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 durin...Sea ice and the snow pack on top of it were investigated using Chinese National Arctic Research Expedition (CHINARE) buoy data. Two polar hydrometeorological drifters, known as Zeno ice stations, were deployed during CHINARE 2003. A new type of high-resolution Snow and Ice Mass Balance Arrays, known as SIMBA buoys, were deployed during CHINARE 2014. Data from those buoys were applied to investigate the thickness of sea ice and snow in the CHINARE domain. A simple approach was applied to estimate the average snow thickness on the basis of Zeno temperature data. Snow and ice thicknesses were also derived from vertical temperature profile data based on the SIMBA buoys. A one-dimensional snow and ice thermodynamic model (HIGHTSI) was applied to calculate the snow and ice thickness along the buoy drift trajectories. The model forcing was based on forecasts and analyses of the European Centre for Medium-Range Weather Forecasts (ECMWF). The Zeno buoys drifted in a confined area during 2003-2004. The snow thickness modelled applying HIGHTSI was consistent with results based on Zeno buoy data. The SIMBA buoys drifted from 81. 1°N, 157.4°W to 73.5°N, 134.9°W in 15 months during 2014-2015. The total ice thickness increased from an initial August 2014 value of 1.97 m to a maximum value of 2.45 in before the onset of snow melt in May 2015; the last observation was approximately 1 m in late November 2015. The ice thickness based on HIGHTSI agreed with SIMBA measurements, in particular when the seasonal variation of oceanic heat flux was taken into account, but the modelled snow thickness differed from the observed one. Sea ice thickness derived from SIMBA data was reasonably good in cold conditions, but challenges remain in both snow and ice thickness in summer.展开更多
The negative freeboard of sea ice(i.e., the height of ice surface below sea level) with subsequent flooding is widespread in the Southern Ocean, as opposed to the Arctic, due to the relatively thicker ice and thinner ...The negative freeboard of sea ice(i.e., the height of ice surface below sea level) with subsequent flooding is widespread in the Southern Ocean, as opposed to the Arctic, due to the relatively thicker ice and thinner snow. In this study, we used the observations of snow and ice thickness from 103 ice mass balance buoys(IMBs) and NASA Operation IceBridge Aircraft Missions to investigate the spatial distribution of negative freeboard of Arctic sea ice. The Result showed that seven IMBs recorded negative freeboards, which were sporadically located in the seas around Northeast Greenland, the Central Arctic Ocean, and the marginal areas of the Chukchi–Beaufort Sea. The observed maximum values of negative freeboard could reach-0.12 m in the seas around Northeast Greenland. The observations from IceBridge campaigns also revealed negative freeboard comparable to those of IMBs in the seas around North Greenland and the Beaufort Sea. We further investigated the large-scale distribution of negative freeboard using NASA CryoSat-2 radar altimeter data, and the result indicates that except for the negative freeboard areas observed by IMBs and IceBridge, there are negative freeboards in other marginal seas of the Arctic Ocean. However, the comparison of the satellite data with the IMB data and IceBridge data shows that the Cryosat-2 data generally overestimate the extent and magnitude of the negative freeboard in the Arctic.展开更多
Variation of vertical profiles of sea ice temperature and adjacent atmosphere and ocean temperatures were measured by ice drifting buoys deployed in the northeast Chukchi Sea as part of the 2003 Chinese Arctic Researc...Variation of vertical profiles of sea ice temperature and adjacent atmosphere and ocean temperatures were measured by ice drifting buoys deployed in the northeast Chukchi Sea as part of the 2003 Chinese Arctic Research Expedition.The buoy observations (September 2003 to February 2005) show that the cooling of the ice began in late September,propagated down through the ice,reaching the bottom of the ice in December,and continued throughout the winter.In winter 2003/04,some obvious warmings were observed in the upper portion of the ice in response to major warmings in the overlying atmosphere associated with the periodicity of storms in the northeast Chukchi Sea.It is found that the melt season at the buoy site in 2004 was about 15% longer than normal.The buoy observed vertical ice temperature profiles were used as a diagnostic for sea ice model evaluation.The results show that the simulated ice temperature profiles have large discrepancies as compared with the observations.展开更多
An ice mass balance buoy(IMB)monitors the evolution of snow and ice cover on seas,ice caps and lakes through the measurement of various variables.The crucial measurement of snow and ice thickness has been achieved usi...An ice mass balance buoy(IMB)monitors the evolution of snow and ice cover on seas,ice caps and lakes through the measurement of various variables.The crucial measurement of snow and ice thickness has been achieved using acoustic sounders in early devices but a more recently developed IMB called the Snow and Ice Mass Balance Array(SIMBA)measures vertical temperature profiles through the air-snow-ice-water column using a thermistor string.The determination of snow depth and ice thickness from SIMBA temperature profiles is presently a manual process.We present an automated algorithm to perform this task.The algorithm is based on heat flux continuation,limit ratio between thermal heat conductivity of snow and ice,and minimum resolution(±0.0625°C)of the temperature sensors.The algorithm results are compared with manual analyses,in situ borehole measurements and numerical model simulation.The bias and root mean square error between algorithm and other methods ranged from 1 to 9 cm for ice thickness counting 2%–7%of the mean observed values.The algorithm works well in cold condition but becomes less reliable in warmer conditions where the vertical temperature gradient is reduced.展开更多
基金The National Natural Science Foundation of China under contract Nos 41428603,41376188,41376005 and 41506221the Academy of Finland under contract No.283101+1 种基金the Chinese Arctic and Antarctic Administration Project under contract No.201614the Chinese Polar Environment Comprehensive Investigation and Assessment Programs under contract No.CHINARE-03-01
