Abstract
Abstract. The temperature measurements of the rotational Raman lidar of the University of Hohenheim (UHOH RRL) during the High Definition of Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observation Prototype Experiment (HOPE) in April and May 2013 are discussed. The lidar consists of a frequency-tripled Nd:YAG laser at 355 nm with 10 W average power at 50 Hz, a two-mirror scanner, a 40 cm receiving telescope, and a highly efficient polychromator with cascading interference filters for separating four signals: the elastic backscatter signal, two rotational Raman signals with different temperature dependence, and the vibrational Raman signal of water vapor. The main measurement variable of the UHOH RRL is temperature. For the HOPE campaign, the lidar receiver was optimized for high and low background levels, with a novel switch for the passband of the second rotational Raman channel. The instrument delivers atmospheric profiles of water vapor mixing ratio as well as particle backscatter coefficient and particle extinction coefficient as further products. As examples for the measurement performance, measurements of the temperature gradient and water vapor mixing ratio revealing the development of the atmospheric boundary layer within 25 h are presented. As expected from simulations, a reduction of the measurement uncertainty of 70% during nighttime was achieved with the new low-background setting. A two-mirror scanner allows for measurements in different directions. When pointing the scanner to low elevation, measurements close to the ground become possible which are otherwise impossible due to the non-total overlap of laser beam and receiving telescope field of view in the near range. An example of a low-level temperature measurement is presented which resolves the temperature gradient at the top of the stable nighttime boundary layer 100 m above the ground.
Highlights
In recent years, different techniques for measuring the atmospheric temperature profile with lidar have been developed, namely the rotational Raman technique, the integration technique, and the resonance fluorescence technique, as well as the high-spectralresolution lidar (HSRL) technique and differential absorption lidar (DIAL)
The lidar consists of a frequency-tripled Nd:YAG laser at 355 nm with 10 W average power at 50 Hz, a twomirror scanner, a 40 cm receiving telescope, and a highly efficient polychromator with cascading interference filters for separating four signals: the elastic backscatter signal, two rotational Raman signals with different temperature dependence, and the vibrational Raman signal of water vapor
The rotational Raman lidar (RRL) and the WV DIAL of University of Hohenheim (UHOH) were collocated with a Doppler lidar from Karlsruhe Institute of Technology (KIT) to acquire a complete data set of temperature, water vapor content, and vertical wind for the determination of fluxes of sensible and latent heat (e.g., Behrendt et al, 2011)
Summary
Different techniques for measuring the atmospheric temperature profile with lidar have been developed, namely the rotational Raman technique, the integration technique (using elastic and Raman signals), and the resonance fluorescence technique, as well as the high-spectralresolution lidar (HSRL) technique and differential absorption lidar (DIAL) (see Behrendt, 2005, for an overview). The RRL and the WV DIAL of UHOH were collocated with a Doppler lidar from KIT to acquire a complete data set of temperature, water vapor content, and vertical wind for the determination of fluxes of sensible and latent heat (e.g., Behrendt et al, 2011) It was the launch site for radiosoundings. This technique was applied to WV DIAL (e.g., Muppa et al, 2014) and Doppler lidar data (Lenschow et al, 2012), elastic backscatter lidar data (Pal et al, 2010), and water vapor Raman lidar data (Wulfmeyer et al, 2010; Turner et al, 2014a, b) It was applied for the first time to temperature lidar data by using measurements of the UHOH RRL during HOPE (Behrendt et al, 2014). The comparison between the errors derived with Poisson statistics and turbulence analysis confirms that the total statistical error is mainly due to photon shot noise
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