2.5
Variability and interpretation of satellite derived cloud properties from MODIS
Brent C. Maddux, CIMSS/Univ. of Wisconsin, Madison, WI; and S. A. Ackerman, P. Menzel, and S. Platnick
The MODIS cloud products allows for an unprecedented ability to create high-quality, well characterized data records of cloud properties. A global cloud data record produced using high spectral and spatial resolution satellite instrument will inherently characterize the observed cloud field more accurately than a coarser resolution instrument. However, this does not mean that the interpretation of the dataset will be more straightforward. Specifically, the aims of producing a well-understood cloud property data set aren't necessarily aligned with goals of a climate record or modeling analysis. Thus, a global cloud dataset is not necessarily a dataset that can be used for other purposes, e.g. climate data records, without proper considerations. As with all satellite data sets, the MODIS data products set thresholds for cloud detection, cloud property processing, etc. these greatly impact the picture of the global cloud field. We will present some the interpretation issues associated with using the MODIS cloud property records. These issues arise from various sources that are common to all satellite data records. Among the sources are the satellite view geometry, instrument calibration, sensor resolution, spectral resolution, cloud detection thresholds, etc. For example, Figure 1 shows the cloud amount using the MODIS cloud mask minus the cloud amount that the cloud optical properties are calculated for. In other words, the difference between the two cloud amounts is the portion of the cloud field that is not included in the optical properties. Figure 2 shows the vertical distribution of clouds for the cloud amounts shown in Figure 1. Note that the vertical distribution of clouds for clouds detected vs. clouds that optical properties are retrieved for is vastly different. Another example of the source of error is the view geometry of the satellite. Beyond the known and well-documented effects of view geometry on the cloud field there are effects that are dependent on cloud type and cloud amount, see Figure 3. Figure 3 shows the difference in the seasonal cycle over the stratocumulus deck off the coast of Peru.
Session 2, Satellite Research and Algorithm Development in Meteorology
Monday, 27 September 2010, 1:30 PM-3:00 PM, Capitol D
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