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The Cloud Depiction and Forecast System version 2 (CDFS II) is the operational global cloud analysis and forecasting model of the 557th Weather Wing, formerly the U.S. Air Force Weather Agency. The CDFS II cloud-detection algorithms are threshold-based tests that compare satellite-observed multispectral reflectance and brightness temperature signatures with those expected for the clear atmosphere. User-prescribed quantitative differences between sensor observations and the expected clear-scene radiances denote cloudy pixels. These radiances historically have been modeled at 24-km resolution from a running 10-day statistical analysis of cloud-free pixels that requires the entire global cloud analysis to be executed twice in real time: once in operational cloud detection mode and a second time in a cloud-clearing mode that is designed explicitly for generating clear-scene statistics. Having to run the cloud analysis twice means the availability of fewer compute cycles for other operational models and requires costly interactive maintenance of distinct cloud-detection and cloud-clearing threshold sets. Additionally, this technique breaks down whenever a region is persistently cloudy. These problems are eliminated by means of the optimal spectral sampling (OSS) radiative transfer model of Moncet et al., optimized for execution in the CDFS run-time environment. OSS is particularly well suited for real-time remote sensing applications because of its user-tunable computational speed and numerical accuracy, with respect to a reference line-by-line model. The use of OSS has cut cloud model processing times in half, eliminated the influence of cloudy pixel artifacts in the statistical time series prescription of cloud-cleared radiances, and improved cloud-mask quality.

The Optimum Spectral Sampling method for fast and accurate radiative transfer has been enhanced for speed in clear atmospheres and extended to cloudy atmospheres. Applications to retrieval of cloud properties from infrared measurements are described.