北极冰间水道反演和敏感性试验

We derive the Arctic sea ice leads and concentrations from MODIS/Terra using the MPA (MODIS potential open water algorithm) method which is based on the thermal and visible radiometric properties. The original sea ice surface temperature (IST) data are provided by National Snow and Ice Data Center (NSIDC) and its spatial resolution is 1 km. The characteristic values of sea ice leads including the length, orientation, density and so on, will be computed statistically. The derived Arctic sea ice leads and concentrations will be applied in the Los Alamos sea ice model (CICE) 4.0 with its spatial resolution of 1o×1o and 0.1o×0.1o respectively. Sensitivity test will be done to test if the sea ice model is improved after the statistical values of sea ice leads are added. The results will provide support to the parameterization of Arctic sea ice leads in coupled sea ice-ocean and climate models.

利用美国雪冰中心（NSIDC）提供的MODIS/Terra 1km分辨率的冰温数据，基于热红外和可见光辐射特性的反演方法MPA（MODIS potential open water algorithm）方法，反演得到全北极的冰间水道和海冰密集度数据，并对水道的长度、走向、分布密度等特征进行数学统计，量化结果。将反演得到的水道和海冰密集度数据，应用于美国Los Alamos国家实验室发展的海冰模式CICE 4.0中，分别在空间分辨率为1o×1o和0.1o×0.1o的海冰模式中进行敏感性试验，验证水道信息的引入对模式的改进。所得成果可为北极冰-海耦合模式和气候模式中的水道参数化改进提供依据。

基于热红外和可见光的辐射特性，反演得到了可见光（MODIS）全北极冰间水道和海冰密集度数据；基于海冰的辐射特性，反演得到了微波（AMSR-E和AMSR2）全北极冰间水道和海冰密集度数据。采用水道的自动识别方法，对全北极水道的位置、走向、长度和分布密度等特征进行了量化分析，分析了全北极冰间水道的气候平均和月平均分布特征。将反演得到的北极冰间水道和海冰密集度数据，独立发展了一个北极冰间水道的参数化方案，最高空间分辨率达到6.25 km。