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| Titel |
Statistical analysis of a new European Cloud Dynamics and Radiation Database |
| VerfasserIn |
D. Casella, M. Formenton, W.-Y. Leung, A. Mugnai, P. Sanò, E. A. Smith, G. J. Tripoli |
| Konferenz |
EGU General Assembly 2009
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 11 (2009) |
| Datensatznummer |
250031237
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| Zusammenfassung |
| Physically-based algorithms for the retrieval of precipitation from satellite-borne
microwave (MW) radiometers, make use of Cloud Radiation Databases (CRD’s) that are
composed of thousands of detailed microphysical cloud profiles, obtained from Cloud
Resolving Model (CRM) simulations, coupled with the corresponding brightness
temperatures (TB’s), calculated by applying Radiative Transfer (RT) schemes to the CRM
outputs. Usually, CRD’s are generated on the basis of CRM simulations of past
precipitation events and then utilized for the analysis of satellite observations of new
events.
Notably, retrieval precision and accuracy is strictly related to the appropriate generation
of the cloud profile datasets associated to the typologies of the observed precipitation events
more than to an a-posteriori statistical treatment of uncertainties. In essence, the retrieval
performance can be improved by generating a statistically significant CRD by means of a
large number of different CRM simulations representing all precipitation regimes that are of
interest for the zone(s) and season(s) under investigation. In addition, it should
be noted that despite some reasonable successes with the CRD and the Bayesian
approach, there is a considerable reservoir of potential information available that
has not been yet tapped. This ancillary information exists in the knowledge of the
“synoptic situation” of the considered event and the geographical and temporal
location of the event. This knowledge renders some entries into the CRD more
relevant than others by virtue of how similar the circumstances of the simulated events
are to those of the event for which the database is applied. We can capture this
information in the form of “dynamical tags” which can be used to link a satellite-observed
event to a subset of the entire CRD using an independent estimate of these tags.
To accomplish this, we have expanded the CRD approach so as to include these
“dynamical tags” and have developed a new passive MW precipitation retrieval algorithm
which employs these tags in addition to the upwelling TB’s. We call these the Cloud
Dynamics and Radiation Database (CDRD) approach and the CDRD Algorithm,
respectively.
Recently, we have generated a CDRD database for Europe using a large amount of CRM
simulations of precipitating systems over this area by means of the “University of Wisconsin
– Non-hydrostatic Modeling System” (UW-NMS). In our presentation, we will briefly review
the main design features of the CDRD approach and will show an analysis of the statistical
properties of this highly-populated European CDRD database. Finally, we will compare its
radiative characteristics with an equivalent set of MW radiometric measurements from polar
satellites. |
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