An assessment of arctic sea ice concentration retrieval based on “HY-2” scanning radiometer data using field observations during CHINARE-2012 and other satellite instruments

A retrieval algorithm of arctic sea ice concentration (SIC) based on the brightness temperature data of “HY-2” scanning microwave radiometer has been constructed. The tie points of the brightness tempe...     

中国第四次北极科学考察期间北极点附近海冰和融池的航空遥感观测

An aerial photography has been used to provide validation data on sea ice near the North Pole where most polar orbiting satellites cannot cover. This kind of data can also be used as a supplement for missing data and for reducing the uncertainty of data interpolation. The aerial photos are analyzed near the North Pole collected during the Chinese national arctic research expedition in the summer of 2010(CHINARE2010). The result shows that the average fraction of open water increases from the ice camp at approximately 87°N to the North Pole, resulting in the decrease in the sea ice. The average sea ice concentration is only 62.0% for the two flights(16 and 19 August 2010). The average albedo(0.42) estimated from the area ratios among snow-covered ice,melt pond and water is slightly lower than the 0.49 of HOTRAX 2005. The data on 19 August 2010 shows that the albedo decreases from the ice camp at approximately 87°N to the North Pole, primarily due to the decrease in the fraction of snow-covered ice and the increase in fractions of melt-pond and open-water. The ice concentration from the aerial photos and AMSR-E(The Advanced Microwave Scanning Radiometer-Earth Observing System) images at 87.0°–87.5°N exhibits similar spatial patterns, although the AMSR-E concentration is approximately 18.0%(on average) higher than aerial photos. This can be attributed to the 6.25 km resolution of AMSR-E, which cannot separate melt ponds/submerged ice from ice and cannot detect the small leads between floes. Thus, the aerial photos would play an important role in providing high-resolution independent estimates of the ice concentration and the fraction of melt pond cover to validate and/or supplement space-borne remote sensing products near the North Pole.     

Modelling the annual cycle of landfast ice near Zhongshan Station,East Antarctica

A high resolution one-dimensional thermodynamic snow and ice(HIGHTSI) model was used to model the annual cycle of landfast ice mass and heat balance near Zhongshan Station, East Antarctica. The model was forced and initialized by meteorological and sea ice in situ observations from April 2015 to April 2016. HIGHTSI produced a reasonable snow and ice evolution in the validation experiments, with a negligible mean ice thickness bias of(0.003±0.06) m compared to in situ observations. To further examine the impact of different snow conditions on annual evolution of first-year ice(FYI), four sensitivity experiments with different precipitation schemes(0, half, normal, and double) were performed. The results showed that compared to the snow-free case,the insulation effect of snow cover decreased bottom freezing in the winter, leading to 15%–26% reduction of maximum ice thickness. Thick snow cover caused negative freeboard and flooding, and then snow ice formation,which contributed 12%–49% to the maximum ice thickness. In early summer, snow cover delayed the onset of ice melting for about one month, while the melting of snow cover led to the formation of superimposed ice,accounting for 5%–10% of the ice thickness. Internal ice melting was a significant contributor in summer whether snow cover existed or not, accounting for 35%–56% of the total summer ice loss. The multi-year ice(MYI)simulations suggested that when snow-covered ice persisted from FYI to the 10 th MYI, winter congelation ice percentage decreased from 80% to 44%(snow ice and superimposed ice increased), while the contribution of internal ice melting in the summer decreased from 45% to 5%(bottom ice melting dominated).     

基于HY-2A散射计数据的极区海冰范围反演方法及其评估

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.     

