Spatial-Temporal Changes of Soil Organic Carbon During Vegetation Recovery at Ziwuling, China

To probe the processes and mechanisms of soil organic carbon (SOC) changes during forest recovery, a 150-yearchronosequence study on SOC was conducted for various vegetation succession stages at the Ziwuling area, in the centralpart of the Loess Plateau, China. Results showed that during the 150 years of local vegetation rehabilitation SOC increasedsignificantly (P < 0.05) over time in the initial period of 55-59 years, but slightly decreased afterwards. Average SOCdensities for the 0-100 cm layer of farmland, grassland, shrubland and forest were 4.46, 5.05, 9.95, and 7.49 kg C m-3,respectively. The decrease in SOC from 60 to 150 years of abandonment implied that the soil carbon pool was a sink forCO2 before the shrubland stage and became a source in the later period. This change resulted from the spatially variedcomposition and structure of the vegetation. Vegetation recovery had a maximum effect on the surface (0-20 cm) SOCpool. It. was concluded that vegetation recovery on the Loess Plateau could result in significantly increased sequestrationof atmospheric CO2 in soil and vegetation, which was ecologically important for mitigating the increase of atmosphericconcentration of CO2 and for ameliorating the local eco-environment.

Spatial-temporal changes of tidal flats in the Huanghe River Delta using Landsat TM/ETM+ images

Integrating remote sensing, geographic information system (GIS) and fractal theory, change characteristics of tidal flats and tidal creeks in the Huanghe (Yellow) River Delta over the period of 1986-2001 were discussed. The results show that evolutions of tidal flats throughout the Huanghe River Delta are influenced by various factors, and that progressive succession and regression of tidal flats concur in different coastal segments of the delta. Human activities have played an increasingly important role in the succession process of tidal flats. Due to land reclamation in coastal zones of the delta in the last 15 years, lots of tidal flats were occupied, the artificial coastline migrated seaward (the maximum change rate was 0.8 kmyr-1) and tidal creeks became sparser (the highest decreasing rate of length of tidal creeks was 14.9 kmyr-1). Except for two coastal segments from the Tiaohe Estuary to the 106 Station and from the south of the Huanghe River mouth to the north of the Xiaodao River Estuary, fractal dimension values of tidal creeks in the remaining coastal segments of the delta decreased. In addition, the time dimension, sediment fluxes into the sea, waves and tidal-currents have profound influences on the evolution process of tidal flats. Four types of tidal flats-river-dominated tidal flats, tide-dominated tidal flats, wave-dominated tidal flats and man-dominated tidal flats can be identified. Owing to the intensification of human activities in coastal zones of the delta, man-dominated tidal flats have become the main kind of tidal flats.

Spatial-temporal Changes of Vegetation Cover in Guizhou Province, Southern China

Guizhou Province is an important karst area in the world and a fragile ecological area in China. Ecological risk assessment is very necessary to be conducted in this region. This study investigates different characteristics of the spatial-temporal changes of vegetation cover in Guizhou Province of Southern China using the data set of SPOT VEGETATION(1999–2015) at spatial resolution of 1-km and temporal resolution of 10-day. The coefficient of variation, the Theil-Sen median trend analysis, and the Mann-Kendall test are used to investigate the spatial-temporal change of vegetation cover and its future trend. Results show that: 1) the spatial distribution pattern of vegetation cover in Guizhou Plateau is high in the east whereas low in the west. The average annual normalized difference vegetation index(NDVI) from west to east is higher than that from south to north. 2) Average annual NDVI improved obviously in the past 17 years. The growth rate of average annual NDVI is 0.028/10 yr, which is slower than that of vegetation in the country(0.048/10 yr) from 1998 to 2007. Average annual NDVI in karst area is lower than that in non-karst area. However, the growing rate of average annual NDVI in karst area(0.030/10 yr) is faster than that in non-karst area(0.023/10 yr), indicating that vegetation coverage increases more rapidly in karst area. 3) Vegetation coverage in the study area is stable overall, but fluctuates in the local scales. 4) Vegetation coverage presents a continuous increasing trend. The Hurst exponent of NDVI in different vegetation types has an obvious threshold in various elevations. 5) The proportion of vegetation cover with sustainable increase is higher than that of vegetation cover with sustainable decrease. The improvement in vegetation cover may expand to most parts of the study area.

