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1.
Projected 21st-century changes to Arctic marine access   总被引：1，自引：0，他引：1  
Climate models project continued Arctic sea ice reductions with nearly ice-free summer conditions by the mid-21st century. However, how such reductions will realistically enable marine access is not well understood, especially considering a range of climatic scenarios and ship types. We present 21st century projections of technical shipping accessibility for circumpolar and national scales, the international high seas, and three potential navigation routes. Projections of marine access are based on monthly and daily CCSM4 sea ice concentration and thickness simulations for 2011–2030, 2046–2065, and 2080–2099 under 4.5, 6.0, and 8.5 W/m2 radiative forcing scenarios. Results suggest substantial areas of the Arctic will become newly accessible to Polar Class 3, Polar Class 6, and open-water vessels, rising from ~54 %, 36 %, and 23 %, respectively of the circumpolar International Maritime Organization Guidelines Boundary area in the late 20th century to ~95 %, 78 %, and 49 %, respectively by the late 21st century. Of the five Arctic Ocean coastal states, Russia experiences the greatest percentage access increases to its exclusive economic zone, followed by Greenland/Denmark, Norway, Canada and the U.S. Along the Northern Sea Route, July-October navigation season length averages ~120, 113, and 103 days for PC3, PC6, and OW vessels, respectively by late-century, with shorter seasons but substantial increases along the Northwest Passage and Trans-Polar Route. While Arctic navigation depends on other factors besides sea ice including economics, infrastructure, bathymetry, and weather, these projections are useful for strategic planning by governments, regulatory agencies, and the global maritime industry to assess spatial and temporal ranges of potential Arctic marine operations in the coming decades.  相似文献   

2.
Based on adjoint sensitivities of the coupled Massachusetts Institute of Technology ocean–sea ice circulation model, the potential influence of thermodynamic atmospheric forcing on the interannual variability of the September sea ice area (AREA) and volume (VOLUME) in the Arctic is investigated for the three periods 1980–1989, 1990–1999 and 2000–2009. Sensitivities suggest that only large forcing anomalies prior to the spring melting onset in May can influence the September sea ice characteristics while even small changes in the atmospheric variables during subsequent months can significantly influence September sea ice state. Specifically, AREA close to the ice edge in the Arctic seas is highly sensitive to thermodynamic atmospheric forcing changes from June to July. In contrast, VOLUME is highly sensitive to atmospheric temperature changes occurring during the same period over the central parts of the Arctic Ocean. A comparison of the sea ice conditions and sensitivities during three different periods reveals that, due to the strong decline of sea ice concentration and sea ice thickness, sea ice area became substantially more sensitive to the same amplitude thermodynamic atmospheric forcing anomalies during 2000–2009 relative to the earlier periods. To obtain a quantitative estimate of changes that can be expected from existing atmospheric trends, adjoint sensitivities are multiplied by monthly temperature differences between 1980s and two following decades. Strongest contributions of surface atmospheric temperature differences to AREA and VOLUME changes are observed during May and September. The strongest contribution from the downward long-wave heat flux to AREA changes occurs in September and to VOLUME changes in July–August. About 62 % of the AREA decrease simulated by the model can be explained by summing all contributions to the thermodynamic atmospheric forcing. The changing sea ice state (sensitivity) is found to enhance the decline and accounts for about one third of the explained reduction. For the VOLUME decrease, the explained fraction of the decrease is only about 37 %.  相似文献   

3.
Arctic climate change in 21st century CMIP5 simulations with EC-Earth   总被引：4，自引：2，他引：2  
The Arctic climate change is analyzed in an ensemble of future projection simulations performed with the global coupled climate model EC-Earth2.3. EC-Earth simulates the twentieth century Arctic climate relatively well but the Arctic is about 2 K too cold and the sea ice thickness and extent are overestimated. In the twenty-first century, the results show a continuation and strengthening of the Arctic trends observed over the recent decades, which leads to a dramatically changed Arctic climate, especially in the high emission scenario RCP8.5. The annually averaged Arctic mean near-surface temperature increases by 12 K in RCP8.5, with largest warming in the Barents Sea region. The warming is most pronounced in winter and autumn and in the lower atmosphere. The Arctic winter temperature inversion is reduced in all scenarios and disappears in RCP8.5. The Arctic becomes ice free in September in all RCP8.5 simulations after a rapid reduction event without recovery around year 2060. Taking into account the overestimation of ice in the twentieth century, our model results indicate a likely ice-free Arctic in September around 2040. Sea ice reductions are most pronounced in the Barents Sea in all RCPs, which lead to the most dramatic changes in this region. Here, surface heat fluxes are strongly enhanced and the cloudiness is substantially decreased. The meridional heat flux into the Arctic is reduced in the atmosphere but increases in the ocean. This oceanic increase is dominated by an enhanced heat flux into the Barents Sea, which strongly contributes to the large sea ice reduction and surface-air warming in this region. Increased precipitation and river runoff lead to more freshwater input into the Arctic Ocean. However, most of the additional freshwater is stored in the Arctic Ocean while the total Arctic freshwater export only slightly increases.  相似文献   