基于AMSR-E数据的多年冰密集度反演算法研究

In recent years, the rapid decline of Arctic sea ice area(SIA) and sea ice extent(SIE), especially for the multiyear(MY) ice, has led to significant effect on climate change. The accurate retrieval of MY ice concentration retrieval is very important and challenging to understand the ongoing changes. Three MY ice concentration retrieval algorithms were systematically evaluated. A similar total ice concentration was yielded by these algorithms, while the retrieved MY sea ice concentrations differs from each other. The MY SIA derived from NASA TEAM algorithm is relatively stable. Other two algorithms created seasonal fluctuations of MY SIA, particularly in autumn and winter. In this paper, we proposed an ice concentration retrieval algorithm, which developed the NASA TEAM algorithm by adding to use AMSR-E 6.9 GHz brightness temperature data and sea ice concentration using 89.0GHz data. Comparison with the reference MY SIA from reference MY ice, indicates that the mean difference and root mean square(rms) difference of MY SIA derived from the algorithm of this study are 0.65×106 km2 and0.69×106 km2 during January to March, –0.06×106 km2 and 0.14×106 km2 during September to December respectively. Comparison with MY SIE obtained from weekly ice age data provided by University of Colorado show that, the mean difference and rms difference are 0.69×106 km2 and 0.84×106 km2, respectively. The developed algorithm proposed in this study has smaller difference compared with the reference MY ice and MY SIE from ice age data than the Wang's, Lomax' and NASA TEAM algorithms.     

Application of the HY-1 satellite to sea ice monitoring and forecasting

The HY-1A satellite is the first oceanic satellite of China. During the winter of 2002-2003, the data of the HY-1A were applied to the sea ice monitoring and forecasting for the Bohai Sea of China for the fhst time. The sea ice retrieval system of the HY-1A has been constructed. It receives 1B data from the satellite, outputs sea ice images and provides digital products of ice concentration, ice thickness and ice edge, which can be used as important information for sea ice monitoring and the initial fields of the numeric sea ice forecast and as one of the reference data for the sea ice forecasting verification. The sea ice retrieval system of the satellite is described, including its processes, methods and parameters. The retrieving results and their application to the sea ice monitoring and forecasting for the Bohai Sea are also discussed.     

基于中国北极考察布放浮标观测和数值模拟的海冰和积雪厚度变化分析

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 during2014–2015.The total ice thickness increased from an initial August 2014 value of 1.97 m to a maximum value of2.45 m before the onset of snow melt in May 2015;the last observation was approximately 1 m in late November2015.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.     

2018年北极太平洋区域夏季海冰物理及光学性质的研究

The reduction in Arctic sea ice in summer has been reported to have a significant impact on the global climate. In this study, Arctic sea ice/snow at the end of the melting season in 2018 was investigated during CHINARE-2018, in terms of its temperature, salinity, density and textural structure, the snow density, water content and albedo, as well as morphology and albedo of the refreezing melt pond. The interior melting of sea ice caused a strong stratification of temperature, salinity and density. The temperature of sea ice ranged from –0.8℃ to 0℃, and exhibited linear cooling with depth. The average salinity and density of sea ice were approximately 1.3 psu and 825 kg/m~3, respectively, and increased slightly with depth. The first-year sea ice was dominated by columnar grained ice. Snow cover over all the investigated floes was in the melt phase, and the average water content and density were 0.74% and 241 kg/m~3, respectively. The thickness of the thin ice lid ranged from 2.2 cm to 7.0 cm, and the depth of the pond ranged from 1.8 cm to 26.8 cm. The integrated albedo of the refreezing melt pond was in the range of 0.28–0.57. Because of the thin ice lid, the albedo of the melt pond improved to twice as high as that of the mature melt pond. These results provide a reference for the current state of Arctic sea ice and the mechanism of its reduction.     

东南极中山站陆缘固定冰2011/2012年度的时空变化

Annual observations of first-year ice(FYI) and second-year ice(SYI) near Zhongshan Station, East Antarctica,were conducted for the first time from December 2011 to December 2012. Melt ponds appeared from early December 2011. Landfast ice partly broke in late January, 2012 after a strong cyclone. Open water was refrozen to form new ice cover in mid-February, and then FYI and SYI co-existed in March with a growth rate of 0.8 cm/d for FYI and a melting rate of 2.7 cm/d for SYI. This difference was due to the oceanic heat flux and the thickness of ice,with weaker heat flux through thicker ice. From May onward, FYI and SYI showed a similar growth by 0.5 cm/d.Their maximum thickness reached 160.5 cm and 167.0 cm, respectively, in late October. Drillings showed variations of FYI thickness to be generally less than 1.0 cm, but variations were up to 33.0 cm for SYI in March,suggesting that the SYI bottom was particularly uneven. Snow distribution was strongly affected by wind and surface roughness, leading to large thickness differences in the different sites. Snow and ice thickness in Nella Fjord had a similar "east thicker, west thinner" spatial distribution. Easterly prevailing wind and local topography led to this snow pattern. Superimposed ice induced by snow cover melting in summer thickened multi-year ice,causing it to be thicker than the snow-free SYI. The estimated monthly oceanic heat flux was ～30.0 W/m2 in March–May, reducing to ～10.0 W/m2 during July–October, and increasing to ～15.0 W/m2 in November. The seasonal change and mean value of 15.6 W/m2 was similar to the findings of previous research. The results can be used to further our understanding of landfast ice for climate change study and Chinese Antarctic Expedition services.     

