Four-to Six-Year Periodic Variation of Arctic Sea-Ice Extent and Its Three Main Driving Factors

Besides the rapid retreating trend of Arctic sea-ice extent(SIE),this study found the most outstanding low-frequency variation of SIE to be a 4-6-year periodic variation.Using a clustering analysis algorithm,the SIE in most ice-covered regions was clustered into two special regions:Region-1 around the Barents Sea and Region-2 around the Canadian Basin,which were located on either side of the Arctic Transpolar Drift.Clear 4-6-year periodic variation in these two regions was identified using a novel method called“running linear fitting algorithm”.The rate of temporal variation of the Arctic SIE was related to three driving factors:the regional air temperature,the sea-ice areal flux across the Arctic Transpolar Drift,and the divergence of sea-ice drift.The 4-6-year periodic variation was found to have always been present since 1979,but the SIE responded to different factors under heavy and light ice conditions divided by the year 2005.The joint contribution of the three factors to SIE variation exceeded 83%and 59%in the two regions,respectively,remarkably reflecting their dynamic mechanism.It is proven that the process of El Niño-Southern Oscillation(ENSO)is closely associated with the three factors,being the fundamental source of the 4-6-year periodic variations of Arctic SIE.

Evaluating Parameterizations for Turbulent Fluxes over the Landfast Sea-Ice Surface in Prydz Bay, Antarctica

It is crucial to appropriately determine turbulent fluxes in numerical models.Using data collected in East Antarctica from 8 April to 26 November 2016,this study evaluates parameterization schemes for turbulent fluxes over the landfast seaice surface in five numerical models.The Community Noah Land Surface Model with Multi-Parameterizations Options(Noah_mp)best replicates the turbulent momentum flux,while the Beijing Climate System Model(BCC_CSM)produces the optimum sensible and latent heat fluxes.In particular,two critical issues of parameterization schemes,stability functions and roughness lengths,are investigated.Sensitivity tests indicate that roughness lengths play a decisive role in model performance.Based on the observed turbulent fluxes,roughness lengths over the landfast sea-ice surface are calculated.The results,which can provide a basis for setting up model parameters,reveal that the dynamic roughness length(z0m)increases with the increase of frictional velocity(u*)when u*≤0.4 m s^(−1) and fluctuates around 10^(−3 )m when u*>0.4 m s^(−1);thermal roughness length(z0t)is linearly related to the temperature gradient between air and sea-ice surface(ΔT)with a relation of lg(z0t)=−0.29ΔT−3.86;and the mean water vapor roughness length(z0q)in the specific humidity gradient(Δq)range ofΔq≤−0.6 g kg^(−1) is 10^(−6) m,3.5 times smaller than that in the range ofΔq˃−0.6 g kg^(−1).

Evaluation of the Arctic Sea-Ice Simulation on SODA3 Datasets

This study evaluates the Arctic sea-ice simulation of the SODA3 dataset driven by different atmospheric forcing fields and explores the errors of the Arctic sea-ice simulation caused by the forcing field.We find that the SODA3 data driven by different forcing fields represent a significant systematical error in the simulation of Arctic sea-ice concentration,showing a low concentration of thick ice and a high concentration of thin ice.In terms of sea-ice extent,the SODA3 data from different versions well characterize the interannual variability and declining trend in the observed data,but they overestimate the overall Arctic sea-ice extent,which is related to excessive simulation of ice in the sea-ice margin.Compared to observations,all the chosen SODA3 reanalysis versions driven by different atmospheric forcing generally tend to underestimate the Arctic sea-ice thickness,especially for thick ice in the multi-year sea-ice regions.Inaccurate simulations of Arctic sea-ice transport may partly explain the error in SODA3 sea-ice thickness in multi-year sea-ice areas.The results of different SDOA3 versions differ greatly in the Beaufort Sea,the Fram Strait,and the Central Arctic Sea.The difference in sea-ice thickness among different SODA3 versions is primarily due to the thermodynamic contribution,which may come from the diversity of atmospheric forcing fields.Our work provides a reference for using SODA3 data to study Arctic sea ice.

