Masashige Nakayama

Thin sea ice thickness as inferred from passive microwave and in situ observations

[1] Microwave radiometric signals from sea ice strongly reflect physical conditions of a layer near the ice surface. This study examines the extent to which the relationships of thickness with brightness temperature and with emissivity hold for thin sea ice, approximately <0.2-0.3 m, and how those relationships may arise from changes in brine characteristics through modification of dielectric properties near the ice surface. In order to address these questions we made concurrent measurements of sea ice thickness in the Sea of Okhotsk from a ship and passive microwave radiometry from an over-flying aircraft. The results show that the brightness temperature and emissivity increase with thickness approximately within the thin ice for a frequency range of 10-37 GHz. The relationship is more pronounced at lower frequencies and at the horizontal polarization. We also established an empirical relationship between ice thickness and salinity in the layer near the ice surface from a field experiment, which qualitatively supports the idea that changes in the near-surface brine characteristics contribute to the observed thickness-brightness temperature/emissivity relationship. On the basis of our results, we conclude that for thin ice, passive microwave radiometric signals likely contain indirect information on ice thickness through the dependence of dielectric properties on brine, which provides a plausible and common explanation for previously proposed passive microwave thickness algorithms.

Validation studies of AMSR-E ice concentrations in the Sea of Okhotsk

The data from aircraft and ship campaigns in February 2003 in conjunction with high resolution satellite images aid in validating sea ice concentrations derived from AMSR-E brightness temperatures. Patrol Vessel SOYA conducted time series observations of geophysical parameters such as ice type, floe size, snow cover vertical profiles of snow and ice surface temperature, density, grain size, and salinity. Surface data were used to interpret aircraft microwave and visible channel data used to interpret high resolution Landsat-7 and MODIS images. The latter were then utilized to interpret the ice concentration data derived from AMSR-E. The co-registered images of aircraft PSR: Landsat-7 and MODIS data exhibit good coherence in signatures. In highly consolidated ice cover, the ice concentrations were in agreement to within 5 to 10% in ice concentration. However, in highly divergent areas, the derived ice concentration has a negative bias due to the dominant presence of new ice. The new ice has relatively lower emissivity than first year ice which is snow cover and is affected by waves and wetness. The relationship between the thickness and brightness temperature of sea ice was studied in detail

Study on the sea ice thickness observation in the Sea of Okhotsk by using dual-frequency and fully polarimetric airborne SAR (Pi-SAR) data

The Sea of Okhotsk is located in the most southerly region of the Northern Hemisphere in which sea ice exists during winter. Since the area and volume of the sea ice in this region are related to climate change locally as well as globally, it is important to develop methods for monitoring sea ice parameters around this region. Since Synthetic Aperture Radar (SAR) can observe continuously in any weather conditions, it is useful for observing the sea ice covered region. In order to investigate the possibilities of dual frequency and polarimetric SAR to monitor the sea ice, we derived the relation between backscattering coefficients each polarization and sea ice physical parameters, and then we proposed a sea ice classification using a polarimetric decomposition and a sea ice thickness estimation using the backscatter ratio

Preparation of multi-stage remote sensing for monitoring sea ice in the Okhotsk Sea with ALOS sensors

In order to develop and/or improve algorithms of extracting various sea ice parameters, such as sea ice concentration, sea ice thickness, and sea ice types from ALOS data, it is necessary to prepare certain data set for verification. This paper describes about the preparation of multi-stage remote sensing for obtaining a series of remotely sensed data of sea ice in the Okhotsk Sea.