Arctic sea ice volume export through the Fram Strait from combined satellite and model data:1979–2012

By combing satellite-derived ice motion and concentration with ice thickness fields from a popular model PIOMAS we obtain the estimates of ice volume flux passing the Fram Strait over the 1979–2012 period. Since current satellite and field observations for sea ice thickness are limited in time and space, the use of PIOMAS is expected to fill the gap by providing temporally continued ice thickness fields. Calculated monthly volume flux exhibits a prominent annual cycle with the peak record in March（roughly 145 km3/month） and the trough in August（10 km^3/month）. Annual ice volume flux（1 132 km^3） is primarily attributable to winter（October through May） outflow（approximately 92%）. Uncertainty in annual ice volume export is estimated to be 55 km^3（or 5.7%）. Our results also verified the extremely large volume flux appearing between late 1980 s and mid-1990 s. Nevertheless, no clear trend was found in our volume flux results. Ice motion is the primary factor in the determination of behavior of volume flux. Ice thickness presented a general decline trend may partly enhance or weaken the volume flux trend. Ice concentration exerted the least influences on modulating trends and variability in volume flux. Moreover, the linkage between winter ice volume flux and three established Arctic atmospheric schemes were examined. Compared to NAO, the DA and EOF3 mechanism explains a larger part of variations of ice volume flux across the strait.

Towards a semi-empirical model of the sea ice thickness based on hyperspectral remote sensing in the Bohai Sea

Sea ice thickness is one of the most important input parameters for the prevention and mitigation of sea ice disasters and the prediction of local sea environments and climates. Estimating the sea ice thickness is currently the most important issue in the study of sea ice remote sensing. With the Bohai Sea as the study area, a semiempirical model of the sea ice thickness（SEMSIT） that can be used to estimate the thickness of first-year ice based on existing water depth estimation models and hyperspectral remote sensing data according to an optical radiative transfer process in sea ice is proposed. In the model, the absorption and scattering properties of sea ice in different bands（spectral dimension information） are utilized. An integrated attenuation coefficient at the pixel level is estimated using the height of the reflectance peak at 1 088 nm. In addition, the surface reflectance of sea ice at the pixel level is estimated using the 1 550–1 750 nm band reflectance. The model is used to estimate the sea ice thickness with Hyperion images. The first validation results suggest that the proposed model and parameterization scheme can effectively reduce the estimation error associated with the sea ice thickness that is caused by temporal and spatial heterogeneities in the integrated attenuation coefficient and sea ice surface. A practical semi-empirical model and parameterization scheme that may be feasible for the sea ice thickness estimation using hyperspectral remote sensing data are potentially provided.

Characteristics of the sea ice reflectance spectrum polluted by oil spills based on field experiments in the Bohai Sea

Oil spilled on the sea ice surface in the Bohai Sea of China is studied through the field measurements of the reflectance of a simulated sea ice-oil film mixed pixel. The reflection characteristics of sea ice and oil film are also analyzed. It is found that the mixed pixel of sea ice and oil film is a linear mixed pixel. The means of extracting sea ice pixels containing oil film is presented using a double-band ratio oil-film sea-ice index（DROSI） and a normalized difference oil-film sea-ice index（NDOSI） through the analysis of the reflectance curves of the sea iceoil film pixel for different ratios of oil film. The area proportion of the oil film in the sea ice-oil film pixel can be accurately estimated by the average reflectance of the band of 1 610–1 630 nm, and the volume of the spilled oil can be further estimated. The method of the sea ice-oil film pixel extraction and the models to estimate the proportion of oil film area in the sea ice-oil film pixel can be applied to the oil spill monitoring of the ice-covered area in the Bohai Sea using multispectral or hyperspectral remote sensing images in the shortwave infrared band（1 500–1 780 nm）.

A study on remote sensing models of sea ice thickness by microwave radiometry

Extrapolating from the propagation theories of electromagnetic waves in a layered medium, a three-layer medium model is deduced in this paper by using microwave radiometric remote sensing technology which is suitable to first-year sea ice condition of the northern part of China seas. Comparison with in situ data indicates that for microwave wavelength of 10 cm, the coherent model gives a quite good fit result for the thickness of sea ice less than 20 cm, and the incoherent model also works well for thickness within 20 to 40 cm. Based on three theoretical models, the inversion soft ware from microwave remote sensing data for calculating the thickness of sea ice can be set up. The relative complex dielectrical constants of different types of sea ice in the Liaodong Gulf calculated by using these theoretical models and measurement data are given in this paper. The extent of their values is (0. 5-4. 0)-j(0. 07~0. 19).