2021 Vol. 43, No. 7
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2021, 43(7): 1-10.
doi: 10.12284/hyxb2021119
Abstract:
Along with the global warming, the sea ice in the Arctic decreased rapidly, however the sea ice in the Antarctic has experienced a weak expansion. While many researchers are studying the mechanisms for this paradox in the Antarctic, the sea ice extent (SIE) began a rapid decline in 2016 and reached a record low in austral spring 2016. A rapid decrease of SIE anomaly occurred in December, with a 20.5% (2.13\begin{document}$ \times $\end{document} ![]()
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Along with the global warming, the sea ice in the Arctic decreased rapidly, however the sea ice in the Antarctic has experienced a weak expansion. While many researchers are studying the mechanisms for this paradox in the Antarctic, the sea ice extent (SIE) began a rapid decline in 2016 and reached a record low in austral spring 2016. A rapid decrease of SIE anomaly occurred in December, with a 20.5% (2.13
2021, 43(7): 11-22.
doi: 10.12284/hyxb2021151
Abstract:
Antarctic sea ice plays an important role in the global climate system. In contrast to the rapid decrease in Arctic sea ice extent, Antarctic sea ice extent exhibits a gradually increasing trend before 2014, followed by an abrupt decline in the last four decades. A single large-scale atmospheric circulation cannot fully explain the long-term trend of Antarctic sea ice, and the coupling influence of ocean-atmosphere interactions has not been sufficiently investigated. Limited by the capabilities of remote sensing and numerical simulation, the Antarctic sea ice thickness and volume variations in the context of global change cannot be quantified precisely with currently available sea ice thickness and volume data. Moreover, the climate effects of Antarctic sea ice change require further investigation. Hence it is strongly urgent to develop a long-term and reliable Antarctic sea ice thickness data set to quantify the Antarctic sea ice volume change. Meanwhile, the influences of multi-climate modes and ocean-atmosphere coupling system on the Antarctic sea ice changes should be considered comprehensively.
Antarctic sea ice plays an important role in the global climate system. In contrast to the rapid decrease in Arctic sea ice extent, Antarctic sea ice extent exhibits a gradually increasing trend before 2014, followed by an abrupt decline in the last four decades. A single large-scale atmospheric circulation cannot fully explain the long-term trend of Antarctic sea ice, and the coupling influence of ocean-atmosphere interactions has not been sufficiently investigated. Limited by the capabilities of remote sensing and numerical simulation, the Antarctic sea ice thickness and volume variations in the context of global change cannot be quantified precisely with currently available sea ice thickness and volume data. Moreover, the climate effects of Antarctic sea ice change require further investigation. Hence it is strongly urgent to develop a long-term and reliable Antarctic sea ice thickness data set to quantify the Antarctic sea ice volume change. Meanwhile, the influences of multi-climate modes and ocean-atmosphere coupling system on the Antarctic sea ice changes should be considered comprehensively.
2021, 43(7): 23-34.
doi: 10.12284/hyxb2021111
Abstract:
The key regions for formation of the Antarctic Bottom Water occupied in the Indian sector of the Southern Ocean. The salinity change of the region has a profound influence on the global climate change. EN4 reanalysis-gridded data, measured seal data, WOD18 data combined with atmospheric reanalysis and sea ice concentration data were all used to explore the sea surface salinity changes in the Indian sector of the Southern Ocean and the response to large-scale circulation anomaly. The observation and reanalysis data both illustrated a significant positive surface salinity anomaly occurred in the Antarctic coast since 2008, especially in the Indian sector. The surface positive salinity anomaly was mainly centered in the Darnley Polynya and the north of Shackleton Ice Shelf. The high salinity shelf water expanded northward from the Antarctic coast and deepened. Meanwhile, the upwelling of Circumpolar Deep Water became increasingly distinct. Our study showed that this positive salinity anomaly was connected with the Antarctic Oscillation (AAO) and the Indian Ocean Dipole (IOD). During the positive AAO and IOD phases, the westerly wind enhanced significantly in the Indian sector and promoted the formation of sea ice, which increased surface salt flux. The significant negative wind curl and low pressure anomaly resulted in the upwelling of salty Circumpolar Deep Water and maintained the positive salinity anomaly. Additionally, increased locally zonal wind shear and enhanced evaporation were important factors as well.
The key regions for formation of the Antarctic Bottom Water occupied in the Indian sector of the Southern Ocean. The salinity change of the region has a profound influence on the global climate change. EN4 reanalysis-gridded data, measured seal data, WOD18 data combined with atmospheric reanalysis and sea ice concentration data were all used to explore the sea surface salinity changes in the Indian sector of the Southern Ocean and the response to large-scale circulation anomaly. The observation and reanalysis data both illustrated a significant positive surface salinity anomaly occurred in the Antarctic coast since 2008, especially in the Indian sector. The surface positive salinity anomaly was mainly centered in the Darnley Polynya and the north of Shackleton Ice Shelf. The high salinity shelf water expanded northward from the Antarctic coast and deepened. Meanwhile, the upwelling of Circumpolar Deep Water became increasingly distinct. Our study showed that this positive salinity anomaly was connected with the Antarctic Oscillation (AAO) and the Indian Ocean Dipole (IOD). During the positive AAO and IOD phases, the westerly wind enhanced significantly in the Indian sector and promoted the formation of sea ice, which increased surface salt flux. The significant negative wind curl and low pressure anomaly resulted in the upwelling of salty Circumpolar Deep Water and maintained the positive salinity anomaly. Additionally, increased locally zonal wind shear and enhanced evaporation were important factors as well.
