Variation of Sea Ice Temperature from CHINARE 2003 and Its Application on Sea Ice Model Evaluation

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.

Comparison of summer Arctic sea ice surface temperatures from in situ and MODIS measurements

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%.

Links between Arctic sea ice and extreme summer precipitation in China:an alternative view

Potential links between the Arctic sea-ice concentration anomalies and extreme precipitation in China are explored. Associations behind these links can be explained by physical interpretations aided by visualisations of temporarily lagged composites of variables such as atmospheric mean sea level pressure and sea surface temperature. This relatively simple approach is verified by collectively examining already known links between the Arctic sea ice and rainfall in China. For example, similarities in the extreme summer rainfall response to Arctic sea-ice concentration anomalies either in winter （DJF） or in spring （MAM） are highlighted. Furthermore, new links between the Arctic sea ice and the extreme weather in India and Eurasia are proposed. The methodology developed in this study can be further applied to identify other remote impacts of the Arctic sea ice variability.

Winter sea ice albedo variations in the Bohai Sea of China

Sea ice conditions in the Bohai Sea of China are sensitive to large-scale climatic variations. On the basis of CLARA-A1-SAL data, the albedo variations are examined in space and time in the winter（December, January and February） from 1992 to 2008 in the Bohai Sea sea ice region. Time series data of the sea ice concentration（SIC）, the sea ice extent（SIE） and the sea surface temperature（SST） are used to analyze their relationship with the albedo. The sea ice albedo changed in volatility appears along with time, the trend is not obvious and increases very slightly during the study period at a rate of 0.388% per decade over the Bohai Sea sea ice region.The interannual variation is between 9.93% and 14.50%, and the average albedo is 11.79%. The sea ice albedo in years with heavy sea ice coverage, 1999, 2000 and 2005, is significantly higher than that in other years; in years with light sea ice coverage, 1994, 1998, 2001 and 2006, has low values. For the monthly albedo, the increasing trend（at a rate of 0.988% per decade） in December is distinctly higher than that in January and February. The mean albedo in January（12.90%） is also distinctly higher than that in the other two months. The albedo is significantly positively correlated with the SIC and is significantly negatively correlated with the SST（significance level 90%）.

Evaluating a satellite-based sea surface temperature by shipboard survey in the Northwest Indian Ocean

A summer-time shipboard meteorological survey is described in the Northwest Indian Ocean. Shipboard observations are used to evaluate a satellite-based sea surface temperature（SST）, and then find the main factors that are highly correlated with errors. Two satellite data, the first is remote sensing product of a microwave, which is a Tropical Rainfall Measuring Mission Microwave Imager（TMI）, and the second is merged data from the microwave and infrared satellite as well as drifter observations, which is Operational Sea Surface Temperature and Sea Ice Analysis（OSTIA）. The results reveal that the daily mean SST of merged data has much lower bias and root mean square error as compared with that from microwave products. Therefore the results support the necessary of the merging infrared and drifter SST with a microwave satellite for improving the quality of the SST. Furthermore, the correlation coefficient between an SST error and meteorological parameters, which include a wind speed, an air temperature, a relative humidity, an air pressure, and a visibility. The results show that the wind speed has the largest correlation coefficient with the TMI SST error. However, the air temperature is the most important factor to the OSTIA SST error. Meanwhile,the relative humidity shows the high correlation with the SST error for the OSTIA product.

Evaluation of the relationships and uncertainties of airborne and ground-based sea ice surface temperature measurements against remotely sensed temperature records

Sea ice surface temperature(IST)is an important indicator of environmental changes in the Arctic Ocean.In this study,the relative performance of four mainstream IST records,i.e.airborne IST,infrared radiometer measured IST(IR IST),longwave radiation derived IST(LWR IST),and snow and ice mass balance array buoy derived IST(Buoy IST),were evaluated against the MODIS IST product.Bias,standard deviation(STD),and root mean square error(RMSE)were used to evaluate the data quality.Results revealed that airborne IST had the best accuracy,which was 0.21 K colder than MODIS IST,with STD of 1.46 K and RMSE of 1.47 K.Ground-based ISTs were biased with each other but all warmer than the MODIS IST.The IR IST had the best overall accuracy(bias=0.55 K;STD=1.52 K;RMSE=1.61 K),while the LWR IST was the noisiest measurement with the largest outlier data percent.Besides,co-located IR and LWR ISTs were more consistent than any type of evaluated IST against MODIS IST(correlation coefficient=0.99).Airborne and IR ISTs are thus the premier choice for monitoring the rapidly changing Arctic sea ice,together with satellite observations.

Relationship Between Arctic Sea Ice Thickness Distribution and Climate of China

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