The spatial-temporal changes of the land use/cover in the Dongting Lake area during the last decade

The research on the land use/cover change is one of the frontiers and the hot spots in the global change research. Based on the Chinese resource and environment spatial-temporal database, and using the Landsat TM and ETM data of 1990 and 2000 respectively, we analyzed the spatial-temporal characteristics of land use/cover changes in the Dongting Lake area during the last decade. The result shows that during the last ten years there were three land-use types that had changed remarkably. The cultivated land decreased by 0.57% of the total cultivated land. The built-up land and water area expanded, with an increase of 8.97% and 0.43% respectively. The conversion between land use types mostly happened among these three land-use types, especially frequently between cultivated land and water area. The land-use change speed of land-use type is different. Three cities experienced the greatest degree of land-use change among all the administrative districts, which means that the land use in these cities changed much quickly. The following changed area was the west and south of the Dongting Lake area. The slowest changed area is the north and east area.

Spatial-temporal Changes in Ecological Risk of Land Use before and after Grain-for-Green Policy in Zhengning County, Gansu Province

The Grain-for-Green Policy aims to convert cropland to grassland and forest across western China, and evaluating ecological risk is essential to its implementation. Because few recent studies have focused on eco-risk changes of land use in the areas affected by significant policies, this paper took Zhengning County in Gansu Province as our focal area, and studied spatial-temporal changes in ecological risk before and after policy implementation. Based on indices of landscape fragmentation and ecosystem service value, an ecological risk assessment method using ArcGIS and Fragstats was done. The regional gravity center model and land spatial distribution model were also used to enrich the quantitative description of divisional eco-risk and its spatial-temporal variation in the county. Results showed that the implementation of the policy has contributed to an overall reduction in ecological risk in Zhengning County, with a divisional degree order reduction following the pattern： eastern Zhengning 〉 western Zhengning 〉 central Zhengning. The gravity center for eco-risk shifted 4288 m southwest from 1995 to 2010 due to landscape fragmentation. The study implies that greater attention should be paid to forest and grassland restoration in eastern Zhengning, cropland protection in central Zhengning, and soil and water conservation in western Zhengning.

Spatial-temporal Pattern and Differences of Land Use Changes in the Three Gorges Reservoir Area of China during 1975-2005

Regional land use changes are an important part of global changes.The research on land use changes in the Three Gorges Reservoir Area of China attracts a lot of attention owing to the Three Gorges Dam building.The Three Gorges Reservoir Area becomes one of the important research areas.This study analyzed the transforming processes and traits of each land use type and the regional differences of land use changes during the past 30 years,summarized the distribution of different land use types in different buffer zones and regresses the equation areas and different buffer distances based on buffer analyses and regression analyses,and then analyzed the transforming rules in different buffer distances,got the optimal influence distances.The research results indicate that,(1) cultivated land lies at the northwest of the reservoir and was decreasing,however,the construction land was increasing,especially the urban construction land,a large number of land was flooded because of the reservoir water level rise;(2) urban area was sprawling quickly in developed and neighboring areas,and a great deal of cultivated land and a considerable amount of grassland were occupied;in the earlier time,rural settlements occupied lots of cultivated land and a sum of forestry land in the later time;(3) the optimum influenced distances for cultivated land and forestry land were 10-35 km,and for urban and rural settlements were in 5-20 km.Overall,this research can reflect the spatial-temporal characteristics of land use changes during the 30 years,and it is helpful for urban planning and land use planning in the reservoir area.

Spatial-Temporal Changes of Housing Bubbles in China＇s Major Cities： 1999 to 2012

Existing literature is characterized by certain deficiencies in measuring housing bubbles in China. By extending the analytical framework of Black et al. （2006） to a spatial panel VAR structure, this paper measures housing bubbles in China＇s 35 major cities from 1999Q2 to 2012Q3 and analyzes the spatial-temporal changes of the housing bubbles in these cities. Results indicate that 1） changes to housing bubbles in most cities highly correspond with changes in the main real estate policies of the country and 2） housing bubbles in eastern developed cities such as Beijing, Shanghai, Shenzhen, Hangzhou, and Ningbo, have been relatively large in recent years although the average housing bubble is not very serious over the 35 major cities. Through the Kernel Density Function and local indicators of spatial autocorrelation analysis, this paper finds that housing bubbles are concentrated in several eastern developed cities. Based on empirical analysis, this paper proposes policy recommendations on inhibiting the expansion and diffusion of housing bubbles.

