Previous temperature retrieval methods applied to Rayleigh-scatter lidar observations suffer from shortcomings and limitations, notably their incomplete uncertainty characterization. The paper by Sica and Haefele introduces important advances in the retrieval of temperature profiles from Rayleigh-scatter lidar by applying the optimal estimation method (OEM). Earlier, OEM has been successfully used with passive sensors for obtaining information about the atmospheric state, or with elastic backscatter lidars for analyzing aerosol properties.
OEM requires a forward model which best describes the system. In their paper, Sica and Haefele present performance comparisons for two forward models, which were chosen following careful investigations. These models are based essentially on the lidar equation with or without the assumption of hydrostatic equilibrium. Both forward models showed good performance and comparability against modelled temperature profiles when using synthetically produced lidar photocount profiles. However, once measured lidar photocount profiles were used, the forward model with released assumption of hydrostatic equilibrium produced different temperature profiles when compared to other methods. This discrepancy was shown to arise from the pressure profiles being used, which must necessarily be accurate. Therefore, with currently available pressure profiles, the forward operator that assumes hydrostatic equilibrium is better at producing the desired temperature profiles.
A typical problem when data from two lidar channels are combined is the merging of observations, and subsequently of their uncertainties, right in an overlapping region. The method applied by Sica and Haefele leads to a smooth transition between two observation profiles. Thus, one of the main benefits of OEM is its potential for synergetic temperature retrieval from multiple observation sources. Yet another advantage is that this method allows improved budgeting of uncertainties that are related to retrieved temperature profiles.
As a conclusion, OEM showed very good applicability and significant improvements in temperature retrievals from multi-channel Rayleigh backscatter lidar observations. Therefore, it is expected that this method will become more widely used among the lidar community.
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