2019, Tesche, Matthias, Kolgotin, Alexei, Haarig, Moritz, Burton, Sharon P., Ferrare, Richard A., Hostetler, Chris A., Müller, Detlef

The typical multiwavelength aerosol lidar data set for inversion of optical to microphysical parameters is composed of three backscatter coefficients (β) at 355, 532, and 1064 nm and two extinction coefficients (α) at 355 and 532 nm. This data combination is referred to as a 3β C 2α or 3 + 2 data set. This set of data is sufficient for retrieving some important microphysical particle parameters if the particles have spherical shape. Here, we investigate the effect of including the particle linear depolarization ratio (δ) as a third input parameter for the inversion of lidar data. The inversion algorithm is generally not used if measurements show values of d that exceed 0.10 at 532 nm, i.e. in the presence of nonspherical particles such as desert dust, volcanic ash, and, under special circumstances, biomass-burning smoke. We use experimental data collected with instruments that are capable of measuring d at all three lidar wavelengths with an inversion routine that applies the spheroidal light-scattering model of Dubovik et al. (2006) with a fixed axis-ratio distribution to replicate scattering properties of non-spherical particles. The inversion gives the fraction of spheroids required to replicate the optical data as an additional output parameter. This is the first systematic test of the effect of using all theoretically possible combinations of d taken at 355, 532, and 1064 nm as input in the lidar data inversion. We find that depolarization information of at least one wavelength already provides useful information for the inversion of optical data that have been collected in the presence of non-spherical mineral dust particles. However, any choice of d will give lower values of the single-scattering albedo than the traditional 3 + 2 data set. We find that input data sets that include d355 give a spheroid fraction that closely resembles the dust ratio we obtain from using β532 and d532 in a methodology applied in aerosol-type separation. The use of d355 in data sets of two or three d? reduces the spheroid fraction that is retrieved when using d532 and d1064. Use of the latter two parameters without accounting for d355 generally leads to high spheroid fractions that we consider not trustworthy. The use of three d instead of two δ, including the constraint that one of these is measured at 355 nm does not provide any advantage over using 3 + 2 + d355 for the observations with varying contributions of mineral dust considered here. However, additional measurements at wavelengths different from 355 nm would be desirable for application to a wider range of aerosol scenarios that may include non-spherical smoke particles, which can have values of d355 that are indistinguishable from those found for mineral dust. We therefore conclude that - depending on measurement capability - the future standard input for inversion of lidar data taken in the presence of mineral dust particles and using the spheroid model of Dubovik et al. (2006) might be 3+2Cδ355 or 3 + 2 + δ355 + δ532. © 2019 The Author(s).

2018-5-18, Wüst, Sabine, Offenwanger, Thomas, Schmidt, Carsten, Bittner, Michael, Jacobi, Christoph, Stober, Gunter, Yee, Jeng-Hwa, Mlynczak, Martin G., Russell III, James M.

For the first time, we present an approach to derive zonal, meridional, and vertical wavelengths as well as periods of gravity waves based on only one OH* spectrometer, addressing one vibrational-rotational transition. Knowledge of these parameters is a precondition for the calculation of further information, such as the wave group velocity vector. OH(3-1) spectrometer measurements allow the analysis of gravity wave ground-based periods but spatial information cannot necessarily be deduced. We use a scanning spectrometer and harmonic analysis to derive horizontal wavelengths at the mesopause altitude above Oberpfaffenhofen (48.09∘ N, 11.28∘ E), Germany for 22 nights in 2015. Based on the approximation of the dispersion relation for gravity waves of low and medium frequencies and additional horizontal wind information, we calculate vertical wavelengths. The mesopause wind measurements nearest to Oberpfaffenhofen are conducted at Collm (51.30∘ N, 13.02∘ E), Germany, ca. 380 km northeast of Oberpfaffenhofen, by a meteor radar. In order to compare our results, vertical temperature profiles of TIMED-SABER (thermosphere ionosphere mesosphere energetics dynamics, sounding of the atmosphere using broadband emission radiometry) overpasses are analysed with respect to the dominating vertical wavelength.

2017, Baars, Holger, Seifert, Patric, Engelmann, Ronny, Wandinger, Ulla

Absolute calibrated signals at 532 and 1064 nm and the depolarization ratio from a multiwavelength lidar are used to categorize primary aerosol but also clouds in high temporal and spatial resolution. Automatically derived particle backscatter coefficient profiles in low temporal resolution (30 min) are applied to calibrate the lidar signals. From these calibrated lidar signals, new atmospheric parameters in temporally high resolution (quasi-particle-backscatter coefficients) are derived. By using thresholds obtained from multiyear, multisite EARLINET (European Aerosol Research Lidar Network) measurements, four aerosol classes (small; large, spherical; large, non-spherical; mixed, partly nonspherical) and several cloud classes (liquid, ice) are defined. Thus, particles are classified by their physical features (shape and size) instead of by source. The methodology is applied to 2 months of continuous observations (24 h a day, 7 days a week) with the multiwavelength-Raman-polarization lidar PollyXT during the High-Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) in spring 2013. Cloudnet equipment was operated continuously directly next to the lidar and is used for comparison. By discussing three 24 h case studies, it is shown that the aerosol discrimination is very feasible and informative and gives a good complement to the Cloudnet target categorization. Performing the categorization for the 2-month data set of the entire HOPE campaign, almost 1 million pixel (5 min×30 m) could be analysed with the newly developed tool. We find that the majority of the aerosol trapped in the planetary boundary layer (PBL) was composed of small particles as expected for a heavily populated and industrialized area. Large, spherical aerosol was observed mostly at the top of the PBL and close to the identified cloud bases, indicating the importance of hygroscopic growth of the particles at high relative humidity. Interestingly, it is found that on several days non-spherical particles were dispersed from the ground into the atmosphere.

2023, Yamazaki, Yosuke

This paper describes a simple method for characterizing global-scale waves in the mesosphere and lower thermosphere (MLT), such as tides and traveling planetary waves, using uniformly gridded two-dimensional longitude-Time data. The technique involves two steps. In the first step, the Fourier transform is performed in space (longitude), and then the time series of the space Fourier coefficients are derived. In the second step, the wavelet transform is performed on these time series, and wavelet coefficients are derived. A Fourier-wavelet spectrum can be obtained from these wavelet coefficients, which gives the amplitude and phase of the wave as a function of time and wave period. It can be used to identify wave activity that is localized in time, similar to a wavelet spectrum, but the Fourier-wavelet spectrum can be obtained separately for eastward-and westward-propagating components and for different zonal wavenumbers. The Fourier-wavelet analysis can be easily implemented using existing Fourier and wavelet software. MATLAB and Python scripts are created and made available at https://igit.iap-kborn.de/yamazaki/fourierwavelet (last access: 18 August 2023) that compute Fourier-wavelet spectra using the wavelet software provided by . Some application examples are presented using MLT data from atmospheric models.