is the key pathogen circulating in patients 6–10 months of age with diarrhea.G9P[8](58.25%,60/103)was found to be the predominant genotype in the RVA strains,and the 41 RVA-positive strains that were successfully sequenced belonged to three different RVA genotypes in the phylogenetic analysis.Recombination analysis showed that gene reassortment events,selection pressure,codon usage bias,gene polymorphism,and post-translational modifications(PTMs)occurred in the G9P[8]and G3P[8]strains.Conclusion This study provides molecular evidence of RVA prevalence in the Pearl River Delta region of China,further enriching the existing information on its genetics and evolutionary characteristics and suggesting the emergence of genetic diversity.Strengthening the surveillance of genotypic changes and gene reassortment in RVA strains is essential for further research and a better understanding of strain variations for further vaccine development.

A Path Planning Algorithm Based on Improved RRT Sampling Region

For the problem of slow search and tortuous paths in the Rapidly Exploring Random Tree(RRT)algorithm,a feedback-biased sampling RRT,called FS-RRT,is proposedbasedon RRT.Firstly,toimprove the samplingefficiency of RRT to shorten the search time,the search area of the randomtree is restricted to improve the sampling efficiency.Secondly,to obtain better information about obstacles to shorten the path length,a feedback-biased sampling strategy is used instead of the traditional random sampling,the collision of the expanding node with an obstacle generates feedback information so that the next expanding node avoids expanding within a specific angle range.Thirdly,this paper proposes using the inverse optimization strategy to remove redundancy points from the initial path,making the path shorter and more accurate.Finally,to satisfy the smooth operation of the robot in practice,auxiliary points are used to optimize the cubic Bezier curve to avoid path-crossing obstacles when using the Bezier curve optimization.The experimental results demonstrate that,compared to the traditional RRT algorithm,the proposed FS-RRT algorithm performs favorably against mainstream algorithms regarding running time,number of search iterations,and path length.Moreover,the improved algorithm also performs well in a narrow obstacle environment,and its effectiveness is further confirmed by experimental verification.

Why ecosystem characteristics predicted from remotely sensed data are unbiased and biased at the same time-and how this affects applications

Remotely sensed data are frequently used for predicting and mapping ecosystem characteristics,and spatially explicit wall-to-wall information is sometimes proposed as the best possible source of information for decisionmaking.However,wall-to-wall information typically relies on model-based prediction,and several features of model-based prediction should be understood before extensively relying on this type of information.One such feature is that model-based predictors can be considered both unbiased and biased at the same time,which has important implications in several areas of application.In this discussion paper,we first describe the conventional model-unbiasedness paradigm that underpins most prediction techniques using remotely sensed(or other)auxiliary data.From this point of view,model-based predictors are typically unbiased.Secondly,we show that for specific domains,identified based on their true values,the same model-based predictors can be considered biased,and sometimes severely so.We suggest distinguishing between conventional model-bias,defined in the statistical literature as the difference between the expected value of a predictor and the expected value of the quantity being predicted,and design-bias of model-based estimators,defined as the difference between the expected value of a model-based estimator and the true value of the quantity being predicted.We show that model-based estimators(or predictors)are typically design-biased,and that there is a trend in the design-bias from overestimating small true values to underestimating large true values.Further,we give examples of applications where this is important to acknowledge and to potentially make adjustments to correct for the design-bias trend.We argue that relying entirely on conventional model-unbiasedness may lead to mistakes in several areas of application that use predictions from remotely sensed data.

A News Media Bias and Factuality Profiling Framework Assisted by Modeling Correlation

News media profiling is helpful in preventing the spread of fake news at the source and maintaining a good media and news ecosystem.Most previous works only extract features and evaluate media from one dimension independently,ignoring the interconnections between different aspects.This paper proposes a novel news media bias and factuality profiling framework assisted by correlated features.This framework models the relationship and interaction between media bias and factuality,utilizing this relationship to assist in the prediction of profiling results.Our approach extracts features independently while aligning and fusing them through recursive convolu-tion and attention mechanisms,thus harnessing multi-scale interactive information across different dimensions and levels.This method improves the effectiveness of news media evaluation.Experimental results indicate that our proposed framework significantly outperforms existing methods,achieving the best performance in Accuracy and F1 score,improving by at least 1%compared to other methods.This paper further analyzes and discusses based on the experimental results.

Flower development and sexual dimorphism in Vernicia montana

The mu oil tree(Vernicia montana Lour.) is a dioecious species, but the genetic mechanisms underlying its phenotypic sexual dimorphism are unclear. In this study, we determined two pivotal phases of sex differentiation of mu oil tree via morphological and histological analyses of unisexual flowers:(Ⅰ) differentiation of male or female primordia to produce staminate flowers(SFs) or transient hermaphrodite flowers(HFs),and(Ⅱ) complete abortion of stamens in transient HFs to generate pistillate flowers(PFs). A total of 1621 sex-biased genes were identified by comparative transcriptome analysis which exhibited elevated rates of protein evolution than unbiased genes. The female-biased genes were enriched in the production of defense compounds while male-biased genes were focused on the production of viable pollens. Transcriptomebased analysis revealed that the differentially expressed genes(DEGs) between PFs and SFs in phase Ⅰ involved in abscisic acid(ABA), auxin(AUX), cytokinin(CK), ethylene(ET), and gibberellin(GA) biosynthesis and signaling showed higher expression levels in males than in females in general, whereas the DEGs involved in jasmonic acid(JA) and salicylic acid(SA) pathways displayed opposite expression patterns. Moreover,differentially expressed endogenous ABA, AUX, GAs, JA, and SA exhibited consistent biased expression patterns with the DEGs by UPLC-MSbased analysis. Exogenous application of an anti-ethylene plant growth regulator could promote the development of stamens in PFs and generated HFs. Comparative transcriptomic and hormonal analyses of PFs and SFs in phase Ⅱ indicated an increase in ET concentration when abortion of stamens in PFs occurred. This study suggested that phytohormones play key roles in sex dimorphism and ET may determine the development of stamens in PFs of mu oil tree, which provides an insight into plant sex differentiation mechanisms.

