Aerosol and Cloud Detection Software Package for High Resolution Infrared Sounders
Current version: v2.3, January 2017
This cloud and aerosol detection software is based on a pattern recognition algorithm developed for the detection of clouds in AIRS spectra.
The cloud detection algorithm works by taking the first guess departures (i.e. the difference between the observed brightness temperatures and brightness temperatues calculated from a good estimate of the atmospheric state – typically a 6-hour forecast from an NWP model) and looking for the signature of opacity that is not included in the clear-sky calculation (i.e. cloud or aerosol). The aerosol code decides whether an observation, initially defined as being cloud affected, is in fact mainly affected by aerosol. Identification of aerosol contamination is based on first guess departures of window channels in the 8µm region.
The software package is NWP-dependent (i.e., requires an estimate of the atmospheric state vector), but is sufficiently modular to “plug-in” to most NWP systems.
Input data: For each channel selected in the FOV, the algorithm requires the background (model) brightness temperature, the observed brightness temperature and a height assignment for each channel in units defined by the user (e.g., NWP model level, pressure level).
Output data: Output file is produced containing flags indicating clear, cloud-contaminated and aerosol-contaminated channels in each input satellite sounding.
- McNally, A.P. and P.D. Watts, 2003. A cloud detection algorithm for high-spectral-resolution infrared sounders, Q J Roy Meteorol Soc, 129, 3411-3423.
- Eresmaa, R., 2014. Imager-assisted cloud detection for assimilation of Infrared Atmospheric Sounding Interferometer radiances, Q J Roy Meteorol Soc, 140, 2342-2352.