4.
The predictability of the Arctic sea ice is investigated at the interannual time scale using decadal experiments performed within the framework of the fifth phase of the Coupled Model Intercomparison Project with the CNRM-CM5.1 coupled atmosphere–ocean global climate model. The predictability of summer Arctic sea ice extent is found to be weak and not to exceed 2 years. In contrast, robust prognostic potential predictability (PPP) up to several years is found for winter sea ice extent and volume. This predictability is regionally contrasted. The marginal seas in the Atlantic sector and the central Arctic show the highest potential predictability, while the marginal seas in the Pacific sector are barely predictable. The PPP is shown to decrease drastically in the more recent period. Regarding sea ice extent, this decrease is explained by a strong reduction of its natural variability in the Greenland–Iceland–Norwegian Seas due to the quasi-disappearance of the marginal ice zone in the center of the Greenland Sea. In contrast, the decrease of predictability of sea ice volume arises from the combined effect of a reduction of its natural variability and an increase in its chaotic nature. The latter is attributed to a thinning of sea ice cover over the whole Arctic, making it more sensitive to atmospheric fluctuations. In contrast to the PPP assessment, the prediction skill as measured by the anomaly correlation coefficient is found to be mostly due to external forcing. Yet, in agreement with the PPP assessment, a weak added value of the initialization is found in the Atlantic sector. Nevertheless, the trend-independent component of this skill is not statistically significant beyond the forecast range of 3 months. These contrasted findings regarding potential predictability and prediction skill arising from the initialization suggest that substantial improvements can be made in order to enhance the prediction skill.  相似文献   

5.
Along with significant changes in the Arctic climate system, the largest year-to-year variation in sea-ice extent (SIE) has occurred in the Laptev, East Siberian, and Chukchi seas (defined here as the area of focus, AOF), among which the two highly contrasting extreme events were observed in the summers of 2007 and 1996 during the period 1979–2012. Although most efforts have been devoted to understanding the 2007 low, a contrasting high September SIE in 1996 might share some related but opposing forcing mechanisms. In this study, we investigate the mechanisms for the formation of these two extremes and quantitatively estimate the cloud-radiation-water vapor feedback to the sea-ice-concentration (SIC) variation utilizing satellite-observed sea-ice products and the NASA MERRA reanalysis. The low SIE in 2007 was associated with a persistent anticyclone over the Beaufort Sea coupled with low pressure over Eurasia, which induced anomalous southerly winds. Ample warm and moist air from the North Pacific was transported to the AOF and resulted in positive anomalies of cloud fraction (CF), precipitable water vapor (PWV), surface LWnet (down-up), total surface energy and temperature. In contrast, the high SIE event in 1996 was associated with a persistent low pressure over the central Arctic coupled with high pressure along the Eastern Arctic coasts, which generated anomalous northerly winds and resulted in negative anomalies of above mentioned atmospheric parameters. In addition to their immediate impacts on sea ice reduction, CF, PWV and radiation can interplay to lead to a positive feedback loop among them, which plays a critical role in reinforcing sea ice to a great low value in 2007. During the summer of 2007, the minimum SIC is 31 % below the climatic mean, while the maximum CF, LWnet and PWV can be up to 15 %, 20 Wm?2, and 4 kg m?3 above. The high anti-correlations (?0.79, ?0.61, ?0.61) between the SIC and CF, PWV, and LWnet indicate that CF, PWV and LW radiation are indeed having significant impacts on the SIC variation. A new record low occurred in the summer of 2012 was mainly triggered by a super storm over the central Arctic Ocean in early August that caused substantial mechanical ice deformation on top of the long-term thinning of an Arctic ice pack that had become more dominated by seasonal ice.  相似文献   