Extremely thin but very robust:Surprising cryptogam trait combinations at the end of the leaf economics spectrum

Leaf economics spectrum(LES)describes the fundamental trade-offs between leaf structural,chemical,and physiological investments.Generally,structurally robust thick leaves with high leaf dry mass per unit area(LMA)exhibit lower photosynthetic capacity per dry mass(Amass).Paradoxically,“soft and thinleaved”mosses and spikemosses have very low Amass,but due to minute-size foliage elements,their LMA and its components,leaf thickness(LT)and density(LD),have not been systematically estimated.Here,we characterized LES and associated traits in cryptogams in unprecedented details,covering five evolutionarily different lineages.We found that mosses and spikemosses had the lowest LMA and LT values ever measured for terrestrial plants.Across a broad range of species from different lineages,Amass and LD were negatively correlated.In contrast,Amass was only related to LMA when LMA was greater than 14 g cm^(-2).In fact,low Amass reflected high LD and cell wall thickness in the studied cryptogams.We conclude that evolutionarily old plant lineages attained poorly differentiated,ultrathin mesophyll by increasing LD.Across plant lineages,LD,not LMA,is the trait that represents the trade-off between leaf robustness and physiology in the LES.

Vector magnetometry in zero bias magnetic field using nitrogen-vacancy ensembles

The application of the vector magnetometry based on nitrogen-vacancy(NV)ensembles has been widely investigatedin multiple areas.It has the superiority of high sensitivity and high stability in ambient conditions with microscale spatialresolution.However,a bias magnetic field is necessary to fully separate the resonance lines of optically detected magneticresonance(ODMR)spectrum of NV ensembles.This brings disturbances in samples being detected and limits the rangeof application.Here,we demonstrate a method of vector magnetometry in zero bias magnetic field using NV ensembles.By utilizing the anisotropy property of fluorescence excited from NV centers,we analyzed the ODMR spectrum of NVensembles under various polarized angles of excitation laser in zero bias magnetic field with a quantitative numerical modeland reconstructed the magnetic field vector.The minimum magnetic field modulus that can be resolved accurately is downto~0.64 G theoretically depending on the ODMR spectral line width(1.8 MHz),and~2 G experimentally due to noisesin fluorescence signals and errors in calibration.By using 13C purified and low nitrogen concentration diamond combinedwith improving calibration of unknown parameters,the ODMR spectral line width can be further decreased below 0.5 MHz,corresponding to~0.18 G minimum resolvable magnetic field modulus.

Inward particle transport driven by biased endplate in a cylindrical magnetized plasma

The inward particle transport is associated with the formation of peaked density profiles,which contributes to improve the fusion rate and the realization of steady-state discharge.The active control of inward particle transport is considered as one of the most critical issues of magnetic confinement fusion.Recently,it is realized preliminarily by adding a biased endplate in the Peking University Plasma Test(PPT)device.The results reveal that the inward particle flux increases with the bias voltage of the endplate.It is also found that the profile of radial electric field(Er)shear is flattened by the increased bias voltage.Radial velocity fluctuations affect the inward particle more than density fluctuations,and the frequency of the dominant mode driving inward particle flux increases with the biased voltage applied to the endplate.The experimental results in the PPT device provide a method to actively control the inward particle flux using a biased endplate and enrich the understanding of the relationship between E_(r)×B shear and turbulence transport.

Review on high-performance polymeric bipolar membrane design and novel electrochemical applications

Electrochemical devices allow the conversion and storage of renewable energy into high-value chemicals to mitigate carbon emissions,such as hydrogen production by water electrolysis,carbon dioxide reduction,and the electrochemical synthesis of ammonia.Independent regulation of the electrode pH environment is essential for optimizing the electrode reaction kinetics and enriching the catalyst species.The in situ water dissociation(WD,H2O→H++OH-)in bipolar membranes(BPMs)offers the possibility of realizing this pH adjustment.Here,the design principles of high-performance polymeric BPMs in electrochemical device applications are presented by analyzing and connecting WD principles and current–voltage curves.The structure–transport property relationships and membrane durability,including the chemical and mechanical stability of the anion-and cation-exchange layers as well as the integrality of the interfacial junction,are systematically discussed.The advantages of BPMs in new electrochemical devices and major challenges to break through are also highlighted.The improved ion and water transport in the membrane layer and the minimized WD overpotential and ohmic loss at high current densi-ties are expected to facilitate the promotion of BPMs from conventional chemical production to novel electrochemical applications.