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

Abstract. 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 R2 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 (simulation) and radiosonde are compared, too. It is found that the combination of water vapor mixing ratio and GDAS temperature profiles allow us to derive relative humidity profiles with the relative uncertainty of 10–20 %.

[2]  S. H. Melfi,et al.  OBSERVATION OF RAMAN SCATTERING BY WATER VAPOR IN THE ATMOSPHERE , 1969 .

[3]  T. D. Walsh,et al.  Ground-based water vapor Raman lidar measurements up to the upper troposphere and lower stratosphere - Part 1: Instrument development, optimization, and validation , 2011 .

[4]  A. Bucholtz,et al.  Rayleigh-scattering calculations for the terrestrial atmosphere. , 1995, Applied optics.

[5]  O. Bock,et al.  Study and mitigation of calibration factor instabilities in a water vapor Raman lidar , 2017 .

[6]  V. E. Derr,et al.  Atmospheric water vapor measurement by Raman Lidar , 1971 .

[7]  A. Tompkins.  A Prognostic Parameterization for the Subgrid-Scale Variability of Water Vapor and Clouds in Large-Scale Models and Its Use to Diagnose Cloud Cover , 2002 .

[8]  Albert Ansmann,et al.  Relative-humidity profiling in the troposphere with a Raman lidar. , 2002, Applied optics.

[9]  J. Cooney,et al.  Remote Measurements of Atmospheric Water Vapor Profiles Using the Raman Component of Laser Backscatter , 1970 .

[10]  Thierry Leblanc,et al.  Ground-based water vapor raman lidar measurements up to the upper troposphere and lower stratosphere for long-term monitoring , 2012 .

[11]  Eduardo Landulfo,et al.  Comments on "Accuracy of Raman lidar water vapor calibration and its applicability to long-term measurements". , 2011, Applied optics.

[12]  T. Eck,et al.  Sun photometric measurements of atmospheric water vapor column abundance in the 940‐nm band , 1997 .

[13]  A. Smirnov,et al.  AERONET-a federated instrument network and data archive for aerosol Characterization , 1998 .

[14]  Lisa Bengtsson,et al.  The HARMONIE-AROME Model Configuration in the ALADIN-HIRLAM NWP System , 2017 .

[15]  D. Whiteman,et al.  Lamp mapping technique for independent determination of the water vapor mixing ratio calibration factor for a Raman lidar system. , 2011, Applied optics.

[16]  David N Whiteman,et al.  Examination of the traditional Raman lidar technique. I. Evaluating the temperature-dependent lidar equations. , 2003, Applied optics.

[17]  Victoria E. Cachorro,et al.  Precipitable water vapor characterization in the Gulf of Cadiz region (southwestern Spain) based on Sun photometer, GPS, and radiosonde data , 2010 .

[18]  Alexander Smirnov,et al.  Evaluation of AERONET precipitable water vapor versus microwave radiometry, GPS, and radiosondes at ARM sites , 2014 .

[19]  P. Di Girolamo,et al.  Water vapour profiles from Raman lidar automatically calibrated by microwave radiometer data during HOPE , 2015 .

[20]  J. Streicher,et al.  Lidar: Range-Resolved Optical Remote Sensing of the Atmosphere , 2005 .

[21]  S. H. Melfi,et al.  Observations of water vapor by ground-based microwave radiometers and Raman lidar , 1994 .

[22]  Thierry Leblanc,et al.  Accuracy of Raman lidar water vapor calibration and its applicability to long-term measurements. , 2008, Applied optics.

[23]  Vincenzo Cuomo,et al.  CIAO: the CNR-IMAA advanced observatory for atmospheric research , 2010 .

[24]  S. Twomey,et al.  Aerosols, clouds and radiation , 1991 .

[25]  B. Soden,et al.  WATER VAPOR FEEDBACK AND GLOBAL WARMING 1 , 2003 .

[26]  Christina Kluge,et al.  Data Reduction And Error Analysis For The Physical Sciences , 2016 .

[27]  B. Damiri,et al.  Column water vapor determination in night period with a lunar photometer prototype , 2013 .

[28]  Albert Ansmann,et al.  The automated multiwavelength Raman polarization and water-vapor lidar PollyXT: The neXT generation , 2016 .

[29]  D. Brus,et al.  Profiling water vapor mixing ratios in Finland by means of a Raman lidar, a satellite and a model , 2017 .

[30]  P. Chazette,et al.  Calibration of a water vapour Raman lidar with a kite-based humidity sensor , 2016 .

[31]  Dian J. Seidel,et al.  Global radiosonde balloon drift statistics , 2011 .

[32]  Beat Schmid,et al.  Evaluation of daytime measurements of aerosols and water vapor made by an operational Raman lidar over the Southern Great Plains , 2006 .

[33]  Albert Ansmann,et al.  Saharan dust and heterogeneous ice formation: Eleven years of cloud observations at a central European EARLINET site , 2010 .

[34]  S. H. Melfi,et al.  Raman lidar system for the measurement of water vapor and aerosols in the Earth's atmosphere. , 1992, Applied optics.

[35]  Claire L. Parkinson,et al.  Aqua: an Earth-Observing Satellite mission to examine water and other climate variables , 2003, IEEE Trans. Geosci. Remote. Sens..

[36]  T. Eck,et al.  An emerging ground-based aerosol climatology: Aerosol optical depth from AERONET , 2001 .

[37]  Albert Ansmann,et al.  Portable Raman Lidar Polly XT for Automated Profiling of Aerosol Backscatter, Extinction, and Depolarization , 2009 .

[38]  Albert Ansmann,et al.  Ceilometer lidar comparison: backscatter coefficient retrieval and signal-to-noise ratio determination , 2010 .

[39]  Valentin Mitev,et al.  Humidity measurements in the free troposphere using Raman backscatter , 1988 .

[40]  V. Masson,et al.  The AROME-France Convective-Scale Operational Model , 2011 .

[41]  A. Ansmann,et al.  Combined raman elastic-backscatter LIDAR for vertical profiling of moisture, aerosol extinction, backscatter, and LIDAR ratio , 1992 .

[42]  Holger Vömel,et al.  Radiation Dry Bias of the Vaisala RS92 Humidity Sensor , 2007 .

[43]  J. Lenoble,et al.  Methodology for the independent calibration of Raman backscatter water-vapor lidar systems. , 1999, Applied optics.