Spatial and Temporal Differences of Climate Suitability of Ice and Snow Sports in Major Ski Tourism Destinations in China

Ice and snow tourism in China has grown significantly since the country successfully hosted the Beijing Winter Olympics.Climatic conditions profoundly impact the development of ice and snow tourism;however,most studies have focused on constructing different climate suitability indicators for ice and snow tourism to evaluate individual regions,lacking horizontal comparative studies across multiple regions.This study aims to enrich the connotation of climate suitability for ice and snow sports,establish an evaluation model based on snowfall amount,temperature,and wind speed,and use daily meteorological data from 1991 to 2021 to horizontally compare the climate suitability for ice and snow sports in major ski tourism destinations in China.This study boasts four major findings:1)the average ice and snow sports climate index of each region decreases over time,and the overall suitability of the climate for ice and snow sports is reducing;2)northern Xinjiang exhibits the most evident regional differentiation from‘very suitable’to‘generally suitable’;3)the spatial zoning of climate suitability for ice and snow sports exhibits heterogeneity,as northern Xinjiang is divided into two‘suitable and above’zones with rotating empirical orthogonal function(REOF).Correspondingly,the four provinces of Hebei,Heilongjiang,Jilin,and Liaoning are divided into three‘generally suitable and above’zones;4)snowfall amount is the main factor affecting the climate suitability of ice and snow sports in the major ski tourist destinations in China.

Study on Image Recognition Algorithm for Residual Snow and Ice on Photovoltaic Modules

The accumulation of snow and ice on PV modules can have a detrimental impact on power generation,leading to reduced efficiency for prolonged periods.Thus,it becomes imperative to develop an intelligent system capable of accurately assessing the extent of snow and ice coverage on PV modules.To address this issue,the article proposes an innovative ice and snow recognition algorithm that effectively segments the ice and snow areas within the collected images.Furthermore,the algorithm incorporates an analysis of the morphological characteristics of ice and snow coverage on PV modules,allowing for the establishment of a residual ice and snow recognition process.This process utilizes both the external ellipse method and the pixel statistical method to refine the identification process.The effectiveness of the proposed algorithm is validated through extensive testing with isolated and continuous snow area pictures.The results demonstrate the algorithm’s accuracy and reliability in identifying and quantifying residual snow and ice on PV modules.In conclusion,this research presents a valuable method for accurately detecting and quantifying snow and ice coverage on PV modules.This breakthrough is of utmost significance for PV power plants,as it enables predictions of power generation efficiency and facilitates efficient PV maintenance during the challenging winter conditions characterized by snow and ice.By proactively managing snow and ice coverage,PV power plants can optimize energy production and minimize downtime,ensuring a sustainable and reliable renewable energy supply.

A World of Ice and Snow Being also Invaluable Asset:A Case Study of the"Snow Village"

Based on field visit and interview,the current situation of snow village in China is summarized from four aspects:core scenic spots in snow village,skiing industry in snow village,film and television industry in snow village,and ice and snow agritainment.The investigation found that there are still significant problems in homogenization,scenic area infrastructure,and government regulation in snow village.Targeted solutions are proposed from four aspects:tapping internal advantages,strengthening top-level design and infrastructure construction,promoting tourism industry upgrading,and collaborating to innovate the ice and snow tourism supply chain,in order to further promote the economic development of snow village.

Design and realization of the drawing software for snow/ice stratigraphic profile

Snow/ice stratigraphic profile is one of the traditional and important research fields in glaciology. The profile drawn by hand, however, is a tough job. Using the Object Oriented Programming (OOP) Visual Basic (VB), we developed a Drawing Software for Snow/Ice Stratigraphic Profile (DSSISP). This paper introduces the functions, designing process and realizing methods of the drawing software. It presents the key techniques and aspects that should be payed attention to during the software development. Moreover, it also proposes the ideas for complete development of this drawing system. Legend database is a key aspect in the software designing. The major functions of the software include the stratigraphic profile drawing, edition and data management, which can help researchers draw the stratigraphic profile (including the scale, stratigraphic figure, text note and legend) quickly in a computer. In addition, the database technique is used to manage drawing data, which makes the figure drawing convenient and efficient. The drawing data is also convenient to be preserved, exchanged, processed and used.