2021, 43(7): 35-51.
doi: 10.12284/hyxb2021147
Abstract:
The PHC, ECCO2, SODA, GECCO3 and CMIP6 data were used to analyze the horizontal distribution characteristics, seasonal variation and long-term trend of the Arctic Ocean heat content, and analyze the simulation ability of the CMIP6 models in this paper. The results show that the heat content of the Arctic Ocean shows obvious seasonal change, with the lowest in April and the highest in September. Under historical circumstances (1850−2014), compared with the observation and reanalysis data, the heat content of the upper 500 m of the CMIP6 models ensemble average (MME) is warmer in the Greenland Sea, colder in the Norwegian sea, Barents Sea and Eurasian Basin, while the whole water column heat content of MME is warmer in almost all regions of the Arctic Ocean, with the largest deviation in the Greenland Sea. CMIP6 models have a large deviation in the simulation of Arctic Ocean temperature profile, and the average temperature of MME is higher than the observation and reanalysis data at the depth of more than 1 000 m. In the future case (2015−2100), the simulation of ocean heat content of MME shows obvious Arctic Ocean warming, but most of the Chinese models show no obvious warming situation. BCC-CSM2-MR and BCC-ESM1 are poor in simulating the annual mean heat content of the Arctic Ocean, CIESM is poor in simulating the seasonal and interdecadal variations of ocean heat content, while FIO-ESM-2-0 is good in simulating the annual heat content of the upper 500 m, the seasonal and interdecadal variations of heat content of the Arctic Ocean.
The PHC, ECCO2, SODA, GECCO3 and CMIP6 data were used to analyze the horizontal distribution characteristics, seasonal variation and long-term trend of the Arctic Ocean heat content, and analyze the simulation ability of the CMIP6 models in this paper. The results show that the heat content of the Arctic Ocean shows obvious seasonal change, with the lowest in April and the highest in September. Under historical circumstances (1850−2014), compared with the observation and reanalysis data, the heat content of the upper 500 m of the CMIP6 models ensemble average (MME) is warmer in the Greenland Sea, colder in the Norwegian sea, Barents Sea and Eurasian Basin, while the whole water column heat content of MME is warmer in almost all regions of the Arctic Ocean, with the largest deviation in the Greenland Sea. CMIP6 models have a large deviation in the simulation of Arctic Ocean temperature profile, and the average temperature of MME is higher than the observation and reanalysis data at the depth of more than 1 000 m. In the future case (2015−2100), the simulation of ocean heat content of MME shows obvious Arctic Ocean warming, but most of the Chinese models show no obvious warming situation. BCC-CSM2-MR and BCC-ESM1 are poor in simulating the annual mean heat content of the Arctic Ocean, CIESM is poor in simulating the seasonal and interdecadal variations of ocean heat content, while FIO-ESM-2-0 is good in simulating the annual heat content of the upper 500 m, the seasonal and interdecadal variations of heat content of the Arctic Ocean.
2021, 43(7): 52-62.
doi: 10.12284/hyxb2021149
Abstract:
The GPS radiosonde data obtained during the 6th to 9th Chinese National Arctic Research Expedition was used to analyze the spatial and temporal variation characteristics of boundary layer temperature inversions over the seasonal ice zone in Arctic. The results show that: (1) There were strong interannual and spatial changes in the temperature inversions. There were more strong inversions over the pack ice zone at high latitude. And the thickness of inversions and the temperature change through the inversions had a significant logarithmic relationship. (2) The main factors controlling inversion properties were various in different years. The differences in sea ice cover leaded to different characteristics of inversions. Surface melt, radiative cooling, multi-layer cloud and warm-air advection provided different degrees of contribution to inversions in different years. (3) There were different reasons over the open water and sea ice zone. Both surface melt and warm-air advection played a very important role in the formation of inversions in sea ice zone. However, radiative cooling was one of the main factors in the generation of inversions over the open water.
The GPS radiosonde data obtained during the 6th to 9th Chinese National Arctic Research Expedition was used to analyze the spatial and temporal variation characteristics of boundary layer temperature inversions over the seasonal ice zone in Arctic. The results show that: (1) There were strong interannual and spatial changes in the temperature inversions. There were more strong inversions over the pack ice zone at high latitude. And the thickness of inversions and the temperature change through the inversions had a significant logarithmic relationship. (2) The main factors controlling inversion properties were various in different years. The differences in sea ice cover leaded to different characteristics of inversions. Surface melt, radiative cooling, multi-layer cloud and warm-air advection provided different degrees of contribution to inversions in different years. (3) There were different reasons over the open water and sea ice zone. Both surface melt and warm-air advection played a very important role in the formation of inversions in sea ice zone. However, radiative cooling was one of the main factors in the generation of inversions over the open water.
