Spatiotemporal variation and freeze-thaw asymmetry of Arctic sea ice in multiple dimensions during 1979 to 2020

Arctic sea ice is broadly regarded as an indicator and amplifier of global climate change.The rapid changes in Arctic sea ice have been widely concerned.However,the spatiotemporal changes in the horizontal and vertical dimensions of Arctic sea ice and its asymmetry during the melt and freeze seasons are rarely quantified simultaneously based on multiple sources of the same long time series.In this study,the spatiotemporal variation and freeze-thaw asymmetry of Arctic sea ice were investigated from both the horizontal and vertical dimensions during 1979–2020 based on remote sensing and assimilation data.The results indicated that Arctic sea ice was declining at a remarkably high rate of–5.4×10^(4) km^(2)/a in sea ice area(SIA)and–2.2 cm/a in sea ice thickness(SIT)during 1979 to 2020,and the reduction of SIA and SIT was the largest in summer and the smallest in winter.Spatially,compared with other sub-regions,SIA showed a sharper declining trend in the Barents Sea,Kara Sea,and East Siberian Sea,while SIT presented a larger downward trend in the northern Canadian Archipelago,northern Greenland,and the East Siberian Sea.Regarding to the seasonal trend of sea ice on sub-region scale,the reduction rate of SIA exhibited an apparent spatial heterogeneity among seasons,especially in summer and winter,i.e.,the sub-regions linked to the open ocean exhibited a higher decline rate in winter;however,the other sub-regions blocked by the coastlines presented a greater decline rate in summer.For SIT,the sub-regions such as the Beaufort Sea,East Siberian Sea,Chukchi Sea,Central Arctic,and Canadian Archipelago always showed a higher downward rate in all seasons.Furthermore,a striking freeze-thaw asymmetry of Arctic sea ice was also detected.Comparing sea ice changes in different dimensions,sea ice over most regions in the Arctic showed an early retreat and rapid advance in the horizontal dimension but late melting and gradual freezing in the vertical dimension.The amount of sea ice melting and freezing was disequilibrium in the Arctic during the considered period,and the rate of sea ice melting was 0.3×10^(4) km^(2)/a and 0.01 cm/a higher than that of freezing in the horizontal and vertical dimensions,respectively.Moreover,there were notable shifts in the melting and freezing of Arctic sea ice in 1997/2003 and 2000/2004,respectively,in the horizontal/vertical dimension.

Spatial patterns of zooplankton abundance,biovolume,and size structure in response to environmental variables:a case study in the Yellow Sea and East China Sea

The Yellow Sea(YS)and East China Sea(ECS)are highly dynamic marginal seas of the northwestern Pacific Ocean.To gain an in-depth understanding of zooplankton community structure,zooplankton abundance,biovolume,and size structure in summer 2017 in the YS and ECS were assessed using ZooScan imaging analysis.Zooplankton abundance and biovolume ranged 2.94–1187.14 inds./m^(3)and 3.13–3438.51 mm^(3)/m^(3),respectively.Based on the biovolume data of the categorized size classes of 26 identified taxonomic groups,the zooplankton community was classified into five groups,and each group was coupled with distinctive oceanographic features.Under the influence of the Yellow Sea Cold Water Mass,the Yellow Sea offshore group featured the lowest bottom temperature(10.84±3.42℃)and the most abundant Calanoids(mainly in the 2–3 mm size class).In the Yellow Sea inshore group,Hydrozoans showed the largest biovolume and dominated in the 3–4-mm and>5-mm size classes.The East China Sea offshore group,which was affected by the Kuroshio Branch Current,featured high temperature and salinity,and the lowest bottom dissolved oxygen(2.58±0.5 mg/L).The lowest values of zooplankton abundance and biovolume in the East China Sea offshore group might be attributed to the bottom dissolved oxygen contents.The East China Sea inshore group,which was mainly influenced by the Zhejiang-Fujian Coastal Current and Changjiang Diluted Water,was characterized by high chlorophyll a and the largest biovolume of carnivorous Siphonophores(280.82±303.37 mm^(3)/m^(3)).The Changjiang River estuary offshore group showed the most abundant Cyclopoids,which might be associated with the less turbid water mass in this region.Seawater temperature was considered the most important factor in shaping the size compositions of Calanoids in different groups.