Impact of the Shrinkage of Arctic Sea Ice on Eurasian Snow Cover Changes in 1979-2021

Recent research has shown that snow cover induces extreme wintertime cooling and has detrimental impacts.Although the dramatic loss of Arctic sea ice certainly has contributed to a more extreme climate,the mechanism connecting sea-ice loss to extensive snow cover is still up for debate.In this study,a significant relationship between sea ice concentration(SIC)in the Barents-Kara(B-K)seas in November and snow cover extent over Eurasia in winter(November-January)has been found based in observational datasets and through numerical experiments.The reduction in B-K sea ice gives rise to a negative phase of Arctic Oscillation(AO),a deepened East Asia trough,and a shallow trough over Europe.These circulation anomalies lead to colder-than-normal Eurasian mid-latitude temperatures,providing favorable conditions for snowfall.In addition,two prominent cyclonic anomalies near Europe and Lake Baikal affect moisture transport and its divergence,which results in increased precipitation due to moisture advection and wind convergence.Furthermore,anomalous E-P flux shows that amplified upward propagating waves associated with the low SIC could contribute to the weakening of the polar vortex and southward breakouts of cold air.This work may be helpful for further understanding and predicting the snowfall conditions in the middle latitudes.

Retrieval of snow depth on Antarctic sea ice from the FY-3D MWRI data

The snow depth on sea ice is an extremely critical part of the cryosphere.Monitoring and understanding changes of snow depth on Antarctic sea ice is beneficial for research on sea ice and global climate change.The Microwave Radiation Imager(MWRI)sensor aboard the Chinese FengYun-3D(FY-3D)satellite has great potential for obtaining information of the spatial and temporal distribution of snow depth on the sea ice.By comparing in-situ snow depth measurements during the 35th Chinese Antarctic Research Expedition(CHINARE-35),we took advantage of the combination of multiple gradient ratio(GR(36V,10V)and GR(36V,18V))derived from the measured brightness temperature of FY-3D MWRI to estimate the snow depth.This method could simultaneously introduce the advantages of high and low GR in the snow depth retrieval model and perform well in both deep and shallow snow layers.Based on this,we constructed a novel model to retrieve the FY-3D MWRI snow depth on Antarctic sea ice.The new model validated by the ship-based observational snow depth data from CHINARE-35 and the snow depth measured by snow buoys from the Alfred Wegener Institute(AWI)suggest that the model proposed in this study performs better than traditional models,with root mean square deviations(RMSDs)of 8.59 cm and 7.71 cm,respectively.A comparison with the snow depth measured from Operation IceBridge(OIB)project indicates that FY-3D MWRI snow depth was more accurate than the released snow depth product from the U.S.National Snow and Ice Data Center(NSIDC)and the National Tibetan Plateau Data Center(NTPDC).The spatial distribution of the snow depth from FY-3D MWRI agrees basically with that from ICESat-2;this demonstrates its reliability for estimating Antarctic snow depth,and thus has great potential for understanding snow depth variations on Antarctic sea ice in the context of global climate change.

Assessment of the Mechanical Properties of Carbon-Fiber Heating Cables in Snow and Ice Melting Applications

The use of carbon-fiber heating cables(CFHC)to achieve effective melting of snow and ice deposited on roads is a method used worldwide.In this study,tensile and compressive tests have been conducted to analyze the mechan-ical properties of the CFHC and assess whether the maximum tensile and compressive strengths can meet the pavement design specifications.In order to study the aging produced by multiple cycles of heating and cooling,in particular,the CFHC was repeatedly heated in a cold chamber with an ambient temperature ranging between-20℃ and+40℃.Moreover,to evaluate how the strength of the pavement is affected by its presence,the CFHC was embedded at different depths and concrete blocks with different curing ages were subjected to relevant com-pression and splitting tensile tests.Numerical simulations based on the ANSYS software have also been performed and compared with the outcomes of the static loading tests.The results show that the CFHC embedded in the concrete does not affect the compressive splitting tensile strengths of the pavement.Overall,the CFHC meets the conditions required for continued use in road ice melting applications.