2021, 43(7): 63-74.
doi: 10.12284/hyxb2021101
Abstract:
Based on one-dimensional sea ice column model Icepack, albedo and depth of melt pond were simulated. Atmospheric forcing data were collected from ICE06, a long-term ice station established during the Sixth Chinese National Arctic Research Expedition in 2014 in which the radiation and meteorological parameters of three melt ponds were continuously observed. In this paper, observed melt pond depth and thickness of sea ice under ponds were used as initial conditions. Furthermore, the calculation of sea ice freeboard in the melt pond scheme of level ice was improved by considering the effect of melt pond fraction. Consequently, by improving the formula of the maximum depth of melt pond above sea ice, simulation of melt pond albedo as well as other related parameters were successfully realized. Additionally, the inconsistency between the proportion coefficient of the incident solar radiation component and the weight coefficient of the corresponding albedo component was modified. The average errors between the simulated and observed albedo of the three ponds in the standard experiments were 0.01, 0.05 and 0.13, respectively. The sensitivity experiment results for the incident radiation proportion suggested that when the proportion of visible radiation increased by 8%, the simulation results of the melt pond albedo increased by 6%−8%. Results of the melt pond refreezing experiments suggested that when the thickness of lid ice is less than 0.02 m, the increase of simulated ice albedo is less than 0.006, resulting in a decrease of surface energy budget by about 1.1 W/m2. It is pointed out that providing an accurate proportion of incident radiation is necessary to improve the simulation of Arctic sea ice albedo. Furthermore, there are still some physical processes which need to be improved in Icepack/CICE model such as melt pond surface refreezing schemes, surface heat budget calculation, surface snow blowing effect and so on.
Based on one-dimensional sea ice column model Icepack, albedo and depth of melt pond were simulated. Atmospheric forcing data were collected from ICE06, a long-term ice station established during the Sixth Chinese National Arctic Research Expedition in 2014 in which the radiation and meteorological parameters of three melt ponds were continuously observed. In this paper, observed melt pond depth and thickness of sea ice under ponds were used as initial conditions. Furthermore, the calculation of sea ice freeboard in the melt pond scheme of level ice was improved by considering the effect of melt pond fraction. Consequently, by improving the formula of the maximum depth of melt pond above sea ice, simulation of melt pond albedo as well as other related parameters were successfully realized. Additionally, the inconsistency between the proportion coefficient of the incident solar radiation component and the weight coefficient of the corresponding albedo component was modified. The average errors between the simulated and observed albedo of the three ponds in the standard experiments were 0.01, 0.05 and 0.13, respectively. The sensitivity experiment results for the incident radiation proportion suggested that when the proportion of visible radiation increased by 8%, the simulation results of the melt pond albedo increased by 6%−8%. Results of the melt pond refreezing experiments suggested that when the thickness of lid ice is less than 0.02 m, the increase of simulated ice albedo is less than 0.006, resulting in a decrease of surface energy budget by about 1.1 W/m2. It is pointed out that providing an accurate proportion of incident radiation is necessary to improve the simulation of Arctic sea ice albedo. Furthermore, there are still some physical processes which need to be improved in Icepack/CICE model such as melt pond surface refreezing schemes, surface heat budget calculation, surface snow blowing effect and so on.
2021, 43(7): 75-89.
doi: 10.12284/hyxb2021143
Abstract:
Due to its high surface albedo, snow plays an important role in the air-ice-ocean interaction in high-latitude regions. Accurate snow mass balance calculations are needed to understand the evolution of sea ice and interaction between snow-ice and atmosphere better. One of the factors affecting snow mass balance is snow density. Constant mean snow bulk density is used to convert snow water equivalent to snow depth in the present 1-D high-resolution thermodynamic snow-ice model (such as HIGHTSI). Simplified to 2 snow layers, being fresh and old, algorithm reference to Lagrangian snow-evolution model (SnowModel-LG) used to treat layered snow compaction is introduced into HIGHTSI to reproduce the physical process of compacting in both the fresh and old layer and affecting the snow depth following the principle of mass conservation. Forced by ERA-Interim reanalysis data, modified HIGHTSI was applied to investigate the impact of snow density on snow depth along drift trajectories of 15 sea ice mass balance buoys (IMB) during snow accumulation period and assess the model results against observation. In contrast to the previous bulk snow density setting, with a constant density of 330 kg/m3 (T1) or 200 kg/m3 (T2), our new algorithm calculates snow depth by considering both the fresh and old snow densifying over time (T3). The simulations indicate that the improved algorithm is more reasonable to deal with the density evolution, and can reproduced the snow depth well. The overaccumulation caused by heaping continuously at the lower density of new snowfall can be avoided by considering the response of both the fresh and old snow depth to compaction. The absolute error calculated by layered snow compaction is reduced by 5 cm by setting the observation as a reference of both the fresh and old snow depth to compaction. The absolute error calculated by layered snow compaction in T2 is reduced by 5 cm by setting the observation as a reference.
Due to its high surface albedo, snow plays an important role in the air-ice-ocean interaction in high-latitude regions. Accurate snow mass balance calculations are needed to understand the evolution of sea ice and interaction between snow-ice and atmosphere better. One of the factors affecting snow mass balance is snow density. Constant mean snow bulk density is used to convert snow water equivalent to snow depth in the present 1-D high-resolution thermodynamic snow-ice model (such as HIGHTSI). Simplified to 2 snow layers, being fresh and old, algorithm reference to Lagrangian snow-evolution model (SnowModel-LG) used to treat layered snow compaction is introduced into HIGHTSI to reproduce the physical process of compacting in both the fresh and old layer and affecting the snow depth following the principle of mass conservation. Forced by ERA-Interim reanalysis data, modified HIGHTSI was applied to investigate the impact of snow density on snow depth along drift trajectories of 15 sea ice mass balance buoys (IMB) during snow accumulation period and assess the model results against observation. In contrast to the previous bulk snow density setting, with a constant density of 330 kg/m3 (T1) or 200 kg/m3 (T2), our new algorithm calculates snow depth by considering both the fresh and old snow densifying over time (T3). The simulations indicate that the improved algorithm is more reasonable to deal with the density evolution, and can reproduced the snow depth well. The overaccumulation caused by heaping continuously at the lower density of new snowfall can be avoided by considering the response of both the fresh and old snow depth to compaction. The absolute error calculated by layered snow compaction is reduced by 5 cm by setting the observation as a reference of both the fresh and old snow depth to compaction. The absolute error calculated by layered snow compaction in T2 is reduced by 5 cm by setting the observation as a reference.
