Calibration of Raman lidar water vapor profiles by means of AERONET photometer observations and GDAS meteorological data

We present a practical method to continuously calibrate Raman lidar observations of water vapor mixing ratio profiles. The water vapor profile measured with the multiwavelength polarization Raman lidar Polly XT is calibrated by means of co-located AErosol RObotic NETwork (AERONET) sun photometer obs...

Full description

Bibliographic Details
Published in:Atmospheric Measurement Techniques
Main Authors: G. Dai, D. Althausen, J. Hofer, R. Engelmann, P. Seifert, J. Bühl, R.-E. Mamouri, S. Wu, A. Ansmann
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2018
Subjects:
Online Access:https://doi.org/10.5194/amt-11-2735-2018
https://doaj.org/article/eb9d8bb8cc464fa1bdf72d31ba22f483
_version_ 1821574917106171904
author G. Dai
D. Althausen
J. Hofer
R. Engelmann
P. Seifert
J. Bühl
R.-E. Mamouri
S. Wu
A. Ansmann
author_facet G. Dai
D. Althausen
J. Hofer
R. Engelmann
P. Seifert
J. Bühl
R.-E. Mamouri
S. Wu
A. Ansmann
author_sort G. Dai
collection Directory of Open Access Journals: DOAJ Articles
container_issue 5
container_start_page 2735
container_title Atmospheric Measurement Techniques
container_volume 11
description We present a practical method to continuously calibrate Raman lidar observations of water vapor mixing ratio profiles. The water vapor profile measured with the multiwavelength polarization Raman lidar Polly XT is calibrated by means of co-located AErosol RObotic NETwork (AERONET) sun photometer observations and Global Data Assimilation System (GDAS) temperature and pressure profiles. This method is applied to lidar observations conducted during the Cyprus Cloud Aerosol and Rain Experiment (CyCARE) in Limassol, Cyprus. We use the GDAS temperature and pressure profiles to retrieve the water vapor density. In the next step, the precipitable water vapor from the lidar observations is used for the calibration of the lidar measurements with the sun photometer measurements. The retrieved calibrated water vapor mixing ratio from the lidar measurements has a relative uncertainty of 11 % in which the error is mainly caused by the error of the sun photometer measurements. During CyCARE, nine measurement cases with cloud-free and stable meteorological conditions are selected to calculate the precipitable water vapor from the lidar and the sun photometer observations. The ratio of these two precipitable water vapor values yields the water vapor calibration constant. The calibration constant for the Polly XT Raman lidar is 6.56 g kg −1 ± 0.72 g kg −1 (with a statistical uncertainty of 0.08 g kg −1 and an instrumental uncertainty of 0.72 g kg −1 ). To check the quality of the water vapor calibration, the water vapor mixing ratio profiles from the simultaneous nighttime observations with Raman lidar and Vaisala radiosonde sounding are compared. The correlation of the water vapor mixing ratios from these two instruments is determined by using all of the 19 simultaneous nighttime measurements during CyCARE. Excellent agreement with the slope of 1.01 and the R 2 of 0.99 is found. One example is presented to demonstrate the full potential of a well-calibrated Raman lidar. The relative humidity profiles from lidar, GDAS ...
format Article in Journal/Newspaper
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
id ftdoajarticles:oai:doaj.org/article:eb9d8bb8cc464fa1bdf72d31ba22f483
institution Open Polar
language English
op_collection_id ftdoajarticles
op_container_end_page 2748
op_doi https://doi.org/10.5194/amt-11-2735-2018
op_relation https://www.atmos-meas-tech.net/11/2735/2018/amt-11-2735-2018.pdf
https://doaj.org/toc/1867-1381
https://doaj.org/toc/1867-8548
doi:10.5194/amt-11-2735-2018
1867-1381
1867-8548
https://doaj.org/article/eb9d8bb8cc464fa1bdf72d31ba22f483
op_source Atmospheric Measurement Techniques, Vol 11, Pp 2735-2748 (2018)
publishDate 2018
publisher Copernicus Publications
record_format openpolar