Molecular genetic diversity of bacteria in the bottom section of arctic sea ice from the Canada Basin

PCR-DGGE approach was used to analyze bacterial diversity in the bottom section of seven arctic sea ice samples colleted from the Canada Basin. Thirty-two 16S rDNA sequences were obtained from prominent DGGE bands. The closest relatives of these sequences are found to be those of cultivated or uncultured bacteria from antarctic or arctic sea ice. Phylogenetic analysis clustered these sequences or phylotypes within α- proteobacteria, γ-proteobacteria and CFB (cytophaga-flexibacter-bacteroides) group. Sequences belonging to γ-proteobacteria were dominant and members of the CFB group were highly abundant. It was suggested that the CFB group was the representative of the bottom section of sea ice samples.     

Validation of the “HY-2” altimeter wet tropospheric path delay correction based on radiosonde data

Wet tropospheric path delay （PD） is a highly variable term for the altimeter measurement of a sea surface height, caused by the refraction effect of atmospheric water vapor and cloud liquid water. In order to esti- mate PD values, the ＂HY-2＂ system includes a calibration microwave radiometer （CMR） operating at 18.7, 23.8 and 37 GHz. The PD data of the CMR were compared and validated by coincident radiosonde profiles from ten globally distributed radiosonde stations during October 2011 to August 2012. The temporal interval was 1 h. In order to avoid land contamination, different spatial intervals between these two data sets were tested. The empirical fit function of PD uncertainty and spatial interval was found and extrapolated to the ideal situation that the data of CMR and radiosonde were totally coincident. The stability of the brightness temperature of the CMR and its impact on the PD correction was also studied. Consequently, the uncertainty of the PD algorithm of the CMR was estimated to be 2.1 cm.     

Physical structure and vertical distribution of chlorophyll a in winter sea ice from the northwestern Weddell Sea, Antarctica

The investigation on sea-ice biology in combination with physics, chemistry and ecology was carried out in the northwestern Weddell Sea, Antarctica, during the cruise ANT/XX III-7 on board POLARSTERN in the austral winter (August-October) in 2006. The distribution of chlorophyll a was measured and related to sea ice texture. The mean concentrations of chlorophyll a in the sea ice varied considerably with ice texture. The concentration of chlorophyll a per core ranged from 2.10– 84.40 μg/dm 3 with a mean of 16.56 μg/dm 3 . And the value of R (chlorophyll a / gross chlorophyll) ranged from 0.79–0.83. These high winter chlorophyll values indicate that primary production is considerable and confirms that there is significant primary production in Antarctic sea ice during winter. Thus this constitutes a major proportion of southern ocean primary production and carbon flux before the sea ice retreats.     

北极海冰变率的独特模式及其与大气强迫的关系

The spatial structure of the Arctic sea ice concentration(SIC) variability and the connection to atmospheric as well as radiative forcing during winter and summer for the 1979–2017 period are investigated. The interannual variability with different spatial characteristics of SIC in summer and winter is extracted using the empirical orthogonal function(EOF) analysis. The present study confirms that the atmospheric circulation has a strong influence on the SIC through both dynamic and thermodynamic processes, as the heat flux anomalies in summer are radiatively forced while those in winter contain both radiative and "circulation-induced" components. Thus,atmospheric fluctuations have an explicit and extensive influence to the SIC through complex mechanisms during both seasons. Moreover, analysis of a variety of atmospheric variables indicates that the primary mechanism about specific regional SIC patterns in Arctic marginal seas are different with special characteristics.     

