Joint Probability Analysis and Prediction of Sea Ice Conditions in Liaodong Bay

Sea ice conditions in Liaodong Bay of China are often described by sea ice grades,which classify annual sea ice conditions based on the annual maximum sea ice thickness(AM-SIT)and annual maximum floating ice extent(AM-FIE).The joint probability distribution of AM-SIT and AM-FIE was established on the basis of their data pairs from 1949/1950 to 2019/2020 in Liaodong Bay.The joint intensity index of the sea ice condition in the current year is calculated,and the joint classification criteria of the sea ice grades in past years are established on the basis of the joint intensity index series.A comparison of the joint criteria with the 1973 and 2022 criteria revealed that the joint criteria of the sea ice grade match well,and the joint intensity index can be used to quantify the sea ice condition over the years.A time series analysis of the sea ice grades and the joint intensity index sequences based on the joint criteria are then performed.Results show a decreasing trend of the sea ice condition from 1949/1950 to 2019/2020,a mutation in 1990/1991,and a period of approximately 91 years of the sea ice condition.In addition,the Gray-Markov model(GMM)is applied to predict the joint sea ice grade and the joint intensity index of the sea ice condition series in future years,and the error between the results and the actual sea ice condition in 2020/2021 is small.

Sea ice extent retrieval with HY-2A scatterometer data and its assessment

A sea ice extent retrieval algorithm over the polar area based on scatterometer data of HY-2A satellite has been established. Four parameters are used for distinguishing between sea ice and ocean with Fisher＇s linear discriminant analysis method. The method is used to generate polar sea ice extent maps of the Arctic and Antarctic regions of the full 2013-2014 from the scatterometer aboard HY-2A （HY-2A-SCAT） backscatter data. The time series of the ice mapped imagery shows ice edge evolution and indicates a similar seasonal change trend with total ice area from DMSP-F17 Special Sensor Microwave Imager/Sounder （SSMIS） sea ice concentration data. For both hemispheres, the HY-2A-SCAT extent correlates very well with SSMIS 15% extent for the whole year period. Compared with Synthetic Aperture Radar （SAR） imagery, the HY-2A-SCAT ice extent shows good correlation with the Sentinel-1 SAR ice edge. Over some ice edge area, the difference is very evident because sea ice edges can be very dynamic and move several kilometers in a single day.

Causes for different spatial distributions of minimum Arctic sea-ice extent in 2007 and 2012

Satellite records show the minimum Arctic sea ice extents （SIEs） were observed in the Septembers of 2007 and 2012, but the spatial distributions of sea ice concentration reduction in these two years were quite different. Atmospheric circulation pattern and the upper-ocean state in summer were investigated to explain the difference. By employing the ice-temperature and ice-specific humidity （SH） positive feedbacks in the Arctic Ocean, this paper shows that in 2007 and 2012 the higher surface air temperature （SAT） and sea level pressure （SLP） accompanied by more surface SH and higher sea surface temperature （SST）, as a consequence, the strengthened poleward wind was favorable for melting summer Arctic sea ice in different regions in these two years. SAT was the dominant factor influencing the distribution of Arctic sea ice melting. The correlation coefficient is -0.84 between SAT anomalies in summer and the Arctic SIE anomalies in autumn. The increase SAT in different regions in the summers of 2007 and 2012 corresponded to a quicker melting of sea ice in the Arctic. The SLP and related wind were promoting factors connected with SAT. Strengthening poleward winds brought warm moist air to the Arctic and accelerated the melting of sea ice in different regions in the summers of 2007 and 2012. Associated with the rising air temperature, the higher surface SH and SST also played a positive role in reducing summer Arctic sea ice in different regions in these two years, which form two positive feedbacks mechanism.

Variation of sea ice extent in different regions of the Arctic Ocean

Sea ice in the Arctic has been reducing rapidly in the past half century due to global warming. This study analyzes the variations of sea ice extent in the entire Arctic Ocean and its sub regions. The results indicate that sea ice extent reduction during 1979-2013 is most significant in summer, following by that in autumn, winter and spring. In years with rich sea ice, sea ice extent anomaly with seasonal cycle removed changes with a period of 4-6 years. The year of 2003-2006 is the ice-rich period with diverse regional difference in this century. In years with poor sea ice, sea ice margin retreats further north in the Arctic. Sea ice in the Fram Strait changes in an opposite way to that in the entire Arctic. Sea ice coverage index in melting-freezing period is an critical indicator for sea ice changes, which shows an coincident change in the Arctic and sub regions. Since 2002, Region C2 in north of the Pacific sector contributes most to sea ice changes in the central Aarctic, followed by C1 and C3. Sea ice changes in different regions show three relationships. The correlation coefficient between sea ice coverage index of the Chukchi Sea and that of the East Siberian Sea is high, suggesting good consistency of ice variation. In the Atlantic sector, sea ice changes are coincided with each other between the Kara Sea and the Barents Sea as a result of warm inflow into the Kara Sea from the Barents Sea. Sea ice changes in the central Arctic are affected by surrounding seas.