Influence of Arctic Sea-ice Concentration on Extended-range Forecasting of Cold Events in East Asia

Utilizing the Community Atmosphere Model,version 4,the influence of Arctic sea-ice concentration(SIC)on the extended-range prediction of three simulated cold events(CEs)in East Asia is investigated.Numerical results show that the Arctic SIC is crucial for the extended-range prediction of CEs in East Asia.The conditional nonlinear optimal perturbation approach is adopted to identify the optimal Arctic SIC perturbations with the largest influence on CE prediction on the extended-range time scale.It shows that the optimal SIC perturbations are more inclined to weaken the CEs and cause large prediction errors in the fourth pentad,as compared with random SIC perturbations under the same constraint.Further diagnosis reveals that the optimal SIC perturbations first modulate the local temperature through the diabatic process,and then influence the remote temperature by horizontal advection and vertical convection terms.Consequently,the optimal SIC perturbations trigger a warming center in East Asia through the propagation of Rossby wave trains,leading to the largest prediction uncertainty of the CEs in the fourth pentad.These results may provide scientific support for targeted observation of Arctic SIC to improve the extended-range CE prediction skill.

Change of Arctic sea-ice volume and its relationship with sea-ice extent in CMIP5 simulations

The future change of September Arctic sea-ice volume,simulated by 30 state-of-the-art climate models from the Coupled Model Intercomparison Project Phase 5（CMIP5）,is examined,which depends on both ice extent and ice thickness.In comparison with the September sea-ice extent,the September sea-ice volume has larger spread in the historical simulation but faster convergence in the projection simulation,especially in the context of increasing greenhouse gas emissions.This indicates that the ice volume might be more sensitive to external forcings than the ice extent.Using the averaged projection of those climate models from the 30 CMIP5 models that can better reflect the ‘observed＇ sea-ice volume climatology and variability,it is shown that the September sea ice volume will decrease to ~3000 km3 in the early 2060 s,and then level off under a medium-mitigation scenario.However,it will drop to ~3000 km3 in the early 2040 s and reach a near-zero ice volume in the mid-2070 s under a high-emission scenario.With respect to the historical condition,the reduction of the ice volume,associated with increasing greenhouse gas emissions,is more rapid than that of the ice extent during the twenty-first century.

Possible Impacts of Winter Arctic Oscillation on Siberian High, the East Asian Winter Monsoon and Sea-Ice Extent

Using the NCEP/ NCAR reanalysis dataset covering a 40-year period from January 1958 to December 1997, sea surface temperature (1950-1992), and monthly sea-ice concentration dataset for the period from 1953 to 1995, we investigate connections between winter Arctic Oscillation (AO) and Siberian high (SH), the East Asian winter monsoon (EAWM), and winter sea-ice extent in the Barents Sea. The results indicate that winter AO not only influences climate variations in the Arctic and the North Atlantic sector, but also shows possible effects on winter SH, and further influences EAWM, When winter AO is in its positive phase, both of winter SH and the EAWM are weaker than normal, and air temperature from near the surface to the middle troposphere is about 0.5-2degreesC higher than normal in the southeastern Siberia and the East Asian coast, including eastern China, Korea, and Japan. When AO reaches its negative phase, an opposite scenario can be observed. The results also indicate that winter SH has no significant effects on climate variations in Arctic and the North Atlantic sector. Its influence intensity and extent are obviously weaker than AO, exhibiting a 'local, feature in contrast to AO. This study further reveals the possible mechanism of how the winter AO is related to winter SH. It is found that winter SH variation is closely related to both dynamic processes and air temperature variations from the surface to the middle troposphere. The western SH variation mainly depends on dynamic processes, while its eastern part is more closely related to air temperature variation. The maintaining of winter SH mainly depends on downward motion of airflow of the nearly entire troposphere. The airflow originates from the North Atlantic sector, whose variation is influenced by the AO. When AO is in its positive (negative) phase, downward motion remarkably weakened (strengthened), which further influences winter SH. In addition, winter AO exhibits significant influences on the simultaneous sea-ice extent in the Barents Sea.

Retrieving the antarctic sea-ice concentration based on AMSR-E 89 GHz data

Sea-ice concentration is a key item in global climate change research. Recent progress in remotely sensed sea-ice concentration product has been stimulated by the use of a new sensor, advanced microwave scan- ning radiometer for EOS （AMSR-E）, which offers a spatial resolution of 6 km×4 km at 89GHz, A new inver- sion algorithm named LASI （linear ASI） usingAMSR-E 89GHz data was proposed and applied in the antarc- tic sea areas. And then comparisons between the LASI ice concentration products and those retrieved by the other two standard algorithms, ASI （arctic radiation and turbulence interaction study sea-ice algorithm） and bootstrap, were made. Both the spatial and temporal variability patterns of ice concentration differ- ences, LASI minus ASI and LASI minus bootstrap, were investigated. Comparative data suggest a high result consistency, especially between LASI and ASI. On the other hand, in order to estimate the LASI ice concen- tration errors introduced by the tie-points uncertainties, a sensitivity analysis was carried out. Additionally an LASI algorithm error estimation based on the field measurements was also completed. The errors suggest that the moderate to high ice concentration areas （〉70%） are less affected （never exceeding 10%） than those in the low ice concentration. LASI and ASI consume 75 and 112 s respectively when processing the same AMSR-E time series thourghout the year 2010. To conclude, by using the LASI algorithm, not only the sea- ice concentration can be retrieved with at least an equal quality as that of the two extensively demonstrated operational algorithms, ASI and bootstrap, but also in a more efficient way than ASI.