Verification and recalibration of HY-2A microwave radiometer brightness temperature

HY-2A is the first one of the Chinese HY-2 ocean satellite series carrying a microwave radiometer(RM)to measure sea surface temperature,sea surface wind speed,atmospheric water vapor,cloud liquid water content,and rain rate.We verified the RM level 1B brightness temperature(T B)to retrieve environmental parameters.In the verification,TB that simulated using the ocean-atmosphere radiative transfer model(RTM)was used as a reference.The total bias and total standard deviation(SD)of the RM level 1B TB,with reference to the RTM simulation,ranged-20.6-4.38 K and 0.7-2.93 K,respectively.We found that both the total bias and the total SD depend on the frequency and polarization,although the values for ascending and descending passes are different.In addition,substantial seasonal variation of the bias was found at all channels.The verification results indicate the RM has some problems regarding calibration,e.g.,correction of antenna spillover and antenna physical emission,especially for the 18.7-GHz channel.Based on error analyses,a statistical recalibration algorithm was designed and recalibration was performed for the RM level 1B TB.Validation of the recalibrated TB indicated that the quality of the recalibrated RM level 1B TB was improved significantly.The bias of the recalibrated T B at all channels was reduced to<0.4 K,seasonal variation was almost eradicated,and SD was diminished(i.e.,the SD of the 18.7-GHz channel was reduced by more than 0.5K).     

The validation of the significant wave height product of HY-2 altimeter-primary results

The HY-2 satellite was successfully launched on 16 August 2011. The HY-2 significant wave height （SWH） is validated by the data from the South China Sea （SCS） field experiment, National Data Buoy Center （NDBC/ buoys and Jason-1/2 altimeters, and is corrected using a linear regression with in-situ measurements. Com- pared with NDBC SWH, the HY-2 SWH show a RMS of 0.36 m, which is similar to Jason- 1 and Jason-2 SWH with the RMS of 0.35 m and 0.37 m respectively; the RMS of corrected HY-2 SWH is 0.27 m, similar to 0.27 m and 0.23 m of corrected Jason-1 and Jason-2 SWH. Therefore the accuracy of HY-2 SWH products is close to that of Jason-1/2 SWH, and the linear regression function derived can improve the accuracy of HY-2 SWH products.     

基于MODIS热红外数据的渤海海冰厚度反演

Level ice thickness distribution pattern in the Bohai Sea in the winter of 2009–2010 was investigated in this paper using MODIS night-time thermal infrared imagery.The cloud cover in the imagery was masked out manually.Level ice thickness was calculated using MODIS ice surface temperature and an ice surface heat balance equation.Weather forcing data was from the European Centre for Medium-Range Weather Forecasts(ECMWF) analyses.The retrieved ice thickness agreed reasonable well with in situ observations from two off-shore oil platforms.The overall bias and the root mean square error of the MODIS ice thickness are –1.4 cm and 3.9 cm,respectively.The MODIS results under cold conditions(air temperature –10°C) also agree with the estimated ice growth from Lebedev and Zubov models.The MODIS ice thickness is sensitive to the changes of the sea ice and air temperature,in particular when the sea ice is relatively thin.It is less sensitive to the wind speed.Our method is feasible for the Bohai Sea operational ice thickness analyses during cold freezing seasons.     

夏季北极海冰表皮温度实测资料与MODIS产品的对比分析

Ship-borne infrared radiometric measurements conducted during the Chinese National Arctic Research Expedition(CHINARE) in 2008, 2010, 2012, 2014, 2016 and 2017 were used for in situ validation studies of the Moderate Resolution Imaging Spectroradiometer(MODIS) sea ice surface temperature(IST) product.Observations of sea ice were made using a KT19.85 radiometer mounted on the Chinese icebreaker Xuelong between July and September over six years. The MODIS-derived ISTs from the satellites, Terra and Aqua, both show close correspondence with ISTs derived from radiometer spot measurements averaged over areas of 4 km×4 km, spanning the temperature range of 262–280 K with a ±1.7 K(Aqua) and ±1.6 K(Terra) variation. The consistency of the results over each year indicates that MODIS provides a suitable platform for remotely deriving surface temperature data when the sky is clear. Investigation into factors that cause the MODIS IST bias(defined as the difference between MODIS and KT19.85 ISTs) shows that large positive bias is caused by increased coverage of leads and melt ponds, while large negative bias mostly arises from undetected clouds. Thin vapor fog forming over Arctic sea ice may explain the cold bias when cloud cover is below 20%.     

