83rd Annual

Thursday, 13 February 2003
Improved Detection of Nocturnal Low Clouds by MODIS
Thomas F. Lee, NRL, Monterey, CA; and S. D. Miller
Poster PDF (168.1 kB)
Research using GOES and AVHRR data sets has demonstrated that cloud tops containing supercooled liquid water can be detected with reasonable accuracy from satellite. This is turn has led to improvements to aircraft icing nowcasting schemes. Combined with surface reports, radar data, and mesoscale model output, satellite retrievals now add significantly to the skill of icing nowcasts. However, current operational satellite schemes have limitations that can be improved upon using the MODIS instrument.

A key parameter that must be investigated is cloud phase. With the advent of MODIS data, there are channels that can be combined to retrieve cloud phase. For example, in combination with the 11 12 micron difference, the 8 11 micron difference offers the prospect of determining cloud phase twenty-four hours a day. Images of these differences can be compared to images of the 3.7 and 1.6 micron channels which also contain useful information about cloud phase. Once cloud phase is determined, water phase clouds are classified as supercooled if IR cloud top temperatures are lower than 0 C.

Of particular interest is the case of supercooled large drops (SLD) that cause particularly severe aircraft icing. These drops, ranging from 40 to 200 microns, are not identifiable using AVHRR and GOES satellite data. Although drop size algorithms are available for these satellites, they are not capable of distinguishing SLD from other water droplets or adjacent ice crystals. More sophisticated algorithms from MODIS may be able to identify these regions. Currently, regions of SLD are inferred mainly from surface precipitation reports. Freezing rain and drizzle at the surface are strong indicators of SLD conditions aloft. If MODIS algorithms can identify regions of SLD, we will compare these regions with surface reports of freezing precipitation.

Supplementary URL: