Ice supersaturation in the upper troposphere is a complex and important issue for the understanding of cirrus cloud formation. On one hand, infrared sounders have the ability to provide cloud properties and atmospheric profiles of temperature and humidity. On the other hand, they suffer from coarse vertical resolution, especially in the upper troposphere and therefore are unable to detect shallow ice supersaturated layers. We have used data from the Measurements of OZone and water vapour by AIrbus in-service airCraft experiment (MOZAIC) in combination with Atmospheric InfraRed Sounder (AIRS) relative humidity measurements and cloud properties to develop a calibration method for an estimation of occurrence frequencies of ice supersaturation. This method first determines the occurrence probability of ice supersaturation, detected by MOZAIC, as a function of the relative humidity determined by AIRS. The occurrence probability function is then applied to AIRS data, independently of the MOZAIC data, to provide a global climatology of upper-tropospheric ice supersaturation occurrence. Our climatology is then compared to ice supersaturation occurrence statistics from MOZAIC alone and related to high cloud occurrence from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). As an example of application it is compared to model climatologies of ice supersaturation from the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) and from the European Centre HAmburg Model (ECHAM4). This study highlights the benefits of multi-instrumental synergies for the investigation of upper tropospheric ice supersaturation.