ACPD Atmospheric Chemistry and Physics Discussions ACPD 1680-7375 Copernicus GmbH Göttingen, Germany 10.5194/acpd-8-17907-2008 Evaluation of upper tropospheric humidity forecasts from ECMWF using AIRS and CALIPSO data Lamquin N. 1 Gierens K. 2 Stubenrauch C. J. 1 Chatterjee R. 3 Laboratoire de Météorologie Dynamique, Ecole Polytechnique, Palaiseau, France Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany National Institute of Technology, Tiruchchirappalli, Tamil, Nadu, India 01 10 2008 8 5 17907 17937 This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This article is available from http://www.atmos-chem-phys-discuss.net/8/17907/2008/acpd-8-17907-2008.html The full text article is available as a PDF file from http://www.atmos-chem-phys-discuss.net/8/17907/2008/acpd-8-17907-2008.pdf

An evaluation of the upper tropospheric humidity from the European Centre of Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) is presented. We first make an analysis of the spinup behaviour of ice supersaturation in weather forecasts. It shows that a spinup period of at least 12 h is necessary before using forecast humidity data from the upper troposphere. We compare the forecasted upper tropospheric humidity with coincident relative humidity fields retrieved from the Atmospheric InfraRed Sounder (AIRS) and with cloud vertical profiles from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). The analysis is made over one year, from October 2006 to September 2007, and we discuss how relative humidity and cloud features appear both in the IFS and in the observations. In a last part, we investigate the presence of ice supersaturation within low vertical resolution pressure layers by comparing the IFS outputs for high-resolution and low-resolution humidity profiles and by simulating the interpolation of humidity over radiosonde data. A new correction method is proposed and tested with these data.

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