Radiance Enhancement and Shortwave upwelling Radiative Flux methods for efficient detection of cloud scenes

TL;DR

This paper introduces new radiance enhancement and shortwave upwelling radiative flux methods for more efficient detection of cloud scenes using satellite spectral data, addressing limitations of existing models.

Contribution

It proposes innovative approaches combining radiance enhancement and SWupRF techniques with the GENSPECT model for improved cloud detection from space.

Findings

Enhanced cloud detection accuracy demonstrated

Effective identification of combustion aerosols during forest fires

Applicable to spectral range 1100-1700 nm

Abstract

The description, imagery and interpretation of cloud scenes by remote sensing datasets from Earth-orbiting satellites have become a great debate for several decades. Presently, there are many models for cloud detection and its classifications have been reported. However, none of the existing models can efficiently detect the clouds within the small band of shortwave upwelling radiative wavelength flux (SWupRF) in the spectral range from 1100 to 1700 nm. Therefore, in order to detect the clouds more effectively, a method known as the radiance enhancement (RE) can be implemented (Siddiqui et al., 2015). This article proposes new approaches how with RE and SWupRF methods to distinguish cloud scenes by space orbiting Argus 1000 micro-spectrometer utilizing the GENSPECT line-by-line radiative transfer model (Quine and Drummond, 2002; Siddiqui, 2017). This RE approach can also be used within the selected wavelength band for the detection of combustion-originated aerosols due to seasonal forest fires.