Analysis of Spatial-Temporal Changes in the Landscape Structure of Yushu Prefecture in Qinghai Province

Yushu Tibetan Autonomous Prefecture, an area located in the Qinghai-Tibet Plateau, is an area very sensitive to global climate change. Due to impacts from climate change and human disturbances, grassland vegetation in the area has been degraded and desertification has been expanding. Ecosystems in the area are very sensitive and fragile and ecological problems have become increasingly serious in the area, resulting in an adverse effect on the local socio-economic development and environment of Qinghai province. Using data gathered from Landsat TM/ETM images for 1987, 1997 and 2007, we analyzed landscape patterns across Yushu Prefecture. Spatial structure indices indicated that： （i） the area of grassland has significantly decreased in the form of degradation and conversion from grassland into bare land and farmland; （ii） grassy vegetation patches changed into fragmented and isolated patches; （iii） the main landscapes in Yushu Prefecture are grasslands, forests and rivers; （iv） patches of grass have reiatively high connectivity; and （v） landscape change is significantly correlated with human activities and climate change. This study provides a strong theoretical and technical basis for policy-making regarding environmental protection of and management in Yushu Prefecture of Qinghai Province.

Extraction and Dynamic Spatial-Temporal Changes of Grassland Deterioration Research Hot Regions in China

The authors use a web crawler to retrieve all periodical articles from CNKI between the 1950 s and 2016 and then parse the abstracts of 293368 articles about grassland deterioration by word segmentation, location matching and other methods. The authors also construct a research hot regions extraction model of grassland deterioration in China based on a comprehensive research hot regions index of toponyms and then analyze the spatial pattern and dynamic change in research hot regions of grassland deterioration in China. The research shows the following：（1） The spatial heterogeneity of grassland deterioration in China can be effectively described by a model of grassland deterioration based on the comprehensive research hot regions index.（2） The research hot regions of grassland deterioration are mainly distributed in most regions of Inner Mongolia, Xinjiang, Qinghai, Tibet, Gansu and other provinces. The northeastern region of Inner Mongolia（such as Hulunbeier） and the eastern region of Inner Mongolia（such as Xilin Gol, Chifeng and Wulanchabu） are significant hot regions in the study of grassland deterioration.（3） The number of high research hot regions increases from 81 in the 1950 s to 99 in the 2000s; the area increases from 1.038 million km2 to 1.146 million km2. The degree of hot for grassland deterioration research in 197 counties showed an upward trend. This paper also discusses the relationship between the region of research hot regions and the region of grassland deterioration and then indicates the differences between them in time matching, space matching and concept matching.

Projected changes in extreme snowfall events over the Tibetan Plateau based on a set of RCM simulations

Extreme snowfall events over the Tibetan Plateau(TP)cause considerable damage to local society and natural ecosystems.In this study,the authors investigate the projected changes in such events over the TP and its surrounding areas based on an ensemble of a set of 21st century climate change projections using a regional climate model,RegCM4.The model is driven by five CMIP5 global climate models at a grid spacing of 25 km,under the RCP4.5 and RCP8.5 pathways.Four modified ETCCDI extreme indices-namely,SNOWTOT,S1mm,S10mm,and Sx5day-are employed to characterize the extreme snowfall events.RegCM4 generally reproduces the spatial distribution of the indices over the region,although with a tendency of overestimation.For the projected changes,a general decrease in SNOWTOT is found over most of the TP,with greater magnitude and better cross-simulation agreement over the eastern part.All the simulations project an overall decrease in S1mm,ranging from a 25%decrease in the west and to a 50%decrease in the east of the TP.Both S10mm and Sx5day are projected to decrease over the eastern part and increase over the central and western parts of the TP.Notably,S10mm shows a marked increase(more than double)with high cross-simulation agreement over the central TP.Significant increases in all four indices are found over the Tarim and Qaidam basins,and northwestern China north of the TP.The projected changes show topographic dependence over the TP in the latitudinal direction,and tend to decrease/increase in low-/high-altitude areas.

