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1.
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. 相似文献
2.
WANG Yunhe BI Haibo HUANG Haijun LIU Yanxia LIU Yilin LIANG Xi FU Min ZHANG Zehua 《海洋湖沼学报（英文）》2019,(1):18-37
Arctic sea ice cover has decreased dramatically over the last three decades. This study quanti?es the sea ice concentration(SIC) trends in the Arctic Ocean over the period of 1979–2016 and analyzes their spatial and temporal variations. During each month the SIC trends are negative over the Arctic Ocean, wherein the largest(smallest) rate of decline found in September(March) is-0.48%/a(-0.10%/a).The summer(-0.42%/a) and autumn(-0.31%/a) seasons show faster decrease rates than those of winter(-0.12%/a) and spring(-0.20%/a) seasons. Regional variability is large in the annual SIC trend. The largest SIC trends are observed for the Kara(-0.60%/a) and Barents Seas(-0.54%/a), followed by the Chukchi Sea(-0.48%/a), East Siberian Sea(-0.43%/a), Laptev Sea(-0.38%/a), and Beaufort Sea(-0.36%/a). The annual SIC trend for the whole Arctic Ocean is-0.26%/a over the same period. Furthermore, the in?uences and feedbacks between the SIC and three climate indexes and three climatic parameters, including the Arctic Oscillation(AO), North Atlantic Oscillation(NAO), Dipole anomaly(DA), sea surface temperature(SST), surface air temperature(SAT), and surface wind(SW), are investigated. Statistically, sea ice provides memory for the Arctic climate system so that changes in SIC driven by the climate indices(AO, NAO and DA) can be felt during the ensuing seasons. Positive SST trends can cause greater SIC reductions, which is observed in the Greenland and Barents Seas during the autumn and winter. In contrast, the removal of sea ice(i.e., loss of the insulating layer) likely contributes to a colder sea surface(i.e., decreased SST), as is observed in northern Barents Sea. Decreasing SIC trends can lead to an in-phase enhancement of SAT, while SAT variations seem to have a lagged in?uence on SIC trends. SW plays an important role in the modulating SIC trends in two ways: by transporting moist and warm air that melts sea ice in peripheral seas(typically evident inthe Barents Sea) and by exporting sea ice out of the Arctic Ocean via passages into the Greenland and Barents Seas, including the Fram Strait, the passage between Svalbard and Franz Josef Land(S-FJL),and the passage between Franz Josef Land and Severnaya Zemlya(FJL-SZ). 相似文献
3.
The variation features of the Antarctic sea ice (Ⅱ) 总被引：1，自引：0，他引：1
ＴｈｅｖａｒｉａｔｉｏｎｆｅａｔｕｒｅｓｏｆｔｈｅＡｎｔａｒｃｔｉｃｓｅａｉｃｅ（Ⅱ）￥ＸｉｅＳｉｍｅｉ；ＨａｏＣｈｕｎｊｉａｎｇ；ＱｉａｎＰｉｎｇａｎｄＺｈａｎｇＬｉｎ（ＲｅｃｅｉｖｅｄＦｅｂｒｕａｒｙ６，１９９３；ａｃｃｅｐｔｅｄＡｕｇｕｓｔ２９... 相似文献
4.
Diatoms are major primary producers of microbial biomass in the Antarctica. They are found in the water and sea ice. The distribution, abundance of the ice diatoms and their relation to the environmental factors inside and outside the ice have been studied for its special role in the Antarctic Ocean ecology. In this paper we describe the abundance, distribution and composition of diatom assemblages in 相似文献
5.
1NTRODUcrIONThe bohai As is a seasonally ice-covered sea and is located in the lowest latitudes (37' -4l'N), where sea ice occurs. The bohai ffea is nearly enclosed by land in the south, the northand the west, and only connects to the Huanghai ffea through the bohai Strait in the east.The width of the strait is abeut l06 km. The boai ffea is very shallow basin with the meandepth of l8 m and the maximum depth of 78 m. The topography of the sea bottom and thecoastal regions has an importan… 相似文献
6.
