Physics
Scientific paper
May 2006
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006agusmsa51a..01d&link_type=abstract
American Geophysical Union, Fall Meeting 2007, abstract #SA51A-01
Physics
0320 Cloud Physics And Chemistry, 0340 Middle Atmosphere: Composition And Chemistry, 0394 Instruments And Techniques, 3305 Climate Change And Variability (1616, 1635, 3309, 4215, 4513), 3360 Remote Sensing
Scientific paper
Satellite observations of polar mesospheric clouds (PMCs) are extremely valuable because they typically have daily coverage to characterize seasonal variations, sufficient detections for each season to give good statistics, quantitative information for physical analysis, and coverage of both hemispheres to evaluate global behavior. The first measurements of PMCs from space were made in 1969, and regular measurements have been made since 1978. Since current satellite instruments are not designed to measure PMCs, a variety of observing techniques have been used, each with specific advantages and disadvantages. Satellite data provide a comprehensive picture of PMC characteristics and variability over a wide range of latitudes in both hemispheres, and on time scales ranging from daily to decadal. At least 10 different satellite instruments have observed PMCs in the last five years alone, and six instruments are currently operating. These measurements have produced many interesting results, including the following topics: altitude, occurrence frequency, brightness, particle size and shape, planetary waves, rocket exhaust effects, diurnal variations, latitudinal variations, hemispheric differences, interannual variations, and long-term variations. An important goal for future PMC work is the ability to understand the relative importance of major forcing mechanisms in the mesosphere, such as water vapor, temperature, and dynamics. The NASA Aeronomy of Ice in the Mesosphere (AIM) mission, scheduled to launch in September 2006, will provide satellite PMC data with unprecedented spatial resolution as well as simultaneous measurements of some of these key parameters. Our challenge will be to understand the information in these data, so that we can better interpret the extensive PMC database that will continue into the future.
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