Influence of Interannual Variability of Antarctic Sea-Ice on Summer Rainfall in Eastern China

Based on the Antarctic sea-ice coverage reanalysis data from the Hadlcy Center and other observational data during the 30-year period from 1969 to 1998, it is shown that Antarctic sea-ice coverage exhibits considerable interannual variability with a complex relation to El Ni?o and the South Oscillation (ENSO). Besides this, the ice maintains the seasonal persistence of the atmospheric circulation in high latitudes of the Southern Hemisphere. Thus it can be used as a predictor in short-term climate prediction. Both correlation and time series analyses demonstrate that summer rainfall in eastern China is closely related to Antarctic sea-ice coverage. When it is extended during boreal spring through summer, there is more rainfall in the lower reaches of the Yellow River of North China, and in contrast, less rainfall is found in the Zhujiang River basin of South China and Northeast China. A further analysis indicates that this rainfall pattern is related to the intensity of the East Asian summer monsoon caused by interannual variability of Antarctic sea-ice coverage.

Inter-comparisons of thermodynamic sea-ice modeling results using various parameterizations of radiative flux

Radiative fluxes are of primary importance in the energy and mass balance of the sea-ice cover. Various parameterizations of the radiative fluxes are studied in a thermodynamic sea-ice model. Model outputs of the surface radiative and heat fluxes and mass balance are compared with observations. The contribution of short-wave radiation is limited to a long part of winter. Therefore, simple schemes are often sufficient. Errors in estimations of the short-wave radiation are due mainly to cloud effects and occasionally to multi-reflection between surface and ice crystals in the air. The long-wave radiation plays an important role in the ice surface heat and mass balance during most part of a winter. The effect of clouds on the accuracy of the simple radiative schemes is critical, which needs further attention. In general, the accuracy of an ice model depends on that of the radiative fluxes.

A hybrid Lagrangian-Eulerian numerical model for sea-ice dynamics

A hybrid Lagrangian - Eulerian （HLE） method is developed for sea ice dynamics, which combines the high computational efficiency of finite difference method （FDM） with the high numerical accuracy of smoothed particle hydrodynamics （SPH）. In this HLE model, the sea ice cover is represented by a group of Lagrangian ice particles with their own thicknesses and concentrations. These ice variables are interpolated to the Eularian gird nodes using the Gaussian interpolation function. The FDM is used to determine the ice velocities at Eulerian grid nodes, and the velocities of Lagrangian ice particles are interpolated from these grid velocities with the Gaussian function also. The thicknesses and concentrations of ice particles are determined based on their new locations. With the HLE numerical model, the ice ridging process in a rectangular basin is simulated, and the simulated results are validated with the analytical solution. This method is also applied to the simulation of sea ice dynamics in a vortex wind field. At last, this HLE model is applied to the Bohai Sea, and the simulated concentration, thickness and velocity match the satellite images and the field observed data well.

Western Indian Ocean SST signal and anomalous Antarctic sea-ice concentration variation

Teleconnection between El Nino/La Nina-Southern Oscillation （ENSO） phenomenon and anomalous Antarctic sea-ice variation has been studied extensively.In this study,impacts of sea surface temperature in the Indian Ocean on Antarctic sea-ice change were investigated during Janaury 1979 and October 2009.Based on previous research results,sea areas in the western Indian Ocean （WIO;50°–70°E,10 °–20 °S） are selected for the resreach.All variables showed 1-10 year interannual timescales by Fast Founer Tranaform （FFT） transformation.Results show that i） strong WIO signals emerged in the anomalous changes of Antarctic sea-ice concentration;ii） significant positive correlations occurred around the Antarctic Peninsula,Ross Sea and its northwest peripheral sea region iii） negative correlation occurred in the Indian Ocean section of the Southern Ocean,Amundsen Seas,and the sea area over northern Ross Sea;and iv） the atmospheric anomalies associated with the WIO including wind,meridional heat flux,and surface air temperature over southern high latitudes were the possible factors for the teleconnection.

