2017 Vol. 36, No. 8
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2017, 36(8): 1-8.
doi: 10.1007/s13131-017-1029-8
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This paper is focused on the seasonality change of Arctic sea ice extent (SIE) from 1979 to 2100 using newly available simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). A new approach to compare the simulation metric of Arctic SIE between observation and 31 CMIP5 models was established. The approach is based on four factors including the climatological average, linear trend of SIE, span of melting season and annual range of SIE. It is more objective and can be popularized to other comparison of models. Six good models (GFDL-CM3, CESM1-BGC, MPI-ESM-LR, ACCESS-1.0, HadGEM2-CC, and HadGEM2-AO in turn) are found which meet the criterion closely based on above approach. Based on ensemble mean of the six models, we found that the Arctic sea ice will continue declining in each season and firstly drop below 1 million km2 (defined as the ice-free state) in September 2065 under RCP4.5 scenario and in September 2053 under RCP8.5 scenario. We also study the seasonal cycle of the Arctic SIE and find out the duration of Arctic summer (melting season) will increase by about 100 days under RCP4.5 scenario and about 200 days under RCP8.5 scenario relative to current circumstance by the end of the 21st century. Asymmetry of the Arctic SIE seasonal cycle with later freezing in fall and early melting in spring, would be more apparent in the future when the Arctic climate approaches to "tipping point", or when the ice-free Arctic Ocean appears. Annual range of SIE (seasonal melting ice extent) will increase almost linearly in the near future 30-40 years before the Arctic appears ice-free ocean, indicating the more ice melting in summer, the more ice freezing in winter, which may cause more extreme weather events in both winter and summer in the future years.
This paper is focused on the seasonality change of Arctic sea ice extent (SIE) from 1979 to 2100 using newly available simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). A new approach to compare the simulation metric of Arctic SIE between observation and 31 CMIP5 models was established. The approach is based on four factors including the climatological average, linear trend of SIE, span of melting season and annual range of SIE. It is more objective and can be popularized to other comparison of models. Six good models (GFDL-CM3, CESM1-BGC, MPI-ESM-LR, ACCESS-1.0, HadGEM2-CC, and HadGEM2-AO in turn) are found which meet the criterion closely based on above approach. Based on ensemble mean of the six models, we found that the Arctic sea ice will continue declining in each season and firstly drop below 1 million km2 (defined as the ice-free state) in September 2065 under RCP4.5 scenario and in September 2053 under RCP8.5 scenario. We also study the seasonal cycle of the Arctic SIE and find out the duration of Arctic summer (melting season) will increase by about 100 days under RCP4.5 scenario and about 200 days under RCP8.5 scenario relative to current circumstance by the end of the 21st century. Asymmetry of the Arctic SIE seasonal cycle with later freezing in fall and early melting in spring, would be more apparent in the future when the Arctic climate approaches to "tipping point", or when the ice-free Arctic Ocean appears. Annual range of SIE (seasonal melting ice extent) will increase almost linearly in the near future 30-40 years before the Arctic appears ice-free ocean, indicating the more ice melting in summer, the more ice freezing in winter, which may cause more extreme weather events in both winter and summer in the future years.
2017, 36(8): 9-19.
doi: 10.1007/s13131-016-0886-x
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Sea ice in the Arctic has been reducing rapidly in the past half century due to global warming. This study analyzes the variations of sea ice extent in the entire Arctic Ocean and its sub regions. The results indicate that sea ice extent reduction during 1979-2013 is most significant in summer, following by that in autumn, winter and spring. In years with rich sea ice, sea ice extent anomaly with seasonal cycle removed changes with a period of 4-6 years. The year of 2003-2006 is the ice-rich period with diverse regional difference in this century. In years with poor sea ice, sea ice margin retreats further north in the Arctic. Sea ice in the Fram Strait changes in an opposite way to that in the entire Arctic. Sea ice coverage index in melting-freezing period is an critical indicator for sea ice changes, which shows an coincident change in the Arctic and sub regions. Since 2002, Region C2 in north of the Pacific sector contributes most to sea ice changes in the central Aarctic, followed by C1 and C3. Sea ice changes in different regions show three relationships. The correlation coefficient between sea ice coverage index of the Chukchi Sea and that of the East Siberian Sea is high, suggesting good consistency of ice variation. In the Atlantic sector, sea ice changes are coincided with each other between the Kara Sea and the Barents Sea as a result of warm inflow into the Kara Sea from the Barents Sea. Sea ice changes in the central Arctic are affected by surrounding seas.
Sea ice in the Arctic has been reducing rapidly in the past half century due to global warming. This study analyzes the variations of sea ice extent in the entire Arctic Ocean and its sub regions. The results indicate that sea ice extent reduction during 1979-2013 is most significant in summer, following by that in autumn, winter and spring. In years with rich sea ice, sea ice extent anomaly with seasonal cycle removed changes with a period of 4-6 years. The year of 2003-2006 is the ice-rich period with diverse regional difference in this century. In years with poor sea ice, sea ice margin retreats further north in the Arctic. Sea ice in the Fram Strait changes in an opposite way to that in the entire Arctic. Sea ice coverage index in melting-freezing period is an critical indicator for sea ice changes, which shows an coincident change in the Arctic and sub regions. Since 2002, Region C2 in north of the Pacific sector contributes most to sea ice changes in the central Aarctic, followed by C1 and C3. Sea ice changes in different regions show three relationships. The correlation coefficient between sea ice coverage index of the Chukchi Sea and that of the East Siberian Sea is high, suggesting good consistency of ice variation. In the Atlantic sector, sea ice changes are coincided with each other between the Kara Sea and the Barents Sea as a result of warm inflow into the Kara Sea from the Barents Sea. Sea ice changes in the central Arctic are affected by surrounding seas.
