Water vapour mixing ratio and ozone measurements by a solar blind Raman lidar

2002 ◽  
Author(s):  
F. de Tomasi ◽  
G. Torsello ◽  
M.R. Perrone
Keyword(s):  
Water Vapour ◽  
Mixing Ratio ◽  
Raman Lidar ◽  
Solar Blind

scholarly journals Tropospheric water vapour and relative humidity profiles from lidar and microwave radiometry

2014 ◽  
Vol 7 (5) ◽  
pp. 1201-1211 ◽  
Author(s):  
F. Navas-Guzmán ◽  
J. Fernández-Gálvez ◽  
M. J. Granados-Muñoz ◽  
J. L. Guerrero-Rascado ◽  
J. A. Bravo-Aranda ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Water Vapour ◽  
Microwave Radiometer ◽  
Radiosonde Data ◽  
Mixing Ratio ◽  
Raman Lidar ◽  
Night Time ◽  
New Approach ◽  
Lidar Measurements ◽  
Humidity Profiles

Abstract. In this paper, we outline an iterative method to calibrate the water vapour mixing ratio profiles retrieved from Raman lidar measurements. Simultaneous and co-located radiosonde data are used for this purpose and the calibration results obtained during a radiosonde campaign in summer and autumn 2011 are presented. The water vapour profiles measured during night-time by the Raman lidar and radiosondes are compared and the differences between the methodologies are discussed. Then, a new approach to obtain relative humidity profiles by combination of simultaneous profiles of temperature (retrieved from a microwave radiometer) and water vapour mixing ratio (from a Raman lidar) is addressed. In the last part of this work, a statistical analysis of water vapour mixing ratio and relative humidity profiles obtained during 1 year of simultaneous measurements is presented.

Combined use of Raman lidar and DIAL measurements and MESO-NH model simulations for the characterization of complex water vapour field structures and their genesis: a case study from HyMeX-SOP 1

2020 ◽  
Author(s):  
Paolo Di Girolamo ◽  
Marie-Noelle Bouin ◽  
Cyrille Flamant ◽  
Donato Summa ◽  
Benedetto De Rosa
Keyword(s):  
Water Vapour ◽  
Heavy Precipitation ◽  
Time Interval ◽  
Mixing Ratio ◽  
Raman Lidar ◽  
Model Simulations ◽  
Combined Use ◽  
Geographical Regions ◽  
Lidar Measurements ◽  
Precipitation Events

<p>As part of the Cevennes-Vivarais site, the University of Basilicata Raman lidar system BASIL was deployed in Candillargues and operated throughout the duration of HyMeX-SOP 1 (September-November 2012), providing high-resolution and accurate measurements, both in daytime and night-time, of atmospheric temperature, water vapour mixing ratio and particle backscattering and extinction coefficient at three wavelengths.</p><p>Measurements carried out by BASIL on 28 September 2012 reveal a water vapour field characterized by a quite complex vertical structure. Reported measurements were run in the time interval between two consecutive heavy precipitation events, from 15:30 UTC on 28 September to 03:30 UTC on 29 September 2012. Throughout most of this observation period, lidar measurements reveal the presence of four distinct humidity layers.</p><p>The present research effort aims at assessing the origin and transport path of the different humidity filaments observed by BASIL on this day. The analysis approach relies on the comparison between Raman lidar measurements and MESO-NH and NOAA-HYSPLIT model simulations. Back-trajectory analyses from MESO-NH reveal that air masses ending in Candillargues at different altitudes levels are coming and are originated from different geographical regions.</p><p>The four distinct humidity layers observed by BASIL are also identified in the water vapour mixing ratio profiles collected by the air-borne DIAL LEANDRE 2 on-board of the French research aircraft ATR42. The exact correspondence, in terms of back-trajectories computation and water budget, between the humidity layers observed by BASIL and those identified in LEANDRE2 measurements has been verified based on a dedicated simulation effort.</p><p>In the paper we also try to identify the presence of dry layers and cold pools and assess their role in the genesis of the mesoscale convective systems and the heavy precipitation events observed on 29 September 2012 based on the combined use of water vapour mixing ratio and temperature profile measurements from BASIL and water vapour mixing ratio profile measurements from LEANDRE 2, again supported by MESO-NH simulations.</p>

