Subpixel Characterization of HIRS Spectral Radiances Using Cloud Properties...

The core information for this publication's citation.: 
Staten, P. W., B. Kahn, M. M. Schreier, and Andrew Heidinger (2016), Subpixel Characterization of HIRS Spectral Radiances Using Cloud Properties from AVHRR, J. Atmos. Oceanic Technol., 33, 1519-1538, doi:10.1175/JTECH-D-15-0187.1.
Abstract: 

This paper describes a cloud type radiance record derived from NOAA polar-orbiting weather satellites using cloud properties retrieved from the Advanced Very High Resolution Radiometer (AVHRR) and spectral brightness temperatures (Tb) observed by the High Resolution Infrared Radiation Sounder (HIRS). The authors seek to produce a seamless, global-scale, long-term record of cloud type and Tb statistics intended to better characterize clouds from seasonal to decadal time scales. Herein, the methodology is described in which the cloud type statistics retrieved from AVHRR are interpolated onto each HIRS footprint using two cloud classification methods. This approach is tested over the northeast tropical and subtropical Pacific Ocean region, which contains a wide variety of cloud types during a significant ENSO variation from 2008 to 2009. It is shown that the Tb histograms sorted by cloud type are realistic for all HIRS channels. The magnitude of Tb biases among spatially coincident satellite intersections over the northeast Pacific is a function of cloud type and wavelength. While the sign of the bias can change, the magnitudes are generally small for NOAA-18 and NOAA-19, and NOAA-19 and MetOp-A intersections. The authors further show that the differences between calculated standard deviations of cloud-typed Tb well exceed intersatellite calibration uncertainties. The authors argue that consideration of higher-order statistical moments determined from spectral infrared observations may serve as a useful long-term measure of small-scale spatial changes, in particular cloud types over the HIRS–AVHRR observing record.

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