2017, 36(8): 20-33.
doi: 10.1007/s13131-017-1027-x
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A slowdown of sea surface height (SSH) rise occurred in the Nordic (GIN) seas around 2004. In this study, SSH satellite data and constructed steric height data for the decades before and after 2004 (i.e., May 1994 to April 2014) were used for comparative analysis. The findings indicate that the rate of slowdown of SSH rises in the GIN seas (3.0 mm/a) far exceeded that of the global mean (0.6 mm/a). In particular, the mean steric height of the GIN seas increased at a rate of 4.5 mm/a and then decreased at a slower pace. This was the main factor responsible for the stagnation of the SSH rises, while the mass factor only increased slightly. The Norwegian Sea particularly experienced the most prominent slowdown in SSH rises, mainly due to decreased warming of the 0-600 m layer. The controlling factors of this decreased warming were cessation in the increase of volume of the Atlantic inflow and stagnation of warming of the inflow. However, variations in air-sea thermal flux were not a major factor. In the recent two decades, mean halosteric components of the GIN seas decreased steadily and remained at a rate of 2 mm/a or more because of increased flow and salinity of the Atlantic inflow during the first decade, and reduction in freshwater inputs from the Arctic Ocean in the second decade.
A slowdown of sea surface height (SSH) rise occurred in the Nordic (GIN) seas around 2004. In this study, SSH satellite data and constructed steric height data for the decades before and after 2004 (i.e., May 1994 to April 2014) were used for comparative analysis. The findings indicate that the rate of slowdown of SSH rises in the GIN seas (3.0 mm/a) far exceeded that of the global mean (0.6 mm/a). In particular, the mean steric height of the GIN seas increased at a rate of 4.5 mm/a and then decreased at a slower pace. This was the main factor responsible for the stagnation of the SSH rises, while the mass factor only increased slightly. The Norwegian Sea particularly experienced the most prominent slowdown in SSH rises, mainly due to decreased warming of the 0-600 m layer. The controlling factors of this decreased warming were cessation in the increase of volume of the Atlantic inflow and stagnation of warming of the inflow. However, variations in air-sea thermal flux were not a major factor. In the recent two decades, mean halosteric components of the GIN seas decreased steadily and remained at a rate of 2 mm/a or more because of increased flow and salinity of the Atlantic inflow during the first decade, and reduction in freshwater inputs from the Arctic Ocean in the second decade.
2017, 36(8): 34-41.
doi: 10.1007/s13131-017-1021-3
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Large parts of North America, Europe, Siberia, and East Asia have experienced cold snaps and heavy snowfalls for the past few winters, which have been linked to rapid decline of Arctic sea ice. Although the role of reduction in Arctic sea ice in recent cold and snowy winters is still a matter of debate, there is considerable interest in determining whether such an emerging climate feedback will persist into the future in a warming environment. Here we show that increased winter snowfall would be a robust feature throughout the 21st century in the northeastern Europe, central and northern Asia and northern North America as projected by current-day climate model simulations under the medium mitigation scenario. We argue that the increased winter snowfall in these regions during the 21st century is due primarily to the diminishing autumn Arctic sea ice (largely externally forced). Variability of the winter Arctic Oscillation (dominant mode of natural variability in the Northern Hemisphere), in contrast, has little contribution to the increased winter snowfall. This is evident in not only the multi-model ensemble mean, but also each individual model (not model-dependent). Our findings reinforce suggestions that a strong sea ice-snowfall feedback might have emerged, and would be enhanced in coming decades, increasing the chance of heavy snowfall events in northern high-latitude continents.
Large parts of North America, Europe, Siberia, and East Asia have experienced cold snaps and heavy snowfalls for the past few winters, which have been linked to rapid decline of Arctic sea ice. Although the role of reduction in Arctic sea ice in recent cold and snowy winters is still a matter of debate, there is considerable interest in determining whether such an emerging climate feedback will persist into the future in a warming environment. Here we show that increased winter snowfall would be a robust feature throughout the 21st century in the northeastern Europe, central and northern Asia and northern North America as projected by current-day climate model simulations under the medium mitigation scenario. We argue that the increased winter snowfall in these regions during the 21st century is due primarily to the diminishing autumn Arctic sea ice (largely externally forced). Variability of the winter Arctic Oscillation (dominant mode of natural variability in the Northern Hemisphere), in contrast, has little contribution to the increased winter snowfall. This is evident in not only the multi-model ensemble mean, but also each individual model (not model-dependent). Our findings reinforce suggestions that a strong sea ice-snowfall feedback might have emerged, and would be enhanced in coming decades, increasing the chance of heavy snowfall events in northern high-latitude continents.