2021, 43(7): 90-99.
doi: 10.12284/hyxb2021117
Abstract:
The evolution of atmospheric factors and sea ice growth of the Arctic high latitude region process are analyzed based on the data observed by the drifting automatic weather station over the period from August 2018 to May 2019. The evolution shows two different phases according to the sea ice drifting trajectory. The sea ice mainly drifted to the southeast in the first phase and drifted to the northeast in the second phase. The averaged air temperature and averaged relative humidity are −6.6℃ and 93% for the first phase and those are −29.3℃ and 76% for the second phase. The averaged pressure is higher in the second than that in the first phase. The sea ice drifting trajectory are mainly affected by the Beaufort High. The sea ice velocity from automatic weather station derived and NSIDC (National Snow and Ice Data Center) are compared and the result show that the zonal velocity is unanimous. The sea ice is mainly melting in the first and sea ice thickness show decrease in the first phase. The sea ice growth rate is −0.11 cm/d in August. The sea ice growth mainly occurs in the second phase. The sea ice growth rate is larger than 0.9 cm/d from January to March 2019. The largest monthly averaged sea ice growth rate is in March with the value of 1.1 cm/d and the sea ice keep growth until the end of the observation period.
The evolution of atmospheric factors and sea ice growth of the Arctic high latitude region process are analyzed based on the data observed by the drifting automatic weather station over the period from August 2018 to May 2019. The evolution shows two different phases according to the sea ice drifting trajectory. The sea ice mainly drifted to the southeast in the first phase and drifted to the northeast in the second phase. The averaged air temperature and averaged relative humidity are −6.6℃ and 93% for the first phase and those are −29.3℃ and 76% for the second phase. The averaged pressure is higher in the second than that in the first phase. The sea ice drifting trajectory are mainly affected by the Beaufort High. The sea ice velocity from automatic weather station derived and NSIDC (National Snow and Ice Data Center) are compared and the result show that the zonal velocity is unanimous. The sea ice is mainly melting in the first and sea ice thickness show decrease in the first phase. The sea ice growth rate is −0.11 cm/d in August. The sea ice growth mainly occurs in the second phase. The sea ice growth rate is larger than 0.9 cm/d from January to March 2019. The largest monthly averaged sea ice growth rate is in March with the value of 1.1 cm/d and the sea ice keep growth until the end of the observation period.
2021, 43(7): 100-113.
doi: 10.12284/hyxb2021123
Abstract:
Beaufort Gyre (BG) had presented the significant changes associated with the complicated interactions between the Arctic air-ice-ocean system. In this paper, the observed McLane Moored Profiler data combined with the oceanic and atmospheric reanalysis datasets are used to discuss the influence of atmospheric momentum input on the BG long term changes. The BG exhibited the three different stages from 1980 to 2018 (1980−1995, 1996−2007, 2008−2018). The BG kept a stable state during the recent period (2008−2018). Compared with the first period (1980−1995), the BG strength reached up to 4.39×10−7, and increased nearly twice during the recent period. Meanwhile, the upper ocean processes showed the measurable discrepancies, such as the BG area expanded, gyre moved northwestward, and upper baroclinicity enhanced. Accordingly, the leading upper circulation mode had undergone a significant shift during these two periods. During the recent period, that is the leading Pacific sector mode played the main role in the upper circulation, while the basin mode receded the domination. Since the air-ocean stress represents the atmospheric momentum input process, our study indicated the summer air-ocean stress (August−October) increased remarkably and was even equivalent to the contribution of sea ice. The increased atmospheric momentum input may benefit to the mean kinetic energy increasing, together with the Ekman pumping enhancing and cold halocline deepening. Thus, the mentioned processes resulted in the BG obvious enhancement during the recent period. The southern Canada basin was the key area for the atmospheric momentum input.
Beaufort Gyre (BG) had presented the significant changes associated with the complicated interactions between the Arctic air-ice-ocean system. In this paper, the observed McLane Moored Profiler data combined with the oceanic and atmospheric reanalysis datasets are used to discuss the influence of atmospheric momentum input on the BG long term changes. The BG exhibited the three different stages from 1980 to 2018 (1980−1995, 1996−2007, 2008−2018). The BG kept a stable state during the recent period (2008−2018). Compared with the first period (1980−1995), the BG strength reached up to 4.39×10−7, and increased nearly twice during the recent period. Meanwhile, the upper ocean processes showed the measurable discrepancies, such as the BG area expanded, gyre moved northwestward, and upper baroclinicity enhanced. Accordingly, the leading upper circulation mode had undergone a significant shift during these two periods. During the recent period, that is the leading Pacific sector mode played the main role in the upper circulation, while the basin mode receded the domination. Since the air-ocean stress represents the atmospheric momentum input process, our study indicated the summer air-ocean stress (August−October) increased remarkably and was even equivalent to the contribution of sea ice. The increased atmospheric momentum input may benefit to the mean kinetic energy increasing, together with the Ekman pumping enhancing and cold halocline deepening. Thus, the mentioned processes resulted in the BG obvious enhancement during the recent period. The southern Canada basin was the key area for the atmospheric momentum input.
