Aerosol and Cloud Detection Software Package for High Resolution Infrared Sounders
Current version: v2.4, March 2019
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 temperatures 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). The aerosol detection algorithm compares observed window channel brightness temperatures on both sides of the 9.6 micrometer ozone absorption band and diagnoses presence of aerosol if pre-defined threshold values are exceeded. Both of the algorithms provide channel-specific flags indicating which channels are affected in each situation.
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.