2017, 36(8): 42-51.
doi: 10.1007/s13131-017-1025-z
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The Arctic near-surface air temperatures are increasing more than twice as fast as the global average-a feature known as Arctic amplification (AA). A modified AA index is constructed in this paper to emphasize the contrast of warming rate between polar and mid-latitude regions, as well as the spatial and temporal characteristics of AA and their influence on atmospheric circulation over the Northern Hemisphere. Results show that AA has a pronounced annual cycle. The positive or negative phase activities are the strongest in autumn and winter, the weakest in summer. After experiencing a remarkable decadal shift from negative to positive phase in the early global warming hiatus period, the AA has entered into a state of being enlarged continuously, and the decadal regime shift of AA in about 2002 is affected mainly by decadal shift in autumn. In terms of spatial distribution, AA has maximum warming near the surface in almost all seasons except in summer. Poleward of 20°N, AA in autumn has a significant influence on the atmospheric circulation in the following winter. The reason may be that the autumn AA increases the amplitude of planetary waves, slows the wave speeds and weakens upper-level zonal winds through the thermal wind relation, thus influencing surface air temperature in the following winter. The AA correlates to negative phase of the Arctic oscillation (AO) and leads AO by 0-3 months within the period 1979-2002. However, weaker relationship between them is indistinctive after the decadal shift of AA.
The Arctic near-surface air temperatures are increasing more than twice as fast as the global average-a feature known as Arctic amplification (AA). A modified AA index is constructed in this paper to emphasize the contrast of warming rate between polar and mid-latitude regions, as well as the spatial and temporal characteristics of AA and their influence on atmospheric circulation over the Northern Hemisphere. Results show that AA has a pronounced annual cycle. The positive or negative phase activities are the strongest in autumn and winter, the weakest in summer. After experiencing a remarkable decadal shift from negative to positive phase in the early global warming hiatus period, the AA has entered into a state of being enlarged continuously, and the decadal regime shift of AA in about 2002 is affected mainly by decadal shift in autumn. In terms of spatial distribution, AA has maximum warming near the surface in almost all seasons except in summer. Poleward of 20°N, AA in autumn has a significant influence on the atmospheric circulation in the following winter. The reason may be that the autumn AA increases the amplitude of planetary waves, slows the wave speeds and weakens upper-level zonal winds through the thermal wind relation, thus influencing surface air temperature in the following winter. The AA correlates to negative phase of the Arctic oscillation (AO) and leads AO by 0-3 months within the period 1979-2002. However, weaker relationship between them is indistinctive after the decadal shift of AA.
2017, 36(8): 52-58.
doi: 10.1007/s13131-017-1018-y
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The recent decline in the Arctic sea ice has coincided with more cold winters in Eurasia. It has been hypothesized that the Arctic sea ice loss is causing more mid-latitude cold extremes and cold winters, yet there is lack of consensus in modeling studies on the impact of Arctic sea ice loss. Here we conducted modeling experiments with Community Atmosphere Model Version 5 (CAM5) to investigate the sensitivity and linearity of Eurasian winter temperature response to the Atlantic sector and Pacific sector of the Arctic sea ice loss. Our experiments indicate that the Arctic sea ice reduction can significantly affect the atmospheric circulation by strengthening the Siberian High, exciting the stationary Rossby wave train, and weakening the polar jet stream, which in turn induce the cooling in Eurasia. The temperature decreases by more than 1℃ in response to the ice loss in the Atlantic sector and the cooling is less and more shifts southward in response to the ice loss in the Pacific sector. More interestingly, sea ice loss in the Atlantic and Pacific sectors together barely induces cold temperatures in Eurasia, suggesting the nonlinearity of the atmospheric response to the Arctic sea ice loss.
The recent decline in the Arctic sea ice has coincided with more cold winters in Eurasia. It has been hypothesized that the Arctic sea ice loss is causing more mid-latitude cold extremes and cold winters, yet there is lack of consensus in modeling studies on the impact of Arctic sea ice loss. Here we conducted modeling experiments with Community Atmosphere Model Version 5 (CAM5) to investigate the sensitivity and linearity of Eurasian winter temperature response to the Atlantic sector and Pacific sector of the Arctic sea ice loss. Our experiments indicate that the Arctic sea ice reduction can significantly affect the atmospheric circulation by strengthening the Siberian High, exciting the stationary Rossby wave train, and weakening the polar jet stream, which in turn induce the cooling in Eurasia. The temperature decreases by more than 1℃ in response to the ice loss in the Atlantic sector and the cooling is less and more shifts southward in response to the ice loss in the Pacific sector. More interestingly, sea ice loss in the Atlantic and Pacific sectors together barely induces cold temperatures in Eurasia, suggesting the nonlinearity of the atmospheric response to the Arctic sea ice loss.
2017, 36(8): 59-65.
doi: 10.1007/s13131-017-1009-z
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An increasing amount of freshwater has been observed to enter the Arctic Ocean from the six largest Eurasian rivers over the past several decades. The increasing trend is projected to continue in the twenty-first century according to Coupled Model Intercomparison Project Phase 5 (CMIP5) coupled models. The present study found that water flux from rivers to the Arctic Ocean at the end of the century will be 1.4 times that in 1950 according to CMIP5 projection results under Representative Concentration Pathway 8.5. The effect of increasing Arctic river runoff on the Atlantic meridional overturning circulation (AMOC) was investigated using an ocean-ice coupled model. Results obtained from two numerical experiments show that 100, 150 and 200 years after the start of an increase in the Arctic river runoff at a rate of 0.22%/a, the AMOC will weaken by 0.6 (3%), 1.2 (7%) and 1.8 (11%) Sv. AMOC weakening is mainly caused by freshwater transported from increasing Arctic river runoff inhibiting the formation of North Atlantic Deep Water (NADW). As the AMOC weakens, the deep seawater age will become older throughout the Atlantic Basin owing to the increasing of Arctic runoff.