Analysis of piezoelectric semiconductor fibers under gradient temperature changes

Piezoelectric semiconductors(PSs)possess both semiconducting properties and piezoelectric coupling effects,making them optimal building blocks for semiconductor devices.PS fiber-like structures have wide applications in multi-functional semiconductor devices.In this paper,a one-dimensional(1D)theoretical model is established to describe the piezotronic responses of a PS fiber under gradient temperature changes.The theoretical model aims to explain the mechanism behind the resistance change caused by such gradient temperature changes.Numerical results demonstrate that a gradient temperature change significantly affects the physical fields within the PS fiber,and can induce changes in its surface resistance.It provides important theoretical guidance on the development of piezotronic devices that are sensitive to temperature effects.

Spatiotemporal changes of gross primary productivity and its response to drought in the Mongolian Plateau under climate change

Gross primary productivity(GPP)of vegetation is an important constituent of the terrestrial carbon sinks and is significantly influenced by drought.Understanding the impact of droughts on different types of vegetation GPP provides insight into the spatiotemporal variation of terrestrial carbon sinks,aiding efforts to mitigate the detrimental effects of climate change.In this study,we utilized the precipitation and temperature data from the Climatic Research Unit,the standardized precipitation evapotranspiration index(SPEI),the standardized precipitation index(SPI),and the simulated vegetation GPP using the eddy covariance-light use efficiency(EC-LUE)model to analyze the spatiotemporal change of GPP and its response to different drought indices in the Mongolian Plateau during 1982-2018.The main findings indicated that vegetation GPP decreased in 50.53% of the plateau,mainly in its northern and northeastern parts,while it increased in the remaining 49.47%area.Specifically,meadow steppe(78.92%)and deciduous forest(79.46%)witnessed a significant decrease in vegetation GPP,while alpine steppe(75.08%),cropland(76.27%),and sandy vegetation(87.88%)recovered well.Warming aridification areas accounted for 71.39% of the affected areas,while 28.53% of the areas underwent severe aridification,mainly located in the south and central regions.Notably,the warming aridification areas of desert steppe(92.68%)and sandy vegetation(90.24%)were significant.Climate warming was found to amplify the sensitivity of coniferous forest,deciduous forest,meadow steppe,and alpine steppe GPP to drought.Additionally,the drought sensitivity of vegetation GPP in the Mongolian Plateau gradually decreased as altitude increased.The cumulative effect of drought on vegetation GPP persisted for 3.00-8.00 months.The findings of this study will improve the understanding of how drought influences vegetation in arid and semi-arid areas.

Multivariate Time Series Anomaly Detection Based on Spatial-Temporal Network and Transformer in Industrial Internet of Things

In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.Although many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these methods.Owing to the superior capability of Transformer in learning time series features.This paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved Transformer.Additionally,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are interdependent.However,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each other.This scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each module.This interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory results.We introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph structure.Experiments on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods.

Comprehensive evaluation and spatial-temporal evolution characteristics of urban resilience in Chengdu-Chongqing Economic Circle

To clarify the connotations and extensions of urban resilience,this study focuses on the Chengdu-Chongqing Economic Circle with 16 cities as research subjects.A comprehensive evaluation index system was constructed to measure the resilience of each city from 2003 to 2020.The spatial-temporal evolution characteristics were analyzed using Kernel density estimation,standard deviation ellipse,and spatial Markov chain analysis,and the spatial Tobit model was introduced to discover the influencing factors.The results indicate the following:①Urban resilience in the Chengdu-Chongqing Economic Circle displays an upward trend,with the center of gravity moving to the southwest,and the polarization phenomenon intensifying.②The urban resilience level in a region has certain spatial and geographical dependence,while the probability of urban resilience transfer differs in adjacent cities with different resilience levels.③Urban centrality,economic scale,openness level,and financial development promote urban resilience,whereas government scale significantly inhibits it.Finally,this paper proposes countermeasures and suggestions to improve the urban resilience of the Chengdu-Chongqing Economic Circle.