2021, 43(7): 114-124.
doi: 10.12284/hyxb2021141
Abstract:
The extreme cyclones in the Arctic can reflect the characteristics of climate change in the Arctic and have important influence on the regulation of hydrometeorological elements in the Arctic. The characteristics of their activities and atmospheric circulation situation deserve attention. Using the daily reanalysis data provided by National Centers for Environmental Prediction and the National Center for Atmospheric Research (NCEP/NCAR) defines the Arctic Super Cyclone (ASC) processes. Then analyze the activity characteristics of the ASCs and their atmospheric circulation characteristics based on the NCEP/NCAR reanalysis data of the National Snow and Ice Data Center (NSIDC). The results show that the 5% threshold of the minimum pressure in the Arctic for identifying ASCs have a significant unimodal seasonal variation characteristic that is low in winter and high in summer, which means the intensity of ASC in winter is much stronger than that in summer. Most of the ASCs are imported from the Atlantic sector to the polar region via the Nordic Sea, Barents Sea and the Kara Sea. Besides, a small part of the ASCs are imported from the original or Pacific sector. Most ASCs are generated on the north side of the jet axis or outlet area of the jet stream on two oceans. A minimal number of ASCs are generated in the continent or the middle and low latitudes. And the vast majority of ASCs disappear in the polar region and cannot return to the middle latitudes. The frequency of polar native ASC accounted for about one-third of the total, and there was no significant trend of increase or decrease overall. However, the frequency of long-life ASCs increased with a 0.49 times/decade trend, indicating their duration increased. There is a strong correlation between ASCs frequency and the Arctic Oscillation (AO) in winter. There are low-temperature and low-pressure anomalies in the polar region of the regression of the atmospheric circulation pattern. The upper polar vortex deepens and the two ocean jets turn northward, while the central axis of the mid-latitude jet stream is weak. The formation and development of ASCs are not only conducive to the transition of AO to the positive phase, but also conducive to the enhancement of ASC activity under the positive phase of AO, which is a potential indicator of AO phase change.
The extreme cyclones in the Arctic can reflect the characteristics of climate change in the Arctic and have important influence on the regulation of hydrometeorological elements in the Arctic. The characteristics of their activities and atmospheric circulation situation deserve attention. Using the daily reanalysis data provided by National Centers for Environmental Prediction and the National Center for Atmospheric Research (NCEP/NCAR) defines the Arctic Super Cyclone (ASC) processes. Then analyze the activity characteristics of the ASCs and their atmospheric circulation characteristics based on the NCEP/NCAR reanalysis data of the National Snow and Ice Data Center (NSIDC). The results show that the 5% threshold of the minimum pressure in the Arctic for identifying ASCs have a significant unimodal seasonal variation characteristic that is low in winter and high in summer, which means the intensity of ASC in winter is much stronger than that in summer. Most of the ASCs are imported from the Atlantic sector to the polar region via the Nordic Sea, Barents Sea and the Kara Sea. Besides, a small part of the ASCs are imported from the original or Pacific sector. Most ASCs are generated on the north side of the jet axis or outlet area of the jet stream on two oceans. A minimal number of ASCs are generated in the continent or the middle and low latitudes. And the vast majority of ASCs disappear in the polar region and cannot return to the middle latitudes. The frequency of polar native ASC accounted for about one-third of the total, and there was no significant trend of increase or decrease overall. However, the frequency of long-life ASCs increased with a 0.49 times/decade trend, indicating their duration increased. There is a strong correlation between ASCs frequency and the Arctic Oscillation (AO) in winter. There are low-temperature and low-pressure anomalies in the polar region of the regression of the atmospheric circulation pattern. The upper polar vortex deepens and the two ocean jets turn northward, while the central axis of the mid-latitude jet stream is weak. The formation and development of ASCs are not only conducive to the transition of AO to the positive phase, but also conducive to the enhancement of ASC activity under the positive phase of AO, which is a potential indicator of AO phase change.
2021, 43(7): 125-137.
doi: 10.12284/hyxb2021079
Abstract:
Using archived data from Chinese Polar Numerical Weather Forecasting System (PNWFS) and America Antarctic Mesoscale Prediction System, the spatial and temporal distribution of katabatic winds and air mass flux from Dome A to the coast of Prydz Bay are analyzed, and basic characteristics of katabatic winds in the region are depicted. It is found that the katabatic winds in this area is strongly affected by the terrain of the Antarctica ice sheet. Steep terrain such as the western side of the Amery Ice Shelf sees stronger katabatic winds than smooth terrain does; and the katabatic winds vary greatly with the season for temporal distribution with stronger winds in winter. Adiabatic warming, which can be found in the area where strong katabatic winds flow, causes increasing of near surface temperature at the Amery Ice Shelf. The maximum katabatic wind speed zone is located at a height of about 100 m to 200 m above the ground. Katabatic winds extents to higher altitudes while surface winds are stronger. The surface air mass flux of the katabatic winds along the coast of the Prydz Bay is extremely uneven in spatial and temporal distribution. Strong katabatic winds in the Amery Ice Shelf are linked to more mesoscale cyclone activities in the Prydz Bay waters. The process of mesoscale cyclones induced by katabatic winds in the Prydz Bay is worthy of attention, thus the mechanism of cyclogenesis forced by katabatic winds needs further notice.
