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.
Highlights
Atmospheric temperature and humidity in the low atmosphere are together essential to comprehend weather phenomena and their evolution in a changing climate
Such high values can be reached by increasing the laser power and pulse repetition frequency (PRF) or enlarging the integration over altitude and time, as signal-to-noise ratio (SNR) is usually magnified by the square roots of the energy and number of averaged samples
By simulating the variation in Q with the Weather and Aerosol Lidar (WALI) filter parameters (Sect. 3), we find a large impact of a wavelength drift λ: dQ/Q/dλ ≈ −0.26 pm−1 and T ≈ −0.34 ◦C pm−1 λ, meaning just 3 pm of drift in either filter or laser wavelengths can lead to biases above 1 ◦C
Summary
Atmospheric temperature and humidity in the low atmosphere are together essential to comprehend weather phenomena and their evolution in a changing climate. The VR channels have been replaced by a Newton reflector and a polychromator including RR channels for temperature profiling On this occasion, we have established that biases due to various sources, in particular from the dependency of spectral filtering on the angle of incidence, detector non-uniformities, and other non-common-path differences between Raman channels, may be several times greater than the requirements if left unchecked. We have established that biases due to various sources, in particular from the dependency of spectral filtering on the angle of incidence, detector non-uniformities, and other non-common-path differences between Raman channels, may be several times greater than the requirements if left unchecked Correctible as they are by measuring the ratios of overlap factors on the individual channels, these effects are not reported in the literature of lidar temperature measurements. Kand fare obtained by confronting lidar profiles of R and Q with collocated in situ measurements of rH2O and T (e.g., from a radiosounding), aiming for a wide range of values for a better constraint on the calibration
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