Sea ice characteristics between the middle Weddell Sea and the Prydz Bay, Antarctica during the austral summer of 2003 总被引：1，自引：0，他引：1
The antarctic sea ice was investigated upon five occasions between January 4 and February 15, 2003. The investigations included: (1) estimation of sea ice distribution by ship-based observations between the middle Weddell Sea and the Prydz Bay; (2) estimation of sea ice distribution by aerial photography in the Prydz Bay; (3) direct measurements of fast ice thickness and snow cover, as well as ice core sampling in Nella Fjord; (4) estimation of melting sea ice distribution near the Zhongshan Station; and (5) observation of sea ice early freeze near the Zhongshan Station. On average, sea ice covered 14.4% of the study area. The highest sea ice concentration (80%) was observed in the Weddell Sea. First-year ice was dominant (99.7%-99.8%). Sea ice distributions in the Prydz Bay were more variable due to complex inshore topography, proximity of the Larsemann Hills, and/or grounded icebergs. The average thickness of landfast ice in NeUa Fjord was 169.5 cm. Wind-blown snow redistribution plays an important role in affecting the ice thickness in Nella Fjord. Preliminary freezing of sea ice near the Zhongshan Station follows the first two phases of the pancake cycle. 相似文献
7.
Sea-ice retreat processes are examined in the Sea of Okhotsk. A heat budget analysis in the sea-ice zone shows that net heat
flux from the atmosphere at the water surface is about 77 W m−2 on average in the active ice melt season (April) due to large solar heating, while that at the ice surface is about 12 W m−2 because of the difference in surface albedo. The temporal variation of the heat input into the upper ocean through the open
water fraction corresponds well to that of the latent heat required for ice retreat. These results suggest that heat input
into the ice–upper ocean system from the atmosphere mainly occurs at the open water fraction, and this heat input into the
upper ocean is an important heat source for ice melting. The decrease in ice area in the active melt season (April) and the
geostrophic wind just before the melt season (March) show a correlation: the decrease is large when the offshoreward wind
is strong. This relationship can be explained by the following process. Once ice concentration is decreased (increased) by
the offshoreward (onshoreward) wind just before the melt season, solar heating of the upper ocean through the increased (decreased)
open water fraction is enhanced (reduced), leading to (suppressing) a further decrease in ice concentration. This positive
feedback is regarded as the ice–ocean albedo feedback, and explains in part the large interannual variability of the ice cover
in the ice melt season. 相似文献
8.
《Deep Sea Research Part II: Topical Studies in Oceanography》1999,46(6-7):1169-1198
Simulations from a coupled ice–ocean model that highlight the importance of synoptic forcing on sea-ice dynamics are described. The ocean model is a non-hydrostatic primitive equation model coupled to a dynamic thermodynamic sea ice model. The ice modelling sensitivity study presented here is part of an ongoing research programme to define the role played by sea ice in the energy balance of the Greenland Sea. The different categories of sea ice found in the subpolar regions are simulated through the use of equations for thin ice, thick ice and the Marginal Ice Zone. A basin scale numerical model of the Greenland, Iceland and Norwegian Seas has a horizontal resolution of 20 km and a vertical grid spacing of 50 m. This resolution is adequate for resolving the mesoscale topographic structures known to control the circulation in this region. The spin-up reproduces the main features of the circulation, including the cyclonic gyres in the Norwegian and Greenland Basins and Iceland Plateau. Topographic steering of the flow is evident. The baroclinic Rossby radius of deformation is between 5 and 10 km so that the model is not eddy-resolving. The coupled ice–ocean model was run for a period of two weeks. The influence of horizontal resolution of the atmospheric model was tested by comparing simulations using six hourly wind fields from the ECMWF with those generated using six hourly fields from a HIRLAM, with horizontal resolutions of 1° and 0.18° respectively. The simulations show reasonable agreement with satellite ice compactness data and data of ice transports across sections at 79°N, 75°N and Denmark Strait. 相似文献
9.