Sea surface temperature retrieval based on simulated microwave polarimetric measurements of a one-dimensional synthetic aperture microwave radiometer

Compared with traditional real aperture microwave radiometers, one-dimensional synthetic aperture microwave radiometers have higher spatial resolution. In this paper, we proposed to retrieve sea surface temperature using a one-dimensional synthetic aperture microwave radiometer that operates at frequencies of 6.9 GHz, 10.65 GHz,18.7 GHz and 23.8 GHz at multiple incidence angles. We used the ERA5 reanalysis data provided by the European Centre for Medium-Range Weather Forecasts and a radiation transmission forward model to calculate the model brightness temperature. The brightness temperature measured by the spaceborne one-dimensional synthetic aperture microwave radiometer was simulated by adding Gaussian noise to the model brightness temperature.Then, a backpropagation(BP) neural network algorithm, a random forest(RF) algorithm and two multiple linear regression algorithms(RE1 and RE2) were developed to retrieve sea surface temperature from the measured brightness temperature within the incidence angle range of 0°–65°. The results show that the retrieval errors of the four algorithms increase with the increasing Gaussian noise. The BP achieves the lowest retrieval errors at all incidence angles. The retrieval error of the RE1 and RE2 decrease first and then increase with the incidence angle and the retrieval error of the RF is contrary to that of RE1 and RE2.     

基于卫星高度计的北极海冰厚度变化研究

A modified algorithm taking into account the first year(FY) and multiyear(MY) ice densities is used to derive a sea ice thickness from freeboard measurements acquired by satellite altimetry ICESat(2003–2008). Estimates agree with various independent in situ measurements within 0.21 m. Both the fall and winter campaigns see a dramatic extent retreat of thicker MY ice that survives at least one summer melting season. There were strong seasonal and interannual variabilities with regard to the mean thickness. Seasonal increases of 0.53 m for FY the ice and 0.29 m for the MY ice between the autumn and the winter ICESat campaigns, roughly 4–5 month separation, were found. Interannually, the significant MY ice thickness declines over the consecutive four ICESat winter campaigns(2005–2008) leads to a pronounced thickness drop of 0.8 m in MY sea ice zones. No clear trend was identified from the averaged thickness of thinner, FY ice that emerges in autumn and winter and melts in summer. Uncertainty estimates for our calculated thickness, caused by the standard deviations of multiple input parameters including freeboard, ice density, snow density, snow depth, show large errors more than 0.5 m in thicker MY ice zones and relatively small standard deviations under 0.5 m elsewhere. Moreover, a sensitivity analysis is implemented to determine the separate impact on the thickness estimate in the dependence of an individual input variable as mentioned above. The results show systematic bias of the estimated ice thickness appears to be mainly caused by the variations of freeboard as well as the ice density whereas the snow density and depth brings about relatively insignificant errors.     

西北冰洋楚科奇海台南部08P23孔氧同位素3期以来的古海洋与古气候记录

Multiproxy investigations have been performed on Core 08P23 collected from the Chukchi Plateau, the western Arctic Ocean, during the Third Chinese National Arctic Expedition. The core was dated back to Marine Isotope Stage(MIS) 3 by a combination of Accelerator Mass Spectrometric(AMS) carbon-14 dating and regional core correlation. A total of five prominent ice-rafted detritus(IRD) events were recognized in MIS 2 and MIS 3. The IRD sources in MIS 3 are originated from vast carbonate rock outcrops of the Canadian Arctic Archipelago and clastic quartz in MIS 2 may have a Eurasian origin. Most δ18O and δ13C values of Neogloboquadrina pachyderma(sinistral)(Nps) in Core 08P23 are lighter than the average values of surface sediments. The lighter δ18O and δ13C values of Nps in the two brown layers in MIS 1 and MIS 3 were resulted from meltwater events; and those in the gray layers in MIS 3 were caused by the enhanced sea ice formation. The δ18O values varied inversely with δ13C in MIS 2 indicate that the study area was covered by thick sea ice or ice sheet with low temperature and little meltwater, which prevented the biological productivity and sea-atmosphere exchange, as well as water mass ventilation. The covaried light values of δ18O and δ13C in MIS 1 and MIS 3 were resulted from meltwater and/or brine injection.