Crystals and fabrics analysis of an Arctic thermal growth multi-year ice sample

One of sea ice core samples was taken from Arctic by the First Chinese National Arctic Research Expedition Team in 1999. 20 vertical and 2 horizontal ice sections were cut out of the ice core sample 2.22 m in length, which covered the ice sheet from surface to bottom except losses for during sampling and section cutting. From the observation and analysis of the fabrics and crystals along the depth of the ice core sample, followings were found. Whole ice sheet consists of columnar, refrozen clastic pieces, granular, columnar, refrozen clastic pieces, granular, columnar and refrozen clastic pieces. This indicates that the ice core sample was 3-year old, and the ice sheet surface thawed and the melt water flowed into ice sheet during summer. Hence, the annual energy balance in Arctic can be determined by the ice sheet surface thawing in summer, and bottom growth in winter. The thickness of the ice sheet is kept constantly at a certain position based on the corresponding climate and ocean conditions; A new

Mechanisms associated with winter intraseasonal extreme sea ice extent in the Weddell Sea

Previous studies have shown evidence of atmospheric extratropical wave trains modulating sea ice area in the Weddell and Amundsen/Bellingshausen seas on intraseasonal time-scales(20–100 d). Here we investigate mechanisms relating intraseasonal extreme sea ice extent and Ekman layer dynamics with emphasis on the Weddell Sea. This study extends from 1989 to 2013 and focuses on the winter season. Wind stress τ is calculated with winds from the Climate Forecast System reanalysis(CFSR) to evaluate momentum transfer between the atmosphere and the Ekman layer. Lag-composites of the anomalies of Ekman transport and the Ekman pumping indicate that divergence of mass in the Ekman layer and upwelling lead the occurrence of extreme sea ice contraction on intraseasonal time-scales in the Weddell Sea. Opposite conditions(i.e., convergence of the mass and downwelling) lead extreme sea ice expansion on intraseasonal time-scales. This study suggests that the Ekman pumping resulting from the anomalous wind stress on intraseasonal time-scales can transport these warmer waters to the surface contributing to sea ice melting. Additionally, high resolution sea ice fraction and ocean currents obtained from satellite and in situ data are used to investigate in detail mechanisms associated with persistent extreme sea ice expansion and contraction on intraseasonal time-scales. These case studies reveal that atmospheric circumpolar waves on intraseasonal time-scales can induce contrasting anomalies of about ±20% in sea ice concentration at the Weddell and western Antarctica Peninsula margins within less than 30 d. This study shows that extreme anomalies in sea ice may lag between 5–25 d(1–5 pentads) the ocean-atmospheric forcing on intraseasonal time-scales.

Impact of the El Nino on the Variability of the Antarctic Sea Ice Extent

In this paper, the spreading way in the southern hemisphere that anomalous warm water piled in tropical eastern Pacific is analysed and then impact of El Nino on the variability of the Antarctic sea ice extent is investigated by using a dataset from 1970 to 2002. The analysis result show that in El Nino event the anomalous warm water piled in tropical eastern Pacific is poleward propagation yet the westward propagation along southern equator current hasn't been discovered . The poleward propagation time of the anomalous warm water is about 1 year or so. El Nino event has a close relationship with the sea ice extent in the Amundsen sea , Bellingshausen sea and Antarctic peninsula .After El Nino appears , there is a lag of two years that the sea ice in the Amundsen sea , Bellingshausea sea, especially in the Antarctic peninsula decreases obviously. The processes that El Nino has influence with Antarctic sea ice extent is the warm water piled in tropical eastern Pacific poleward propagation along off the coast of southern America and cause the anomalous temperature raise in near pole and then lead the sea ice in Amundsen sea , Bellingshausen sea and Antarctic peninsula to decrease where the obvious decrease of the sea ice since 80' decade has close relation to the frequently appearance of El Nino .

Statistical study on the spatial - temporal distribution features of the arctic sea ice extent

On the basis of the arctic monthly mean sea ice extent data set during 1953-1984, the arctic region is divided into eight subregions,and the analyses of empirical orthogonal functions, power spectrum and maximum entropy spectrum are made to indentify the major spatial and temporal features of the sea ice fluctuations within 32-year period. And then, a brief appropriate physical explanation is tentatively suggested. The results show that both seasonal and non-seasonal variations of the sea ice extent are remarkable, and iis mean annual peripheral positions as well as their interannu-al shifting amplitudes are quite different among all subregions. These features are primarily affected by solar radiation, o-cean circulation, sea surface temperature and maritime-continental contrast, while the non-seasonal variations are most possibly affected by the cosmic-geophysical factors such as earth pole shife, earth rotation oscillation and solar activity.