The Fram Strait(FS) is the primary region of sea ice export from the Arctic Ocean and thus plays an important role in regulating the amount of sea ice and fresh water entering the North Atlantic seas. A 5 a(2011–2015) sea ice thickness record retrieved from Cryo Sat-2 observations is used to derive a sea ice volume flux via the FS. Over this period, a mean winter accumulative volume flux(WAVF) based on sea ice drift data derived from passivemicrowave measurements, which are provided by the National Snow and Ice Data Center(NSIDC) and the Institut Francais de Recherche pour d'Exploitation de la Mer(IFREMER), amounts to 1 029 km~3(NSIDC) and1 463 km~3(IFREMER), respectively. For this period, a mean monthly volume flux(area flux) difference between the estimates derived from the NSIDC and IFREMER drift data is –62 km~3 per month(–18×10~6 km~2 per month).Analysis reveals that this negative bias is mainly attributable to faster IFREMER drift speeds in comparison with slower NSIDC drift data. NSIDC-based sea ice volume flux estimates are compared with the results from the University of Bremen(UB), and the two products agree relatively well with a mean monthly bias of(5.7±45.9) km~3 per month for the period from January 2011 to August 2013. IFREMER-based volume flux is also in good agreement with previous results of the 1990 s. Compared with P1(1990/1991–1993/1994) and P2(2003/2004–2007/2008), the WAVF estimates indicate a decline of more than 600 km~3 in P3(2011/2012–2014/2015). Over the three periods, the variability and the decline in the sea ice volume flux are mainly attributable to sea ice motion changes, and second to sea ice thickness changes, and the least to sea ice concentration variations. 相似文献
10.
The impact of spatiotemporal variability of the ice-covered area in the Arctic on the value and interannual dynamics of turbulent heat fluxes on the ocean–atmosphere border is considered. An expected inverse dependence of the heat fluxes integrated over the Arctic area and the area of ice is not detected. The largest interannual oscillations of heat fluxes from the ocean to the atmosphere are timed to the varying position of the ice edge and, to a lesser extent, are connected with total area of ice. The role of the marginal ice zone in oceanic heat transfer is analyzed. In particular, it is shown that while moving along the marginal zone from the ice-free surface to the surface with an ice concentration of 0.8, latent and sensible heat fluxes are reduced by a factor of 2.5–3. 相似文献
11.
The characteristic low-frequency oscillation of the sea surface temperature anomaly (SSTA) of ENSO related regions, Nino 1 + 2, Nino 3, Nino 4 and Nino West, and the Southern Oscillation index (SOI) is analyzed with the method of maximum entropy spectrum. Antarctic sea ice is divided into 4 regions, i. e. East Antarctic is Region Ⅰ (0°-120° E), the region dominated by Ross Sea ice is Region Ⅱ (120° E-120° W), the region dominated by Ross Sea ice is Region Ⅲ (120° W-0°), and the whole Antarctic sea ice area is Region Ⅳ. Also, the month-to-month correlation series of the sea ice with ENSO from contemporary to 5-years lag is calculated. The optimum correlation period is selected from the series. The characteristics and the rules obtained are as follows.1. There are a common 4-years main period of the SSTA of Ninos 1 + 2,3 and 4, a rather strong 4-years secondary period and a quasi-8-years main period of that of Nino West. There are also 1. 5 and 2 to 3-years secondary periods of that of all 4 Nin 相似文献
12.
1Introduction Seaiceoccupiesthemainpartofthesurfaceof theArcticOcean.ThefocusoftheSecondChineseNa- tionalArcticResearchExpedition(CHINAE-2003) wastounderstandthevariationsofarcticmarineenvi- ronmentsandtheseaiceeffectsontheclimatechanges ofglobalextent,inmiddleandlowerlatitudesareas, especiallyinChina.Therefore,thejointsea-ice-airob- servationforseaicestudieswasoneofthekeypro- jectsinCHINARE-2003.Theinvestigatedareacov- ered3000kmfromsouthtonorthand900kmfrom westtoeast.Seventemporali… 相似文献
13.
