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Titel |
Fast cloud parameter retrievals of MIPAS/Envisat |
VerfasserIn |
R. Spang, K. Arndt, A. Dudhia, M. Höpfner, L. Hoffmann, J. Hurley, R. G. Grainger, S. Griessbach, C. Poulsen, J. J. Remedios, M. Riese, H. Sembhi, R. Siddans, A. Waterfall, C. Zehner |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1680-7316
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Digitales Dokument |
URL |
Erschienen |
In: Atmospheric Chemistry and Physics ; 12, no. 15 ; Nr. 12, no. 15 (2012-08-07), S.7135-7164 |
Datensatznummer |
250011375
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Publikation (Nr.) |
copernicus.org/acp-12-7135-2012.pdf |
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Zusammenfassung |
The infrared limb spectra of the Michelson Interferometer for Passive
Atmospheric Sounding (MIPAS) on board the Envisat satellite include detailed
information on tropospheric clouds and polar stratospheric clouds (PSC).
However, no consolidated cloud product is available for the scientific
community. Here we describe a fast prototype processor for cloud parameter
retrieval from MIPAS (MIPclouds). Retrieval of parameters such as cloud top
height, temperature, and extinction are implemented, as well as retrieval of
microphysical parameters, e.g. effective radius and the integrated
quantities over the limb path (surface area density and volume density).
MIPclouds classifies clouds as either liquid or ice cloud in the upper
troposphere and polar stratospheric clouds types in the stratosphere based
on statistical combinations of colour ratios and brightness temperature
differences.
Comparison of limb measurements of clouds with model results or cloud
parameters from nadir looking instruments is often difficult due to
different observation geometries. We therefore introduce a new concept, the
limb-integrated surface area density path (ADP). By means of validation and
radiative transfer calculations of realistic 2-D cloud fields as input for a
blind test retrieval (BTR), we demonstrate that ADP is an extremely valuable
parameter for future comparison with model data of ice water content, when
applying limb integration (ray tracing) through the model fields. In
addition, ADP is used for a more objective definition of detection
thresholds of the applied detection methods. Based on BTR, a detection
threshold of ADP = 107 μm2 cm−2 and an ice water content
of 10−5 g m−3 is estimated, depending on the horizontal and
vertical extent of the cloud.
Intensive validation of the cloud detection methods shows that the
limb-sounding MIPAS instrument has a sensitivity in detecting stratospheric
and tropospheric clouds similar to that of space- and ground-based lidars,
with a tendency for higher cloud top heights and consequently higher
sensitivity for some of the MIPAS detection methods. For the high cloud
amount (HCA, pressure levels below 440 hPa) on global scales the sensitivity
of MIPAS is significantly greater than that of passive nadir viewers. This
means that the high cloud fraction will be underestimated in the ISCCP
dataset compared to the amount of high clouds deduced by MIPAS. Good
correspondence in seasonal variability and geographical distribution of
cloud occurrence and zonal means of cloud top height is found in a detailed
comparison with a climatology for subvisible cirrus clouds from the
Stratospheric Aerosol and Gas Experiment II (SAGE II) limb sounder. Overall,
validation with various sensors shows the need to consider differences in
sensitivity, and especially the viewing geometries and field-of-view size,
to make the datasets comparable (e.g. applying integration along the limb
path through nadir cloud fields). The simulation of the limb path
integration will be an important issue for comparisons with cloud-resolving
global circulation or chemical transport models. |
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