Using archived data from Chinese Polar Numerical Weather Forecasting System (PNWFS) and America Antarctic Mesoscale Prediction System, the spatial and temporal distribution of katabatic winds and air mass flux from Dome A to the coast of Prydz Bay are analyzed, and basic characteristics of katabatic winds in the region are depicted. It is found that the katabatic winds in this area is strongly affected by the terrain of the Antarctica ice sheet. Steep terrain such as the western side of the Amery Ice Shelf sees stronger katabatic winds than smooth terrain does; and the katabatic winds vary greatly with the season for temporal distribution with stronger winds in winter. Adiabatic warming, which can be found in the area where strong katabatic winds flow, causes increasing of near surface temperature at the Amery Ice Shelf. The maximum katabatic wind speed zone is located at a height of about 100 m to 200 m above the ground. Katabatic winds extents to higher altitudes while surface winds are stronger. The surface air mass flux of the katabatic winds along the coast of the Prydz Bay is extremely uneven in spatial and temporal distribution. Strong katabatic winds in the Amery Ice Shelf are linked to more mesoscale cyclone activities in the Prydz Bay waters. The process of mesoscale cyclones induced by katabatic winds in the Prydz Bay is worthy of attention, thus the mechanism of cyclogenesis forced by katabatic winds needs further notice.
2021, 43(7): 138-151.
doi: 10.12284/hyxb2021153
Abstract:
In the Canadian Circumpolar Flaw Lead System Study, the physical and optical properties of first-year ice during the freezing season were observed at the Amundsen Gulf from November 24th, 2007 to January 26th, 2008. The results show that the thickness of sea ice during this period ranged from 27 cm to 108 cm, while the snow depth varied between 0 cm and 6 cm. The changes of temperature, salinity and density in the interior of sea ice are respectively: temperature within the sea ice rose monotonically along with the increasing of depth, reaching a maximum of −2.2℃ at the surface and a minimum of −22.4℃ at the bottom; the salinity ranged from 3.30 to 11.70 with a C-shaped pattern in its vertical section, which means that the salinity of upper surface and bottom layer is larger than that in the middle part; the average density of the sea ice was slightly larger, which is (0.91±0.03) g/cm3. With the special designing of artificial light source and in-situ instrumentation, an obvious two-peek structure at 490 nm and 589 nm was found in the spectral distribution of the transmitted radiation through the first-year ice. The two-peak structure weakens as the thickness of sea ice increases, indicating the spectrum dependence of the attenuation. In the visible band, the spectral absorbance of both bare ice and snow-covered ice reaches its minimum at 490 nm, and rises as the wavelength moves towards 443 nm or 683 nm. However, for snow-covered ice, the variation of absorption rate is little enough to present a spectral independence. In addition, the spectral distribution of the attenuation coefficient was U-shaped in the visible band, with a minimum of 1.7 m−1 at 589 nm. The integral diffuse attenuation coefficient of the first-year ice in visible band was about 2.3 m−1, which was slightly higher than 1.5 m−1, the diffuse attenuation coefficient of multi-year floe ice. The difference of the optical properties between first-year ice in the Amundsen Gulf and multi-year ice in the north of Canada Basin is mainly attributed to various components of the sea ice inclusions caused by the input of terrestrial materials with different absorption and scattering properties.
In the Canadian Circumpolar Flaw Lead System Study, the physical and optical properties of first-year ice during the freezing season were observed at the Amundsen Gulf from November 24th, 2007 to January 26th, 2008. The results show that the thickness of sea ice during this period ranged from 27 cm to 108 cm, while the snow depth varied between 0 cm and 6 cm. The changes of temperature, salinity and density in the interior of sea ice are respectively: temperature within the sea ice rose monotonically along with the increasing of depth, reaching a maximum of −2.2℃ at the surface and a minimum of −22.4℃ at the bottom; the salinity ranged from 3.30 to 11.70 with a C-shaped pattern in its vertical section, which means that the salinity of upper surface and bottom layer is larger than that in the middle part; the average density of the sea ice was slightly larger, which is (0.91±0.03) g/cm3. With the special designing of artificial light source and in-situ instrumentation, an obvious two-peek structure at 490 nm and 589 nm was found in the spectral distribution of the transmitted radiation through the first-year ice. The two-peak structure weakens as the thickness of sea ice increases, indicating the spectrum dependence of the attenuation. In the visible band, the spectral absorbance of both bare ice and snow-covered ice reaches its minimum at 490 nm, and rises as the wavelength moves towards 443 nm or 683 nm. However, for snow-covered ice, the variation of absorption rate is little enough to present a spectral independence. In addition, the spectral distribution of the attenuation coefficient was U-shaped in the visible band, with a minimum of 1.7 m−1 at 589 nm. The integral diffuse attenuation coefficient of the first-year ice in visible band was about 2.3 m−1, which was slightly higher than 1.5 m−1, the diffuse attenuation coefficient of multi-year floe ice. The difference of the optical properties between first-year ice in the Amundsen Gulf and multi-year ice in the north of Canada Basin is mainly attributed to various components of the sea ice inclusions caused by the input of terrestrial materials with different absorption and scattering properties.
2021, 43(7): 152-161.
doi: 10.12284/hyxb2021145
Abstract:
The melting of sea ice affects the ocean heat absorption in the form of positive feedback, and plays an important role in the changes of the Arctic environment and economic activities in the Arctic region. Based on the daily sea ice concentration data of the Arctic Ocean from 1979 to 2018, the estimation method of sea ice retreat onset dates in the Arctic marginal sea was improved by comprehensively considering the factors such as sea ice conditions and so on in different seas. Comparative analyses of different methods show that this improved method can reflect the changes of ice conditions in different sea areas and different years, and can eliminate some influences of weather disturbance on the estimation of retreat onset, so as to avoid premature estimation results. By using this method, it is found that the retreat onset dates of every Arctic marginal sea are generally advanced. The advanced trends of retreat onset dates are generally the same as advanced trends of melt onset dates. However, different sea areas have different degrees of advancement. The Kara Sea and the Chukchi Sea have the strongest trend of early retreating, reaching 9 d/（10 a）, while the East Siberian Sea has the weakest trend, only 4 d/（10 a）. The difference of retreat onset dates gradually increases between these regions. There are significant interannual variations in the retreat onset dates, the standard deviations of each marginal sea are about 15 d. In the past decade, the difference between the earliest and the latest retreating reaches 50 d, which appeared in the Beaufort Sea.
