Constrained Cirrus Cloud Properties from MPLNET Retrievals

The most current MPLNET Version 3 cloud detection algorithm reports thin cirrus cloud properties (e.g. optical depth, extinction) using bookend lidar ratios of 20 and 30 sr. However, reducing the uncertainty in the lidar ratio, and the resulting cirrus cloud properties, is important for studies of radiative forcing. In this presentation, we use constrained retrievals when the molecular signal can be determined below and above the cloud layer in order to solve directly for the optical depth and lidar ratio. Then assuming a constant value of the lidar ratio throughout the cloud layer, profiles of the extinction are derived. Simulated lidar data are used to assess the efficacy of the constrained solutions and comparisons are made to the unconstrained bookend solutions. Finally, cirrus cloud retrievals from multiple sites are used to show how the lidar ratio changes as a function of temperature, height, and cirrus type. Because MPLNET is a global network, with sites in tropical, midlatitude, and polar locations, the results are relevant for the validation of similar retrievals from existing and future satellite lidar instruments (e.g. CALIOP, CATS, EarthCARE).