6.
Simulations performed with the climate model LOVECLIM, aided with a simple data assimilation technique that forces a close matching of simulated and observed surface temperature variations, are able to reasonably reproduce the observed changes in the lower atmosphere, sea ice and ocean during the second half of the twentieth century. Although the simulated ice area slightly increases over the period 1980–2000, in agreement with observations, it decreases by 0.5 × 106 km2 between early 1960s and early 1980s. No direct and reliable sea ice observations are available to firmly confirm this simulated decrease, but it is consistent with the data used to constrain model evolution as well as with additional independent data in both the atmosphere and the ocean. The simulated reduction of the ice area between the early 1960s and early 1980s is similar to the one simulated over that period as a response to the increase in greenhouse gas concentrations in the atmosphere while the increase in ice area over the last decades of the twentieth century is likely due to changes in atmospheric circulation. However, the exact contribution of external forcing and internal variability in the recent changes cannot be precisely estimated from our results. Our simulations also reproduce the observed oceanic subsurface warming north of the continental shelf of the Ross Sea and the salinity decrease on the Ross Sea continental shelf. Parts of those changes are likely related to the response of the system to the external forcing. Modifications in the wind pattern, influencing the ice production/melting rates, also play a role in the simulated surface salinity decrease.  相似文献   

7.
《大气与海洋》2013,51(1):101-118
Abstract

A number of recent sea‐ice and ocean changes in the Arctic and subarctic regions are simulated using the global University of Victoria (UVic) Earth System Climate Model version 2.6. This is an intermediate complexity model which includes a three‐dimensional ocean model (MOM 2.2), an energy‐moisture balance model for the atmosphere with heat and moisture transport, and a dynamic‐thermodynamic sea‐ice model with elastic‐viscous‐plastic rheology. The model is first spun up for 1800 years with monthly wind stress forcing derived from the National Centers for Environmental Prediction (NCEP) climatology winds and a pre‐industrial atmospheric CO2 concentration of 280 ppm. After a second spin‐up for the period 1800–1947 with daily climatology winds‐tress forcing, and a linearly increasing atmospheric CO2 concentration, the model is run with interannually varying wind stresses for the period 1948–2002 with an average forcing interval of 2.5 days and an exponentially increasing atmospheric CO2 concentration varying from 315 to 365 ppm. However, the analysis of the model output is only carried out for the years 1955–2002.

The simulated maximum and minimum sea‐ice areas for the Arctic are within 6% of the observed climatologies for the years 1978–2001. The model output also shows a small downward trend in sea‐ice extent, which, however, is smaller than has been observed during the past few decades. In addition, the model simulates a decrease in sea‐ice thickness in the SCICEX (SCientific ICe EXpeditions) measurement area in the central Arctic that is consistent with, but smaller than, that observed from submarine sonar profiling data.

The observed variability and magnitude of the export of sea ice through Fram Strait is quite well captured in the simulation. The change in correlation between the North Atlantic Oscillation (NAO) index and the sea‐ice export around 1977 as found in a data study by Hilmer and Jung (2000) is also reproduced. Within the Arctic basin the model simulates well the patterns and the timing of the two major regimes of wind‐forced sea‐ice drift circulation (cyclonic and anticyclonic) as found earlier by Proshutinsky and Johnson (1997). The influence of variations in the Fram Strait ice export on the strength of the North Atlantic thermohaline circulation and surface air temperature are also determined. In particular, it is shown that 3–4 years after a large ice export, the maximum meridional overturning streamfunction decreases by more than 10%.