A Review of Thermo- and Diffusio-Phoresis in the Atmospheric Aerosol Scavenging Process. Part 2: Ice Crystal and Snow Scavenging

The role of phoretic forces in the identification of particles acting as ice nuclei in mixed phase cloud is discussed. A method used to identify the effective ice nucleating particles is to sample ice crystals, which are afterwards sublimated, and to examine the particles remaining after evaporation. The procedure takes into account only crystal with a maximum diameter of 20 μm, by assuming that small crystals do not scavenge aerosol during growth, and therefore that crystals contain only the effective nucleating particles. This assumption is questionable, however, as experiments have shown that even small ice crystals can scavenge aerosol. Another approach has been to compare the number and elemental composition of residual particles in small ice crystals and of aerosol near the cloud. By considering as example soot and black carbon aerosol, contradictory conclusions on their importance in the processes of ice nucleation have been reported in the literature. We suggest that, in addition to physico-chemical properties of soot/carbon aerosol particles, even the microphysical and environmental parameters involved in the transition of aerosol from gas phase to ice crystals in cloud should be considered. The contribution of phoretic forces should also be considered. After initial growth ice crystals can continue to grow by water vapour diffusion. Laboratory experiments confirm the contribution of diffusiophoresis with Stefan flow in the scavenging by snow crystals up to 3 mm in diameter. The particle scavenging efficiency of snow crystals is related to crystalline shape and depends on air relative humidity and temperature.

Light-absorbing Particles in Snow and Ice: Measurement and Modeling of Climatic and Hydrological impact

Light absorbing particles（LAP, e.g., black carbon, brown carbon, and dust） influence water and energy budgets of the atmosphere and snowpack in multiple ways. In addition to their effects associated with atmospheric heating by absorption of solar radiation and interactions with clouds, LAP in snow on land and ice can reduce the surface reflectance（a.k.a., surface darkening）, which is likely to accelerate the snow aging process and further reduces snow albedo and increases the speed of snowpack melt. LAP in snow and ice（LAPSI） has been identified as one of major forcings affecting climate change, e.g.in the fourth and fifth assessment reports of IPCC. However, the uncertainty level in quantifying this effect remains very high. In this review paper, we document various technical methods of measuring LAPSI and review the progress made in measuring the LAPSI in Arctic, Tibetan Plateau and other mid-latitude regions. We also report the progress in modeling the mass concentrations, albedo reduction, radiative forcing, and climatic and hydrological impact of LAPSI at global and regional scales. Finally we identify some research needs for reducing the uncertainties in the impact of LAPSI on global and regional climate and the hydrological cycle.

The physical structures of snow and sea ice in the Arctic section of 150°-180°W during the summer of 2010

The physical structures of snow and sea ice in the Arctic section of 150°-180°W were observed on the basis of snow-pit, ice-core, and drill-hole measurements from late July to late August 2010. Almost all the in- vestigated floes were first-year ice, except for one located north of Alaska, which was probably multi-year ice transported from north of the Canadian Arctic Archipelago during early summer. The snow covers over all the investigated floes were in the melting phase, with temperatures approaching 0℃and densities of 295-398 kg/m3. The snow covers can be divided into two to five layers of different textures, with most cases having a top layer of fresh snow, a round-grain layer in the middle, and slush and/or thin icing layers at the bottom. The first-year sea ice contained about 7%-17% granular ice at the top. There was no granular ice in the lower layers. The interior melting and desalination of sea ice introduced strong stratifications of temper- ature, salinity, density, and gas and brine volume fractions. The sea ice temperature exhibited linear cooling with depth, while the salinity and the density increased linearly with normalized depth from 0.2 to 0.9 and from 0 to 0.65, respectively. The top layer, especially the freeboard layer, had the lowest salinity and density, and consequently the largest gas content and the smallest brine content. Both the salinity and density in the ice basal layer were highly scattered due to large differences in ice porosity among the samples. The bulk average sea ice temperature, salinity, density, and gas and brine volume fractions were -0.8℃, 1.8, 837 kg/m3, 9.3% and 10.4%, respectively. The snow cover, sea ice bottom, and sea ice interior show evidences of melting during mid-August in the investigated floe located at about 87°N, 175°W.

