Abstract
Abstract. Lidars using vibrational and rotational Raman scattering to continuously
monitor both the water vapor and temperature profiles in the low and middle
troposphere offer enticing perspectives for applications in weather prediction
and studies of aerosol–cloud–water vapor interactions by simultaneously deriving
relative humidity and atmospheric optical properties. Several
heavy systems exist in European laboratories, but only recently have they been
downsized and ruggedized for deployment in the field. In this paper, we
describe in detail the technical choices made during the design and
calibration of the new Raman channels for the mobile Weather and Aerosol Lidar
(WALI), going over the important sources of bias and uncertainty on the water
vapor and temperature profiles stemming from the different optical elements
of the instrument. For the first time, the impacts of interference filters and
non-common-path differences between Raman channels, and their mitigation, in particular are
investigated, using horizontal shots in a homogeneous
atmosphere. For temperature, the magnitude of the highlighted biases can be
much larger than the targeted absolute accuracy of 1 ∘C
defined by the WMO (up to 6 ∘C bias below 300 m
range). Measurement errors are quantified using simulations and a number of
radiosoundings launched close to the laboratory. After de-biasing, the
remaining mean differences are below 0.1 g kg−1 on water vapor and
1 ∘C on temperature, and rms differences are consistent with
the expected error from lidar noise, calibration uncertainty, and horizontal
inhomogeneities of the atmosphere between the lidar and radiosondes.
Reference42 articles.
1. Adam, S., Behrendt, A., Schwitalla, T., Hammann, E., and Wulfmeyer, V.: First assimilation of temperature lidar data into an NWP model: impact on the simulation of the temperature field, inversion strength and PBL depth, Q. J. Roy. Meteor. Soc., 142, 2882–2896, https://doi.org/10.1002/qj.2875, 2016.
2. Behrendt, A.: Temperature Measurements with Lidar, in: Lidar: Range-Resolved Optical Remote Sensing of the Atmosphere, vol. 102, edited by: Weitkamp, C., Springer-Verlag, New York, 273–306, 2005.
3. Behrendt, A. and Reichardt, J.: Atmospheric temperature profiling in the presence of clouds with a pure rotational Raman lidar by use of an interference-filter-based polychromator, Appl. Optics, 39, 1372, https://doi.org/10.1364/AO.39.001372, 2000.
4. Behrendt, A., Wulfmeyer, V., Hammann, E., Muppa, S. K., and Pal, S.: Profiles of second- to fourth-order moments of turbulent temperature fluctuations in the convective boundary layer: first measurements with rotational Raman lidar, Atmos. Chem. Phys., 15, 5485–5500, https://doi.org/10.5194/acp-15-5485-2015, 2015.
5. Buck, A. L.: New Equations for Computing Vapor Pressure and Enhancement
Factor, J. Appl. Meteorol., 20, 1527–1532,
https://doi.org/10.1175/1520-0450(1981)020<1527:NEFCVP>2.0.CO;2, 1981.
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