Influence of Irregular Coastlines on a Tornadic Mesovortex in the Pearl River Delta during the Monsoon Season. Part Ⅰ:Pre-storm Environment and Storm Evolution

The Pearl River Delta(PRD),a tornado hotspot,forms a distinct trumpet-shaped coastline that concaves toward the South China Sea.During the summer monsoon season,low-level southwesterlies over the PRD’s sea surface tend to be turned toward the west coast,constituting a convergent wind field along with the landward-side southwesterlies,which influences regional convective weather.This two-part study explores the roles of this unique land–sea contrast of the trumpet-shaped coastline in the formation of a tornadic mesovortex within monsoonal flows in this region.Part I primarily presents observational analyses of pre-storm environments and storm evolutions.The rotating storm developed in a lowshear environment(not ideal for a supercell)under the interactions of three air masses under the influence of the land–sea contrast,monsoon,and storm cold outflows.This intersection zone(or“triple point”)is typically characterized by local enhancements of ambient vertical vorticity and convergence.Based on a rapid-scan X-band phased-array radar,finger-like echoes were recognized shortly after the gust front intruded on the triple point.Developed over the triple point,they rapidly wrapped up with a well-defined low-level mesovortex.It is thus presumed that the triple point may have played roles in the mesovortex genesis,which will be demonstrated in Part II with multiple sensitivity numerical simulations.The findings also suggest that when storms pass over the boundary intersection zone in the PRD,the expected possibility of a rotating storm occurring is relatively high,even in a low-shear environment.Improved knowledge of such environments provides additional guidance to assess the regional tornado risk.

Deep Learning Shows Promise for Seasonal Prediction of Antarctic Sea Ice in a Rapid Decline Scenario

The rapidly changing Antarctic sea ice has garnered significant interest. To enhance the prediction skill for sea ice and respond to the Sea Ice Prediction Network-South's latest call, this study presents the reforecast results of Antarctic sea-ice area and extent from December to June of the coming year with a Convolutional Long Short-Term Memory(Conv LSTM)Network. The reforecast experiments demonstrate that Conv LSTM captures the interannual and interseasonal variability of Antarctic sea ice successfully, and performs better than the European Centre for Medium-Range Weather Forecasts. Based on this, we present the prediction from December 2023 to June 2024, indicating that the Antarctic sea ice will remain at lows, but may not create a new record low. This research highlights the promising application of deep learning in Antarctic sea-ice prediction.

Influence of lithospheric thickness distribution on oil and gas basins,China seas and adjacent areas

The distribution of oil and gas resources is intricately connected to the underlying structure of the lithosphere.Therefore,investigating the characteristics of lithospheric thickness and its correlation with oil and gas basins is highly important.This research utilizes recently enhanced geological–geophysical data,including topographic,geoid,rock layer thickness,variable rock layer density,and interface depth data.Employing the principles of lithospheric isostasy and heat conduction,we compute the laterally varying lithospheric thickness in the China seas and adjacent areas.From these results,two pivotal parameters for different types of oil and gas basins were statistically analyzed:the minimum lithospheric thickness and the relative fluctuation in lithospheric thickness.A semiquantitative analysis was used to explore the connection between these parameters and the hydrocarbon abundance within the oil and gas basins.This study unveils distinct variations in lithospheric thickness among basins,with oil and gas rich basins exhibiting a thicker lithosphere in the superimposed basins of central China and a thinner lithosphere in the rift basins of eastern China.Notably,the relative fluctuations in lithospheric thickness in basins demonstrate significant disparities:basins rich in oil and gas often exhibit greater thickness fluctuations.Additionally,in the offshore basins of China,a conspicuous negative linear correlation is observed between the minimum lithospheric thickness and the relative fluctuation in lithospheric thickness.This study posits that deep-seated thermal upwelling results in lithospheric undulations and extensional thinning in oil and gas basins.Concurrently,sustained deep-seated heat influences sedimentary materials in basins,creating favorable conditions for oil and gas generation.The insights derived from this study contribute to a quantitative understanding of the intricate relationships between deep lithospheric structures and oil and gas basins.These findings provide valuable guidance for future oil and gas exploration in the studied areas.