The melting of sea ice affects the ocean heat absorption in the form of positive feedback, and plays an important role in the changes of the Arctic environment and economic activities in the Arctic region. Based on the daily sea ice concentration data of the Arctic Ocean from 1979 to 2018, the estimation method of sea ice retreat onset dates in the Arctic marginal sea was improved by comprehensively considering the factors such as sea ice conditions and so on in different seas. Comparative analyses of different methods show that this improved method can reflect the changes of ice conditions in different sea areas and different years, and can eliminate some influences of weather disturbance on the estimation of retreat onset, so as to avoid premature estimation results. By using this method, it is found that the retreat onset dates of every Arctic marginal sea are generally advanced. The advanced trends of retreat onset dates are generally the same as advanced trends of melt onset dates. However, different sea areas have different degrees of advancement. The Kara Sea and the Chukchi Sea have the strongest trend of early retreating, reaching 9 d/（10 a）, while the East Siberian Sea has the weakest trend, only 4 d/（10 a）. The difference of retreat onset dates gradually increases between these regions. There are significant interannual variations in the retreat onset dates, the standard deviations of each marginal sea are about 15 d. In the past decade, the difference between the earliest and the latest retreating reaches 50 d, which appeared in the Beaufort Sea.
2021, 43(7): 162-172.
doi: 10.12284/hyxb2021115
Abstract:
During the ice melting season, the surface, bottom and lateral melting of natural ice floes coexist, and the melting rate of the three is that the melting rate of the bottom is greater than the lateral, and the lateral is greater than the surface. And the smaller the ice floe size, the higher the proportion of lateral velocity. In order to solve the problem of including the small-scale ice floe scale indicators into the melting parameterization plan, in the low-temperature environment laboratory without radiation, no flow rate, controlled air temperature and water temperature, the disk samples of natural sea ice and artificially frozen fresh water ice were carried out. Experiments on the melting process of disc samples with different initial water temperatures and different initial diameters were carried out. Obtain the disc sample diameter, thickness and mass melting process. Based on these experimental data, a new indicator of sample diameter-to-thickness ratio was constructed. Through physical analysis and mathematical statistics, the melting rate of the surface and bottom surface of the sea ice and freshwater ice sample was established with the temperature gradient, the lateral melting rate, temperature difference, and diameter. The relationship between the thickness ratio. These relationships can be applied to the melting parameterization scheme of floating ice within a natural diameter range of 100 m. It is expected to solve the demand for numerical simulation of the energy and mass balance of the summer melting season of Arctic sea ice and coastal freshwater ice at the sea estuary.
During the ice melting season, the surface, bottom and lateral melting of natural ice floes coexist, and the melting rate of the three is that the melting rate of the bottom is greater than the lateral, and the lateral is greater than the surface. And the smaller the ice floe size, the higher the proportion of lateral velocity. In order to solve the problem of including the small-scale ice floe scale indicators into the melting parameterization plan, in the low-temperature environment laboratory without radiation, no flow rate, controlled air temperature and water temperature, the disk samples of natural sea ice and artificially frozen fresh water ice were carried out. Experiments on the melting process of disc samples with different initial water temperatures and different initial diameters were carried out. Obtain the disc sample diameter, thickness and mass melting process. Based on these experimental data, a new indicator of sample diameter-to-thickness ratio was constructed. Through physical analysis and mathematical statistics, the melting rate of the surface and bottom surface of the sea ice and freshwater ice sample was established with the temperature gradient, the lateral melting rate, temperature difference, and diameter. The relationship between the thickness ratio. These relationships can be applied to the melting parameterization scheme of floating ice within a natural diameter range of 100 m. It is expected to solve the demand for numerical simulation of the energy and mass balance of the summer melting season of Arctic sea ice and coastal freshwater ice at the sea estuary.
2021, 43(7): 173-182.
doi: 10.12284/hyxb2021107
Abstract:
Using RADASAT-2 sea ice SAR images, by the way of Prewitt, Sobel and Canny edge detection operators to calculate the sea ice perimeter in the image, and consider the influence of different image resolutions and different edge detection operators on the calculation results respectively. Combined with the ice lateral melting rate parameterization scheme, the sensitivity experiment of the lateral melting of sea ice to temperature was carried out, and the effect of image reconstruction resolution on the simulation results of sea ice lateral melting was analyzed. The results show that the best edge detection operator corresponding to different degrees of sea ice breakage in the image is different, and the best resolution is also different. Under the condition of only lateral melting, the melting area of sea ice increases exponentially with increasing temperature. The simulation trends of the three operators are basically the same. The Prewitt operator has the best simulation effect, and the corresponding optimal reconstruction resolution is 30 m×30 m, 65 m×65 m and 155 m×155 m.
