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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 6, issue 5 | Copyright
Atmos. Meas. Tech., 6, 1347-1358, 2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 22 May 2013

Research article | 22 May 2013

Raman Lidar for Meteorological Observations, RALMO – Part 2: Validation of water vapor measurements

E. Brocard1, R. Philipona1, A. Haefele1, G. Romanens1, A. Mueller1, D. Ruffieux1, V. Simeonov2, and B. Calpini1 E. Brocard et al.
  • 1Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
  • 2Laboratory of Environmental Fluid Mechanics and Hydrology, Lausanne, Switzerland

Abstract. The Raman Lidar for Meteorological Observations (RALMO) was installed at the MeteoSwiss Regional Center of Payerne, Switzerland, in summer 2008. One of its aims is to provide continuous vertical profiles of tropospheric water vapor during day and night at a high temporal resolution. Twelve months (October 2009–September 2010) of lidar data are analyzed. During this period of time, the lidar produced 9086 profiles, representing 52.6% of the time (this figure reached 63.2% for the first 6 months of 2011). Under cloud-free conditions, half of the profiles reached more than 8610 m above ground level at night, and 4050 m during the day. In order to validate the capabilities of the instrument, the year of lidar data was compared to the collocated radiosondes. On average, lidar water vapor mixing ratio was found to be within 5 to 10% of radiosonde values up to 8 km at night, and within 3% up to 3 km during the day. Relative humidity results show an agreement within 2 and 5% for day and night, respectively. An integrated water vapor comparison also shows a good correlation with both radiosondes and GPS measurements: the lidar had a 4.2% dry bias compared to radiosondes and a 5.3% wet bias compared to GPS. These results validate the performance of the lidar and the humidity profiles with a 30 min time resolution.

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