Seasonal influence of freshwater discharge on spatio-temporal variations in primary productivity, sea surface temperature, and euphotic zone depth in the northern Bay of Bengal

Ocean productivity is the foundation of marine food web,which continuously removes atmospheric carbon dioxide and supports life at sea and on land.Spatio-temporal variability of net primary productivity(NPP),sea surface temperature(SST),sea surface salinity(SSS),mixed layer depth(MLD),and euphotic zone depth(EZD) in the northern B ay of Bengal(BoB) during three monsoon seasons were examined in this study based on remote sensing data for the period 2005 to 2020.To compare the NPP distribution between the coastal zones and open BoB,the study area was divided into five zones(Z1-Z5).Results suggest that most productive zones Z2 and Zl are located at the head bay area and are directly influenced by freshwater discharge together with riverine sediment and nutrient loads.Across Z1-Z5,the NPP ranges from 5 315.38 mg/(m^(2)·d) to 346.7 mg/(m^(2)·d)(carbon,since then the same).The highest monthly average NPP of 5 315.38 mg/(m^(2)·d) in February and 5 039.36 mg/(m^(2)·d) in June were observed from Z2,while the lowest monthly average of 346.72 mg/(m^(2)·d) was observed in March from Z4,which is an oceanic zone.EZD values vary from 6-154 m for the study area,and it has an inverse correlation with NPP concentration.EZD is deeper during the summer season and shallower during the wintertime,with a corresponding increase in productivity.Throughout the year,monthly SST shows slight fluctuation for the entire study area,and statistical analysis shows a significant correlation among NPP,and EZD,overall positive between NPP and MLD,whereas no significant correlation among SSS,and SST for the northern BoB.Long-term trends in SST and productivity were significantly po sitive in head bay zones but negatively productive in the open ocean.The findings in this study on the distribution of NPP,SST,SSS,MLD,and EZD and their seasonal variability in five different zones of BoB can be used to further improve the management of marine resources and overall environmental condition in response to climate changes in BoB as they are of utmost relevance to the fisheries for the three bordering countries.

Global Celebrationof ‘Nihao!China’--2024 China Ice& Snow Tourism Overseas Promotion Season

The successful holding of"Nihao!China"--2024 China Ice&Snow Tourism Overseas Promotion Season has not only deepened the understanding of the people of various countries on the ice&snow cultural and tourist resources with Chinese characteristics,enhanced the exchanges and cooperation between Chinese and foreign cultural and tourist industries,but also accumulated rich experience for the brand construction of the series of event"Themed Tourism Overseas Promotion Season".

‘Nihao!China’——China's Grand Canal Tourism Overseas Promotion Season 2024 Launched

On April 2,hosted by Network of International Culturalink Entities(NICE),Jiangsu Provincial Department of Culture and Tourism,and Wuxi Municipal People's Government,with special support from the International Cooperation Department of the National Radio and Television Administration,and undertake by Wuxi Municipal Culture,Radio,Television and Tourism Bureau and Wuxi Liangxi District People's Government,the launch ceremony of"Nihao!China"-China's Grand Canal Tourism Overseas Promotion Season 2024 washeld in Wuxi,Jiangsu Province.

The Relationship between Extreme Precipitation Events in East Africa during the Short Rainy Season and Indian Ocean Sea Surface Temperature

The East African short rainy season (October-November-December) is one of the major flood seasons in the East African region. The amount of rainfall during the short rainy season is closely related to the lives of the people and the socio-economic development of the area. By using precipitation data and sea surface temperature data, this study reveals the spatial and temporal variation patterns of extreme precipitation during the East African short rainy season. Key findings include significant rainfall variability, with Tanzania experiencing the highest amounts in December due to the southward shift of the Intertropical Convergence Zone (ITCZ), while other regions receive less than 100 mm. Extreme rainfall events (90th percentiles) are evenly distributed, averaging 2 to 10 days annually. Historical data shows maximum seasonal rainfall often peaks at 15 mm, with frequent occurrences of daily rainfall exceeding 10 mm during OND. Additionally, a positive correlation (0.48) between OND precipitation extremes and Indian Ocean Dipole (IOD) anomalies is statistically significant. These findings highlight the climatic variability and potential trends in extreme rainfall events in East Africa, providing valuable insights for regional climate adaptation strategies.