Satellite remote sensing of sea-ice and its operational monitoring method along the coast of China

Sea-ice is an important operational item for real timely monitoring and forecasting marine environment of China. This paper introduces an operational method of satellite remote sensing to monitor sea- ice using quantitative data of NOAA, and its contents include computer processing of AVHRR sounding data of NOAA and its program design, imagery processing of sea-ice imagery from satellite and their thematic analysis. The sea-ice satellite colour imageries processed via this software system are able to interpret sea-ice pattern, characterizing it by thickness, maximum position of ice boundary, floe concentration and dynamic process of ice changing. At the same time, analyses of the ice condition of the Bohai Sea for the two-year period (1986-1988) as monitored by satellite have been summarized.

Advantages of the latest Los Alamos Sea-Ice Model(CICE):evaluation of the simulated spatiotemporal variation of Arctic sea ice

The Los Alamos Sea-Ice Model(CICE)is one of the most popular sea-ice models.All versions of it have been the main sea-ice module coupled to climate system models.Therefore,evaluating their simulation capability is an important step in developing climate system models.Compared with observations and previous versions(CICE4.0 and CICE5.0),the advantages of CICE6.0(the latest version)are analyzed in this paper.It is found that CICE6.0 has the minimum interannual errors,and the seasonal cycle it simulates is the most consistent with observations.CICE4.0 overestimates winter sea-ice and underestimates summer sea-ice severely.Meanwhile,the errors of CICE5.0 in winter are larger than for the other versions.The main attention is paid to the perennial ice and the seasonal ice.The spatial distribution of root-mean-square errors indicates that the simulated errors are distributed in the Atlantic sector and the outer Arctic.Both CICE4.0 and CICE5.0 underestimate the concentration of the perennial ice and overestimate that of the seasonal ice in these areas.Meanwhile,CICE6.0 solves this problem commendably.Moreover,the decadal trends it simulates are comparatively the best,especially in the central Arctic sea.The other versions underestimate the decadal trend of the perennial ice and overestimate that of the seasonal ice.In addition,an index used to objectively describe the difference in the spatial distribution between the simulation and observation shows that CICE6.0 produces the best simulated spatial distribution.

Locality preserving fusion of multi-source images for sea-ice classification

We present a novel sea-ice classification framework based on locality preserving fusion of multi-source images information.The locality preserving fusion arises from two-fold,i.e.,the local characterization in both spatial and feature domains.We commence by simultaneously learning a projection matrix,which preserves spatial localities,and a similarity matrix,which encodes feature similarities.We map the pixels of multi-source images by the projection matrix to a set fusion vectors that preserve spatial localities of the image.On the other hand,by applying the Laplacian eigen-decomposition to the similarity matrix,we obtain another set of fusion vectors that preserve the feature local similarities.We concatenate the fusion vectors for both spatial and feature locality preservation and obtain the fusion image.Finally,we classify the fusion image pixels by a novel sliding ensemble strategy,which enhances the locality preservation in classification.Our locality preserving fusion framework is effective in classifying multi-source sea-ice images(e.g.,multi-spectral and synthetic aperture radar(SAR)images)because it not only comprehensively captures the spatial neighboring relationships but also intrinsically characterizes the feature associations between different types of sea-ices.Experimental evaluations validate the effectiveness of our framework.

Antarctica Sea-ice Oscillation and Its Possible Impact on Monsoon of South Sea

Antarctic sea-ice oscillation index with a seesaw pattern is defined using NCEP/NCAR reanalysis girds data of monthly Antarctica sea-ice concentration from 1979 to 2002.The relationships between the index of winter and the summer precipitations in China as well as the onset date of the summer East Asia monsoon are presented.The study result shows that the grids of correlation coefficients passed 5% confidence level between Antarctic sea-ice oscillation index and Antarctic sea-ice concentration are more than 1/3 of all grids of Antarctica sea-ice,that means the index can represent 1/3 sea-ice area.The winter index has a significant correlation with abnormal summer（June-August） precipitation in China.The area of positive correlation lies in the Yangtze River basin and its south,and that of negative correlation lies mainly in the north of Yangtze River basin.While the winter index is positive（negative）,the onset date of South China Sea monsoon is earlier（later）,with a probability of 79%（80%）.Consequently, a conceptual model is given in term of discussing the possible process between the winter Antarctic sea ice and the monsoon precipitation in China.