The temperature and salinity increase at depths of 200–300 m, as observed in the eastern Arctic by Morison et al. (1998), between the USS Pargo cruise in 1993 and the Environmental Working Group (EWG) Joint USRussian Arctic Atlas climatology for the years 1948–87, are just visible in the model simulation. The increases are more noticeable, however, when the ocean model data are averaged over the pentade 1995–2000 and compared with model data averaged over the pentade 1955–60. The fact that these, and some of the other modelled changes, are smaller than the observed changes can likely be attributed to the relatively coarse resolution of the UVic Earth System Climate Model (3.6°E‐W and 1.8°N‐S). Nevertheless, the fact that the model captures qualitatively many of the recent sea‐ice and ocean changes in the Arctic suggests that it can be successfully used to investigate other Arctic‐North Atlantic Ocean climate interactions during past and future eras.  相似文献   

8.
Polar climate studies are severely hampered by the sparseness of the sea ice observations. We aim at filling this critical gap by producing two 5-member sea ice historical simulations strongly constrained by ocean and atmosphere observational data and covering the 1958–2006 and 1979–2012 periods. This is the first multi-member sea ice reconstruction covering more than 50 years. The obtained sea ice conditions are in reasonable agreement with the few available observations. These best estimates of sea ice conditions serve subsequently as initial sea ice conditions for a set of 28 3-year-long retrospective climate predictions. We compare it to a set in which the sea ice initial conditions are taken from a single-member sea ice historical simulation constrained by atmosphere observations only. We find an improved skill in predicting the Arctic sea ice area and Arctic near surface temperature but a slightly degraded skill in predicting the Antarctic sea ice area. We also obtain a larger spread between the members for the sea ice variables, thus more representative of the forecast error.  相似文献   

9.
Abstract

The Barents Sea is divided into a northern and a southern part by the Polar Front (at about 75–76° N) where Atlantic waters descend under Arctic waters. Near to and north of the Polar Front, the spring bloom of phytoplankton is triggered by the stability induced in the upper 20 m by the melting of ice. The pycnocline is too strong to be eroded by wind. Primary productivity after the bloom is therefore small and largely regenerative. Underneath the pycnocline there is a 3–5 m thick layer characterized by dense, slow‐growing algal populations. New productivity north of the Polar Front is no more than 40 g C m?2 a?1.

In permanently open waters south of the Polar Front, the spring bloom starts in early May. Rhythmic wind‐induced mixing related to the atmospheric low‐pressure belt reaches an average 40–60 m depth in the growth season, and secondary phytoplankton maxima may arise. As a result, new annual productivity is more than doubled, i.e. 90 g C m?2 a?1, relative to the same system without wind. Although productivity is highest south of the Polar Front, it is more concentrated north of it, in the sense that high new production is mainly related to a 20–50 km wide belt that sweeps the area following the ice edge northwards while the ice melts through the summer.  相似文献   

10.
The atmospheric general circulation model EC-EARTH-IFS has been applied to investigate the influence of both a reduced and a removed Arctic sea ice cover on the Arctic energy budget and on the climate of the Northern mid-latitudes. Three 40-year simulations driven by original and modified ERA-40 sea surface temperatures and sea ice concentrations have been performed at T255L62 resolution, corresponding to 79?km horizontal resolution. Simulated changes between sensitivity and reference experiments are most pronounced over the Arctic itself where the reduced or removed sea ice leads to strongly increased upward heat and longwave radiation fluxes and precipitation in winter. In summer, the most pronounced change is the stronger absorption of shortwave radiation which is enhanced by optically thinner clouds. Averaged over the year and over the area north of 70° N, the negative energy imbalance at the top of the atmosphere decreases by about 10?W/m2 in both sensitivity experiments. The energy transport across 70° N is reduced. Changes are not restricted to the Arctic. Less extreme cold events and less precipitation are simulated in sub-Arctic and Northern mid-latitude regions in winter.  相似文献   

11.
The area integral of the sea ice thickness in the Arctic Basin is estimated from the measurements of sea ice surface fluctuations at drift-ice stations. The 1970–1990 linear trend is indicative of an approximately 10-cm reduction in the average sea ice thickness over the entire Arctic Basin, which makes 3% of the average ice thickness (about 3 m). Seasonal changes made 40 cm. The amplitude of variations of the average ice thickness in that period is 20 cm with a period of changes of approximately 6–8 years. The observations were interrupted during 1991–2003 and then resumed in 2004. During 1990–2005, the old ice thickness over the entire Arctic Basin decreased, on average, by 110 cm.  相似文献   