Wintertime Arctic Sea-Ice Decline Related to Multi-Year La Niña Events

Arctic sea ice has undergone a significant decline in the Barents-Kara Sea(BKS)since the late 1990s.Previous studies have shown that the decrease in sea ice caused by increased poleward moisture transport is modulated by tropical sea temperature changes(mainly referring to La Niña events).The occurrence of multi-year La Niña(MYLA)events has increased significantly in recent decades,and their impact on Arctic sea ice needs to be further explored.In this study,we investigate the relationship between sea-ice variation and different atmospheric diagnostics during MYLA and other La Niña(OTLA)years.The decline in BKS sea ice during MYLA winters is significantly stronger than that during OTLA years.This is because MYLA events tend to be accompanied by a warm Arctic-cold continent pattern with a barotropic high pressure blocked over the Urals region.Consequently,more frequent northward atmospheric rivers intrude into the BKS,intensifying longwave radiation downward to the underlying surface and melting the BKS sea ice.However,in the early winter of OTLA years,a negative North Atlantic Oscillation presents in the high latitudes of the Northern Hemisphere,which obstructs the atmospheric rivers to the south of Iceland.We infer that such a different response of BKS sea-ice decline to different La Niña events is related to stratospheric processes.Considering the rapid climate changes in the past,more frequent MYLA events may account for the substantial Arctic sea-ice loss in recent decades.

Long-Chain Alkenones in the South Yellow Sea Sediments and Their Indicative Significance for Haptophytes Species

Long-chain alkenones(LCAs)have been widely used as important biomarkers in palaeoceanographic studies.However,the commonly used LCAs proxies are mainly based on C_(37) alkenones,and it is still lack of the studies about the distribution and in-dications of LCAs with different chain lengths other than C_(37) alkenones.Here,the composition and distribution of LCAs were ana-lyzed in surface sediments from the southern Yellow Sea(SYS)and a sedimentary core(A02-C)from the central Yellow Sea(YS)mud area.The results showed that C_(37),C_(38) and C_(39) alkenones were the major LCAs in surface sediments of the SYS,and the relative contents of C_(38:2)Et,C_(37:2)Me,C_(37:3)Me,C_(38:2)Me,C_(38:3)Et,C_(38:3)Me,C_(39:2)Et and C_(39:3)Et were 18.3%-59.8%,22.6%-41.2%,7.4%-23.0%,6.6%-15.4%,3.8%-13.3%,3.6%-8.7%,2.8%-6.0% and 0.7%-3.0%,respectively.Then the relationships of U_(38Me)^(K)-U_(38Et)^(K) and U_(37)^(K')-U_(38Et)^(K) indicate that LCAs are mainly derived from Emiliania huxleyi(E.huxleyi).High ratios of total C_(37) alkenones to total C_(38) alkenones(K_(37)/K_(38))(1-1.2)were found in the central SYS,corresponding to the relatively high abundance of E.huxleyi;while low ratios of K_(37)/K_(38)(0.7-0.9)were observed at nearshore area of the SYS where Gephyrocapsa oceanica(G.oceanica)has rela-tively high abundance.The spatial distribution of K_(37)/K_(38) ratio is also consistent with that of coccolithophores nannofossil in the sediments.In addition,K_(37)/K_(38) ratio in core A02-C varied from 0.7 to 1.1 with a gradual decreasing trend during the past 5.5 kyr.This suggests that the relative abundance of E.huxleyi decreased gradually,caused by the changes in the Yellow Sea Warm Current(YSWC)and the East Asian Winter Monsoon(EAWM)during this period.

Acoustic Velocity-Based Inversion of the Physical Properties of Sea Ice in the Central Arctic Region

Studying the Arctic sea ice contributes to a comprehensive understanding of the climate system in polar regions and offers valuable insights into the interplay between polar climate change and the global climate and environment.One of the key research aspects is the investigation of the temperature,salinity,and density parameters of sea ice to obtain essential insights.During the 11th Chinese National Arctic Research Expedition,acoustic velocity was measured on an ice core at a short-term ice station,however,temperature,salinity,and density were not measured.In the present work,we utilized a genetic algorithm to invert these obtained acoustic velocity data to sea ice temperature,salinity,and density parameters on the basis of the relationship between acoustic velocity and the physical properties of Arctic summer sea ice.We validated the effectiveness of this inversion procedure by comparing its findings with those of other researchers.The results indicate that within the normalized depth range of 0.43-0.94,the ranges for temperature,salinity,and density are -0.48--0.29℃,1.63-3.35,and 793.1-904.1 kg m^(-3),respectively.