Water vapour mixing ratio distribution in the area of Naples by Raman lidar measurements and a high resolution model

2007 ◽  
Author(s):  
Maria G. Frontoso ◽  
Rossella Ferretti ◽  
Gianluca Pisani ◽  
Xuan Wang ◽  
Nicola Spinelli
Keyword(s):  
High Resolution ◽  
Water Vapour ◽  
Mixing Ratio ◽  
Raman Lidar ◽  
Ratio Distribution ◽  
Lidar Measurements ◽  
Resolution Model ◽  
High Resolution Model

scholarly journals Tropospheric water vapour and relative humidity profiles from lidar and microwave radiometry

2013 ◽  
Vol 6 (6) ◽  
pp. 10481-10510
Author(s):  
F. Navas-Guzmán ◽  
J. Fernández-Gálvez ◽  
M. J. Granados-Muñoz ◽  
J. L. Guerrero-Rascado ◽  
J. A. Bravo-Aranda ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Water Vapour ◽  
Microwave Radiometer ◽  
Radiosonde Data ◽  
Mixing Ratio ◽  
Raman Lidar ◽  
New Approach ◽  
Lidar Measurements ◽  
One Year ◽  
Humidity Profiles

Abstract. In this paper, we outline an iterative method to calibrate the water vapour mixing ratio profiles retrieved from Raman lidar measurements. Simultaneous and co-located radiosonde data are used for this purpose and the calibration results obtained during a radiosonde campaign performed in Summer and Autumn 2011 are presented. The water vapour profiles measured during nighttime by the Raman lidar and radiosondes are compared and the differences between the methodologies are discussed. Moreover, a new approach to obtain relative humidity profiles by combination of simultaneous profiles of temperature (retrieved from a microwave radiometer) and water vapour mixing ratio (from a Raman lidar) is addressed. In the last part of this work, a statistical analysis of water vapour mixing ratio and relative humidity profiles obtained during one year of simultaneous measurements is presented.

End-to-end Simulator of a space-borne Raman Lidar for the thermodynamic profiling of the atmosphere

2021 ◽  
Author(s):  
Noemi Franco ◽  
Paolo Di Girolamo ◽  
Donato Summa ◽  
Benedetto De Rosa ◽  
Andreas Behrendt ◽  
...  
Keyword(s):  
Numerical Model ◽  
Water Vapour ◽  
Vertical Profile ◽  
Molecular Nitrogen ◽  
Reference Signal ◽  
Temperature Measurements ◽  
Mixing Ratio ◽  
Raman Lidar ◽  
Atmospheric Water ◽  
Atmospheric Water Vapour

<p>An end-to-end model has been developed in order to simulate the expected performance of a space-borne Raman Lidar, with a specific focus on the Atmospheric Thermodynamics LidAr in Space – ATLAS proposed as a “mission concept” to the ESA in the frame of the “Earth Explorer-11 Mission Ideas” Call. The numerical model includes a forward module, which simulates the lidar signals with their statistical uncertainty, and a retrieval module able to provide vertical profiles of atmospheric water vapour mixing ratio and temperature based on the analyses of the simulated signals. Specifically, the forward module simulates the interaction mechanisms of laser radiation with the atmospheric constituents and the behavior of all the devices present in the experimental system(telescope, optical reflecting and transmitting components, avalanche photodiodes, ACCDs). An analytical expression of the lidar equation for the water vapour and molecular nitrogen roto-vibrational Raman signals and the pure rotational Raman signals from molecular oxygen and nitrogen is used. The analytically computed signals are perturbed by simulating their shot-noise through Poisson statistics. Perturbed signals thus take into account the fluctuations in the number of photons reaching the detector over a certain time interval. The simulator also provides an estimation of the background due to the solar contribution. Daylight background includes three distinct terms: a cloud-free atmospheric contribution, a surface contribution and a cloud contribution[1]. Background is calculated as a function of the solar zenith angle. In order to better estimatethe background contribution, an integration on slant path is performed instead of a classical parallel-planes approximation. The proposed numerical model allows to better simulate solar background for high solar zenith angles, even higher than 90 degrees. Signals simulated through the forward model are then fed into the retrieval module. A background subtraction scheme is used to remove the solar contribution and a vertical averaging is performed to smooth the signals. Based on the application of the roto-vibrational Raman lidar technique, the vertical profile of atmospheric water vapour mixing ratio is obtained from the power ratio of the water vapour to a reference signal, such as molecular nitrogen roto-vibrational Raman signal or an alternative temperature-independent reference signal. A vertical profile of temperature is then obtained through the ratio of high-to-low quantum number rotational Raman signals by the application of the pure rotational Raman lidar technique. Both atmospheric water vapour mixing ratio and temperature measurements require the determination of calibration constants, which can be obtained from the comparison with simultaneous and co-located measurements from a different sensor [2]. The simulator finally provides statistical (RMS) and systematic (bias) uncertainties. Estimates are provided in terms of percentage and absolute (g/kg) uncertainty for water vapour mixing ratio measurements and in terms of absolute uncertainty (K) for temperature measurements.</p><p><strong> </strong><strong>References</strong></p><p>1 - P.Di Girolamo et al., "Spaceborne profiling of atmospheric temperature and particle extinction with pure rotational Raman lidar and of relative humidity in combination with differential absorption lidar: performance simulations"Appl.Opt. 45, 2474-2494(2006)</p><p>2 - P.Di Girolamo et al., "Space-borne profiling of atmospheric thermodynamic variables with Raman lidar: performance simulations,"Opt.Express 26, 8125-8161(2018)</p>