Observed and modelled snow and ice thickness in the Arctic Ocean with CHINARE buoy data

Sea ice and the snow pack on top of it were investigated using Chinese National Arctic Research Expedition （CHINARE） buoy data. Two polar hydrometeorological drifters, known as Zeno ice stations, were deployed during CHINARE 2003. A new type of high-resolution Snow and Ice Mass Balance Arrays, known as SIMBA buoys, were deployed during CHINARE 2014. Data from those buoys were applied to investigate the thickness of sea ice and snow in the CHINARE domain. A simple approach was applied to estimate the average snow thickness on the basis of Zeno temperature data. Snow and ice thicknesses were also derived from vertical temperature profile data based on the SIMBA buoys. A one-dimensional snow and ice thermodynamic model （HIGHTSI） was applied to calculate the snow and ice thickness along the buoy drift trajectories. The model forcing was based on forecasts and analyses of the European Centre for Medium-Range Weather Forecasts （ECMWF）. The Zeno buoys drifted in a confined area during 2003-2004. The snow thickness modelled applying HIGHTSI was consistent with results based on Zeno buoy data. The SIMBA buoys drifted from 81. 1°N, 157.4°W to 73.5°N, 134.9°W in 15 months during 2014-2015. The total ice thickness increased from an initial August 2014 value of 1.97 m to a maximum value of 2.45 in before the onset of snow melt in May 2015; the last observation was approximately 1 m in late November 2015. The ice thickness based on HIGHTSI agreed with SIMBA measurements, in particular when the seasonal variation of oceanic heat flux was taken into account, but the modelled snow thickness differed from the observed one. Sea ice thickness derived from SIMBA data was reasonably good in cold conditions, but challenges remain in both snow and ice thickness in summer.

Radiative Forcing and Climate Response Due to Black Carbon in Snow and Ice

The radiative forcing and climate response due to black carbon（BC） in snow and/or ice were investigated by integrating observed effects of BC on snow/ice albedo into an atmospheric general circulation model（BCC AGCM2.0.1） developed by the National Climate Center（NCC） of the China Meteorological Administration（CMA）.The results show that the global annual mean surface radiative forcing due to BC in snow/ice is ＋0.042 W m 2,with maximum forcing found over the Tibetan Plateau and regional mean forcing exceeding ＋2.8 W m 2.The global annual mean surface temperature increased 0.071 C due to BC in snow/ice.Positive surface radiative forcing was clearly shown in winter and spring and increased the surface temperature of snow/ice in the Northern Hemisphere.The surface temperatures of snow-covered areas of Eurasia and North America in winter（spring） increased by 0.83 C（0.6 C） and 0.83 C（0.46 C）,respectively.Snowmelt rates also increased greatly,leading to earlier snowmelt and peak runoff times.With the rise of surface temperatures in the Arctic,more water vapor could be released into the atmosphere,allowing easier cloud formation,which could lead to higher thermal emittance in the Arctic.However,the total cloud forcing could decrease due to increasing cloud cover,which will offset some of the positive feedback mechanism of the clouds.

Observation and modelling of snow and sea ice mass balance and its sensitivity to atmospheric forcing during spring and summer 2007 in the Central Arctic

Snow depth and sea ice thickness were observed applying an ice mass balance buoy(IMB)in the drifting ice station Tara during the International Polar Year in 2007.Detailed in situ observations on meteorological variables and surface fluxes were taken during May to August.For this study,the operational analyses and short-term forecasts from two numerical weather prediction(NWP)models(ECMWF and HIRLAM)were extracted for the Tara drift trajectory.We compared the IMB,meteorological and surface flux observations against the NWP products,also applying a one-dimensional thermodynamic sea ice model(HIGHTSI)to calculate the snow and ice mass balance and its sensitivity to atmospheric forcing.The modelled snow depth time series,controlled by NWP-based precipitation,was in line with the observed one.HIGHTSI reproduced well the snowmelt onset,the progress of the melt,and the first date of snow-free conditions.HIGHTSI performed well also in the late August freezing season.Challenges remain to model the“false bottom”observed during the melting season.The evolution of the vertical temperature profiles in snow and ice was better simulated when the model was forced by in situ observations instead of NWP results.During the melting period,the nonlinear ice temperature profile was successfully modelled with both forcing options.During spring and the melting season,total sea ice mass balance was most sensitive to uncertainties in NWP results for the downward longwave radiation,followed by the downward shortwave radiation,air temperature,and wind speed.

