Search for: All records

Abstract. Many passive remote-sensing techniques have beendeveloped to retrieve cloud microphysical properties from satellite-basedsensors, with the most common approaches being the bispectral andpolarimetric techniques. These two vastly different retrieval techniqueshave been implemented for a variety of polar-orbiting and geostationarysatellite platforms, providing global climatological data sets. Priorinstrument comparison studies have shown that there are systematicdifferences between the droplet size retrieval products (effective radius)of bispectral (e.g., MODIS, Moderate Resolution Imaging Spectroradiometer)and polarimetric (e.g., POLDER, Polarization and Directionality of Earth'sReflectances) instruments. However, intercomparisons of airborne bispectraland polarimetric instruments have yielded results that do not appear to besystematically biased relative to one another. Diagnosing this discrepancyis complicated, because it is often difficult for instrument intercomparisonstudies to isolate differences between retrieval technique sensitivities andspecific instrumental differences such as calibration and atmosphericcorrection. In addition to these technical differences the polarimetricretrieval is also sensitive to the dispersion of the droplet sizedistribution (effective variance), which could influence the interpretationof the droplet size retrieval. To avoid these instrument-dependentcomplications, this study makes use of a cloud remote-sensing retrievalsimulator. Created by coupling a large-eddy simulation (LES) cloud modelwith a 1-D radiative transfer model, the simulator serves as a test bed forunderstanding differences between bispectral and polarimetric retrievals.With the help of this simulator we can not only compare the two techniquesto one another (retrieval intercomparison) but also validate retrievalsdirectly against the LES cloud properties. Using the satellite retrievalsimulator, we are able to verify that at high spatial resolution (50m) thebispectral and polarimetric retrievals are highly correlated with oneanother within expected observational uncertainties. The relatively smallsystematic biases at high spatial resolution can be attributed to differentsensitivity limitations of the two retrievals. In contrast, a systematicdifference between the two retrievals emerges at coarser resolution. Thisbias largely stems from differences related to sensitivity of the tworetrievals to unresolved inhomogeneities in effective variance and opticalthickness. The influence of coarse angular resolution is found to increaseuncertainty in the polarimetric retrieval but generally maintains aconstant mean value.