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Start date: 2024 × WGL Institute: IAP ×

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    Greenhouse gas effects on the solar cycle response of water vapour and noctilucent clouds
    (Katlenburg, Lindau : Copernicus, 2023) Vellalassery, Ashique; Baumgarten, Gerd; Grygalashvyly, Mykhaylo; Lübken, Franz-Josef
    The responses of water vapour (H2O) and noctilucent clouds (NLCs) to the solar cycle are studied using the Leibniz Institute for Middle Atmosphere (LIMA) model and the Mesospheric Ice Microphysics And tranSport (MIMAS) model. NLCs are sensitive to the solar cycle because their formation depends on background temperature and the H2O concentration. The solar cycle affects the H2O concentration in the upper mesosphere mainly in two ways: directly through the photolysis and, at the time and place of NLC formation, indirectly through temperature changes. We found that H2O concentration correlates positively with the temperature changes due to the solar cycle at altitudes above about 82 km, where NLCs form. The photolysis effect leads to an anti-correlation of H2O concentration and solar Lyman-α radiation, which gets even more pronounced at altitudes below ∼83 km when NLCs are present. We studied the H2O response to Lyman-α variability for the period 1992 to 2018, including the two most recent solar cycles. The amplitude of Lyman-α variation decreased by about 40 % in the period 2005 to 2018 compared to the preceding solar cycle, resulting in a lower H2O response in the late period. We investigated the effect of increasing greenhouse gases (GHGs) on the H2O response throughout the solar cycle by performing model runs with and without increases in carbon dioxide (CO2) and methane (CH4). The increase of methane and carbon dioxide amplifies the response of water vapour to the solar variability. Applying the geometry of satellite observations, we find a missing response when averaging over altitudes of 80 to 85 km, where H2O has a positive response and a negative response (depending on altitude), which largely cancel each other out. One main finding is that, during NLCs, the solar cycle response of H2O strongly depends on altitude.
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    Ground-based noontime D-region electron density climatology over northern Norway
    (Katlenburg-Lindau : EGU, 2023) Renkwitz, Toralf; Sivakandan, Mani; Jaen, Juliana; Singer, Werner
    The bottom part of the Earth's ionosphere is the so-called D region, which is typically less dense than the upper regions. Despite the comparably lower electron density, the ionization state of the D region has a significant influence on signal absorption for propagating lower to medium radio frequencies. We present local noon climatologies of electron densities in the upper middle atmosphere (50-90km) at high latitudes as observed by an active radar experiment. The radar measurements cover 9 years (2014-2022) from the solar maximum of cycle 24 to the beginning of cycle 25. Reliable electron densities are derived by employing signal processing, applying interferometry methods, and applying the Faraday-International Reference Ionosphere (FIRI) model. For all years a consistent spring-fall asymmetry of the electron density pattern with a gradual increase during summer as well as a sharp decrease at the beginning of October was found. These findings are consistent with very low frequency (VLF) studies showing equivalent signatures for nearby propagation paths. It is suggested that the meridional circulation associated with downwelling in winter could cause enhanced electron densities through NO transport. However, this mechanism can not explain the reduction in electron density in early October.
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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)
    (Katlenburg-Lindau : Copernicus, 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.