Climate prediction of the seasonal sea-ice early melt onset in the Bering Sea

基于大尺度环流异常对海冰消融的影响过程,本文采用年际增量预测方法研制了白令海季节性海冰早期消融开始日期(EMO)的统计预测模型.预测模型选取了3个具有明确物理意义的预测因子:1月波弗特高压,前期11月东西伯利亚地区海平面气压,以及11月东欧平原积雪覆盖率。1月波弗特高压可以通过海气相互作用影响白令海地区海温异常,该海温异常能够从1月持续到3月,进而影响白令海EMO.11月东西伯利亚地区海平面气压与11月至次年2月北太平洋中纬度东部海温密切相关。伴随着北太平洋中纬度东部冷海温异常的出现,白令海地区会出现暖海温异常,进而导致白令海海冰范围减少,EMO较晚.1月北极偶极子异常是11月东欧平原积雪覆盖率影响次年白令海EMO的桥梁之一.1981-2022年的交叉检验结果表明:统计模型对白令海EMO具有较好的预测能力,预测与观测的EMO之间时间相关系数达到了0.45,超过了99%的置信水平.统计模型对白令海EMO正常年份和异常年份的预测准确率分别为60%和41%.

A Statistical Linkage between Extreme Cold Wave Events in Southern China and Sea Ice Extent in the Barents-Kara Seas from 1289 to 2017

Arctic sea ice loss and the associated enhanced warming has been related to midlatitude weather and climate changes through modulate meridional temperature gradients linked to circulation. However, contrasting lines of evidence result in low confidence in the influence of Arctic warming on midlatitude climate. This study examines the additional perspectives that palaeoclimate evidence provides on the decadal relationship between autumn sea ice extent (SIE) in the Barents-Kara (B-K) Seas and extreme cold wave events (ECWEs) in southern China. Reconstruction of the winter Cold Index and SIE in the B-K Seas from 1289 to 2017 shows that a significant anti-phase relationship occurred during most periods of decreasing SIE, indicating that cold winters are more likely in low SIE years due to the “bridge” role of the North Atlantic Oscillation and Siberian High. It is confirmed that the recent increase in ECWEs in southern China is closely related to the sea ice decline in the B-K Seas. However, our results show that the linkage is unstable, especially in high SIE periods, and it is probably modulated by atmospheric internal variability.

Influence of the Moho surface distribution on the oil and gas basins in China seas and adjacent areas

Owing to the strategic significance of national oil and gas resources,their exploration and production must be prioritized in China.Oil and gas resources are closely related to deep crustal structures,and Moho characteristics influence oil and gas distribution.Therefore,it is important to study the relationship between the variation of the Moho surface depth undulation and hydrocarbon basins for the future prediction of their locations.The Moho depth in the study area can be inverted using the Moho depth control information,the Moho gravity anomaly,and the variable density distribution calculated by the infinite plate.Based on these results,the influences of Moho characteristics on petroleum basins were studied.We found that the Moho surface depth undulation deviation and crustal thickness undulation deviation in the hydrocarbon-rich basins are large,and the horizontal gradient deviation of the Moho surface shows a positive linear relationship with oil and gas resources in the basin.The oil-bearing mechanism of the Moho basin is further discussed herein.The Moho uplift area and the slope zone correspond to the distribution of oil and gas fields.The tensile stress produced by the Moho uplift can form tensile fractures or cause tensile fractures on the surface,further developing into a fault or depression basin that receives deposits.The organic matter can become oil and natural gas under suitable chemical and structural conditions.Under the action of groundwater or other dynamic forces,oil and natural gas are gradually transported to the uplift or the buried hill in the depression zone,and oil and gas fields are formed under the condition of good caprock.The research results can provide new insights into the relationship between deep structures and oil and gas basins as well as assist in the strategic planning of oil and gas exploration activities.

Integrated gravity and magnetic study on patterns of petroleum basin occurrence in the China seas and adjacent areas

The China seas and adjacent areas contain numerous petroleum basins.One of the main challenges for future oil and gas exploration is to identify the inherent patterns of petroleum basin distribution.The formation and evolution of petroleum basins along with the migration and accumulation of oil and gas are often closely related to the tectonic environment.The gravity and magnetic fields with high lateral resolution and wide coverage provide important data for regional tectonic research.Based on the gravity data in the Global Satellite Gravity Anomaly Database(V31.1)and magnetic data from the Earth Magnetic Anomaly Grid(2-arc-minute resolution)(V2),this study uses integrated gravity and magnetic field technique to obtain integrated gravity and magnetic field result for the China seas and adjacent areas,and then adopts the normalized vertical derivative of the total horizontal derivative technique to conduct partition.Finally,it identifies the relationship between the partition characteristics and tectonics as well as the patterns of petroleum basin occurrence.The research shows that the partition of gravity and magnetic field integrated result has a good correlation with the Neo-Cathaysian tectonic system and tectonic units.The petroleum basins are characterized according to three blocks arranged from north to south and four zones arranged from east to west.The north-south block structure causes the uneven distribution of oil and gas resources in the mainland area and the differences in the hydrocarbon-bearing strata.Petroleum basins are more abundant in the north than in the south.The ages of the main oil-and gas-bearing strata are“Paleozoic–Mesozoic,Paleozoic–Mesozoic–Cenozoic,and Paleozoic–Mesozoic”,in order from north to south.The difference in the overall type of oil and gas resources in all basins is controlled by the east–west zonation.From east to west,the oil and gas resource type exhibits a wave-like pattern of“oil and gas,gas,oil and gas,gas”.The vertical distribution is characterized by an upper oil(Mesozoic–Cenozoic)and lower gas(Mesozoic–Paleozoic)structure.Within the study area,the Paleozoic marine strata should be the main strata of future natural gas exploration.