An increasing amount of freshwater has been observed to enter the Arctic Ocean from the six largest Eurasian rivers over the past several decades. The increasing trend is projected to continue in the twenty-first century according to Coupled Model Intercomparison Project Phase 5 (CMIP5) coupled models. The present study found that water flux from rivers to the Arctic Ocean at the end of the century will be 1.4 times that in 1950 according to CMIP5 projection results under Representative Concentration Pathway 8.5. The effect of increasing Arctic river runoff on the Atlantic meridional overturning circulation (AMOC) was investigated using an ocean-ice coupled model. Results obtained from two numerical experiments show that 100, 150 and 200 years after the start of an increase in the Arctic river runoff at a rate of 0.22%/a, the AMOC will weaken by 0.6 (3%), 1.2 (7%) and 1.8 (11%) Sv. AMOC weakening is mainly caused by freshwater transported from increasing Arctic river runoff inhibiting the formation of North Atlantic Deep Water (NADW). As the AMOC weakens, the deep seawater age will become older throughout the Atlantic Basin owing to the increasing of Arctic runoff.
2017, 36(8): 66-75.
doi: 10.1007/s13131-017-1020-4
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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 m 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.
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 m 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.
2017, 36(8): 76-83.
doi: 10.1007/s13131-017-1022-2
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A sea ice extent retrieval algorithm over the polar area based on scatterometer data of HY-2A satellite has been established. Four parameters are used for distinguishing between sea ice and ocean with Fisher's linear discriminant analysis method. The method is used to generate polar sea ice extent maps of the Arctic and Antarctic regions of the full 2013-2014 from the scatterometer aboard HY-2A (HY-2A-SCAT) backscatter data. The time series of the ice mapped imagery shows ice edge evolution and indicates a similar seasonal change trend with total ice area from DMSP-F17 Special Sensor Microwave Imager/Sounder (SSMIS) sea ice concentration data. For both hemispheres, the HY-2A-SCAT extent correlates very well with SSMIS 15% extent for the whole year period. Compared with Synthetic Aperture Radar (SAR) imagery, the HY-2A-SCAT ice extent shows good correlation with the Sentinel-1 SAR ice edge. Over some ice edge area, the difference is very evident because sea ice edges can be very dynamic and move several kilometers in a single day.
A sea ice extent retrieval algorithm over the polar area based on scatterometer data of HY-2A satellite has been established. Four parameters are used for distinguishing between sea ice and ocean with Fisher's linear discriminant analysis method. The method is used to generate polar sea ice extent maps of the Arctic and Antarctic regions of the full 2013-2014 from the scatterometer aboard HY-2A (HY-2A-SCAT) backscatter data. The time series of the ice mapped imagery shows ice edge evolution and indicates a similar seasonal change trend with total ice area from DMSP-F17 Special Sensor Microwave Imager/Sounder (SSMIS) sea ice concentration data. For both hemispheres, the HY-2A-SCAT extent correlates very well with SSMIS 15% extent for the whole year period. Compared with Synthetic Aperture Radar (SAR) imagery, the HY-2A-SCAT ice extent shows good correlation with the Sentinel-1 SAR ice edge. Over some ice edge area, the difference is very evident because sea ice edges can be very dynamic and move several kilometers in a single day.
2017, 36(8): 84-93.
doi: 10.1007/s13131-017-1019-x
Abstract:
A one-dimensional thermodynamic model of melt pond is established in this paper. The observation data measured in the summer of 2010 by the Chinese National Arctic Research Expedition (CHINARE-2010) are used to partially parameterize equations and to validate results of the model. About 85% of the incident solar radiation passed through the melt pond surface, and some of it was released in the form of sensible and latent heat. However, the released energy was very little (about 15%), compared to the incident solar radiation. More than 58.6% of the incident energy was absorbed by melt pond water, which caused pond-covered ice melting and variation of pond water temperature. The simulated temperature of melt pond had a diurnal variation and its value ranged between 0.0℃ and 0.3℃. The melting rate of upper pond-covered ice is estimated to be around two times faster than snow-covered ice. At same time, the change of melting rate was relatively quick for pond depth less than 0.4 m, while the melting rate kept relatively constant (about 1.0 cm/d) for pond depth greater than 0.4 m.
A one-dimensional thermodynamic model of melt pond is established in this paper. The observation data measured in the summer of 2010 by the Chinese National Arctic Research Expedition (CHINARE-2010) are used to partially parameterize equations and to validate results of the model. About 85% of the incident solar radiation passed through the melt pond surface, and some of it was released in the form of sensible and latent heat. However, the released energy was very little (about 15%), compared to the incident solar radiation. More than 58.6% of the incident energy was absorbed by melt pond water, which caused pond-covered ice melting and variation of pond water temperature. The simulated temperature of melt pond had a diurnal variation and its value ranged between 0.0℃ and 0.3℃. The melting rate of upper pond-covered ice is estimated to be around two times faster than snow-covered ice. At same time, the change of melting rate was relatively quick for pond depth less than 0.4 m, while the melting rate kept relatively constant (about 1.0 cm/d) for pond depth greater than 0.4 m.
