Abstract
The present study documents optimal methods for the retrieval of cloud properties using five channels (0.6, 3.7, 6.7, 10.8 and 12.0 μm) that are used in many geostationary meteorological satellite observations. Those channels are also to be adopted for the Communication, Ocean and Meteorological Satellite (COMS) scheduled to be launched in 2008. The cloud properties focused on are cloud thermodynamic phase, cloud optical thickness, effective particle radius and cloud-top properties with specific uncertainties. Discrete ordinate radiative transfer models are simulated to build up the retrieval algorithm. The cloud observations derived from the Moderate-resolution Imaging Spectroradiometer (MODIS) are compared with the results to assess the validity of the algorithm. The preliminary validation indicates that the additional use of a band at 6.7 μm would be better in discriminating the cloud ice phase. Cloud optical thickness and effective particle radius can also be produced up to, respectively, 64 and 32 μm by functionally eliminating both ground-reflected and cloud- and ground-thermal radiation components at 0.6 and 3.7 μm. Cloud-top temperature (pressure) in ±3 K (± 50 hPa) uncertainties can be estimated by a simple 10.8-μm method for opaque clouds, and by an infrared ratioing method using 6.7 and 10.8 μm for semitransparent clouds.
Original language | English |
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Pages (from-to) | 4715-4732 |
Number of pages | 18 |
Journal | International Journal of Remote Sensing |
Volume | 28 |
Issue number | 21 |
DOIs | |
State | Published - 10 Nov 2007 |
Bibliographical note
Funding Information:This study was undertaken for the COMS project funded by the Korean Meteorological Administration. Y.-S.C. and Y.-M.K. are supported by the BK21 project of the Korean government. We thank an anonymous reviewer for valuable comments. The MODIS data were provided by the Earth Observing System Data and Information System, Distributed Active Archive Center, at Goddard Space Flight Center, which archives, manages, and distributes these data.