Retrieval of Snow Depth on Sea Ice in the Arctic Using the FengYun-3B Microwave Radiation Imager

Snow on sea ice is a sensitive indicator of climate change because it plays an important role regulating surface and near surface air temperatures. Given its high albedo and low thermal conductivity, snow cover is considered a key reason for amplified warming in polar regions. This study focuses on retrieving snow depth on sea ice from brightness temperatures recorded by the Microwave Radiation Imager(MWRI) on board the FengYun(FY)-3 B satellite. After cross calibration with the Advanced Microwave Scanning Radiometer-EOS(AMSR-E) Level 2 A data from January 1 to May 31, 2011, MWRI brightness temperatures were used to calculate sea ice concentrations based on the Arctic Radiation and Turbulence Interaction Study Sea Ice(ASI) algorithm. Snow depths were derived according to the proportional relationship between snow depth and surface scattering at 18.7 and 36.5 GHz. To eliminate the influence of uncertainties in snow grain sizes and sporadic weather effects, seven-day averaged snow depths were calculated. These results were compared with snow depths from two external data sets, the IceBridge ICDIS4 and AMSR-E Level 3 Sea Ice products. The bias and standard deviation of the differences between the MWRI snow depth and IceBridge data were respectively 1.6 and 3.2 cm for a total of 52 comparisons. Differences between MWRI snow depths and AMSR-E Level 3 products showed biases ranging between-1.01 and-0.58 cm, standard deviations from 3.63 to 4.23 cm, and correlation coefficients from 0.61 to 0.79 for the different months.

Measurements of physical characteristics of summer snow cover on sea ice during the Third Chinese Arctic Expedition

The spatial distribution of snow cover on the central Arctic sea ice is investigated here based on the observations made during the Third Chinese Arctic Expedition. Six types of snow were observed during the expedition： new/recent snow, melt-fi＇eeze crust, icy layer, depth hoar, coarse-grained, and chains of depth hoar. Across most measurement areas, the snow surface was covered by a melt-freeze crust 2-3 cm thick, which was produced by alternate strong solar radiation and the sharp temperature decrease over the summer Arctic Ocean. There was an intermittent layer of snow and ice at the base of the snow pack. The mean bulk density of the snow was 304.01~29.00 kg/m3 along the expedition line, and the surface values were generally smaller than those of the sub- surface, confirming the principle of snow densification. In addition, the thicknesses and water equivalents of the new/recent and total-layer snow showed a decreasing trend with latitude, suggesting that the amount of snow cover and its spatial variations were mainly determined by precipitation. Snow temperature also presented significant variations in the vertical profile, and ablation and evaporation were not the primary factors in the snow assessment in late summer. The mean temperature of the surface snow was -2.01±0.96℃, which was much higher than that observed in the interface of snow and sea ice.

Characterization of sea ice and its snow cover in the Arctic Pacific sector during the summer of 2016

A comprehensive analysis of sea ice and its snow cover during the summer in the Arctic Pacific sector was conducted using the observations recorded during the 7th Chinese National Arctic Research Expedition(CHIANRE-2016)and the satellite-derived parameters of the melt pond fraction(MPF)and snow grain size(SGS)from MODIS data.The results show that there were many low-concentration ice areas in the south of 78°N,while the ice concentration and thickness increased significantly with the latitude above the north of 78°N during CHIANRE-2016.The average MPF presented a trend of increasing in June and then decreasing in early September for 2016.The average snow depth on sea ice increased with latitude in the Arctic Pacific sector.We found a widely developed depth hoar layer in the snow stratigraphic profiles.The average SGS generally increased from June to early August and then decreased from August to September in 2016,and two valley values appeared during this period due to snowfall incidents.

