Sea ice thickness estimated from passive microwave radiometers

This study presents the findings of research into the correlation between sea ice thickness and passive microwave radiation. In-situ sea ice thickness samples were obtained from video observations by the icebreaker Soya during 1996-1998 and surface feature observations in 1997 by the visible and near-infrared radiometer AVNIR mounted on the ADEOS satellite. These sea ice thickness data were binned into grid cell data of the satellite microwave radiometer SSM/I for the same location, and averaged to provide an average ice thickness for a grid cell. In order to survey the relationship between sea ice thickness and microwave radiation, two sea ice classification parameters for SSM/I were investigated as to their ability to estimate sea ice thickness. One sea ice classification parameter is the Polarization Ratio (PR), which was developed for a seasonally ice covered area and can distinguish three ice types: new ice, young ice, and first-year ice. Another parameter is the ratio between 37GHz vertical polarization and 85GHz vertical polarization (R_). It can distinguish fast ice in addition to the three ice types that can be distinguished by the PR. These parameters showed correlation coefficients with in-situ sea ice thickness, -0.77 and 0.67, respectively, in this study. Estimated sea ice thickness derived from multiple regression analysis using PR and R_ showed good correlation (R=0.81) with in-situ sea ice thickness

Preliminary results for the Antarctic sea ice physics and ecosystems experiment (SIPEX-2)

第3回極域科学シンポジウム/第35回極域気水圏シンポジウム 11月29日（木） 国立国語研究所 ２階多目的

CNVs in Three Psychiatric Disorders

BACKGROUND: We aimed to determine the similarities and differences in the roles of genic and regulatory copy number variations (CNVs) in bipolar disorder (BD), schizophrenia (SCZ), and autism spectrum disorder (ASD). METHODS: Based on high-resolution CNV data from 8708 Japanese samples, we performed to our knowledge the largest cross-disorder analysis of genic and regulatory CNVs in BD, SCZ, and ASD. RESULTS: In genic CNVs, we found an increased burden of smaller (500 kb) exonic CNVs in SCZ/ASD. Pathogenic CNVs linked to neurodevelopmental disorders were significantly associated with the risk for each disorder, but BD and SCZ/ASD differed in terms of the effect size (smaller in BD) and subtype distribution of CNVs linked to neurodevelopmental disorders. We identified 3 synaptic genes (DLG2, PCDH15, and ASTN2) as risk factors for BD. Whereas gene set analysis showed that BD-associated pathways were restricted to chromatin biology, SCZ and ASD involved more extensive and similar pathways. Nevertheless, a correlation analysis of gene set results indicated weak but significant pathway similarities between BD and SCZ or ASD (r = 0.25–0.31). In SCZ and ASD, but not BD, CNVs were significantly enriched in enhancers and promoters in brain tissue. CONCLUSIONS: BD and SCZ/ASD differ in terms of CNV burden, characteristics of CNVs linked to neurodevelopmental disorders, and regulatory CNVs. On the other hand, they have shared molecular mechanisms, including chromatin biology. The BD risk genes identified here could provide insight into the pathogenesis of BD

Properties of snow overlying the sea ice off East Antarctica in late winter, 2007

The properties of snow on East Antarctic sea ice off Wilkes Land were examined during the Sea Ice Physics and Ecosystem Experiment (SIPEX) in late winter of 2007, focusing on the interaction with sea ice. This observation includes 11 transect lines for the measurement of ice thickness, freeboard, and snow depth, 50 snow pits on 13 ice floes, and diurnal variation of surface heat flux on three ice floes. The detailed profiling of topography along the transects and the d18O, salinity, and density datasets of snow made it possible to examine the snow-sea-ice interaction quantitatively for the first time in this area. In general, the snow displayed significant heterogeneity in types, thickness (mean: 0.14 ± 0.13 m), and density (325 ± 38 kg m^[-3]), as reported in other East Antarctic regions. High salinity was confined to the lowest 0.1 m. Salinity and d18O data within this layer revealed that saline water originated from the surface brine of sea ice in 20% of the total sites and from seawater in 80%. From the vertical profiles of snow density, bulk thermal conductivity of snow was estimated as 0.15W K^[-1] m^[-1] on average, only half of the value used for numerical sea ice models. Although the upward heat flux within snow estimated with this value was significantly lower than that within ice, it turned out that a higher value of thermal conductivity (0.3 to 0.4 W K^[-1] m^[-1]) is preferable for estimating ice growth amount in current numerical models. Diurnal measurements showed that upward conductive heat flux within the snow and net long-wave radiation at the surface seem to play important roles in the formation of snow ice from slush. The detailed surface topography allowed us to compare the air-ice drag coefficients of ice and snow surfaces under neutral conditions, and to examine the possibility of the retrieval of ice thickness distribution from satellite remote sensing. It was found that overall snow cover works to enhance the surface roughness of sea ice rather than moderate it, and increases the drag coefficient by about 10%. As for thickness retrieval, mean ice thickness had a higher correlation with ice surface roughness than mean freeboard or surface elevation, which indicates the potential usefulness of satellite L-band SAR in estimating the ice thickness distribution in the seasonal sea ice zone

Ship-borne electromagnetic induction sounding of sea-ice thickness in the southern Sea of Okhotsk

Recent observations have revealed that dynamical thickening is dominant in the growth process of sea ice in the southern Sea of Okhotsk. That indicates the importance of understanding the nature of thick deformed ice in this area. The objective of the present paper is to establish a ship-based method for observing the thickness of deformed ice with reasonable accuracy. Since February 2003, one of the authors has engaged in the core sampling using a small basket from the icebreaker Soya. Based on these results, we developed a new model which expressed the internal structure of pack ice in the southern Sea of Okhotsk, as a one-dimensional multilayered structure. Since 2004, the electromagnetic (EM) inductive sounding of sea-ice thickness has been conducted on board Soya. By combining the model and theoretical calculations, a new algorithm was developed for transforming the output of the EM inductive instrument to ice + snow thickness (total thickness). Comparison with total thickness by drillhole observations showed fair agreement. The probability density functions of total thickness in 2004 and 2005 showed some difference, which reflected the difference of fractions of thick deformed ice