 |
| Titel |
Validation of cloud property retrievals with simulated satellite radiances: a case study for SEVIRI |
| VerfasserIn |
L. Bugliaro, T. Zinner, C. Keil, B. Mayer, R. Hollmann, M. Reuter, W. Thomas |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1680-7316
|
| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 11, no. 12 ; Nr. 11, no. 12 (2011-06-17), S.5603-5624 |
| Datensatznummer |
250009848
|
| Publikation (Nr.) |
 copernicus.org/acp-11-5603-2011.pdf |
|
|
|
|
|
| Zusammenfassung |
| Validation of cloud properties retrieved from passive spaceborne
imagers is essential for cloud and climate applications but
complicated due to the large differences in scale and observation
geometry between the satellite footprint and the independent ground
based or airborne observations. Here we illustrate and demonstrate
an alternative approach: starting from the output of the COSMO-EU
weather model of the German Weather Service realistic
three-dimensional cloud structures at a spatial scale of 2.33 km
are produced by statistical downscaling and microphysical properties
are associated to them. The resulting data sets are used as input to
the one-dimensional radiative transfer model libRadtran to simulate
radiance observations for all eleven low resolution channels of
MET-8/SEVIRI. At this point, both cloud properties and satellite
radiances are known such that cloud property retrieval results can
be tested and tuned against the objective input "truth". As an
example, we validate a cloud property retrieval of the Institute of
Atmospheric Physics of DLR and that of EUMETSAT's Climate Monitoring
Science Application Facility CMSAF. Cloud detection and cloud phase
assignment perform well. By both retrievals 88% of the pixels are
correctly classified as clear or cloudy. The DLR algorithm assigns
the correct thermodynamic phase to 95% of the cloudy pixels and
the CMSAF retrieval to 84%. Cloud top temperature is slightly
overestimated by the DLR code (+3.1 K mean difference with a
standard deviation of 10.6 K) and to a very low extent by the CMSAF
code (−0.12 K with a standard deviation of 7.6 K). Both
retrievals account reasonably well for the distribution of optical
thickness for both water and ice clouds, with a tendency to
underestimation. Cloud effective radii are most difficult to
evaluate but the APICS algorithm shows that realistic histograms of
occurrences can be derived (CMSAF was not evaluated in this
context). Cloud water path, which is a combination of the last two
quantities, is slightly underestimated by APICS, while CMSAF shows a
larger scattering. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|