The Variability of the Snow and Ice Melt in Alpine Rivers in Northwestern China

The study of snow and ice melt （SIM） is important in water-scarce arid regions for the assessment of water supply and quality. These studies involve unique difficulties, especially in the calibration of hydro-models because there is no direct way to continuously measure the SIM at hydrostations. The recursive digital filter （RDF） and the isotopic hydro-geochemical method （IHM） were coupled to separate the SIM from eight observed series of alpine streamflows in northwestern China. Validation of the calibrated methods suggested a good capture of the SIM characteristics with fair accuracy in both space and time. Applications of the coupled methods in the upper reaches of the Hei River Basin （HRB） suggested a double peak curve of the SIM fraction to streamflow for the multi-component recharged （MCR） rivers, while a single peak curve was suggested for the rainfall-dominant recharged （RDR） rivers. Given inter-annual statistics of the separation, both types of the alpine rivers have experienced an obvious decrease of SIM since 196os. In the past 10 years, the SIM in the two types of rivers has risen to the levels of the 1970s, but has remained lower than the level of the 1960s. The study provided a considerable evidence to quantify the alpine SIMbased on the separation of observed data series at gauge stations. Application of the coupled method could be helpful in the calibration and validation of SIM-related hydro-models in alpine regions.

Assessment of Snow Depth over Arctic Sea Ice in CMIP6 Models Using Satellite Data

Snow depth over sea ice is an essential variable for understanding the Arctic energy budget.In this study,we evaluate snow depth over Arctic sea ice during 1993-2014 simulated by 31 models from phase 6 of the Coupled Model Intercomparison Project(CMIP6)against recent satellite retrievals.The CMIP6 models capture some aspects of the observed snow depth climatology and variability.The observed variability lies in the middle of the models’simulations.All the models show negative trends of snow depth during 1993-2014.However,substantial spatiotemporal discrepancies are identified.Compared to the observation,most models have late seasonal maximum snow depth(by two months),remarkably thinner snow for the seasonal minimum,an incorrect transition from the growth to decay period,and a greatly underestimated interannual variability and thinning trend of snow depth over areas with frequent occurrence of multi-year sea ice.Most models are unable to reproduce the observed snow depth gradient from the Canadian Arctic to the outer areas and the largest thinning rate in the central Arctic.Future projections suggest that snow depth in the Arctic will continue to decrease from 2015 to 2099.Under the SSP5-8.5 scenario,the Arctic will be almost snow-free during the summer and fall and the accumulation of snow starts from January.Further investigation into the possible causes of the issues for the simulated snow depth by some models based on the same family of models suggests that resolution,the inclusion of a hightop atmospheric model,and biogeochemistry processes are important factors for snow depth simulation.

The acid cleaning method of labware for trace element analysis in snow and ice samples

Acid cleaning processes were performed on a class 100 laminar flow clean bench assembled inside a class 1000 clean room.The ultrapure water was produced by Millipore RO (Reverse Osmosis) and Milli-Q water purification systems.The three purity grades of nitric acid used for cleaning include Merck reagent grade HNO3,Fisher 'TraceMetal' grade HNO3,and the purest Fisher 'Optima' grade HNO3.The various bottles,containers and other labware,which are in contact with the samples,are made of low-density polyethylene (LDPE) and FEP or PFA Teflon materials.The acid cleaning procedures of the bottles and other containers follow a successive four times cleaning through immersion in increasing purity of nitric acid baths at different concentrations during four weeks.The first acid bath is performed at room temperature,but the following three acid baths are heated on ceramic hotplates with a surface temperature of 45℃.In order to verify the efficiency of the acid cleaning method,cleaned bottles underwent a blank determination procedure using ELAN 6100 inductively coupled plasma spectrometry (ICP-MS).Results show that most measured trace elements are not detected and the elements detected are at very low concentrations.The blank values are comparable with that of bottles cleaned at Korea Polar Research Institute (KOPRI).Although the acid cleaning method is developed mainly for reliable measurements of trace elements in snow and ice samples,it can also be used for investigations of trace elements in other environmental samples.

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.