Temporal and spatial variation characteristics of Antarctic sea ice and the causes of its record decline during 2015–2016: a review

Satellite observations over the past four decades have shown that the long-term trend of Antarctic sea ice extent(SIE)is opposite to the trend of sea ice extent in the Arctic.Arctic sea ice extent continues to decline while Antarctic SIE is generally on the rise except for a dramatic decline in 2015–2016.Based on the 40-year climatology from 1981 to 2020,Antarctic SIE anomaly in December 2016 is–2.1×10^(6) km^(2),reaching the minimum since 1979.There are many studies on the cause of this record decline.This present review summarizes the spatial and temporal characters of Antarctic sea ice and recaps major findings on the causes of record decline in 2015–2016 from the perspective of direct thermodynamic and dynamic process of atmosphere and ocean as well as the modulation of climate modes.Finally,the challenges and key scientific problems to be solved in the future of Antarctic sea ice research are presented.

Winter sea ice albedo variations in the Bohai Sea of China

Sea ice conditions in the Bohai Sea of China are sensitive to large-scale climatic variations. On the basis of CLARA-A1-SAL data, the albedo variations are examined in space and time in the winter（December, January and February） from 1992 to 2008 in the Bohai Sea sea ice region. Time series data of the sea ice concentration（SIC）, the sea ice extent（SIE） and the sea surface temperature（SST） are used to analyze their relationship with the albedo. The sea ice albedo changed in volatility appears along with time, the trend is not obvious and increases very slightly during the study period at a rate of 0.388% per decade over the Bohai Sea sea ice region.The interannual variation is between 9.93% and 14.50%, and the average albedo is 11.79%. The sea ice albedo in years with heavy sea ice coverage, 1999, 2000 and 2005, is significantly higher than that in other years; in years with light sea ice coverage, 1994, 1998, 2001 and 2006, has low values. For the monthly albedo, the increasing trend（at a rate of 0.988% per decade） in December is distinctly higher than that in January and February. The mean albedo in January（12.90%） is also distinctly higher than that in the other two months. The albedo is significantly positively correlated with the SIC and is significantly negatively correlated with the SST（significance level 90%）.

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.

Arctic warming trends and their uncertainties based on surface temperature reconstruction under different sea ice extent scenarios

IPCC AR6 states that the neglect of recent rapid warming in the Arctic generally leads to an underestimate of global warming trends.In this study,by reconstructing the surface temperature(ST)datasets in the Arctic under different sea ice extent scenarios(Imax and Imin),we respectively evaluated the annual and seasonal warming trends and their uncertainties from 1900 to 2020.The results show that the reconstructed datasets have a good representation of the ST change trends in the Arctic.In 1900e2020,the annual warming trends in the Arctic(0.17±0.031 and 0.14±0.025℃ per decade under the Imax and Imin reconstruction,respectively)are roughly 1.6e1.8 times the global mean warming trends(0.10±0.008 and 0.09±0.008℃ per decade).While in 1979e2020,the Arctic warming trends(0.66±0.100 and 0.55±0.080℃ per decade)increase to 3.1e3.5 times of the global warming trend(0.19±0.023 and 0.18±0.023℃ per decade)for Imax and Imin,respectively,indicating that the Arctic amplification effect has been significantly enhancing in recent decades.Although the seasonal warming trends are closely related to cloud feedback mechanisms,atmospheric circulation,and ocean circulation,they are not sensitive to the different reconstruction scenarios.

MODIS-based Daily Lake Ice Extent and Coverage dataset for Tibetan Plateau

The Tibetan Plateau houses numerous lakes,the phenology and duration of lake ice in this region are sensitive to regional and global climate change,and as such are used as key indicators in climate change research,particularly in environment change comparison studies for the Earth three poles.However,due to its harsh natural environment and sparse population,there is a lack of conventional in situ measurement on lake ice phenology.The Moderate Resolution Imaging Spectroradiometer(MODIS)Normalized Difference Snow Index(NDSI)data,which can be traced back 20 years with a 500 m spatial resolution,were used to monitor lake ice for filling the observation gaps.Daily lake ice extent and coverage under clear-sky conditions was examined by employing the conventional SNOWMAP algorithm,and those under cloud cover conditions were re-determined using the temporal and spatial continuity of lake surface conditions through a series of steps.Through time series analysis of every single lake with size greater than 3 km2 in size,308 lakes within the Tibetan Plateau were identified as the effective records of lake ice extent and coverage to form the Daily Lake Ice Extent and Coverage dataset,including 216 lakes that can be further retrieved with four determinable lake ice parameters:Freeze-up Start(FUS),Freeze-up End(FUE),Break-up Start(BUS),and Break-up End(BUE),and 92 lakes with two parameters,FUS and BUE.Six lakes of different sizes and locations were selected for verification against the published datasets by passive microwave remote sensing.The lake ice phenology information obtained in this paper was highly consistent with that from passive microwave data at an average correlation coefficient of 0.91 and an RMSE value varying from 0.07 to 0.13.The present dataset is more effective at detecting lake ice parameters for smaller lakes than the coarse resolution passive microwave remote sensing observations.The published data are available in https://data.4tu.nl/repository/uuid:fdfd8c76-6b7c-4bbf-aec8-98ab199d9093 and http://www.sciencedb.cn/dataSet/handle/744.

