An Analysis of PMC Detection Sensitivity for the CIPS Instrument

The Cloud Imaging and Particle Size (CIPS) instrument is a nadir-viewing UV imager aboard the Aeronomy of Ice in the Mesosphere (AIM) satellite. CIPS measures scattered solar radiation at 265 nm using a unique four-camera configuration providing an instantaneous field of view of 120o (along-track) by 80 o (cross- track). Full instrument resolution for nadir pixels is 1 by 2 km. By combining data from multiple cameras, CIPS observes a given volume of air at seven different scattering angles ranging from 20 to 180 degrees. Level 4 data processing, which includes PMC detection and cloud parameter retrievals, typically uses binned data with a spatial resolution of 5 x 5 km. The detection algorithm discriminates a PMC signature from the Rayleigh-scattered background by exploiting the fact that the former is strongly forward scattered, whereas the background signal is symmetric about 90 degrees scattering angle. We present an analysis of the CIPS cloud detection sensitivity, with the goal of deriving an effective cloud brightness (albedo) threshold. This threshold is expected to vary with solar zenith angle (and hence latitude) due to both the CIPS measurement sampling characteristics and the geophysical variation in the Rayleigh background. Simulations show that it also depends on the mean cloud particle radius, as well as the desired spatial resolution of the cloud product (data binning). By quantifying these dependencies we can account for the residual effects of varying detection sensitivity in interpreting the cloud occurrence frequencies observed by CIPS, particularly the latitude dependence. This understanding will also provide a quantitative foundation for comparing the CIPS observations with other data sets. We also compare the sensitivity of the operational CIPS algorithm with an alternative cloud detection algorithm similar to that used for SBUV PMC analysis. This technique uses the measured albedo directly from individual CIPS pixels at a fixed scattering angle. Cloudy pixels are detected as enhancements above a background level, which is obtained iteratively by fitting a polynomial curve to an entire orbit's worth of data. This approach is found to work best at lower latitudes, which is precisely where the operational algorithm encounters its greatest difficulty due to increased brightness of the Rayleigh background and decreased measurement sampling of forward scattering angles. Thus results from this analysis may be used to define an optimal method for combining these two techniques in routine CIPS data processing.