Using RADASAT-2 sea ice SAR images, by the way of Prewitt, Sobel and Canny edge detection operators to calculate the sea ice perimeter in the image, and consider the influence of different image resolutions and different edge detection operators on the calculation results respectively. Combined with the ice lateral melting rate parameterization scheme, the sensitivity experiment of the lateral melting of sea ice to temperature was carried out, and the effect of image reconstruction resolution on the simulation results of sea ice lateral melting was analyzed. The results show that the best edge detection operator corresponding to different degrees of sea ice breakage in the image is different, and the best resolution is also different. Under the condition of only lateral melting, the melting area of sea ice increases exponentially with increasing temperature. The simulation trends of the three operators are basically the same. The Prewitt operator has the best simulation effect, and the corresponding optimal reconstruction resolution is 30 m×30 m, 65 m×65 m and 155 m×155 m.
2021, 43(7): 183-193.
doi: 10.12284/hyxb2021109
Abstract:
Based on the CryoSat-2 L1B data for April 2017−2019, this study compares and analyzes the multi temporal and spatial scale differences of UCL13, DTU10, DTU13, DTU15 and DTU18 mean sea surface height (MSS) models and the Arctic sea ice freeboard retrieval. The differences of various mean sea surface height models and the sea ice freeboard retrieval are compared with UCL13. The experimental results show that the average absolute deviation range between different MSS models is 0.19−0.26 m as well as the standard deviation range is 0.55−0.57 m, among which the difference between DTU18 and UCL13 is the smallest. The mean absolute deviation range of sea ice freeboard retrieved by the other four MSS models is 0.50−0.79 cm with the standard deviation range is 1.17−1.74 cm. Compared to airborne Operation IceBridge (OIB) data, the correlation coefficients of sea ice freeboard retrieved by the five MSS models range from 0.70 to 0.71 with the root mean square error range is 7.7−7.8 cm. Therefore, the biases between various MSS models have little influence on sea ice freeboard retrievals in the entire Arctic region, since biases impact both the lead and ice floe height measurements in the same way, and thus cancel out. However, in the areas with sparse leads, such as the northern Canadian Islands and the Laptev Sea, the sea ice freeboard retrieved by different MSS models varies greatly.
Based on the CryoSat-2 L1B data for April 2017−2019, this study compares and analyzes the multi temporal and spatial scale differences of UCL13, DTU10, DTU13, DTU15 and DTU18 mean sea surface height (MSS) models and the Arctic sea ice freeboard retrieval. The differences of various mean sea surface height models and the sea ice freeboard retrieval are compared with UCL13. The experimental results show that the average absolute deviation range between different MSS models is 0.19−0.26 m as well as the standard deviation range is 0.55−0.57 m, among which the difference between DTU18 and UCL13 is the smallest. The mean absolute deviation range of sea ice freeboard retrieved by the other four MSS models is 0.50−0.79 cm with the standard deviation range is 1.17−1.74 cm. Compared to airborne Operation IceBridge (OIB) data, the correlation coefficients of sea ice freeboard retrieved by the five MSS models range from 0.70 to 0.71 with the root mean square error range is 7.7−7.8 cm. Therefore, the biases between various MSS models have little influence on sea ice freeboard retrievals in the entire Arctic region, since biases impact both the lead and ice floe height measurements in the same way, and thus cancel out. However, in the areas with sparse leads, such as the northern Canadian Islands and the Laptev Sea, the sea ice freeboard retrieved by different MSS models varies greatly.
2021, 43(7): 194-204.
doi: 10.12284/hyxb2021113
Abstract:
The Nares Strait, located between Ellesmere Island, Canada and Greenland, is one of the important channels for the export of Arctic sea ice. The surface fresh water brought by the melting of these sea ice has a vital impact on the formation of deep water in the Baffin Bay and the Labrador Sea. However, due to its relatively narrow structure, there is no detailed study on the sea ice motion in this area. In this study, the daily Sentinel-1 images were used to extract the information of sea ice motion in the northern region of Nares Strait from September 2016 to August 2017, to show the motion process of ice floes in the strait, and to analyze the characteristics and influencing factors of ice floe motion combined with wind speed, current speed and other data. The results show that wind and current jointly dominate the motion of sea ice, with the correlation coefficients are 0.767 and 0.709, respectively. The multiple linear regression model established by wind speed, current speed and sea ice concentration with ice speed also has the complex determination coefficient reaching 0.727. Further analysis shows that both wind and sea current have relatively less influence on sea ice speed when their speed is relatively stable. The results of this study on the influence of wind and ocean currents on the process of sea ice motion can provide references for the study of ocean-atmospheric dynamics models.
The Nares Strait, located between Ellesmere Island, Canada and Greenland, is one of the important channels for the export of Arctic sea ice. The surface fresh water brought by the melting of these sea ice has a vital impact on the formation of deep water in the Baffin Bay and the Labrador Sea. However, due to its relatively narrow structure, there is no detailed study on the sea ice motion in this area. In this study, the daily Sentinel-1 images were used to extract the information of sea ice motion in the northern region of Nares Strait from September 2016 to August 2017, to show the motion process of ice floes in the strait, and to analyze the characteristics and influencing factors of ice floe motion combined with wind speed, current speed and other data. The results show that wind and current jointly dominate the motion of sea ice, with the correlation coefficients are 0.767 and 0.709, respectively. The multiple linear regression model established by wind speed, current speed and sea ice concentration with ice speed also has the complex determination coefficient reaching 0.727. Further analysis shows that both wind and sea current have relatively less influence on sea ice speed when their speed is relatively stable. The results of this study on the influence of wind and ocean currents on the process of sea ice motion can provide references for the study of ocean-atmospheric dynamics models.
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