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Volume 15, issue 6
Atmos. Chem. Phys., 15, 3135-3148, 2015
https://doi.org/10.5194/acp-15-3135-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 15, 3135-3148, 2015
https://doi.org/10.5194/acp-15-3135-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 19 Mar 2015

Research article | 19 Mar 2015

Spatiotemporal variability of water vapor investigated using lidar and FTIR vertical soundings above the Zugspitze

H. Vogelmann, R. Sussmann, T. Trickl, and A. Reichert H. Vogelmann et al.
  • Karlsruhe Institute of Technology, IMK-IFU, Garmisch-Partenkirchen, Germany

Abstract. Water vapor is the most important greenhouse gas and its spatiotemporal variability strongly exceeds that of all other greenhouse gases. However, this variability has hardly been studied quantitatively so far. We present an analysis of a 5-year period of water vapor measurements in the free troposphere above the Zugspitze (2962 m a.s.l., Germany). Our results are obtained from a combination of measurements of vertically integrated water vapor (IWV), recorded with a solar Fourier transform infrared (FTIR) spectrometer on the summit of the Zugspitze and of water vapor profiles recorded with the nearby differential absorption lidar (DIAL) at the Schneefernerhaus research station. The special geometrical arrangement of one zenith-viewing and one sun-pointing instrument and the temporal resolution of both instruments allow for an investigation of the spatiotemporal variability of IWV on a spatial scale of less than 1 km and on a timescale of less than 1 h. The standard deviation of differences between both instruments σIWV calculated for varied subsets of data serves as a measure of variability. The different subsets are based on various spatial and temporal matching criteria. Within a time interval of 20 min, the spatial variability becomes significant for horizontal distances above 2 km, but only in the warm season (σIWV =0.35 mm). However, it is not sensitive to the horizontal distance during the winter season. The variability of IWV within a time interval of 30 min peaks in July and August (σIWV > 0.55 mm, mean horizontal distance = 2.5 km) and has its minimum around midwinter (σIWV < 0.2 mm, mean distance > 5 km). The temporal variability of IWV is derived by selecting subsets of data from both instruments with optimal volume matching. For a short time interval of 5 min, the variability is 0.05 mm and increases to more than 0.5 mm for a time interval of 15 h. The profile variability of water vapor is determined by analyzing subsets of water vapor profiles recorded by the DIAL within time intervals from 1 to 5 h. For all altitudes, the variability increases with widened time intervals. The lowest relative variability is observed in the lower free troposphere around an altitude of 4.5 km. Above 5 km, the relative variability increases continuously up to the tropopause by about a factor of 3. Analysis of the covariance of the vertical variability reveals an enhanced variability of water vapor in the upper troposphere above 6 km. It is attributed to a more coherent flow of heterogeneous air masses, while the variability at lower altitudes is also driven by local atmospheric dynamics. By studying the short-term variability of vertical water vapor profiles recorded within a day, we come to the conclusion that the contribution of long-range transport and the advection of heterogeneous layer structures may exceed the impact of local convection by 1 order of magnitude even in the altitude range between 3 and 5 km.

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We quantitatively analyzed the spatiotemporal variability (minutes to hours, 500m to 10km) of water vapor (IWV and profiles) in the free troposphere recorded at the Zugspitze (Germany) with lidar and solar FTIR. We found that long-range transport of heterogeneous air masses may cause relative short-term variations of the water-vapor density which exceed the impact of local convection by 1 order of magnitude. Our results could be useful for issues of model parametrization and co-location.
We quantitatively analyzed the spatiotemporal variability (minutes to hours, 500m to 10km) of...
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