Mitigation of bias sources for atmospheric temperature and humidity in the mobile Raman Weather and Aerosol Lidar (WALI)

<p>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 simult...

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Autores principales:	J. Totems, P. Chazette, A. Baron
Formato:	article
Lenguaje:	EN
Publicado:	Copernicus Publications 2021
Materias:	Environmental engineering TA170-171 Earthwork. Foundations TA715-787
Acceso en línea:	https://doaj.org/article/c0e9142d01744f44b5dd465ccc6f0aac
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spelling	oai:doaj.org-article:c0e9142d01744f44b5dd465ccc6f0aac2021-12-03T15:55:08ZMitigation of bias sources for atmospheric temperature and humidity in the mobile Raman Weather and Aerosol Lidar (WALI)10.5194/amt-14-7525-20211867-13811867-8548https://doaj.org/article/c0e9142d01744f44b5dd465ccc6f0aac2021-12-01T00:00:00Zhttps://amt.copernicus.org/articles/14/7525/2021/amt-14-7525-2021.pdfhttps://doaj.org/toc/1867-1381https://doaj.org/toc/1867-8548<p>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 <span class="inline-formula"><sup>∘</sup>C</span> defined by the WMO (up to 6 <span class="inline-formula"><sup>∘</sup>C</span> bias below 300 <span class="inline-formula">m</span> 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 <span class="inline-formula">g kg<sup>−1</sup></span> on water vapor and 1 <span class="inline-formula"><sup>∘</sup>C</span> 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.</p>J. TotemsP. ChazetteA. BaronCopernicus PublicationsarticleEnvironmental engineeringTA170-171Earthwork. FoundationsTA715-787ENAtmospheric Measurement Techniques, Vol 14, Pp 7525-7544 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Environmental engineering TA170-171 Earthwork. Foundations TA715-787
spellingShingle	Environmental engineering TA170-171 Earthwork. Foundations TA715-787 J. Totems P. Chazette A. Baron Mitigation of bias sources for atmospheric temperature and humidity in the mobile Raman Weather and Aerosol Lidar (WALI)
description	<p>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 <span class="inline-formula"><sup>∘</sup>C</span> defined by the WMO (up to 6 <span class="inline-formula"><sup>∘</sup>C</span> bias below 300 <span class="inline-formula">m</span> 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 <span class="inline-formula">g kg<sup>−1</sup></span> on water vapor and 1 <span class="inline-formula"><sup>∘</sup>C</span> 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.</p>
format	article
author	J. Totems P. Chazette A. Baron
author_facet	J. Totems P. Chazette A. Baron
author_sort	J. Totems
title	Mitigation of bias sources for atmospheric temperature and humidity in the mobile Raman Weather and Aerosol Lidar (WALI)
title_short	Mitigation of bias sources for atmospheric temperature and humidity in the mobile Raman Weather and Aerosol Lidar (WALI)
title_full	Mitigation of bias sources for atmospheric temperature and humidity in the mobile Raman Weather and Aerosol Lidar (WALI)
title_fullStr	Mitigation of bias sources for atmospheric temperature and humidity in the mobile Raman Weather and Aerosol Lidar (WALI)
title_full_unstemmed	Mitigation of bias sources for atmospheric temperature and humidity in the mobile Raman Weather and Aerosol Lidar (WALI)
title_sort	mitigation of bias sources for atmospheric temperature and humidity in the mobile raman weather and aerosol lidar (wali)
publisher	Copernicus Publications
publishDate	2021
url	https://doaj.org/article/c0e9142d01744f44b5dd465ccc6f0aac
work_keys_str_mv	AT jtotems mitigationofbiassourcesforatmospherictemperatureandhumidityinthemobileramanweatherandaerosollidarwali AT pchazette mitigationofbiassourcesforatmospherictemperatureandhumidityinthemobileramanweatherandaerosollidarwali AT abaron mitigationofbiassourcesforatmospherictemperatureandhumidityinthemobileramanweatherandaerosollidarwali
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Mitigation of bias sources for atmospheric temperature and humidity in the mobile Raman Weather and Aerosol Lidar (WALI)

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