spelling ftdoajarticles:oai:doaj.org/article:eb9d8bb8cc464fa1bdf72d31ba22f483 2025-01-16T18:38:48+00:00 Calibration of Raman lidar water vapor profiles by means of AERONET photometer observations and GDAS meteorological data G. Dai D. Althausen J. Hofer R. Engelmann P. Seifert J. Bühl R.-E. Mamouri S. Wu A. Ansmann 2018-05-01T00:00:00Z https://doi.org/10.5194/amt-11-2735-2018 https://doaj.org/article/eb9d8bb8cc464fa1bdf72d31ba22f483 EN eng Copernicus Publications https://www.atmos-meas-tech.net/11/2735/2018/amt-11-2735-2018.pdf https://doaj.org/toc/1867-1381 https://doaj.org/toc/1867-8548 doi:10.5194/amt-11-2735-2018 1867-1381 1867-8548 https://doaj.org/article/eb9d8bb8cc464fa1bdf72d31ba22f483 Atmospheric Measurement Techniques, Vol 11, Pp 2735-2748 (2018) Environmental engineering TA170-171 Earthwork. Foundations TA715-787 article 2018 ftdoajarticles https://doi.org/10.5194/amt-11-2735-2018 2022-12-31T14:10:54Z We present a practical method to continuously calibrate Raman lidar observations of water vapor mixing ratio profiles. The water vapor profile measured with the multiwavelength polarization Raman lidar Polly XT is calibrated by means of co-located AErosol RObotic NETwork (AERONET) sun photometer observations and Global Data Assimilation System (GDAS) temperature and pressure profiles. This method is applied to lidar observations conducted during the Cyprus Cloud Aerosol and Rain Experiment (CyCARE) in Limassol, Cyprus. We use the GDAS temperature and pressure profiles to retrieve the water vapor density. In the next step, the precipitable water vapor from the lidar observations is used for the calibration of the lidar measurements with the sun photometer measurements. The retrieved calibrated water vapor mixing ratio from the lidar measurements has a relative uncertainty of 11 % in which the error is mainly caused by the error of the sun photometer measurements. During CyCARE, nine measurement cases with cloud-free and stable meteorological conditions are selected to calculate the precipitable water vapor from the lidar and the sun photometer observations. The ratio of these two precipitable water vapor values yields the water vapor calibration constant. The calibration constant for the Polly XT Raman lidar is 6.56 g kg −1 ± 0.72 g kg −1 (with a statistical uncertainty of 0.08 g kg −1 and an instrumental uncertainty of 0.72 g kg −1 ). To check the quality of the water vapor calibration, the water vapor mixing ratio profiles from the simultaneous nighttime observations with Raman lidar and Vaisala radiosonde sounding are compared. The correlation of the water vapor mixing ratios from these two instruments is determined by using all of the 19 simultaneous nighttime measurements during CyCARE. Excellent agreement with the slope of 1.01 and the R 2 of 0.99 is found. One example is presented to demonstrate the full potential of a well-calibrated Raman lidar. The relative humidity profiles from lidar, GDAS ... Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Atmospheric Measurement Techniques 11 5 2735 2748
spellingShingle Environmental engineering
TA170-171
Earthwork. Foundations
TA715-787
G. Dai
D. Althausen
J. Hofer
R. Engelmann
P. Seifert
J. Bühl
R.-E. Mamouri
S. Wu
A. Ansmann
Calibration of Raman lidar water vapor profiles by means of AERONET photometer observations and GDAS meteorological data
title Calibration of Raman lidar water vapor profiles by means of AERONET photometer observations and GDAS meteorological data
title_full Calibration of Raman lidar water vapor profiles by means of AERONET photometer observations and GDAS meteorological data
title_fullStr Calibration of Raman lidar water vapor profiles by means of AERONET photometer observations and GDAS meteorological data
title_full_unstemmed Calibration of Raman lidar water vapor profiles by means of AERONET photometer observations and GDAS meteorological data
title_short Calibration of Raman lidar water vapor profiles by means of AERONET photometer observations and GDAS meteorological data
title_sort calibration of raman lidar water vapor profiles by means of aeronet photometer observations and gdas meteorological data
topic Environmental engineering
TA170-171
Earthwork. Foundations
TA715-787
topic_facet Environmental engineering
TA170-171
Earthwork. Foundations
TA715-787
url https://doi.org/10.5194/amt-11-2735-2018
https://doaj.org/article/eb9d8bb8cc464fa1bdf72d31ba22f483