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The InfraRed Sea Surface Emissivity (IRSSE) model

From Paul van Delst’s Work Page at The Cooperative Institute for Meteorological Satellite Studies of the University of Wisconsin – Madison Space Science and Engineering Center.
The InfraRed Sea Surface Emissivity (IRSSE) model was developed for use in the Global Data Assimilation System (GDAS) at NCEP/EMC. Previously, the GDAS used an IRSSE model based on Masuda et al (1988). The Masuda model doesn’t account for the effect of enhanced emission due to reflection from the sea surface (only an issue for larger view angles) and the implementation was based on coarse spectral resolution emissivity data making its application to high resolution instruments, such as AIRS, problematic.

The old IRSSE model has been upgraded to use sea surface emissivities derived via the Wu and Smith (1997) methodology as described in van Delst and Wu (2000). The emissivity spectra are computed assuming the infrared sensors are not polarised and using the data of Hale and Querry (1973) for the refractive index of water, Segelstein (1981) for the extinction coefficient, and Friedman (1969) for the salinitiy/chlorinity corrections.

Infrared Sea Surface Emissivity

“The InfraRed Sea Surface Emissivity (IRSSE) model was developed for use in the Global Data Assimilation System (GDAS) at NCEP/EMC. Previously, the GDAS used an IRSSE model based on Masuda et al (1988).

“The Masuda model doesn’t account for the effect of enhanced emission due to reflection from the sea surface (only an issue for larger view angles) and the implementation was based on coarse spectral resolution emissivity data making its application to high resolution instruments, such as AIRS, problematic.

“The old IRSSE model has been upgraded to use sea surface emissivities derived via the Wu and Smith (1997) methodology as described in van Delst and Wu (2000).

“The emissivity spectra are computed assuming the infrared sensors are not polarised and using the data of Hale for the refractive index of water, Segelstein (1981) for the extinction coefficient, and Friedman (1969) for the salinitiy/chlorinity corrections.

“Instrument spectral response functions (SRFs) are used to reduce the emissivity spectra to instrument resolution. These are the quantities predicted by the IRSSE model.”

Infrared Emittance of Water Clouds

Journal of the Atmospheric Sciences

Article: pp. 1459–1472 | Abstract | PDF (1.02M)

Infrared Emittance of Water Clouds

Petr Chýleka, Peter Damianoa, and Eric P. Shettleb

a. Atmospheric Science Program, Department of Physics and Oceanography, Dalhousie University, Halifax, Nova Scotia, Canada
b. Optical Sciences Division, Naval Research Laboratory, Washington, D.C.

Chýlek, P., P. Damiano, and E.P. Shettle, 1992: Infrared Emittance of Water Clouds. J. Atmos. Sci., 49, 1459–1472.

ABSTRACT

A simple approximation has been developed for the infrared emittance of clouds composed of water spheres based on the absorption approximation for the emittance and on the polynomial approximation to the Mie absorption efficiency. The expression for the IR emittance is obtained in a simple analytical form as a function of the liquid water content and two size distribution parameters, namely, the effective radius and effective variance. The approximation is suitable for numerical weather prediction, climate modeling, and radiative transfer calculations. The accuracy, when compared to the exact Mie calculation and integration over the size distribution, is within a few percent, while the required computer time is reduced by several orders of magnitude. In the limit of small droplet sizes, the derived IR emittance reduces to a term proportional to the liquid water content.

Measurements of the infrared emissivity of a wind-roughened sea surface

Measurements of the infrared emissivity of a wind-roughened sea surface, By Jennifer A. Hanafin and Peter J. Minnett, published in Applied Optics, Vol. 44, Issue 3, pp. 398-411, in 2005 is more properly cited as:

J. A. Hanafin and P. J. Minnett, “Measurements of the infrared emissivity of a wind-roughened sea surface,” Appl. Opt. 44, 398-411 (2005)

And the abstract is available online also as: www.opticsinfobase.org/abstract.cfm?URI=ao-44-3-398

It shows that measurements in the 8-12µm waveband region of the sea surface at viewing angles of 55°, in typical at-sea conditions, could introduce introduce errors of up to 0.7 K in sea-surface temperature measurements.

To Quote:

“The emissivity was found to increase in magnitude with increasing wind speed, rather than decrease, as predicted by widely used parameterizations. Use of these parameterizations can cause significant bias in remote sensing of sea-surface temperature in noncalm conditions.”

The ASTER Spectral Library

The ASTER spectral library, is a compilation of almost 2000 spectra of natural and man made materials that is searchable by material. The search returns a list of materials that match your search criteria, you can see a scaled plot of the spectrum and the ancillary information information for the spectrum, you can also download the spectral data.

Data and (No. of samples) are: Minerals (1348), Rocks (244), Soils (58), Vegetation (4), Water, Snow & Ice (9), Man made materials (56), Lunar (17) and Meteorites (60)