Quantitative Evaluation of Sea-ice Disaster in Bohai Sea Based on GOCI and Sentinel-1

The Circum-Bohai-Sea Region is an important economic zone of China.The sea ice,which occurs at each winter,is the major marine hazard of the Bohai Sea.As a result,it is very important to evaluate the damage effects quantitatively in this region,which is seldom studied and analyzed systematically using long-time-series data.In this paper,the sea-ice disaster in the Bohai Sea is evaluated quantitatively based on the Sentinel-1 and GOCI.For different hazard-bearing bodies of the marine transportation and the offshore constructions,different sea-ice-hazard indexes are defined,which can be applied to analyze the sea-ice disaster quantitatively in the Bohai Sea,including the annual and inter-annual variations in the period from 2011 to 2017.The analysis results can provide the reference of the sea-ice monitoring in the Bohai Sea.

THE FEATURES OF SEA-ICE COVER, SNOW DISTRIBUTION AND ITS DENSIFICATION IN THE CENTRAL ARCTIC OCEAN

Based on the observation of sea-ice cover and measurement of snow depths and stratigraphy during China’s First North Pole Sientific Expedition, three types of surface topography of sea ice and correspondingly three categories of snow distribution in the central Arctic are classified. It is considered that the classification will help to determine the sites for snow depth measurement, stratigraphy Observation and snowpits sampling. The snow cover is slowly accumulated during the long Arctic winter, approximately from September to early May next year, while its ablation shows abrupt from south to north. By the end of August, the snow cover is alment totally removed. The spatial distribution of snow depth is characterized by a northwardly decreasing trend, which is proposed to result from the remote vapour sources, i. e., the major vapour over the Arctic regions is transported from mid-latitudes. The stratigraphy of the snompits are characterized by the extensively existed depth hoar at the deeper part of the pits, which is probably a signal of the beginning of the long Arctic winter.The present of infiltration-congelation ice adhering to sea ice surface at the end of the ablation indicates that the annual accumulation is approximately equals to the annual ablation near north pole.

Archaeal diversity and abundance within different layers of summer sea-ice and seawater from Prydz Bay,Antarctica

Fluorescence in-situ hybridization （FISH） and 16S rRNA gene clone library analyses were used to determine the abundance and diversity of archaea in Prydz Bay, Antarctica. Correlation analysis was also performed to assess links between physicochemical parameters and archaeal abundance and diversity within the sea-ice. Samples of sea-ice and seawater were collected during the 26th Chinese National Antarctic Research Expedition. The results of FISH showed that archaea were relatively abundant within the top layer of the sea-ice, and correlation analysis suggested that the concentration of 4NH＋ might be one of the main factors underlying this distribution pattern. However, using 16S rRNA gene libraries, archaea were not detected in the top and middle layers of the sea-ice. All archaeal clones obtained from the bottom layer of the sea-ice were grouped into the Marine Group I Crenarchaeota while the archaeal clones from seawater were assigned to Marine Group I Crenarchaeota, Marine Group II Euryarchaeota, and Marine Group III Euryarchaeota. Overall, the ifndings of this study showed that the diversity of archaea in the sea-ice in Prydz Bay was low.

SATELLITE REMOTE SENSING OF SEA-ICE AND SEA SURFACE TEMPERATURE

Sea-ice and Sea Surface Temperature in offshore seas are important terms for operational monitoring and forecasting marine environment in China. The software system of regional marine environmental application designed by author is used for realtime operational monitoring sea-ice, SST, oceanic current and colours and characters of land surface. This software system processes quantitative AVHRR data from NOAA satellite to calculate calibration coefficient, solar angle correction, earth location parameter and atmospheric attenuation correction, then SST field will be produced through calculation using special SST model, and top-quality of colour composite imagery of satellite with variable spacial resolution (1, 2 or 5km) will be produced via image processing. Inside front covor Figure 1 is colour enhanced imagery with 5km resolution of NOAA satellite in offshore

Research on changes and circulations of sea-ice in Eurasian in recent 50 years

Using the monthly 1° × 1° sea-ice concentration data of Hadley center and the monthly NCEP geopotential height data from January 1953 to February 2003, temporal and spatial changing characters of sea-ice arc examined. The results show almost all of the sea-ice of eight regions was decreasing, especially all seasons in Europe. But in Asia part, those display some increasing trends in spring and winter, Abrupt times of sea-ice in Europe were at end of 1970＇ s and in Asia the times in summer/fall（spring/winter） were at end of 1980＇ s.