Combined retrievals of boreal forest fire aerosol properties with a polarimeter and lidar

摘要

Absorbing aerosols play an important, but uncertain, role in the globalclimate. Much of this uncertainty is due to a lack of adequate aerosolmeasurements. While great strides have been made in observational capabilityin the previous years and decades, it has become increasingly apparent thatthis development must continue. Scanning polarimeters have been designed tohelp resolve this issue by making accurate, multi-spectral, multi-anglepolarized observations. This work involves the use of the Research ScanningPolarimeter (RSP). The RSP was designed as the airborne prototype for theAerosol Polarimetery Sensor (APS), which was due to be launched as part ofthe (ultimately failed) NASA Glory mission. Field observations with the RSP,however, have established that simultaneous retrievals of aerosol absorptionand vertical distribution over bright land surfaces are quite uncertain. Wetest a merger of RSP and High Spectral Resolution Lidar (HSRL) data withobservations of boreal forest fire smoke, collected during the ArcticResearch of the Composition of the Troposphere from Aircraft and Satellites(ARCTAS). During ARCTAS, the RSP and HSRL instruments were mounted on thesame aircraft, and validation data were provided by instruments on anaircraft flying a coordinated flight pattern. We found that the lidar datadid indeed improve aerosol retrievals using an optimal estimation method,although not primarily because of the contraints imposed on the aerosolvertical distribution. The more useful piece of information from the HSRL wasthe total column aerosol optical depth, which was used to select the initialvalue (optimization starting point) of the aerosol number concentration. Whenground based sun photometer network climatologies of number concentrationwere used as an initial value, we found that roughly half of the retrievalshad unrealistic sizes and imaginary indices, even though the retrievedspectral optical depths agreed within uncertainties to independentobservations. The convergence to an unrealistic local minimum by the optimalestimator is related to the relatively low sensitivity to particles smallerthan 0.1 (μm) at large optical thicknesses. Thus, optimizationalgorithms used for operational aerosol retrievals of the fine mode sizedistribution, when the total optical depth is large, will require initialvalues generated from table look-ups that exclude unrealistic size/complexindex mixtures. External constraints from lidar on initial values used in theoptimal estimation methods will also be valuable in reducing the likelihoodof obtaining spurious retrievals.