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Advanced hodograph-based analysis technique to derive gravity-wave parameters from lidar observations

2020, Strelnikova, Irina, Baumgarten, Gerd, Lübken, Franz-Josef

An advanced hodograph-based analysis technique to derive gravity-wave (GW) parameters from observations of temperature and winds is developed and presented as a step-by-step recipe with justification for every step in such an analysis. As the most adequate background removal technique the 2-D FFT is suggested. For an unbiased analysis of fluctuation whose amplitude grows with height exponentially, we propose applying a scaling function of the form exp (z∕(ςH)), where H is scale height, z is altitude, and the constant ς can be derived by a linear fit to the fluctuation profile and should be in the range 1–10. The most essential part of the proposed analysis technique consists of fitting cosine waves to simultaneously measured profiles of zonal and meridional winds and temperature and subsequent hodograph analysis of these fitted waves. The linear wave theory applied in this analysis is extended by introducing a wave packet envelope term exp(−(z−z0)2/2σ2) that accounts for limited extent of GWs in the observational data set. The novelty of our approach is that its robustness ultimately allows for automation of the hodograph analysis and resolves many more GWs than can be inferred by the manually applied hodograph technique. This technique allows us to unambiguously identify upward- and downward-propagating GWs and their parameters. This technique is applied to unique lidar measurements of temperature and horizontal winds measured in an altitude range of 30 to 70 km.

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Evaluation of satellite-based aerosol datasets and the CAMS reanalysis over the ocean utilizing shipborne reference observations

2020, Witthuhn, Jonas, Hünerbein, Anja, Deneke, Hartwig

Reliable reference measurements over the ocean are essential for the evaluation and improvement of satelliteand model-based aerosol datasets. Within the framework of the Maritime Aerosol Network, shipborne reference datasets have been collected over the Atlantic Ocean since 2004 with Microtops Sun photometers. These were recently complemented by measurements with the multi-spectral GUVis- 3511 shadowband radiometer during five cruises with the research vessel Polarstern. The aerosol optical depth (AOD) uncertainty estimate of both shipborne instruments of ±0:02 can be confirmed if the GUVis instrument is cross calibrated to the Microtops instrument to account for differences in calibration, and if an empirical correction to account for the broad shadowband as well as the effects of forward scattering is introduced. Based on these two datasets, a comprehensive evaluation of aerosol products from the Moderate Resolution Imaging Spectroradiometer (MODIS) flown on NASA's Earth Observing System satellites, the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard the geostationary Meteosat satellite, and the Copernicus Atmosphere Monitoring Service reanalysis (CAMS RA) is presented. For this purpose, focus is given to the accuracy of the AOD at 630 nm in combination with the Ångström exponent (AE), discussed in the context of the ambient aerosol type. In general, the evaluation of MODIS AOD from the official level-2 aerosol products of C6.1 against the Microtops AOD product confirms that 76% of data points fall into the expected error limits given by previous validation studies. The SEVIRI-based AOD product exhibits a 25% larger scatter than the MODIS AOD products at the instrument's native spectral channels. Further, the comparison of CAMS RA and MODIS AOD versus the shipborne reference shows similar performance for both datasets, with some differences arising from the assimilation and model assumptions. When considering aerosol conditions, an overestimation of AE is found for scenes dominated by desert dust for MODIS and SEVIRI products versus the shipborne reference dataset. As the composition of the mixture of aerosol in satellite products is constrained by model assumptions, this highlights the importance of considering the aerosol type in evaluation studies for identifying problematic aspects. © Author(s) 2020.

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The potential of elastic and polarization lidars to retrieve extinction profiles

2020, Giannakaki, Elina, Kokkalis, Panos, Marinou, Eleni, Bartsotas, Nikolaos S., Amiridis, Vassilis, Ansmann, Albert, Komppula, Mika

A new method, called ElEx (elastic extinction), is proposed for the estimation of extinction coefficient lidar profiles using only the information provided by the elastic and polarization channels of a lidar system. The method is applicable to lidar measurements both during daytime and nighttime under well-defined aerosol mixtures. ElEx uses the particle backscatter profiles at 532 nm and the vertically resolved particle linear depolarization ratio measurements at the same wavelength. The particle linear depolarization ratio and the lidar ratio values of pure aerosol types are also taken from literature. The total extinction profile is then estimated and compared well with Raman retrievals. In this study, ElEx was applied in an aerosol mixture of marine and dust particles at Finokalia station during the CHARADMExp campaign. Any difference between ElEx and Raman extinction profiles indicates that the nondust component could be probably attributed to polluted marine or polluted continental aerosols. Comparison with sun photometer aerosol optical depth observations is performed as well during daytime. Differences in the total aerosol optical depth are varying between 1.2 % and 72 %, and these differences are attributed to the limited ability of the lidar to correctly represent the aerosol optical properties in the near range due to the overlap problem. © 2020 Author(s).

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A method to derive Fourier-wavelet spectra for the characterization of global-scale waves in the mesosphere and lower thermosphere and its MATLAB and Python software (fourierwavelet v1.1)

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.