2017, 36(8): 94-100.
doi: 10.1007/s13131-017-1028-9
Abstract:
The third Chinese National Arctic Research Expedition (CHINARE) was conducted in the summer of 2008. During the survey, the surface seawater partial pressure of CO2 (pCO2) was measured, and sea water samples were collected for CO2 measurement in the Canada Basin. The distribution of pCO2 in the Canada Basin was determined, the influencing factors were addressed, and the air-sea CO2 flux in the Canada Basin was evaluated. The Canada Basin was divided into three regions:the ice-free zone (south of 77°N), the partially ice-covered zone (77°-80°N), and the heavily ice-covered zone (north of 80°N). In the ice-free zone, pCO2 was high (320 to 368 μatm, 1 μatm=0.101 325 Pa), primarily due to rapid equilibration with atmospheric CO2 over a short time. In the partially ice-covered zone, the surface pCO2 was relatively low (250 to 270 μatm) due to ice-edge blooms and ice-melt water dilution. In the heavily ice-covered zone, the seawater pCO2 varied between 270 and 300 μatm due to biological CO2 removal, the transportation of low pCO2 water northward, and heavy ice cover. The surface seawater pCO2 during the survey was undersaturated with respect to the atmosphere in the Canada Basin, and it was a net sink for atmospheric CO2. The summertime net CO2 uptake of the ice-free zone, the partially ice-covered zone and the heavily ice-covered zone was (4.14±1.08), (1.79±0.19), and (0.57±0.03) Tg/a (calculated by carbon, 1 Tg=1012 g), respectively. Overall, the net CO2 sink of the Canada Basin in the summer of 2008 was (6.5±1.3) Tg/a, which accounted for 4%-10% of the Arctic Ocean CO2 sink.
The third Chinese National Arctic Research Expedition (CHINARE) was conducted in the summer of 2008. During the survey, the surface seawater partial pressure of CO2 (pCO2) was measured, and sea water samples were collected for CO2 measurement in the Canada Basin. The distribution of pCO2 in the Canada Basin was determined, the influencing factors were addressed, and the air-sea CO2 flux in the Canada Basin was evaluated. The Canada Basin was divided into three regions:the ice-free zone (south of 77°N), the partially ice-covered zone (77°-80°N), and the heavily ice-covered zone (north of 80°N). In the ice-free zone, pCO2 was high (320 to 368 μatm, 1 μatm=0.101 325 Pa), primarily due to rapid equilibration with atmospheric CO2 over a short time. In the partially ice-covered zone, the surface pCO2 was relatively low (250 to 270 μatm) due to ice-edge blooms and ice-melt water dilution. In the heavily ice-covered zone, the seawater pCO2 varied between 270 and 300 μatm due to biological CO2 removal, the transportation of low pCO2 water northward, and heavy ice cover. The surface seawater pCO2 during the survey was undersaturated with respect to the atmosphere in the Canada Basin, and it was a net sink for atmospheric CO2. The summertime net CO2 uptake of the ice-free zone, the partially ice-covered zone and the heavily ice-covered zone was (4.14±1.08), (1.79±0.19), and (0.57±0.03) Tg/a (calculated by carbon, 1 Tg=1012 g), respectively. Overall, the net CO2 sink of the Canada Basin in the summer of 2008 was (6.5±1.3) Tg/a, which accounted for 4%-10% of the Arctic Ocean CO2 sink.
2017, 36(8): 101-108.
doi: 10.1007/s13131-017-1023-1
Abstract:
A combination of δ18O and salinity data was employed to explore the freshwater balance in the Canada Basin in summer 2008. The Arctic river water and Pacific river water were quantitatively distinguished by using different saline end-members. The fractions of total river water, including the Arctic and Pacific river water, were high in the upper 50 m and decreased with depth as well as increasing latitude. In contrast, the fraction of Pacific river water increased gradually with depth but decreased toward north. The inventory of total river water in the Canada Basin was higher than other arctic seas, indicating that Canada Basin was a main storage region for river water in the Arctic Ocean. The fraction of Arctic river water was higher than Pacific river water in the upper 50 m while the opposite was true below 50 m. As a result, the inventories of Pacific river water were higher than those of Arctic river water, demonstrating that the Pacific inflow through the Bering Strait is the main source of freshwater in the Canada Basin. Both the river water and sea-ice melted water in the permanent ice zone were more abundant than those in the region with sea-ice just melted. The fractions of total river water, Arctic river water, Pacific river water increased northward to the north of 82°N, indicating an additional source of river water in the permanent ice zone of the northern Canada Basin. A possible reason for the extra river water in the permanent ice zone is the lateral advection of shelf waters by the Trans-Polar Drift. The penetration depth of sea-ice melted waters was less than 30 m in the southern Canada Basin, while it extended to 125 m in the northern Canada Basin. The inventory of sea-ice melted water suggested that sea-ice melted waters were also accumulated in the permanent ice zone, attributing to the trap of earlier melted waters in the permanent ice zone via the Beaufort Gyre.
