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Extended Validation of an Optimal Estimation Cloud Property Retrieval Algorithm

Results are presented which illustrate the evaluation of the retrieval using in situ data collected during the March 2000 Cloud Intensive Observation Period (IOP) and the incorporation of these observations into the retrieval algorithm. The observations are used to modify the a priori estimates of cloud properties used in the retrieval, and the influence of the modified a priori data are evaluated for a number of liquid cloud cases. The retrieval algorithm is further evaluated using observations over the yearlong period following the Cloud IOP. Finally, the extensibility of the retrieval algorithm is illustrated by incorporating microwave radiometer (MWR) observations to augment the MMCR and VOD inputs. Two cases are examined to evaluate the influence of the liquid water path constraints from the MWR on the retrieval results. Performance of the retrieval algorithm is evaluated in terms of bias and scatter of modeled radiative fluxes versus observations. The inclusion of VOD reduces scatter in all the modeled radiative fluxes in comparison to those obtained using only MMCR observations. The reductions range from 5% to over 50%. For shortwave fluxes, the inclusion of cloud optical depth information reduces both the top-ofatmosphere flux bias and the surface flux bias, while effects on the longwave biases are slight. Overall, the results suggest that the retrievals that include cloud optical depth information provide improved cloud microphysical properties in comparison with radar-only retrievals.