AFSTGCN:Prediction for multivariate time series using an adaptive fused spatial-temporal graph convolutional network

The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries and other fields.Furthermore,it is important to construct a digital twin system.However,existing methods do not take full advantage of the potential properties of variables,which results in poor predicted accuracy.In this paper,we propose the Adaptive Fused Spatial-Temporal Graph Convolutional Network(AFSTGCN).First,to address the problem of the unknown spatial-temporal structure,we construct the Adaptive Fused Spatial-Temporal Graph(AFSTG)layer.Specifically,we fuse the spatial-temporal graph based on the interrelationship of spatial graphs.Simultaneously,we construct the adaptive adjacency matrix of the spatial-temporal graph using node embedding methods.Subsequently,to overcome the insufficient extraction of disordered correlation features,we construct the Adaptive Fused Spatial-Temporal Graph Convolutional(AFSTGC)module.The module forces the reordering of disordered temporal,spatial and spatial-temporal dependencies into rule-like data.AFSTGCN dynamically and synchronously acquires potential temporal,spatial and spatial-temporal correlations,thereby fully extracting rich hierarchical feature information to enhance the predicted accuracy.Experiments on different types of MTS datasets demonstrate that the model achieves state-of-the-art single-step and multi-step performance compared with eight other deep learning models.

Climate Changes and Sustainability

Climate change is the phrase used to describe long-term changes in temperatures and weather patterns. Changes in the atmosphere and their interactions with diverse geologic, chemical, biological, and geographic variables are the main contributors to this cyclical adjustment of the Earth’s climate. Such changes may be induced purposefully, because of burning fossil fuels, clearing forests, and raising animals, or they may be natural, brought on by significant volcanic eruptions or variations in the sun’s activity. By significantly increasing the amount of greenhouse gases already in the atmosphere, this heightens the greenhouse effect and contributes to global warming. This work includes several additional theoretical and practical explanations of sustainable development. The theoretical work encompasses hundreds of researches that identify requirements for how development routes might satisfy sustainable development (SD) criteria using economic theory, complex systems approach, ecological science, and other techniques. The agreements made by the Parties in various nations across the world will consider a wide range of perspectives about what would be considered undesirable effects on the environment, the climate system, sustainability, economic growth, or food production.

The Global Energy and Water Exchanges(GEWEX)Project in Central Asia:The Case for a Regional Hydroclimate Project

Central Asia consists of the former Soviet Republics,Kazakhstan,Kyrgyz Republic,Tajikistan,Turkmenistan,and Uzbekistan.The region’s climate is continental,mostly semi-arid to arid.Agriculture is a significant part of the region’s economy.By its nature of intensive water use,agriculture is extremely vulnerable to climate change.Population growth and irrigation development have significantly increased the demand for water in the region.Major climate change issues include melting glaciers and a shrinking snowpack,which are the foundation of the region’s water resources,and a changing precipitation regime.Most glaciers are located in Kyrgyzstan and Tajikistan,leading to transboundary water resource issues.Summer already has extremely high temperatures.Analyses indicate that Central Asia has been warming and precipitation might be increasing.The warming is expected to increase,but its spatial and temporal distribution depends upon specific global scenarios.Projections of future precipitation show significant uncertainties in type,amount,and distribution.Regional Hydroclimate Projects(RHPs)are an approach to studying these issues.Initial steps to develop an RHP began in 2021 with a widely distributed online survey about these climate issues.It was followed up with an online workshop and then,in 2023,an in-person workshop,held in Tashkent,Uzbekistan.Priorities for the Global Energy and Water Exchanges(GEWEX)project for the region include both observations and modeling,as well as development of better and additional precipitation observations,all of which are topics for the next workshop.A well-designed RHP should lead to reductions in critical climate uncertainties in policy-relevant timeframes that can influence decisions on necessary investments in climate adaptation.

Dust-Holding Capacity and Bio-Chemical Changes of Plant Species Growing in an Around Opencast Mining Area of Bundelkhand Region of Uttar Pradesh, India

