 |
| Titel |
Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR |
| VerfasserIn |
C. A. Poulsen, R. Siddans, G. E. Thomas, A. M. Sayer, R. G. Grainger, E. Campmany, S. M. Dean, C. Arnold, P. D. Watts |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1867-1381
|
| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 5, no. 8 ; Nr. 5, no. 8 (2012-08-07), S.1889-1910 |
| Datensatznummer |
250003045
|
| Publikation (Nr.) |
 copernicus.org/amt-5-1889-2012.pdf |
|
|
|
|
|
| Zusammenfassung |
Clouds play an important role in balancing the Earth's radiation
budget. Hence, it is vital that cloud climatologies are produced that
quantify cloud macro and micro physical parameters and the associated
uncertainty. In this paper, we present an algorithm ORAC (Oxford-RAL
retrieval of Aerosol and Cloud) which is based on fitting
a physically consistent cloud model to satellite observations
simultaneously from the
visible to the mid-infrared, thereby ensuring that the resulting cloud properties
provide both a good representation of the short-wave and
long-wave radiative effects of the observed cloud. The advantages of
the optimal estimation method are that it enables rigorous error
propagation and the inclusion of all measurements and any a priori information and
associated errors in a rigorous mathematical framework. The algorithm
provides a measure of the consistency between retrieval representation of cloud
and satellite radiances. The cloud parameters retrieved
are the cloud top pressure, cloud optical depth, cloud effective radius,
cloud fraction and cloud phase.
The algorithm can be applied to most visible/infrared satellite
instruments. In this paper, we demonstrate the applicability to the
Along-Track Scanning Radiometers ATSR-2 and AATSR. Examples of applying the algorithm to ATSR-2 flight data are presented and the sensitivity of
the retrievals assessed, in particular the algorithm is evaluated for
a number of simulated single-layer and multi-layer conditions. The
algorithm was found to perform well for single-layer cloud except when
the cloud was very thin; i.e., less than 1 optical depths. For the multi-layer
cloud, the algorithm was robust except when the upper ice cloud
layer is less than five optical depths. In these
cases the
retrieved cloud top pressure and cloud effective radius become a weighted average of the 2 layers. The sum of optical
depth of multi-layer cloud is retrieved well until the cloud becomes
thick, greater than 50 optical depths, where the cloud begins to saturate. The cost proved a
good indicator of multi-layer scenarios. Both the retrieval
cost and the error need to be considered together in order to evaluate
the quality of the retrieval.
This algorithm in the configuration described here has been applied to both ATSR-2 and AATSR visible and infrared measurements in the context of
the GRAPE (Global Retrieval and cloud Product Evaluation) project to
produce a 14 yr consistent record for climate research. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|