12.
This study examines pre-industrial control simulations from CMIP5 climate models in an effort to better understand the complex relationships between Arctic sea ice and the stratosphere, and between Arctic sea ice and cold winter temperatures over Eurasia. We present normalized regressions of Arctic sea-ice area against several atmospheric variables at extended lead and lag times. Statistically significant regressions are found at leads and lags, suggesting both atmospheric precursors of, and responses to, low sea ice; but generally, the regressions are stronger when the atmosphere leads sea ice, including a weaker polar stratospheric vortex indicated by positive polar cap height anomalies. Significant positive midlatitude eddy heat flux anomalies are also found to precede low sea ice. We argue that low sea ice and raised polar cap height are both a response to this enhanced midlatitude eddy heat flux. The so-called "warm Arctic, cold continents" anomaly pattern is present one to two months before low sea ice, but is absent in the months following low sea ice, suggesting that the Eurasian cooling and low sea ice are driven by similar processes. Lastly, our results suggest a dependence on the geographic region of low sea ice, with low Barents–Kara Sea ice correlated with a weakened polar stratospheric vortex, whilst low Sea of Okhotsk ice is correlated with a strengthened polar vortex. Overall, the results support a notion that the sea ice, polar stratospheric vortex and Eurasian surface temperatures collectively respond to large-scale changes in tropospheric circulation.  相似文献   

13.
Arctic sea ice responds to atmospheric forcing in primarily a top-down manner, whereby near-surface air circulation and temperature govern motion, formation, melting, and accretion. As a result, concentrations of sea ice vary with phases of many of the major modes of atmospheric variability, including the North Atlantic Oscillation, the Arctic Oscillation, and the El Niño-Southern Oscillation. However, until this present study, variability of sea ice by phase of the leading mode of atmospheric intraseasonal variability, the Madden–Julian Oscillation (MJO), which has been found to modify Arctic circulation and temperature, remained largely unstudied. Anomalies in daily change in sea ice concentration were isolated for all phases of the real-time multivariate MJO index during both summer (May–July) and winter (November–January) months. The three principal findings of the current study were as follows. (1) The MJO projects onto the Arctic atmosphere, as evidenced by statistically significant wavy patterns and consistent anomaly sign changes in composites of surface and mid-tropospheric atmospheric fields. (2) The MJO modulates Arctic sea ice in both summer and winter seasons, with the region of greatest variability shifting with the migration of the ice margin poleward (equatorward) during the summer (winter) period. Active regions of coherent ice concentration variability were identified in the Atlantic sector on days when the MJO was in phases 4 and 7 and the Pacific sector on days when the MJO was in phases 2 and 6, all supported by corresponding anomalies in surface wind and temperature. During July, similar variability in sea ice concentration was found in the North Atlantic sector during MJO phases 2 and 6 and Siberian sector during MJO phases 1 and 5, also supported by corresponding anomalies in surface wind. (3) The MJO modulates Arctic sea ice regionally, often resulting in dipole-shaped patterns of variability between anomaly centers. These results provide an important first look at intraseasonal variability of sea ice in the Arctic.  相似文献   

14.
This study analyses the atmospheric boundary layer over the Bilbao metropolitan area during summer (13–18 Jul 2009) and winter (20–29 Jan 2010) episodes using the Environment–High Resolution Limited Area Model (Enviro-HIRLAM) coupled with the building effect parameterisation (BEP). The main objectives of this study are: to evaluate the performance of the model to simulate the land–sea breezes over this complex terrain; to assess the simulations with the integration of an urban parameterisation in Enviro-HIRLAM and finally; and to analyse the urban–atmosphere interactions. Even if the hydrostraticity of the model is a limitation to simulate atmospheric flows over complex terrain, sensibility tests demonstrate that 2.4 km is the optimal horizontal resolution over Bilbao that allows at the same time: to obtain satisfactory reproducibility of the large-scale processes and to explore the urban effects at local scale. During the summer episode, a typical regime of diurnal sea breeze from the NW-N-NE direction and nocturnal valley breezes from the SE direction are observed over Bilbao. The urban heat island (UHI) phenomenon is developed in the city centre expanding to the suburbs from 22 to 10 local time (LT), covering an area of 130 km2. The maximum UHI intensity, 1 °C, is reached at the end of the night (5 LT), and it is advected 12 km towards the sea by the land breezes. The urban boundary layer (UBL) height amplitude varies from 100 (night time) to 1,360 m (at 14 LT). During the winter episode, the land breeze dominates the atmospheric diffusion during the day and night time. The maximum UHI intensity, 1.7 °C, is observed at 01 LT. It is spread and remained over the city covering an area of 160 km2, with a vertical extension of 33 m. The UBL reaches 780 m height at 16 LT the following day.  相似文献   