Hybrid Seasonal Prediction of Meridional Temperature Gradient Associated with“Warm Arctic-Cold Eurasia”

The meridional gradient of surface air temperature associated with“Warm Arctic–Cold Eurasia”(GradTAE)is closely related to climate anomalies and weather extremes in the mid-low latitudes.However,the Climate Forecast System Version 2(CFSv2)shows poor capability for GradTAE prediction.Based on the year-to-year increment approach,analysis using a hybrid seasonal prediction model for GradTAE in winter(HMAE)is conducted with observed September sea ice over the Barents–Kara Sea,October sea surface temperature over the North Atlantic,September soil moisture in southern North America,and CFSv2 forecasted winter sea ice over the Baffin Bay,Davis Strait,and Labrador Sea.HMAE demonstrates good capability for predicting GradTAE with a significant correlation coefficient of 0.84,and the percentage of the same sign is 88%in cross-validation during 1983−2015.HMAE also maintains high accuracy and robustness during independent predictions of 2016−20.Meanwhile,HMAE can predict the GradTAE in 2021 well as an experiment of routine operation.Moreover,well-predicted GradTAE is useful in the prediction of the large-scale pattern of“Warm Arctic–Cold Eurasia”and has potential to enhance the skill of surface air temperature occurrences in the east of China.

Study on the distribution characteristics of faults and their control over petroliferous basins in the China seas and its adjacent areas

As one of the main controlling factors of oil and gas accumulation,faults are closely related to the distribution of oil and gas reservoirs.Studying how faults control petroliferous basins is particularly important.In this work,we investigated the plane positions of major faults in the China seas and its adjacent areas using the normalized vertical derivative of the total horizontal derivative(NVDR-THDR)of the Bouguer gravity anomaly,the fusion results of gravity and magnetic anomalies,and the residual Bouguer gravity anomaly.The apparent depths of major faults in the China seas and its adjacent areas were inverted using the Tilt-Euler method based on the Bouguer gravity anomaly.The results show that the strikes of the faults in the China seas and its adjacent areas are mainly NE and NW,followed by EW,and near-SN.Among them,the lengths of most ultra-crustal faults are in the range of 1000–3000 km,and their apparent depths lie between 10 km and 40 km.The lengths of crustal faults lie between 300 km and 1000 km,and their apparent depths are between 0 km and 20 km.According to the plane positions and apparent depths of the faults,we put forward the concept of fault influence factor for the first time.Based on this factor,the key areas for oil and gas exploration were found as follows:the east of South North China Basin in the intracontinental rift basins;the southeast region of East China Sea Shelf Basin,the Taixinan and Qiongdongnan basins in the continental margin rift basins;Zhongjiannan Basin in the strike-slip pull-apart basins;the Liyue,Beikang,and the Nanweixi basins in the rifted continental basins.This work provides valuable insights into oil and gas exploration,mineral resource exploration,and deep geological structure research in the China seas and its adjacent areas.