Contributors to tidal duration asymmetry with varied coastline configurations on western shelf of Yellow Sea

Coastal management in China is confronted with an urgent choice between natural restoration and maintenance of existing seawalls and reclaimed land for economic development.A key criterion for making this decision is the resilience to coastal flooding,which depends on the ability to predict tidal level.Tidal duration asymmetry(TDA)is a key parameter in determination of the arrival and duration of flood tides.This study selected the western inner shelf of the Yellow Sea(WYS)as the study area and investigated the responses of TDA to different shoreline configurations and relative sea level rise.The responses of TDA to shoreline reconstruction yielded spatial variability locally and remotely.In the nearshore area,the responses of TDA to the complex ocean environment mainly originated from the combined functions of reflection,bottom friction,and advection,which controlled the energy transfer from M2 or S2 constituents to their overtides or compound tides.The sensitivity of TDA to coastline typologies was not limited to coastal waters but could stretch over the entire inner shelf.The vulnerability of tidal responses was due to the displacement of the M2 amphidrome of the Kelvin wave on the WYS,which in turn changed tidal energy fluxes over the regime.The relative sea level rise could intensify the feedback of TDA to seawalls and land reclamation.

Contribution of Surface Waves to Sea Surface Temperatures in the Arctic Ocean

The aim of our study was to examine the contribution of surface waves from WAVEWATCH-III(WW3)to the variation in sea surface temperature(SST)in the Arctic Ocean.The simulated significant wave height(SWH)were validated against the products from Haiyang-2B(HY-2B)in 2021,obtaining a root mean squared error(RMSE)of 0.45 with a correlation of 0.96 and scatter index of 0.18.The wave-induced effects,i.e.,wave breaking and mixing induced by nonbearing waves resulting in changes in radiation stress and Stokes drift,were calculated from WW3,ERA-5 wind,SST,and salinity data from the National Centers for Environmental Prediction and were taken as forcing fields in the Stony Brook Parallel Ocean Model.The results showed that an RMSE of 0.81℃ with wave-induced effects was less than the RMSE of 1.11℃ achieved without the wave term compared with the simulated SST with the measurements from Argos.Considering the four wave effects and sea ice freezing,the SST in the Arctic Ocean decreased by up to 1℃ in winter.Regression analysis revealed that the SWH was linear in SST(values without subtraction of waves)in summer and autumn,but this behavior was not observed in spring or winter due to the presence of sea ice.The interannual variation also presented a negative relationship between the difference in SST and SWH.

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.

Spatio-temporal variability of surface chlorophyll a in the Yellow Sea and the East China Sea based on reconstructions of satellite data of 2001-2020

Chlorophyll-a(Chl-a)concentration is a primary indicator for marine environmental monitoring.The spatio-temporal variations of sea surface Chl-a concentration in the Yellow Sea(YS)and the East China Sea(ECS)in 2001-2020 were investigated by reconstructing the MODIS Level 3 products with the data interpolation empirical orthogonal function(DINEOF)method.The reconstructed results by interpolating the combined MODIS daily+8-day datasets were found better than those merely by interpolating daily or 8-day data.Chl-a concentration in the YS and the ECS reached its maximum in spring,with blooms occurring,decreased in summer and autumn,and increased in late autumn and early winter.By performing empirical orthogonal function(EOF)decomposition of the reconstructed data fields and correlation analysis with several potential environmental factors,we found that the sea surface temperature(SST)plays a significant role in the seasonal variation of Chl a,especially during spring and summer.The increase of SST in spring and the upper-layer nutrients mixed up during the last winter might favor the occurrence of spring blooms.The high sea surface temperature(SST)throughout the summer would strengthen the vertical stratification and prevent nutrients supply from deep water,resulting in low surface Chl-a concentrations.The sea surface Chl-a concentration in the YS was found decreased significantly from 2012 to 2020,which was possibly related to the Pacific Decadal Oscillation(PDO).