15.
Sea ice variability in the Barents Sea and its impact on climate are analyzed using a 465-year control integration of a global coupled atmosphere–ocean–sea ice model. Sensitivity simulations are performed to investigate the response to an isolated sea ice anomaly in the Barents Sea. The interannual variability of sea ice volume in the Barents Sea is mainly determined by variations in sea ice import into Barents Sea from the Central Arctic. This import is primarily driven by the local wind field. Horizontal oceanic heat transport into the Barents Sea is of minor importance for interannual sea ice variations but is important on longer time scales. Events with strong positive sea ice anomalies in the Barents Sea are due to accumulation of sea ice by enhanced sea ice imports and related NAO-like pressure conditions in the years before the event. Sea ice volume and concentration stay above normal in the Barents Sea for about 2 years after an event. This strongly increases the albedo and reduces the ocean heat release to the atmosphere. Consequently, air temperature is much colder than usual in the Barents Sea and surrounding areas. Precipitation is decreased and sea level pressure in the Barents Sea is anomalously high. The large-scale atmospheric response is limited with the main impact being a reduced pressure over Scandinavia in the year after a large ice volume occurs in the Barents Sea. Furthermore, high sea ice volume in the Barents Sea leads to increased sea ice melting and hence reduced surface salinity. Generally, the climate response is smallest in summer and largest in winter and spring.  相似文献   

16.
Abstract

Using 18O/16O ratio measurements, sea ice and brackish ice have been identified in a 10‐m ice core from Ward Hunt Ice Shelf. Brackish ice constitutes 62% of the core, and sea ice the remainder. The sea ice and brackish ice occur in alternating layers of 2–4 m thickness. The mean salinity of brackish ice (0.22) is an order of magnitude lower than that of the sea ice (1.26). The discrete sea and brackish ice layers and their individual salinity populations have been maintained apparently while the ice has aged and been raised about 40–50 m from the bottom of the ice shelf to its surface, a process taking roughly 400–500 years. Thin sections of the brackish ice reveal variable textures and an almost complete absence of cellular substructure that is associated with brine inclusion and retention in modern sea ice. Thin sections of the old sea ice show evidence of the former cellular substructure that appears to have been altered from the original. The discrete salinity populations and variable textures are briefly discussed.  相似文献   

17.
FGOALS_gg1.1极地气候模拟   总被引：4，自引：0，他引：4  
对中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室发展的气候系统模式FGOALS_g1.1的极地气候模拟现状进行了较为全面的评估.结果表明,FGOALS_g1.1对南北极海冰的主要分布特征、季节变化和年代际变化趋势具有一定的模拟能力.但也注意到,与观测相比,模式存在以下几方面的问题:(1)模拟的海冰总面积北极偏多,而南极偏少.北极,北大西洋海冰全年明显偏多;夏季,西伯利亚沿海海冰偏多,而波弗特海海冰偏少.南极,威德尔海和罗斯海冬季海冰偏少.南北极海冰边缘都存在异常的较大范围密集度很小的碎冰区,夏季尤为显著.(2)海冰流速在南北极海冰边缘和南极大陆沿岸附近较大.北极,模式没能模拟出波弗特涡流,并且由于模式网格中北极点的处理问题,造成其附近错误的海冰流场及厚度分布.这些海冰偏差与模式模拟的大气和海洋状况有着密切的联系.进一步分析表明,FGOALS_g1.1模拟的冰岛低压和南极绕极西风带明显偏弱,其通过大气环流和海表面风应力影响向极地的热量输送,在很大程度上导致上述的海冰偏差.此外,耦合模式中大气-海冰-海洋的相互作用可以放大子模式中的偏差.  相似文献   