The Effect of Boreal Summer Intraseasonal Oscillation on Mixed Layer and Upper Ocean Temperature over the South China Sea

Intraseasonal oscillation of the mixed layer and upper ocean temperature has been found to occur over the South China Sea(SCS)in the summer monsoon season based on the multiple reanalysis and observational data in this study.The method of composite analysis and an upper ocean temperature equation assisted the analysis of physical mechanisms.The results show that the mixed layer depth(MLD)in the SCS has a significant oscillation with a 30-60 d period over the SCS region,which is closely related to boreal summer intraseasonal oscillation(BSISO)activities.The MLD can increase(decrease)during the positive(negative)phase of the BSISO and usually lags behind by approximately one-eighth of the lifecycle(5 days)of the BSISO-related convection.The BSISO may cause periodic anomalies at the air-sea boundary,such as wind stress and heat flux,so it can play a dominant role in modulating the variation in MLD.There also are significant intraseasonal seawater temperature anomalies in both the surface and subsurface layers of the SCS.In addition,during the initial phase of the BSISO,the temperature anomaly signals of the thermocline are obviously opposite to the sea surface temperature(SST),especially in the southern SCS.According to the results from the analysis of the temperature equation,the vertical entrainment term caused by BSISO-related wind stress is stronger than the thermal forcing during the initial stage of convection,and it is more significant in the southern SCS.

A comparison study on structure-function relationship of polysaccharides obtained from sea buckthorn berries using different methods:antioxidant and bile acid-binding capacity

In this study,the structural characters,antioxidant activities and bile acid-binding ability of sea buckthorn polysaccharides(HRPs)obtained by the commonly used hot water(HRP-W),pressurized hot water(HRP-H),ultrasonic(HRP-U),acid(HRP-C)and alkali(HRP-A)assisted extraction methods were investigated.The results demonstrated that extraction methods had significant effects on extraction yield,monosaccharide composition,molecular weight,particle size,triple-helical structure,and surface morphology of HRPs except for the major linkage bands.Thermogravimetric analysis showed that HRP-U with filamentous reticular microstructure exhibited better thermal stability.The HRP-A with the lowest molecular weight and highest arabinose content possessed the best antioxidant activities.Moreover,the rheological analysis indicated that HRPs with higher galacturonic acid content and molecular weight showed higher viscosity and stronger crosslinking network(HRP-C,HRP-W and HRP-U),which exhibited stronger bile acid binding capacity.The present findings provide scientific evidence in the preparation technology of sea buckthorn polysaccharides with good antioxidant and bile acid binding capacity which are related to the structure affected by the extraction methods.

Characteristics and mechanisms of the intraseasonal variability of sea surface salinity in the southeastern Arabian Sea during 2015-2020

Based on Soil Moisture Active Passive sea surface salinity(SSS)data from April 2015 to August 2020,combined with Objectively Analyzed Air-Sea Heat Flux and other observational data and Hybrid Coordinate Ocean Model(HYCOM)data,this work explores the characteristics and mechanisms of the intraseasonal variability of SSS in the southeastern Arabian Sea(SEAS).The results show that the intraseasonal variability of SSS in the SEAS is very significant,especially the strongest intraseasonal signal in SSS,which is located along the northeast monsoon current(NMC)path south of the Indian Peninsula.There are remarkable seasonal differences in intraseasonal SSS variability,which is very weak in spring and summer and much stronger in autumn and winter.This strong intraseasonal variability in autumn and winter is closely related to the Madden-Julian Oscillation(MJO)event during this period.The northeast wind anomaly in the Bay of Bengal(BOB)associated with the active MJO phase strengthens the East India Coastal Current and NMC and consequently induces more BOB low-salinity water to enter the SEAS,causing strong SSS fluctuations.In addition,MJO-related precipitation further amplifies the intraseasonal variability of SSS in SEAS.Based on budget analysis of the mixed layer salinity using HYCOM data,it is shown that horizontal salinity advection(especially zonal advection)dominates the intraseasonal variability of mixed layer salinity and that surface freshwater flux has a secondary role.

Subseasonal transition of Barents-Kara sea-ice anomalies in winter related to the reversed warm Arctic-cold Eurasia pattern

“暖北极-冷欧亚”模态(WACE)的次季节反转会触发中国东部冬季的极端冷/暖转换以及春季沙尘暴.在这一显著的高纬度大气模态反转的驱动下,巴伦支海-喀拉海(BKS)的海冰异常也表现出次季节转换.当北极变暖以及乌拉尔山高压增强时,BKS异常向下的湍流热通量和增强的向下红外辐射有利于海冰融化;近地面的异常偏南风使海冰从薄冰区向多年冰区漂移,进一步扩大了开阔洋面.相反的机制出现在WACE反位相,导致BKS海冰异常偏多.当WACE次季节反转时,上述机制分别发生在前冬和后冬,使得BKS海冰异常出现显著的次季节转换.近10年随着WACE反转频率增多,BKS海冰前后冬的次季节变化增强.本文构建了WACE次季节反转的综合示意图,有助于更好地理解和预测中国东部极端气候.