An ensemble learning method to retrieve sea ice roughness from Sentinel-1 SAR images

Sea ice surface roughness(SIR)affects the energy transfer between the atmosphere and the ocean,and it is also an important indicator for sea ice characteristics.To obtain a small-scale SIR with high spatial resolution,a novel method is proposed to retrieve SIR from Sentinel-1 synthetic aperture radar(SAR)images,utilizing an ensemble learning method.Firstly,the two-dimensional continuous wavelet transform is applied to obtain the spatial information of sea ice,including the scale and direction of ice patterns.Secondly,a model is developed using the Adaboost Regression model to establish a relationship among SIR,radar backscatter and the spatial information of sea ice.The proposed method is validated by using the SIR retrieved from SAR images and comparing it to the measurements obtained by the Airborne Topographic Mapper(ATM)in the summer Beaufort Sea.The determination of coefficient,mean absolute error,root-mean-square error and mean absolute percentage error of the testing data are 0.91,1.71 cm,2.82 cm,and 36.37%,respectively,which are reasonable.Moreover,K-fold cross-validation and learning curves are analyzed,which also demonstrate the method’s applicability in retrieving SIR from SAR images.

An improved algorithm for retrieving thin sea ice thickness in the Arctic Ocean from SMOS and SMAP L-band radiometer data

The aim of this study was to develop an improved thin sea ice thickness(SIT)retrieval algorithm in the Arctic Ocean from the Soil Moisture Ocean Salinity and Soil Moisture Active Passive L-band radiometer data.This SIT retrieval algorithm was trained using the simulated SIT from the cumulative freezing degree days model during the freeze-up period over five carefully selected regions in the Beaufort,Chukchi,East Siberian,Laptev and Kara seas and utilized the microwave polarization ratio(PR)at incidence angle of 40°.The improvements of the proposed retrieval algorithm include the correction for the sea ice concentration impact,reliable reference SIT data over different representative regions of the Arctic Ocean and the utilization of microwave polarization ratio that is independent of ice temperature.The relationship between the SIT and PR was found to be almost stable across the five selected regions.The SIT retrievals were then compared to other two existing algorithms(i.e.,UH_SIT from the University of Hamburg and UB_SIT from the University of Bremen)and validated against independent SIT data obtained from moored upward looking sonars(ULS)and airborne electromagnetic(EM)induction sensors.The results suggest that the proposed algorithm could achieve comparable accuracies to UH_SIT and UB_SIT with root mean square error(RMSE)being about 0.20 m when validating using ULS SIT data and outperformed the UH_SIT and UB_SIT with RMSE being about 0.21 m when validatng using EM SIT data.The proposed algorithm can be used for thin sea ice thickness(<1.0 m)estimation in the Arctic Ocean and requires less auxiliary data in the SIT retrieval procedure which makes its implementation more practical.

The Predictability Limit of Oceanic Mesoscale Eddy Tracks in the South China Sea

Employing the nonlinear local Lyapunov exponent (NLLE) technique, this study assesses the quantitative predictability limit of oceanic mesoscale eddy (OME) tracks utilizing three eddy datasets for both annual and seasonal means. Our findings reveal a discernible predictability limit of approximately 39 days for cyclonic eddies (CEs) and 44 days for anticyclonic eddies (AEs) within the South China Sea (SCS). The predictability limit is related to the OME properties and seasons. The long-lived, large-amplitude, and large-radius OMEs tend to have a higher predictability limit. The predictability limit of AE (CE) tracks is highest in autumn (winter) with 52 (53) days and lowest in spring (summer) with 40 (30) days. The spatial distribution of the predictability limit of OME tracks also has seasonal variations, further finding that the area of higher predictability limits often overlaps with periodic OMEs. Additionally, the predictability limit of periodic OME tracks is about 49 days for both CEs and AEs, which is 5-10 days higher than the mean values. Usually, in the SCS, OMEs characterized by high predictability limit values exhibit more extended and smoother trajectories and often move along the northern slope of the SCS.

