MIPAS/Envisat Observations of Polar Stratospheric Clouds


This data repository provides access to the climatology of polar stratospheric clouds (PSC) observations of Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) onboard the Envisat satellite of the European Space Agency (ESA). The MIPAS instrument operated from July 2002 until April 2012. The infrared limb emission measurements provide a unique dataset of day and night observations of polar stratospheric clouds (PSCs) up to both poles.

A recent classification method for PSC types in IR limb spectra using spectral measurements in different atmospheric windows regions has been applied to the complete mission lifetime of MIPAS (Spang et al., 2012, 2016, 2018). The method applies a simple probabilistic classifier based on Bayes’ theorem with a strong independence assumption to the radiance data. The Bayesian classifier (BC) distinguishes between solid particles of ice and nitric acid trihydrate (NAT), as well as liquid droplets of super-cooled ternary solution (STS). In addition, mixed-type classes (NAT_STS, ICE_STS, and ICE_NAT) have been defined and are part of data product.

In total 9 SH and 10 NH PSC seasons (May-Oct and Nov-Mar) are available for download. In addition, preview images are available on a daily basis and in a number of potential temperature intervals. In due course a DOI will be added to the MIPAS PSC dataset and linked to the repository and data archive web sides.

The compilation of the database is part of the SPARC (Stratosphere-troposphere Processes And their Role in Climate) initiative on PSC and a corresponding initiative PSCi at the International Space Science Institute (ISSI), Bern, Switzerland. Among others both projects are planning to synthesize satellite measurements of CALIPSO, MLS, MIPAS and earlier datasets into a state of the art PSC climatology.

Envisat satellite, artist's impression
Image: ESA/Denmann production

Browse images

The browse images provided on this web site show horizontal distributions of MIPAS PSC composition classes for NH winter and SH winter conditions at altitude levels of 380, 420, 500, and 600 K potential temperature (± variable boundaries). In addition to the different cloud type symbols described in the figure legend, temperature contours for T_ICE (blue) , T_STS = (T_NAT+ T_ICE)/ 2 (red), T_NAT (green), and T_NAT + 2 K (turquoise) based on ERA-Interim data with constant water vapour and nitric acid mixing ratios for the computation of the threshold temperatures, grey contours of the Montgomery stream function at the corresponding theta layer, and black dots for non-cloudy MIPAS profile locations are superimposed.

Data access

The PSC data sets provided on this web site have been created using MIPAS level 1b data of geolocated and calibrated IR radiance spectra (version 4/5) by ESA. These data have been processed with the MIPclouds processor (Spang et al., 2012) for cloud detection and for reduction of the input data for the Bayesian Classifier of PSC spectra. Mean radiances of micro windows (mean radiances of predefined wave number regions of the spectral high resolve L1B spectra) have been used as an internal and intermediate step. The corresponding data product is not available to the public.

The dataset, originally processed mainly with an IDL code and saved in a binary IDL-specific format, has been transferred to the more user-friendly NetCDF format. In addition to the geospatial information (altitude, longitude, latitude) the classifications result [-1, … , 7] for the classes [no-cloud, unknown, Ice, NAT, STS, ICE_NAT, NAT_STS, ICE_STS] and the corresponding three product probabilities PICE, PNAT and PSTS used in Bayesian classifier are listed for each cloudy spectrum. Latter can be used as a quality check of the classification approach.

Results of the Bayesian Classifier are stored in the data repository linked below. Information on the definition of the CLASS data parameter in the files can be found in the global attributes of the netCDF file under:

// global attributes:

type_of_data = "RETRIEVED PSC CLASSES [-1,...,6] = [\"NO-CLOUD\",\"UNSPEC.\",\"ICE\",\"NAT\",\"STSMIX\",\"ICE_NAT\",\"NAT_STS\",\"ICE_STS\"]" ;

Meteorological data like temperature, pressure, geopotential height and equivalent latitude (e.g. EQLAT_ERA) have been interpolated to the measurement locations of the MIPAS tangent points based on the ERA-Interim reanalysis dataset provided by ECMWF, and are part of the climatology data product. The MIPAS PSC climatology includes for each limb profile only the lowest 20 altitude steps, which results in a typical 2D array dimension of 20 times the number of profiles per daily file. The complete measurement period June 2002 to March 2012 has been processed.

We encourage any scientist interested in the data set to contact us for discussions on how you like to use the data. This might help to reduce the risk of mistaken applications and helps us to track the distribution and areas of applications of the data set.

Note that these are non-operational research data products, which have been made available to other scientists and the general public. The archive is updated infrequently.

Legal notes

The data sets and browse images provided on this site are licensed under a Creative Commons Attribution 4.0 International License. You are free to share the material in any medium or format and adapt it for any purpose, even commercially. You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits. The licensor cannot revoke these freedoms as long as you follow the license terms. The data are distributed in the hope that it will be useful, but without any warranty. Please follow the link to see the terms and conditions of the license:


This Envisat MIPAS PSC data repository has been registered with re3data.org, providing a doi for referencing it:

re3data.org: MIPAS/Envisat Observations of Polar Stratospheric Clouds; editing status 2017-09-07; re3data.org - Registry of Research Data Repositories. http://doi.org/10.17616/R3BN26

Citation, if the data are used in publications:

Spang, R., Hoffmann, L., Höpfner, M., Griessbach, S., Müller, R., Pitts, M. C., Orr, A. M. W., and Riese, M.: A multi-wavelength classification method for polar stratospheric cloud types using infrared limb spectra, Atmos. Meas. Tech., 9, 3619-3639, https://doi.org/10.5194/amt-9-3619-2016, 2016.

Spang, R., Hoffmann, L., Müller, R., Grooß, J.-U., Tritscher, I., Höpfner, M., Pitts, M., Orr, A., and Riese, M.: A climatology of polar stratospheric cloud composition between 2002 and 2012 based on MIPAS/Envisat observations, Atmos. Chem. Phys., 18, 5089-5113, https://doi.org/10.5194/acp-18-5089-2018, 2018.

Further information on the MIPAS polar stratospheric clouds analyses and classification methods can be found under:

R. Spang, J. J. Remedios, L. J. Kramer, L. R. Poole, M. D. Fromm, M. Müller, G. Baumgarten, and P. Konopka, Atmos. Chem. Phys., 5, 679-692, https://doi.org/10.5194/acp-5-679-2005, 2005.

Spang, R., Arndt, K., Dudhia, A., Höpfner, M., Hoffmann, L., Hurley, J., Grainger, R. G., Griessbach, S., Poulsen, C., Remedios, J. J., Riese, M., Sembhi, H., Siddans, R., Waterfall, A., and Zehner, C.: Fast cloud parameter retrievals of MIPAS/Envisat, Atmos. Chem. Phys., 12, 7135-7164, https://doi.org/10.5194/acp-12-7135-2012, 2012.

Hoffmann, L., Spang, R., Orr, A., Alexander, M. J., Holt, L. A., and Stein, O.: A decadal satellite record of gravity wave activity in the lower stratosphere to study polar stratospheric cloud formation, Atmos. Chem. Phys., 17, 2901-2920, https://doi.org/10.5194/acp-17-2901-2017, 2017.


Please do not hesitate to contact us if you have any further questions:

Dr. Reinhold Spang

Forschungszentrum Jülich
Institut für Energie- und Klimaforschung, IEK-7
52425 Jülich

e-mail: r.spang@fz-juelich.de

Forschungszentrum J<C3><BC>lich     http://doi.org/10.17616/R3BN26     Creative Commons License