SST effect on the pre-monsoon intraseasonal oscillation over the South China Sea based on atmospheric-coupled GCM comparison

The role of sea surface temperature(SST)variability in the pre-monsoonal(April to July)intraseasonal oscillation(ISO)over the South China Sea(SCS)is investigated using the Community Earth System Model Version 2(CESM2).An Atmospheric Model Intercomparison Project(AMIP)simulation forced by daily sea surface temperatures(SSTs)derived from a parallel coupled general circulation model(CGCM)run was compared with observations and the mother coupled simulation.In the coupled model,the SST warming leads the peak convection about 1/4 period as in observations.The paralell uncoupled model fails to simulate this phase relationship,implying the importance of air-sea coupling in reproducing realistic ISO.Due to the near-quadrature phase relationship between SST and precipitation ISOs during the ISO events,it is difficult to distinguish the active/passive role of SST from observations alone.Significant correlation in intraseasonal precipitation between the daily SST-forced AMIP and mother CGCM runs indicates that SST plays a role in driving the atmospheric ISO.

Functional groups and seasonal diversity of crustacean zooplankton in adjacent waters of Haizhou Bay,South Yellow Sea

Zooplankton are important linkages in the food web and can respond nonlinearly to environmental changes.Marine organisms thrive from spring to summer.Thus,it is crucial to understand how ecological functions of zooplankton communities may shift under seasonal environmental changes during this period.Samples were collected from May to August(May,June-Ⅰ,June-Ⅱ,July-Ⅰ,July-Ⅱ,and August)in 2018 in Haizhou Bay,Jiangsu,East China for zooplankton and environmental variables.Crustaceans accounted for 75 out of 134 zooplankton taxa and 91.8%of total zooplankton abundance.The average abundance of crustacean varied between 2824.6±635.4 inds./m3 in July-Ⅱand 6502.7±1008.8 inds./m3 in June-Ⅱ.Multivariate analyses results showed that the dissimilarity of community increased gradually in the time series.Body length,feeding type,trophic group,and reproduction mode were used to investigate crustacean community functions.Trait-based functional groups contained species with similar ecological roles.Functional diversity fused the differences of species and trait.The proportion of large-sized species(2-5 mm)decreased with the increasing proportion of medium-sized species(1-2 mm).The proportion of current feeders increased with the drop in the proportion of mixed feeders.Parthenogenesis species increased with decreasing free spawners,and omnivores-carnivores increased with decreasing omnivoresherbivores.Generalized additive models suggested that temperature was the main driver of variations in crustacean zooplankton function.Seven identified functional groups varied with increasing temperature.Omnivorous-herbivorous copepods declined(90.0%-68.0%),whereas the parthenogenetic cladocerans increased(0-24.1%).The small egg-brooding ambush copepods fluctuated(6.5%-9.3%)with increasing water temperature.The other functional groups changed slightly.Functional diversity also varied according to temperature changes.The community structure and ecological function of crustacean zooplankton community showed gradual changes with increasing temperature from spring to summer.

Assessments of Data-Driven Deep Learning Models on One-Month Predictions of Pan-Arctic Sea Ice Thickness

In recent years,deep learning methods have gradually been applied to prediction tasks related to Arctic sea ice concentration,but relatively little research has been conducted for larger spatial and temporal scales,mainly due to the limited time coverage of observations and reanalysis data.Meanwhile,deep learning predictions of sea ice thickness(SIT)have yet to receive ample attention.In this study,two data-driven deep learning(DL)models are built based on the ConvLSTM and fully convolutional U-net(FC-Unet)algorithms and trained using CMIP6 historical simulations for transfer learning and fine-tuned using reanalysis/observations.These models enable monthly predictions of Arctic SIT without considering the complex physical processes involved.Through comprehensive assessments of prediction skills by season and region,the results suggest that using a broader set of CMIP6 data for transfer learning,as well as incorporating multiple climate variables as predictors,contribute to better prediction results,although both DL models can effectively predict the spatiotemporal features of SIT anomalies.Regarding the predicted SIT anomalies of the FC-Unet model,the spatial correlations with reanalysis reach an average level of 89%over all months,while the temporal anomaly correlation coefficients are close to unity in most cases.The models also demonstrate robust performances in predicting SIT and SIE during extreme events.The effectiveness and reliability of the proposed deep transfer learning models in predicting Arctic SIT can facilitate more accurate pan-Arctic predictions,aiding climate change research and real-time business applications.