Detection of Polar Stratospheric Clouds Using AVHRR Imagery

In recent years, the role of PSCs in the ozone depletion process has become better understood. PSCs provide the surfaces upon which heterogeneous reactions take place that affect the gas phase partitioning between active and reservoir chlorine and nitrogen species. Present methods of PSC detection include in situ measurements by lidar and various satellite-borne instruments such as the Stratospheric Aerosol Measurement II (SAM II) on the Nimbus 7 spacecraft, which produced PSC measurements from 1978 to 1994 and several instruments onboard the Upper Atmospheric Research Satellite (UARS) such as the Cryogenic Limb Array Etalon Spectrometer (CLAES) which provided measurements for 1991-1993. All of the PSC-detection methods devised so far have been hampered by incomplete sampling of the places and times in which PSCs are likely to form. There is a need to understand the climatology of PSCS, in particular the timing of their onset and duration, their vertical distribution, geographic extent, annual variability and responses to volcanic aerosol forcing. Poole and Pitts [1994] assembled a PSC climatology based on SAM II data, but this climatology is incomplete, as it is limited to the edge of the polar night due to the limitations of the solar occultation scan geometry. The Advanced Very High Resolution Radiometer (AVHRR) five- channel sensors onboard the NOAA polar-orbiting satellites have been collecting data over the polar regions continuously since 1979. These operational satellites provide unmatched coverage in space and time of both polar regions, but were not designed for the detection of optically-thin PSCS. However, the AVHRR data archive would be an invaluable source for the construction of a long-term climatology of PSCs if techniques can be developed and tested to detect PSCs in AVHRR data. In the last few years, the members of our group at San Francisco State University and NASA Ames Research Center have been engaged in the development of various PSC detection methods using AVHRR data. There is strong evidence that a subset of PSCS, those that are optically thick, can be readily identified in the AVHRR data set. Our group has also made significant progress in the identification of optically thinner PSCs using a variety of techniques.