Coral records of Mid-Holocene sea-level highstands and climate responses in the northern South China Sea

High-resolution sea-level data and high-precision dating of corals in the northern South China Sea(SCS)during the Holocene provide a reference and historical background for current and future sea-level changes and a basis for scientific assessment of the evolutionary trend of coral reefs in the SCS.Although sporadic studies have been performed around Hainan Island in the northern SCS,the reconstructed sea level presents different values or is controversial because the indicative meaning of the sea-level indicators were neither quantified nor uniform criteria.Here,we determined the quantitative relationship between modern living coral and sea level by measuring the top surfaces of 27 live Porites corals from the inner reef flat along the east coast of Hainan Island and assessed the accuracy of results obtained using coral as sea-level indicators.Additionally,three in situ fossil Porites corals were analyzed based on elevation measurements,digital X-ray radiography,and U-Th dating.The survey results showed that the indicative meanings for the modern live Porites corals is(146.09±8.35)cm below the mean tide level(MTL).It suggested that their upward growth limit is constrained by the sea level,and the lowest low water is the highest level of survival for the modern live Porites corals.Based on the newly defined indicative meanings,6 new sea-level index points(SLIPs)were obtained and 19 published SLIPs were recalculated.Those SLIPs indicated a relative sea level fluctuation between(227.7±9.8)cm to(154.88±9.8)cm MTL between(5393±25)cal a BP and(3390±12)cal a BP,providing evidences of the Mid-Holocene sea-level highstand in the northern SCS.Besides that,our analysis demonstrated that different sea-level histories may be produced based on different indicative meanings or criteria.The dataset of 276 coral U-Th ages indicates that coral reef development in the northern SCS comprised the initial development,boom growth,decline,and flourishing development again.A comparison with regional records indicated that synergistic effects of climatic and environmental factors were involved in the development of coral reefs in the northern SCS.Thus,the cessation of coral reef development during the Holocene in the northern SCS was probably associated with the dry and cold climate in South China,as reflected in the synchronous weakening of the ENSO and East Asian summer monsoon induced by the reduction of the 65°N summer insolation,which forced the migration of the Intertropical Convergence Zone.

Inversion of Seabed Geotechnical Properties in the Arctic Chukchi Deep Sea Basin Based on Time Domain Adaptive Search Matching Algorithm

The chirp sub-bottom profiler,for its high resolution,easy accessibility and cost-effectiveness,has been widely used in acoustic detection.In this paper,the acoustic impedance and grain size compositions were obtained based on the chirp sub-bottom profiler data collected in the Chukchi Plateau area during the 11th Arctic Expedition of China.The time-domain adaptive search matching algorithm was used and validated on our established theoretical model.The misfit between the inversion result and the theoretical model is less than 0.067%.The grain size was calculated according to the empirical relationship between the acoustic impedance and the grain size of the sediment.The average acoustic impedance of sub-seafloor strata is 2.5026×10^(6) kg(s m^(2))^(-1)and the average grain size(θvalue)of the seafloor surface sediment is 7.1498,indicating the predominant occurrence of very fine silt sediment in the study area.Comparison of the inversion results and the laboratory measurements of nearby borehole samples shows that they are in general agreement.

Soil Cover in the Eastern Part of the Dried Bed of the Aral Sea

The greatest environmental disaster in Central Asiathe drying up of the Aral Seahas led to the formation of a new terrain, extending over 2.7 million hectares in Uzbekistan. This newly formed terrain is dynamically developing, with emerging soil formations replacing bottom sediments. This paper analyzes the results of a study on soil formation in the eastern part of the dried-up seabed, focusing on the influence of natural processes occurring there.

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.

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.

Deep-large faults controlling on the distribution of the venting gas hydrate system in the middle of the Qiongdongnan Basin, South China Sea

Many locations with concentrated hydrates at vents have confirmed the presence of abundant thermogenic gas in the middle of the Qiongdongnan Basin(QDNB).However,the impact of deep structures on gasbearing fluids migration and gas hydrates distribution in tectonically inactive regions is still unclear.In this study,the authors apply high-resolution 3D seismic and logging while drilling(LWD)data from the middle of the QDNB to investigate the influence of deep-large faults on gas chimneys and preferred gasescape pipes.The findings reveal the following:(1)Two significant deep-large faults,F1 and F2,developed on the edge of the Songnan Low Uplift,control the dominant migration of thermogenic hydrocarbons and determine the initial locations of gas chimneys.(2)The formation of gas chimneys is likely related to fault activation and reactivation.Gas chimney 1 is primarily arises from convergent fluid migration resulting from the intersection of the two faults,while the gas chimney 2 benefits from a steeper fault plane and shorter migration distance of fault F2.(3)Most gas-escape pipes are situated near the apex of the two faults.Their reactivations facilitate free gas flow into the GHSZ and contribute to the formation of fracture‐filling hydrates.

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.

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.