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Thermodynamic profiles in the atmospheric boundary layer can be retrieved from ground-based passive remote sensing instruments with an optimal estimation physical retrieval such as Tropospheric Remotely Observed Profiling via Optimal Estimation (TROPoe). The retrieval combines measurements, prior information, and corresponding uncertainties to find an optimal solution of the atmospheric state. TROPoe permits combining passively sensed radiances from infrared spectrometers and microwave radiometers with thermodynamic profiles from Raman lidars, Differential Absorption lidars, Radio Acoustic Sounding Systems, radio soundings, or numerical weather prediction models. After more than 10 years of development, the TROPoe retrieval code was recently converted to Python and put into a Docker container to facilitate its usage for both operations and research. It is currently used operationally by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program and by the Swiss weather service MeteoSwiss as part of the EUMETNET. With a high temporal resolution on the order of minutes, the retrieved thermodynamic profiles are a powerful tool to study the temporal evolution of the boundary layer.Since each profile is retrieved independently from the previous one, the time series of thermodynamic variables contain random uncorrelated noise, which may hinder the study of diurnal cycles and temporal tendencies. In this work, we investigate how the temporal consistency of thermodynamic profiles retrieved with TROPoe can be improved by including information from a previous retrieved profile as input to the retrieval. We demonstrate that this method works well in mid-latitudes, polar and tropical sites and for retrievals based on measurements from infrared spectrometers and microwave radiometers. We further present methods to enhance the availability of valid profiles retrieved from infrared spectrometers by preventing overfitting and by adding information from an additional infrared band in high moisture environments when the typically used spectral bands are saturated.
Adler et al. (Fri,) studied this question.