18.
Based on the simulated ice thickness data from 1949 to 1999, monthly mean temperature data from 160 stations, and monthly mean 1°×1° precipitation data reconstructed from 749 stations in China from 1951 to 2000, the relationship between the Arctic sea ice thickness distribution and the climate of China is analyzed by using the singular value decomposition method. Climate patterns of temperature and precipitation are obtained through the rotated empirical orthogonal function analysis. The results are as follows. (1) Sea ice in Arctic Ocean has a decreasing trend as a whole, and varies with two major periods of 12-14 and 16-20 yr, respectively. (2) When sea ice is thicker in central Arctic Ocean and Beaufort-Chukchi Seas, thinner in Barents-Kara Seas and Baffin Bay-Labrador Sea, precipitation is less in southern China, Tibetan Plateau, and the north part of northeastern China than normal, and vice versa. (3) When sea ice is thinner in the whole Arctic seas, precipitation is less over the middle and lower reaches of Yellow River and north part of northeastern China, more in Tibetan Plateau and south part of northeastern China than normal, and the reverse is also true. (4) When sea ice is thinner in central Arctic Ocean, East Siberian Sea, Beaufort-Chukchi Seas, and Greenland Sea; and thicker in Baffin Bay-Labrador Sea, air temperature is higher in northeastern China, southern Tibetan Plateau, and Hainan Island than normal. (5) When sea ice is thicker in East Siberian Sea 5 months earlier, thinner in Baffin Bay-Labrador Sea 7-15 months earlier, air temperature is lower over the north of Tibetan Plateau and higher in the north part of northwestern China than normal, and a reverse correlation also exists.  相似文献   

19.
Arctic marginal ice zone (MIZ) widths in the Atlantic sector were measured during the months of maximum sea ice extent (February–April) for years 1979–2010 using a novel method based on objective curves through idealized sea ice concentration fields that satisfied Laplace’s equation. Over the record, the Labrador Sea MIZ (MIZL) had an average width of 122 km and narrowed by 28 % while moving 254 km poleward, the Greenland Sea MIZ (MIZG) had an average width of 98 km and narrowed by 43 % while moving 158 km west toward the Greenland coast, and the Barents Sea MIZ (MIZB) had an average width of 136 km and moved 259 km east toward the Eurasian coast without a trend in width. Trends in MIZ position and width were consistent with a warming Arctic and decreasing sea ice concentrations over the record. Beyond the trends, NAO-like atmospheric patterns influenced interannual variability in MIZ position and width: MIZL widened and moved southeast under anomalously strong northerly flow conducive to advection of sea ice into the Labrador Sea, MIZG widened and moved northeast under anomalously weak northerly flow conducive to diminishing the westward component of sea ice drift, and MIZB widened and moved poleward at the expense of pack ice under anomalously strong southwesterly flow conducive to enhancing oceanic heat flux into the Barents Sea. In addition, meridional flow anomalies associated with the NAO per se moved MIZB east and west by modulating sea ice concentration over the Barents Sea.  相似文献   

20.
Freshwater (FW) leaves the Arctic Ocean through sea-ice export and the outflow of low-salinity upper ocean water. Whereas the variability of the sea-ice export is known to be mainly caused by changes in the local wind and the thickness of the exported sea ice, the mechanisms that regulate the variability of the liquid FW export are still under investigation. To better understand these mechanisms, we present an analysis of the variability of the liquid FW export from the Arctic Ocean for the period 1950–2007, using a simulation from an energy and mass conserving global ocean–sea ice model, coupled to an Energy Moisture Balance Model of the atmosphere, and forced with daily winds from the NCEP reanalysis. Our results show that the simulated liquid FW exports through the Canadian Arctic Archipelago (CAA) and the Fram Strait lag changes in the large-scale atmospheric circulation over the Arctic by 1 and 6 years, respectively. The variability of the liquid FW exports is caused by changes in the cyclonicity of the atmospheric forcing, which cause a FW redistribution in the Arctic through changes in Ekman transport in the Beaufort Gyre. This in turn causes changes in the sea surface height (SSH) and salinity upstream of the CAA and Fram Strait, which affect the velocity and salinity of the outflow. The SSH changes induced by the large-scale atmospheric circulation are found to explain a large part of the variance of the liquid FW export, while the local wind plays a much smaller role. We also show that during periods of increased liquid FW export from the Arctic, the strength of the simulated Atlantic meridional overturning circulation is reduced and the ocean heat transport into the Arctic is increased. These results are particularly relevant in the context of global warming, as climate simulations predict an increase in the liquid FW export from the Arctic during the twenty-first century.  相似文献   

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