A combination of δ18O and salinity data was employed to explore the freshwater balance in the Canada Basin in summer 2008. The Arctic river water and Pacific river water were quantitatively distinguished by using different saline end-members. The fractions of total river water, including the Arctic and Pacific river water, were high in the upper 50 m and decreased with depth as well as increasing latitude. In contrast, the fraction of Pacific river water increased gradually with depth but decreased toward north. The inventory of total river water in the Canada Basin was higher than other arctic seas, indicating that Canada Basin was a main storage region for river water in the Arctic Ocean. The fraction of Arctic river water was higher than Pacific river water in the upper 50 m while the opposite was true below 50 m. As a result, the inventories of Pacific river water were higher than those of Arctic river water, demonstrating that the Pacific inflow through the Bering Strait is the main source of freshwater in the Canada Basin. Both the river water and sea-ice melted water in the permanent ice zone were more abundant than those in the region with sea-ice just melted. The fractions of total river water, Arctic river water, Pacific river water increased northward to the north of 82°N, indicating an additional source of river water in the permanent ice zone of the northern Canada Basin. A possible reason for the extra river water in the permanent ice zone is the lateral advection of shelf waters by the Trans-Polar Drift. The penetration depth of sea-ice melted waters was less than 30 m in the southern Canada Basin, while it extended to 125 m in the northern Canada Basin. The inventory of sea-ice melted water suggested that sea-ice melted waters were also accumulated in the permanent ice zone, attributing to the trap of earlier melted waters in the permanent ice zone via the Beaufort Gyre.
2017, 36(8): 109-121.
doi: 10.1007/s13131-017-1033-z
Abstract:
Nutrients and photosynthesis pigments were investigated in the western Arctic Ocean during the 3rd Chinese Arctic Research Expedition Cruise in summer 2008. The study area was divided into five provinces using the K-means clustering method based on the physical and chemical characteristics of the sea water, and to discuss the distribution of the phytoplankton community structure in these provinces. CHEMTAX software was performed using HPLC pigments to estimate the contributions of eight algal classes to the total chlorophyll a (TChl a). The results showed that on the Chukchi Shelf, the Pacific Ocean inflow mainly controlled the Chl a biomass and phytoplankton communities by nutrient concentrations. The high nutrient Anadyr Water and Bering Shelf Water (AnW and BSW) controlled region have high Chl a levels and the diatom dominated community structure. In contrast, in the region occupied by low-nutrient like Alaska Coastal Water (ACW), the Chl a biomass was low, with pico-and nano-phytoplankton as dominated species, such as prasinophytes, chrysophytes and cryptophytes. However, over the off-shelf, the ice cover condition which would affect the physical and nutrient concentrations of the water masses, in consequence had a greater impact on the phytoplankton community structure. Diatom dominated in ice cover region and its contribution to Chl a biomass was up to 75%. In the region close to the Mendeleev Abyssal Plain (MAP), controlled by sea-ice melt water with relatively high salinity (MW-HS), higher nutrient and Chl a concentrations were found and the phytoplankton was dominated by pico-and nano-algae, while the diatom abundance reduced to 33%. In the southern Canada Basin, an ice-free basin (IfB) with the lowest nutrient concentrations and most freshened surface water, low Chl a biomass was a consequence of low nutrients. The ice retreating and a prolonged period of open ocean may not be beneficial to the carbon export efficiency due to reducing the Chl a biomass or intriguing smaller size algae growth.
Nutrients and photosynthesis pigments were investigated in the western Arctic Ocean during the 3rd Chinese Arctic Research Expedition Cruise in summer 2008. The study area was divided into five provinces using the K-means clustering method based on the physical and chemical characteristics of the sea water, and to discuss the distribution of the phytoplankton community structure in these provinces. CHEMTAX software was performed using HPLC pigments to estimate the contributions of eight algal classes to the total chlorophyll a (TChl a). The results showed that on the Chukchi Shelf, the Pacific Ocean inflow mainly controlled the Chl a biomass and phytoplankton communities by nutrient concentrations. The high nutrient Anadyr Water and Bering Shelf Water (AnW and BSW) controlled region have high Chl a levels and the diatom dominated community structure. In contrast, in the region occupied by low-nutrient like Alaska Coastal Water (ACW), the Chl a biomass was low, with pico-and nano-phytoplankton as dominated species, such as prasinophytes, chrysophytes and cryptophytes. However, over the off-shelf, the ice cover condition which would affect the physical and nutrient concentrations of the water masses, in consequence had a greater impact on the phytoplankton community structure. Diatom dominated in ice cover region and its contribution to Chl a biomass was up to 75%. In the region close to the Mendeleev Abyssal Plain (MAP), controlled by sea-ice melt water with relatively high salinity (MW-HS), higher nutrient and Chl a concentrations were found and the phytoplankton was dominated by pico-and nano-algae, while the diatom abundance reduced to 33%. In the southern Canada Basin, an ice-free basin (IfB) with the lowest nutrient concentrations and most freshened surface water, low Chl a biomass was a consequence of low nutrients. The ice retreating and a prolonged period of open ocean may not be beneficial to the carbon export efficiency due to reducing the Chl a biomass or intriguing smaller size algae growth.
2017, 36(8): 122-130.
doi: 10.1007/s13131-017-1024-0
Abstract:
Seasonal meltwater input creates a thin freshen layer in surface seawater under ice, which largely shifts the algae assemblages. Our recent observation of photosynthetic pigments in the high Arctic showed that ice bottom and 5 m of seawater under ice contained relatively high concentration of fucoxanthin, while chlorophyll b and lutein were the major diagnostic pigments in ice-water interface and 0 m of seawater under ice. Additionally, a notable change of dominant phytoplankton occurred in the top 5 m of seawater under ice, from chlorophytes-dominated at surface to diatoms-dominated at 5 m depth, which might attribute to the sharp salinity gradient (salinity from 12.5 to 28.1) in the surface seawater under ice. Our results imply that phytoplankton community in surface layer under ice would become more chlorophytes in the future warming Arctic Ocean.