The spatiotemporal patterns of sea ice in the Bohai Sea during the winter seasons of 2000–2016

In this study,sea ice thickness(SIT)and sea ice extent(SIE)in the Bohai Sea from 2000 to 2016 were investigated.A surface heat balance equation was applied to calculate SIT using ice surface temperatures estimated from the Moderate Resolution Imaging Spectroradiometer(MODIS)data with input from air temperature and wind speed from reanalyzing weather data.No trend was found in SIT during 2000–2016.The mean SIT and SIE during this period were 5.58±0.86 cm and 23×10^(3)±8×10^(3)km^(2),respectively.The largest SIT and SIE periods were observed during the second half of January and the first half of February,respectively.The Spearman correlation coefficient between mean ice thickness and average air temperature from 21 automatic weather stations around the Bohai Sea was–0.94(P<.005),and the coefficient between median ice extent and negative accumulated temperature was–0.503(P<.001).The rate of increase in air temperature around the Bohai Sea is 0.271℃per decade in winter for 1979–2016(P<.05),which is much lower than that in northern polar area(0.648℃per decade).This rate has not resulted in a decreasing trend in SIT and SIE for the past 16 years in the Bohai Sea.

Arctic sea ice bordering on the North Atlantic and inter-annual climate variations

Variations of winter Arctic sea ice bordering on the North Atlantic are closely related to climate variations in the same region. When winter North Atlantic Oscillation (NAO) index is positive (negative) anomaly phase, Icelandic Low is obviously deepened and shifts northwards (southwards). Simultaneously, the Subtropical High over the North Atlantic is also intensified, and moves northwards (southwards). Those anomalies strengthen (weaken) westerly between Icelandic Low and the Subtropical High, and further result in positive (negative) sea surface temperature (SST) anomalies in the mid-latitude of the North Atlantic, and increase (decrease) the warm water transportation from the mid-latitude to the Barents Sea, which causes positive (negative) mixed-layer water temperature anomalies in the south part of the Barents Sea. Moreover, the distribution of anomaly air temperature clearly demonstrates warming (cooling) in northern Europe and the subarctic regions (including the Barents Sea) and cooling

Variations of sea ice in the Antarctic and Arctic from 1997-2006

Sea ice in polar areas is an important part of the global climate system. In order to obtain variations in sea ice extent for the Antarctic and Arctic, this paper analyzed the Special Sensor Microwave/Imager （SSM/I） sea ice data product dating from March 1, 1997 to December 31, 2006. During this period, the sea Antarctic with the trend ice extent increased in the of （0.5467±0.4933）× 10^4 km2.yr^-1, and decreased in the Arctic with the trend of （-7.6125±0.3503）× 10^4 km2.yr^-1. In different sectors of the Antarctic, variations of the sea ice extent are different. The sea ice extent increased in the Weddell Sea and Indian Ocean, but decreased in the Ross Sea, Western Pacific Ocean, and Bellingshausen/Amundsen Seas.

Analysis of sea ice conditions and navigability in the Arctic Northeast Passage during the summer from 2002-2021

The decreasing of Arctic sea ice is projected to continue with global warming,which makes the summer navigation conditions of the Arctic improve.Based on the multi-source remote-sensing data with inter-sensor calibration processing and the ship-based observational data from R/V Xuelong and M/V Yongsheng,the sea ice conditions of the Arctic Northeast Passage(NEP)during the 2002-2021 summer seasons were analyzed,and the navigability of the NEP between July and October from 2002 to 2021 was discussed.Inter-sensor calibration could effectively reduce the deviation from different passive microwave data.Sea ice extent and thickness in the NEP decreased annually,which resulted in the navigability of the NEP showing a potential tendency toward improvement in navigability.The navigation period was mainly concentrated in early August to early October.The middle part of the NEP was primarily affected by sea ice.This influence decreased over time,while the navigation period increased,especially in the Vilkitsky Strait,which is a key shipping area.This analysis of sea ice conditions and navigability in the past 20 years could provide a reference for future scientific investigations and aid in merchant ship navigation in the Arctic summer.