《Ocean Modelling》2001,3(1-2):95-108
Ocean general circulation models usually use an equivalent salt-flux in order to represent the freshwater surface inflow/outflow. This unphysical approach has numerous shortcomings, especially for climate studies. A more physical representation has been originally proposed by R.X. Huang [Journal of Physical Oceanography 23 (1993) 2428–2446] for ocean models. It consists in taking into account the vertical velocity at the sea surface. Here this formulation is introduced in a coupled ice–ocean general circulation model designed for climate studies. The treatment of the ice–ocean exchanges needs special care in order to conserve salt and freshwater masses, and to correctly represent the physics involved. This formulation allows to simulate the Goldsbrough–Stommel circulation and the meridional pathway of the freshwater at the ocean surface. Furthermore, the meridional freshwater transport diagnosed using such an approach is more directly comparable to the atmospheric water-vapor transport. Nevertheless, it produces only small changes in the ocean general circulation. 相似文献
14.
《Ocean Modelling》2009,28(3-4):114-129
A newly developed global Finite Element Sea Ice–Ocean Model (FESOM) is presented. The ocean component is based on the Finite Element model of the North Atlantic (FENA) but has been substantially updated and extended. In addition to a faster realization of the numerical code, state-of-the-art parameterizations of subgrid-scale processes have been implemented. A Redi/GM scheme is employed to parameterize the effects of mesoscale eddies on lateral tracer distribution. Vertical mixing and convection are parameterized as a function of the Richardson number and the Monin–Obukhov length. A finite element dynamic-thermodynamic sea ice–model has been developed and coupled to the ocean component. Sea ice thermodynamics have been derived from the standard AWI sea ice model featuring a prognostic snow layer but neglecting internal heat storage. The dynamic part offers the viscous-plastic and elastic-viscous-plastic rheologies. All model components are discretized on a triangular/tetrahedral grid with a continuous, conforming representation of model variables. The coupled model is run in a global configuration and forced with NCEP daily atmospheric reanalysis data for 1948–2007. Results are analysed with a slight focus on the Southern Hemisphere. Many aspects of sea ice distribution and hydrography are found to be in good agreement with observations. As in most coarse-scale models, Gulf Stream transport is underestimated, but transports of the Kuroshio and the Antarctic Circumpolar Current appear realistic. The seasonal cycles of Arctic and Antarctic sea ice extents and Antarctic sea ice thickness are well captured; long- and short-term variability of ice coverage is found to be reproduced realistically in both hemispheres. The coupled model is now ready to be used in a wide range of applications. 相似文献
15.
1Introduction TheBeringSea,locatedinthesub-arcticNorth Pacific,playsanimportantroleininfluencingtheevo- lutionaryprocessoftheglobalclimaticsystembecause itsseasonalseaiceisformedinrelativelowerlatitudes (Takahashi,1999).ItisalsoasinkofatmosphericCO2, whichisoriginatedfromtheeffectivebiologicalpump inthissea.Particulatefluxdatameasuredinthesea overthelast10aindicatethattheorganic/inorganic carbonratiowasalwaysgreaterthan1,whichexplains thattheBeingSeaoccupiesasignificantpositionin theproces… 相似文献
16.
Designers and offshore operators frequently predict pack ice loading on offshore vessels by conducting scale model tests. One factor that can affect pack ice loading is the hull–ice friction coefficient. This research investigates the effect of hull–ice friction coefficients for a moored offshore vessel model and includes ice floe size and ice concentration as additional variables. A method of non-dimensional analysis is modified in order to deal with the multivariate nature of the new data. The resulting non-dimensional equation provides insight on relationships between the predicted pack ice force and the variables under investigation. The relationship between pack ice force and hull–ice friction coefficient is shown to be approximately a fourth root function, while the relationship for ice floe size, non-dimensionalised by the vessel beam, is approximately linear. The relationship between predicted pack ice force and ice concentration exists in a band bounded by cubic and sixth power curves. Applying the modified equation to the previous data sets shows the current analysis slightly improves the normalization of pack ice forces. 相似文献
17.