Seasonal meltwater input creates a thin freshen layer in surface seawater under ice, which largely shifts the algae assemblages. Our recent observation of photosynthetic pigments in the high Arctic showed that ice bottom and 5 m of seawater under ice contained relatively high concentration of fucoxanthin, while chlorophyll b and lutein were the major diagnostic pigments in ice-water interface and 0 m of seawater under ice. Additionally, a notable change of dominant phytoplankton occurred in the top 5 m of seawater under ice, from chlorophytes-dominated at surface to diatoms-dominated at 5 m depth, which might attribute to the sharp salinity gradient (salinity from 12.5 to 28.1) in the surface seawater under ice. Our results imply that phytoplankton community in surface layer under ice would become more chlorophytes in the future warming Arctic Ocean.
2017, 36(8): 131-136.
doi: 10.1007/s13131-017-1026-y
Abstract:
The content of organic carbon (OC) normalized to the specific surface area (SSA) of sediment is widely used to trace variations in OC loading (OC/SSA). This study presents observations of OC/SSA of surface sediments collected in the Chukchi Sea, a typical Arctic marginal sea. Shelf sediments exhibit much higher OC/SSA values than slope sediments in the study area. Compared with OC/SSA values reported from the East Siberian Shelf and Mackenzie River, the slope sediments possess lower OC loading. This abrupt decrease in OC/SSA is mostly related to the lower primary production on slope as well as possible oxidization processes. The results of linear regression analysis between OC and SSA indicate a sedimentary source rock for the OC in the Chukchi Sea sediments. Moreover, shelf sediments with low SSA possess a larger rock OC fraction than slope sediments do. The dataset of the present study enables a more thorough understanding of regional OC cycling in the Chukchi Sea.
The content of organic carbon (OC) normalized to the specific surface area (SSA) of sediment is widely used to trace variations in OC loading (OC/SSA). This study presents observations of OC/SSA of surface sediments collected in the Chukchi Sea, a typical Arctic marginal sea. Shelf sediments exhibit much higher OC/SSA values than slope sediments in the study area. Compared with OC/SSA values reported from the East Siberian Shelf and Mackenzie River, the slope sediments possess lower OC loading. This abrupt decrease in OC/SSA is mostly related to the lower primary production on slope as well as possible oxidization processes. The results of linear regression analysis between OC and SSA indicate a sedimentary source rock for the OC in the Chukchi Sea sediments. Moreover, shelf sediments with low SSA possess a larger rock OC fraction than slope sediments do. The dataset of the present study enables a more thorough understanding of regional OC cycling in the Chukchi Sea.
2017, 36(8): 137-145.
doi: 10.1007/s13131-017-1032-0
Abstract:
The records of high-resolution terrestrial biological markers (biomarkers) from Core B2-9 from the northern Bering Sea Slope over the last 9.6 ka BP were presented in the study. Variations in input of terrestrial long-chain n-alkanes (referred to as n-alkanes) and vegetation structure in their source regions were investigated. The results show that the nC27 is the main carbon peak and has the greatest contribution rate of the total n-alkane content; this might be related to the abundance of woody plants and their spatial distribution in the source region. nC23 is another n-alkane having a relatively high content; this was mainly derived from submerged plants widespread along the coastal areas in the northern hemisphere. Total n-alkane content dropped quickly at ca. 7.8 ka BP, ca. 6.7 ka BP and ca. 5.4 ka BP, and was followed by four relatively stable stages mostly controlled by sea-level rise, climate change and vegetation distribution in the source region. Variation in carbon preference index (CPI) indicates that the n-alkanes primarily originated from higher land plants, and the average chain length (ACL) and nC31/nC27 ratio reveal the relatively stable presence of woody/herbaceous plants during the Holocene, and dominate woody plants in most of the time. Simultaneous variation in total n-alkane content, nC27 content and its contribution, CPI, ACL and nC31/nC27 ratio over several short periods suggest that the growth rate of the woody plant n-alkane contribution was lower than that of herbaceous plants and fossil n-alkanes under the particular climatic conditions of the source region.
The records of high-resolution terrestrial biological markers (biomarkers) from Core B2-9 from the northern Bering Sea Slope over the last 9.6 ka BP were presented in the study. Variations in input of terrestrial long-chain n-alkanes (referred to as n-alkanes) and vegetation structure in their source regions were investigated. The results show that the nC27 is the main carbon peak and has the greatest contribution rate of the total n-alkane content; this might be related to the abundance of woody plants and their spatial distribution in the source region. nC23 is another n-alkane having a relatively high content; this was mainly derived from submerged plants widespread along the coastal areas in the northern hemisphere. Total n-alkane content dropped quickly at ca. 7.8 ka BP, ca. 6.7 ka BP and ca. 5.4 ka BP, and was followed by four relatively stable stages mostly controlled by sea-level rise, climate change and vegetation distribution in the source region. Variation in carbon preference index (CPI) indicates that the n-alkanes primarily originated from higher land plants, and the average chain length (ACL) and nC31/nC27 ratio reveal the relatively stable presence of woody/herbaceous plants during the Holocene, and dominate woody plants in most of the time. Simultaneous variation in total n-alkane content, nC27 content and its contribution, CPI, ACL and nC31/nC27 ratio over several short periods suggest that the growth rate of the woody plant n-alkane contribution was lower than that of herbaceous plants and fossil n-alkanes under the particular climatic conditions of the source region.
