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Although it is known that satellite data are useful for obtaining ice thickness distribution for perennial sea ice or in stable thin sea ice areas, it is still an unresolved issue for the seasonal sea ice zone (SIZ). In this study, we approach the problem of ice thickness retrieval by using L-band Synthetic Aperture Radar (SAR). In the SIZ, ice thickness growth is closely related to the ridging activity and therefore surface roughness is expected to be correlated with ice thickness. L-band SAR is suitable for detecting such surface roughness, and therefore is expected to be a good tool for obtaining thickness distribution. To verify this idea, we conducted ship-borne electromagnetic (EM) inductive sounding and supersonic profiling observations with an icebreaker, coordinated with airborne L-band SAR observations in the southern Sea of Okhotsk in February 2005. The surface elevation was estimated by representing the ship's motion with a low-pass filter. Backscattering coefficients correlated well with ice thickness and surface roughness, defined by standard deviation of surface elevation. This result sheds light on the possibility of determining ice thickness distribution in the SIZ.

Hyperspectral remote sensing reflectance (Rrs) was measured by a TriOS radiometer system along the East Coast of New Caledonia during the R/V Alis 03-13 October 2011 CALIOPE cruise. The TriOS system consists of radiance and irradiance sensors measuring in the spectral range 320-950 nm, at a spectral resolution of about 10 nm (sampled by every 3.3 nm), and within a 7-degree field-of-view for the radiance sensor. The method developed by Froidefond and Ouillon (2005) was used to determine Rrs, i.e., the radiance sensor was mounted on a small raft to measure upwelling radiance just below the surface, and Rrs was calculated by normalizing water-leaving radiance with downward solar irradiance measured on the ship deck. Inherent Optical Properties (IOPs), i.e., absorption coefficients of phytoplankton and detritus+dissolved substances (a ph and a dg , respectively), and particulate backscattering coefficient (b bp ) were estimated from the hyperspectral Rrs data by applying linear matrix inversion (Hoge and Lyon, 1996). The IOP inversion algorithm was adapted to MODIS data and applied to Level 1b imagery at 500 m resolution to demonstrate the feasibility of regular IOP monitoring from space in the study area. Local characteristics of the IOP spectra were used for the candidate spectra in the algorithm. The estimated MODIS Rrs and IOPs were evaluated using TriOS Rrs and in-situ IOP measurements obtained concomitantly during the cruise.