Optical constants of ice in the infrared*

Schaaf, Joel W.; Williams, D. R.

doi:10.1364/josa.63.000726

Cited by 88 publications

(56 citation statements)

References 13 publications

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“…As for the complex refractive index of ice, there are large difference among investigators. At 10-15*m, a factor of three difference exists between the newly measured results by Schaaf and Williams (1973) and those compiled by Irvine and Pollack (1968). We use the former as recommended by Warren (1984).…”

Section: Model Calculationsmentioning

confidence: 99%

Detection of Clouds in Antarctica from Infrared Multispectral Data of AVHRR

Yamanouchi

Suzuki

Kawaguchi

1987

Journal of the Meteorological Society of Japan

109

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A method to detect cloud cover in the Antarctic using only the infrared channels of AVHRR is discussed. From the data of NOAA-7 received at Syowa Station, the difference in the brightness temperature of each channel appeared to be useful for the identification of clouds. The brightness temperature of the channels 3 (3.7*m) and 4 (11*m) shows the positive difference when the thickness of clouds are in some particular range, and then tends to show negative difference for the thick cloud. Thin clouds have the difference in the brightness temperature between channels 4 and 5 (12 * m). These tendencies are explained by the radiative properties of model clouds theoretically calculated. On the graph of these temperature difference against the channel 4 brightness temperature, pixels of the same cloud distribute on the particular arch starting from the clear pixel. From the arch, clouds can be distinguished from the ground surface. The particle size, temperature and thickness of the cloud can also be inferred. At the low temperature over the inland snow surface, many troubles arise. The channel 3 brightness temperature accompanies poor resolution and large noise at the low temperature. The brightness temperature difference between channels 4 and 5 shows strong dependence on temperature and viewing angle at the low temperature due to the nonlinearity error and variation of snow surface emissivity. An empirical correction is applied to the low temperature data for the automatic cloud detection.

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Section: Model Calculationsmentioning

confidence: 99%

Detection of Clouds in Antarctica from Infrared Multispectral Data of AVHRR

Yamanouchi

Suzuki

Kawaguchi

1987

Journal of the Meteorological Society of Japan

109

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“…Several studies (e.g. Spitzer and Kleinman, 1961;Hale and Querry, 1973;Pollack et al, 1973;Schaaf and Williams, 1973;Volz, 1973;Palmer and Williams, 1975;Wen and Rose, 1994) have pointed out significant differences between silicate, water/ice, and sulfuric acid as well as mineral dust refractive indexes in the infrared domain (Table 1), hence making possible the discrimination of volcanic ash.…”

Section: The Reverse Absorption Techniquementioning

confidence: 99%

Improved space borne detection of volcanic ash for real-time monitoring using 3-Band method

Guéhenneux

Gouhier

Labazuy

2015

Journal of Volcanology and Geothermal Research

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“…The IR camera allows working with both local and integral emissivity of investigated surfaces when processing IR images. Both water and ice are very good emitters over the entire detection waveband with an emissivity approaching that of a blackbody [21], [22].…”

Section: B Advantages and Problems Of Ir Instrumentationmentioning

confidence: 99%

Measuring temperature of the ice surface during its formation by using infrared instrumentation

Karev

Farzaneh

Kollár

2007

International Journal of Heat and Mass Transfer

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A non-destructive remote sensing technique was used to measure the surface temperature of a thin macroscopic water film flowing on a growing asymmetric ice accretion during its formation inside an icing research wind tunnel. Given the underlying thermodynamic conditions of this experimental series, the recorded surface temperature was always below the temperature of water fusion, T m =273.15 K, even when water shedding from growing ice accretions was observed visually. The surface temperature of ice accretions, ș angle between the received radiation and the ice surface normal (degrees).

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Optical constants of ice in the infrared*

Cited by 88 publications

References 13 publications

Detection of Clouds in Antarctica from Infrared Multispectral Data of AVHRR

Detection of Clouds in Antarctica from Infrared Multispectral Data of AVHRR

Improved space borne detection of volcanic ash for real-time monitoring using 3-Band method

Measuring temperature of the ice surface during its formation by using infrared instrumentation

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