2017, 36(8): 146-152.
doi: 10.1007/s13131-017-1030-2
Abstract:
This study was to investigate bacterial and archaeal community structure of pan-Arctic Ocean sediments by pyrosequencing. In total, investigation of three marine sediments revealed 15 002 bacterial and 4 362 archaeal operational taxonomic units (OTUs) at the 97% similarity level. Analysis of community structure indicated that these three samples had high bacterial and archaeal diversity. The most relatively abundant bacterial group in Samples CC1 and R05 was Proteobacteria, while Firmicutes was dominant in Sample BL03. Thaumarchaeota was the most relatively abundant archaeal phylum in Samples CC1 and R05, and the relative abundance of Thaumarchaeota was almost as high as that of Euryarchaeota in Sample BL03. These two phyla accounted for nearly 100% of the archaeal OTUs. δ-Proteobacteria and γ-Proteobacteria were the two most relatively abundant classes at Proteobacterial class level, and their relative abundance was more than 60% in Samples CC1 and R05. There were also differences in the top 10 relatively abundant bacterial and archaeal OTUs among the three samples at the 97% similarity, and only 12 core bacterial OTUs were detected. Overall, this study indicated that there were distinct microbial communities and many unique OTUs in these three samples.
This study was to investigate bacterial and archaeal community structure of pan-Arctic Ocean sediments by pyrosequencing. In total, investigation of three marine sediments revealed 15 002 bacterial and 4 362 archaeal operational taxonomic units (OTUs) at the 97% similarity level. Analysis of community structure indicated that these three samples had high bacterial and archaeal diversity. The most relatively abundant bacterial group in Samples CC1 and R05 was Proteobacteria, while Firmicutes was dominant in Sample BL03. Thaumarchaeota was the most relatively abundant archaeal phylum in Samples CC1 and R05, and the relative abundance of Thaumarchaeota was almost as high as that of Euryarchaeota in Sample BL03. These two phyla accounted for nearly 100% of the archaeal OTUs. δ-Proteobacteria and γ-Proteobacteria were the two most relatively abundant classes at Proteobacterial class level, and their relative abundance was more than 60% in Samples CC1 and R05. There were also differences in the top 10 relatively abundant bacterial and archaeal OTUs among the three samples at the 97% similarity, and only 12 core bacterial OTUs were detected. Overall, this study indicated that there were distinct microbial communities and many unique OTUs in these three samples.
2017, 36(8): 153-162.
doi: 10.1007/s13131-017-1031-1
Abstract:
Abundance and production of bacterioplankton were measured in the Nordic seas and Chukchi Sea during the 5th Chinese Arctic Research Expedition in summer 2012. The results showed that average bacterial abundances ranged from 3.31×1011 cells/m3 to 2.25×1011 cells/m3, and average bacterial productions (calculated by carbon) were 0.46 mg/(m3·d) and 0.54 mg/(m3·d) in the Nordic seas and Chukchi Sea, respectively. T-test result showed that bacterial abundances were significantly different between the Nordic seas and Chukchi Sea, however, no significant difference was observed regarding bacterial productions. Based on the slope of lg bacterial biomass versus lg bacterial production, bacterial communities in the Nordic seas and Chukchi Sea were moderately dominated by bottom-up control. Both Pearson correlation analysis and multivariable linear regression indicated that temperature had significant positive correlation with bacterial abundance in the Chukchi Sea, while no correlations with productions in both areas. Meanwhile, Chl a had positive correlations with both bacterial abundance and production in these two regions. As the temperature and Chl a keep changing in the future, we suggest that both bacterial abundance and production been hanced in the Chukchi Sea but weaken in the Nordic seas, though the enhancement will not be dramatic as a result of higher pressure of predation and viral lysis.
Abundance and production of bacterioplankton were measured in the Nordic seas and Chukchi Sea during the 5th Chinese Arctic Research Expedition in summer 2012. The results showed that average bacterial abundances ranged from 3.31×1011 cells/m3 to 2.25×1011 cells/m3, and average bacterial productions (calculated by carbon) were 0.46 mg/(m3·d) and 0.54 mg/(m3·d) in the Nordic seas and Chukchi Sea, respectively. T-test result showed that bacterial abundances were significantly different between the Nordic seas and Chukchi Sea, however, no significant difference was observed regarding bacterial productions. Based on the slope of lg bacterial biomass versus lg bacterial production, bacterial communities in the Nordic seas and Chukchi Sea were moderately dominated by bottom-up control. Both Pearson correlation analysis and multivariable linear regression indicated that temperature had significant positive correlation with bacterial abundance in the Chukchi Sea, while no correlations with productions in both areas. Meanwhile, Chl a had positive correlations with both bacterial abundance and production in these two regions. As the temperature and Chl a keep changing in the future, we suggest that both bacterial abundance and production been hanced in the Chukchi Sea but weaken in the Nordic seas, though the enhancement will not be dramatic as a result of higher pressure of predation and viral lysis.