文摘Sea ice and the snow pack on top of it were investigated using Chinese National Arctic Research Expedition (CHINARE) buoy data. Two polar hydrometeorological drifters, known as Zeno ice stations, were deployed during CHINARE 2003. A new type of high-resolution Snow and Ice Mass Balance Arrays, known as SIMBA buoys, were deployed during CHINARE 2014. Data from those buoys were applied to investigate the thickness of sea ice and snow in the CHINARE domain. A simple approach was applied to estimate the average snow thickness on the basis of Zeno temperature data. Snow and ice thicknesses were also derived from vertical temperature profile data based on the SIMBA buoys. A one-dimensional snow and ice thermodynamic model (HIGHTSI) was applied to calculate the snow and ice thickness along the buoy drift trajectories. The model forcing was based on forecasts and analyses of the European Centre for Medium-Range Weather Forecasts (ECMWF). The Zeno buoys drifted in a confined area during 2003-2004. The snow thickness modelled applying HIGHTSI was consistent with results based on Zeno buoy data. The SIMBA buoys drifted from 81. 1°N, 157.4°W to 73.5°N, 134.9°W in 15 months during 2014-2015. The total ice thickness increased from an initial August 2014 value of 1.97 m to a maximum value of 2.45 in before the onset of snow melt in May 2015; the last observation was approximately 1 m in late November 2015. The ice thickness based on HIGHTSI agreed with SIMBA measurements, in particular when the seasonal variation of oceanic heat flux was taken into account, but the modelled snow thickness differed from the observed one. Sea ice thickness derived from SIMBA data was reasonably good in cold conditions, but challenges remain in both snow and ice thickness in summer.
基金supported by the National Key Research and Development Program of China (No. 2018YFC1406104)the National Natural Science Foundation of China (Nos. 41425003 and 41971084)。
文摘The negative freeboard of sea ice(i.e., the height of ice surface below sea level) with subsequent flooding is widespread in the Southern Ocean, as opposed to the Arctic, due to the relatively thicker ice and thinner snow. In this study, we used the observations of snow and ice thickness from 103 ice mass balance buoys(IMBs) and NASA Operation IceBridge Aircraft Missions to investigate the spatial distribution of negative freeboard of Arctic sea ice. The Result showed that seven IMBs recorded negative freeboards, which were sporadically located in the seas around Northeast Greenland, the Central Arctic Ocean, and the marginal areas of the Chukchi–Beaufort Sea. The observed maximum values of negative freeboard could reach-0.12 m in the seas around Northeast Greenland. The observations from IceBridge campaigns also revealed negative freeboard comparable to those of IMBs in the seas around North Greenland and the Beaufort Sea. We further investigated the large-scale distribution of negative freeboard using NASA CryoSat-2 radar altimeter data, and the result indicates that except for the negative freeboard areas observed by IMBs and IceBridge, there are negative freeboards in other marginal seas of the Arctic Ocean. However, the comparison of the satellite data with the IMB data and IceBridge data shows that the Cryosat-2 data generally overestimate the extent and magnitude of the negative freeboard in the Arctic.
基金supported by the 100 Talents Program of the Chinese Academy of Sciences,the National Basic Research Program of China (2006CB403605)the National Natural Science Foundation of China (40676003 and 40876099)the China Meteorological Administration (GYHY200806006)
文摘Variation of vertical profiles of sea ice temperature and adjacent atmosphere and ocean temperatures were measured by ice drifting buoys deployed in the northeast Chukchi Sea as part of the 2003 Chinese Arctic Research Expedition.The buoy observations (September 2003 to February 2005) show that the cooling of the ice began in late September,propagated down through the ice,reaching the bottom of the ice in December,and continued throughout the winter.In winter 2003/04,some obvious warmings were observed in the upper portion of the ice in response to major warmings in the overlying atmosphere associated with the periodicity of storms in the northeast Chukchi Sea.It is found that the melt season at the buoy site in 2004 was about 15% longer than normal.The buoy observed vertical ice temperature profiles were used as a diagnostic for sea ice model evaluation.The results show that the simulated ice temperature profiles have large discrepancies as compared with the observations.
基金Academy of Finland[grant number 317999]Natural Science Foundation of China[grant numbers 41376005,41406218,41428603,41506221,11571383]+2 种基金European Union’s Horizon 2020 research and innovation programme[No 727890-INTAROS]the Key Research Program of Frontier Sciences of CAS[QYZDY-SSWDQC021]the Science and Technology Program Guangzhou,China[201804020053].
文摘An ice mass balance buoy(IMB)monitors the evolution of snow and ice cover on seas,ice caps and lakes through the measurement of various variables.The crucial measurement of snow and ice thickness has been achieved using acoustic sounders in early devices but a more recently developed IMB called the Snow and Ice Mass Balance Array(SIMBA)measures vertical temperature profiles through the air-snow-ice-water column using a thermistor string.The determination of snow depth and ice thickness from SIMBA temperature profiles is presently a manual process.We present an automated algorithm to perform this task.The algorithm is based on heat flux continuation,limit ratio between thermal heat conductivity of snow and ice,and minimum resolution(±0.0625°C)of the temperature sensors.The algorithm results are compared with manual analyses,in situ borehole measurements and numerical model simulation.The bias and root mean square error between algorithm and other methods ranged from 1 to 9 cm for ice thickness counting 2%–7%of the mean observed values.The algorithm works well in cold condition but becomes less reliable in warmer conditions where the vertical temperature gradient is reduced.