ALBERT

Description: The MIPAS instrument onboard the ESA Envisat satellite operated from July 2002 until April 2012. The infrared limb emission measurements represent a unique dataset of day and night observations of polar stratospheric clouds (PSCs) up to both poles. Cloud detection sensitivity is comparable to spaceborne lidars, and it is possible to classify different cloud types from the spectral measurements in different atmospheric windows regions. Here we present a new PSC classification scheme based on the combination of a well-established two-colour ratio method and multiple 2D brightness temperature difference probability density functions. The method is a simple probabilistic classifier based on Bayes' theorem with a strong independence assumption. The method has been tested in conjunction with a database of radiative transfer model calculations of realistic PSC particle size distributions, geometries, and composition. The Bayesian classifier distinguishes between solid particles of ice and nitric acid trihydrate (NAT), as well as liquid droplets of super-cooled ternary solution (STS). The classification results are compared to coincident measurements from the space borne lidar CALIOP instrument over the temporal overlap of both satellite missions (June 2006 to March 2012). Both datasets show a good agreement for the specific PSC classes, although the viewing geometries, vertical and horizontal resolution are quite different. Discrepancies are observed for the MIPAS ice class. The Bayesian classifier for MIPAS identifies substantially more ice clouds in the southern hemisphere polar vortex than CALIOP. This disagreement is attributed in parts to the difference in the sensitivity on mixed-type clouds. Ice seems to dominate the spectral behaviour in the limb infrared spectra and may cause an overestimation in ice occurrence compared to the real fraction of ice within the PSC area in the polar vortex. The entire MIPAS measurement period was processed with the new classification approach. Examples like the detection of the Antarctic NAT belt during early winter, and its possible link to mountain wave events over the Antarctic Peninsula, which are observed by the AIRS instrument, are highlighting the importance of a climatology of in total 9 southern and 10 northern hemisphere winters. The new dataset is valuable both for detailed process studies, and for comparisons with and improvements of the PSC parameterisations used in chemistry transport and climate models.