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    Long-term studies of mesosphere and lower-thermosphere summer length definitions based on mean zonal wind features observed for more than one solar cycle at middle and high latitudes in the Northern Hemisphere
    (Katlenburg, Lindau : Copernicus, 2022) Jaen, Juliana; Renkwitz, Toralf; Chau, Jorge L.; He, Maosheng; Hoffmann, Peter; Yamazaki, Yosuke; Jacobi, Christoph; Tsutsumi, Masaki; Matthias, Vivien; Hall, Chris
    Specular meteor radars (SMRs) and partial reflection radars (PRRs) have been observing mesospheric winds for more than a solar cycle over Germany (g1/4g54g gN) and northern Norway (g1/4g69g gN). This work investigates the mesospheric mean zonal wind and the zonal mean geostrophic zonal wind from the Microwave Limb Sounder (MLS) over these two regions between 2004 and 2020. Our study focuses on the summer when strong planetary waves are absent and the stratospheric and tropospheric conditions are relatively stable. We establish two definitions of the summer length according to the zonal wind reversals: (1) the mesosphere and lower-thermosphere summer length (MLT-SL) using SMR and PRR winds and (2) the mesosphere summer length (M-SL) using the PRR and MLS. Under both definitions, the summer begins around April and ends around middle September. The largest year-to-year variability is found in the summer beginning in both definitions, particularly at high latitudes, possibly due to the influence of the polar vortex. At high latitudes, the year 2004 has a longer summer length compared to the mean value for MLT-SL as well as 2012 for both definitions. The M-SL exhibits an increasing trend over the years, while MLT-SL does not have a well-defined trend. We explore a possible influence of solar activity as well as large-scale atmospheric influences (e.g., quasi-biennial oscillation (QBO), El Niño-Southern Oscillation (ENSO), major sudden stratospheric warming events). We complement our work with an extended time series of 31 years at middle latitudes using only PRR winds. In this case, the summer length shows a breakpoint, suggesting a non-uniform trend, and periods similar to those known for ENSO and QBO.
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    Aerosol activation characteristics and prediction at the central European ACTRIS research station of Melpitz, Germany
    (Katlenburg-Lindau : EGU, 2022) Wang, Yuan; Henning, Silvia; Poulain, Laurent; Lu, Chunsong; Stratmann, Frank; Wang, Yuying; Niu, Shengjie; Pöhlker, Mira L.; Herrmann, Hartmut; Wiedensohler, Alfred
    Understanding aerosol particle activation is essential for evaluating aerosol indirect effects (AIEs) on climate. Long-term measurements of aerosol particle activation help to understand the AIEs and narrow down the uncertainties of AIEs simulation. However, they are still scarce. In this study, more than 4 years of comprehensive aerosol measurements were utilized at the central European research station of Melpitz, Germany, to gain insight into the aerosol particle activation and provide recommendations on improving the prediction of number concentration of cloud condensation nuclei (CCN, NCCN). (1) The overall CCN activation characteristics at Melpitz are provided. As supersaturation (SS) increases from 0.1% to 0.7%, the median NCCN increases from 399 to 2144cm-3, which represents 10% to 48% of the total particle number concentration with a diameter range of 10-800nm, while the median hygroscopicity factor (κ) and critical diameter (Dc) decrease from 0.27 to 0.19 and from 176 to 54nm, respectively. (2) Aerosol particle activation is highly variable across seasons, especially at low-SS conditions. At SSCombining double low line0.1%, the median NCCN and activation ratio (AR) in winter are 1.6 and 2.3 times higher than the summer values, respectively. (3) Both κ and the mixing state are size-dependent. As the particle diameter (Dp) increases, κ increases at Dp of 1/440 to 100nm and almost stays constant at Dp of 100 to 200nm, whereas the degree of the external mixture keeps decreasing at Dp of 1/440 to 200nm. The relationships of κ vs. Dp and degree of mixing vs. Dp were both fitted well by a power-law function. (4) Size-resolved κ improves the NCCN prediction. We recommend applying the κ-Dp power-law fit for NCCN prediction at Melpitz, which performs better than using the constant κ of 0.3 and the κ derived from particle chemical compositions and much better than using the NCCN (AR) vs. SS relationships. The κ-Dp power-law fit measured at Melpitz could be applied to predict NCCN for other rural regions. For the purpose of improving the prediction of NCCN, long-term monodisperse CCN measurements are still needed to obtain the κ-Dp relationships for different regions and their seasonal variations.