The present study has been carried out on a total of 50 available plant species to assess their dust-capturing capacity and biochemical performances in and around open cast granite mine areas of Jhansi district and Bundelkhand University campus treated as control site. Plant species existing under a polluted environment for a long time may be considered as potentially resistant species and recommended for green belt design in mining areas, especially to cope with dust pollution. Results showed the pollution level, especially of mining-originated dust particles holding capacity of leaves and effects of different biochemical parameters (Total Chlorophyll, Protein and Carotenoid) of existing plant species both from mining areas as well as from Bundelkhand University campus. Based on their performances, Tectona grandis L., Ficus hispida L., Calotropis procera Aiton., Butea monosperma Lam. and Ficus benghalensis L., etc. are highly tolerant species while Ficus infectoria L., Artocarpus heterophyllus Lam., Ipomoea purpurea L., Allianthus excelsa Roxb. and Bauhinia variegata L. are intermediate tolerant species. T. grandis had shown the highest dust-holding capacity (2.566 ± 0.0004 mg/cm2) whereas Albizia procera (0.018 ± 0.0002 mg/cm2) was found to be the lowest dust-holding capacity. Our findings also showed that the T. grandis and F. hispida have significant dust deposition with minimal effect of dust on their leaf chlorophyll (17.447 ± 0.019 mg/g and 14.703 ± 0.201 mg/g), protein (0.699 ± 0.001 mg/g and 0.604 ± 0.002 mg/g) and carotenoid (0.372 ± 0.003 mg/g and 0.354 ± 0.003 mg/g) content respectively among all selected plant species. Therefore, in the present investigation, plant species with high tolerance to high dust-holding capacity on their leaf surfaces are preferable for green corridors as open cast granite mines and their adjacent areas.

Seasonal changes in Hermit Thrush (Catharus guttatus) song syntax

In many songbird species,birdsong features phonological syntax,meaning that the units within their vocal se-quences are ordered in a non-random way that adheres to a rule.While such syntactical patterns have been richly described in many species,comparatively little is known about how those patterns contribute to song achieving its important functions.For each of song’s main functions,territorial defense and mate attraction,evidence of a role for syntax is limited.One species for which syntax has been thoroughly described is the Hermit Thrush(Catharus guttatus),which presents song types from their repertoires in a semi-predictable order and,in doing so,rapidly cycle up and down the frequency spectrum.The objective of the present study was to explore the importance of song syntax in the Hermit Thrush through a within-subject examination of how measures of syntax,such as the predictability of song type order within song sequences,shift over the breeding season.We hypothesized that,if such syntactical characteristics are important to breeding behaviour,they would be most prominent at the start of the breeding season when activity associated with territory establishment and mate attraction is most intense.Analysis revealed that,as predicted,the rigidness of song type ordering within se-quences was highest at the start of the season and declined thereafter.That song type sequences were most predictable at the vitally important early part of the breeding season fit our hypothesis that this aspect of song syntax is important to song’s functions related to territory establishment and/or mate attraction.Future work will clarify whether that role relates to one of song’s two main functions or serves song transmission in some broader way.

Changes in Spring Snow Cover over the Eastern and Western Tibetan Plateau and Their Associated Mechanism

The spring snow cover(SC)over the western Tibetan Plateau(TP)(TPSC)(W_TPSC)and eastern TPSC(E_TPSC)have displayed remarkable decreasing and increasing trends,respectively,during 1985–2020.The current work investigates the possible mechanisms accounting for these distinct TPSC changes.Our results indicate that the decrease in W_TPSC is primarily attributed to rising temperatures,while the increase in E_TPSC is closely linked to enhanced precipitation.Local circulation analysis shows that the essential system responsible for the TPSC changes is a significant anticyclonic system centered over the northwestern TP.The anomalous descending motion and adiabatic heating linked to this anticyclone leads to warmer temperatures and consequent snowmelt over the western TP.Conversely,anomalous easterly winds along the southern flank of this anticyclone serve to transport additional moisture from the North Pacific,leading to an increase in snowfall over the eastern TP.Further analysis reveals that the anomalous anticyclone is associated with an atmospheric wave pattern that originates from upstream regions.Springtime warming of the subtropical North Atlantic(NA)sea surface temperature(SST)induces an atmospheric pattern resembling a wave train that travels eastward across the Eurasian continent before reaching the TP.Furthermore,the decline in winter sea ice(SIC)over the Barents Sea exerts a persistent warming influence on the atmosphere,inducing an anomalous atmospheric circulation that propagates southeastward and strengthens the northwest TP anticyclone in spring.Additionally,an enhancement of subtropical stationary waves has resulted in significant increases in easterly moisture fluxes over the coastal areas of East Asia,which further promotes more snowfall over eastern TP.