《Ocean Modelling》2002,4(2):137-172
A new sea ice model, GELATO, was developed at Centre National de Recherches Météorologiques (CNRM) and coupled with OPA global ocean model. The sea ice model includes elastic–viscous–plastic rheology, redistribution of ice floes of different thicknesses, and it also takes into account leads, snow cover and snow ice formation. Climatologies of atmospheric surface parameters are used to perform a 20-year global ocean–sea ice simulation, in order to compute surface heat fluxes from diagnosed sea ice or ocean surface temperature. A surface salinity restoring term is applied only to ocean grid cells with no sea ice to avoid significant surface salinity drifts, but no correction of sea surface temperature is introduced. In the Arctic the use of an ocean model substantially improves the representation of sea ice, and particularly of the ice edge in all seasons, as advection of heat and salt can be more accurately accounted for than in the case of, for example, a sea ice–ocean mixed layer model. In contrast, in the Antarctic, a region where ocean convective processes bear a much stronger influence in shaping sea ice characteristics, a better representation of convection and probably of sea ice (for example, of frazil sea ice, brine rejection) would be needed to improve the simulation of the annual cycle of the sea ice cover. The effect of the inclusion of several ice categories in the sea ice model is assessed by running a sensitivity experiment in which only one category of sea ice is considered, along with leads. In the Arctic, such an experiment clearly shows that a multicategory sea ice model better captures the position of the sea ice edge and yields much more realistic sea ice concentrations in most of the region, which is in agreement with results from Bitz et al. [J. Geophys. Res. 106 (C2) (2001) 2441–2463]. 相似文献
18.
Ｌａｔｅｒａｌｉｃｅｆｏｒｃｅａｃｔｉｎｇｏｎａｖｅｒｔｉｃａｌｃｙｌｉｎｄｅｒ￥ＳｈｉＱｉｎｇｚｅｎｇａｎｄＣｈｅｎＸｉｎｇ（ＤｅｐａｒｔｍｅｎｔｏｆＯｃｅａｎＥｎｇｉｎｅｅｒｉｎｇａｎｄＮａｖａｌＡｒｃｈｉｔｅｃｔｕｒｅ，ＴｉａｎｊｉｎＵｎｉｖｅ... 相似文献
19.
Ｕｎｃｅｒｔａｉｎｔｙａｎｄｊｏｉｎｔｐｒｏｂａｂｉｌｉｔｙｏｆｓｅａｉｃｅｌｏａｄｓ￥ＬｉｕＤｅｆｕ；ＹａｎｇＹｏｎｇｃｈｕｎ；ＷａｎｇＣｈａｏａｎｄＬｉＴｏｎｇｋｕｉ（ＯｃｅａｎＵｎｉｖｅｒｓｉｔｙｏｆＱｉｎｇｄａｏ，Ｑｉｎｇｄａｏ２６６００３，... 相似文献
20.
Numerical simulation for dynamical processes of sea ice 总被引：1，自引：0，他引：1
ＮｕｍｅｒｉｃａｌｓｉｍｕｌａｔｉｏｎｆｏｒｄｙｎａｍｉｃａｌｐｒｏｃｅｓｓｅｓｏｆｓｅａｉｃｅＷｕＨｕｉｄｉｎｇ，ＢａｉＳｈａｎ，ＺｈａｎｇＺｈａｎｈａｉａｎｄＬｉＧｕｏｑｉｎｇ（ＲｅｃｅｉｖｅｄＭａｙ１６，１９９６；ａｃｃｅｐｔｅｄＪａｎｕａｒｙ... 相似文献