scholarly journals Characterization of atmospheric thermodynamic variables by Raman lidar in the frame of the International Network for the Detection of Atmospheric Composition Change - NDACC

2018 ◽  
Vol 176 ◽  
pp. 04010
Author(s):  
Benedetto De Rosa ◽  
Paolo Di Girolamo ◽  
Donato Summa
Keyword(s):  
Water Vapour ◽  
Atmospheric Temperature ◽  
Atmospheric Composition ◽  
Vertical Profiles ◽  
Mixing Ratio ◽  
Composition Change ◽  
Raman Lidar ◽  
Lidar System ◽  
Thermodynamic Variables

In November 2012 the Raman Lidar system BASIL, located at the Univ. of Basilicata (Potenza), was approved to enter in NDACC, with the goal of providing accurate routine measurements of the vertical profiles of atmospheric temperature and water vapour mixing ratio. In this presentation we illustrate and discuss water vapour mixing ratio and temperature measurements carried out during these four years and their comparisons with the radiosondes launched from nearby Institute IMAA-CNR (7 km away).

Combined use of Raman Lidar and DIAL measurements and MESO-NH model simulations for the characterization of complex water vapour field structures, their genesis and their role in the activation of Mesoscale Convective Systems

2021 ◽  
Author(s):  
Paolo Di Girolamo ◽  
Marie-Noelle Bouin ◽  
Cyrille Flamant ◽  
Donato Summa ◽  
Benedetto De Rosa ◽  
...  
Keyword(s):  
Water Vapour ◽  
Heavy Precipitation ◽  
Mesoscale Convective Systems ◽  
Mixing Ratio ◽  
Raman Lidar ◽  
Convective Systems ◽  
Combined Use ◽  
Lidar Measurements ◽  
Mesoscale Convective ◽  
Precipitation Events

<p>As part of the Cevennes-Vivarais site, the University of Basilicata Raman lidar system BASIL (Di Girolamo et al., 2009, 2012, 2916) was deployed in Candillargues (Cévennes-Vivarais Southern France Lat: 43°37′ N; Long: 04°04′ E; Elev: 1 m) and operated throughout the duration of HyMeX-SOP 1 (September-November 2012), providing high-resolution and accurate measurements, both in daytime and night-time, of atmospheric temperature, water vapour mixing ratio and particle backscattering and extinction coefficient at three wavelengths.</p><p>Measurements carried out by BASIL on 28 September 2012 reveal a water vapour field characterized by a quite complex vertical structure. Reported measurements were run in the time interval between two consecutive heavy precipitation events, from 15:30 UTC on 28 September to 03:30 UTC on 29 September 2012. Throughout most of this observation period, lidar measurements reveal the presence of four distinct humidity layers.</p><p>The present research effort aims at assessing the origin and transport path of the different humidity filaments observed by BASIL on this day. The analysis approach relies on the comparison between Raman lidar measurements and MESO-NH and NOAA-HYSPLIT model simulations. Back-trajectory analyses from MESO-NH reveal that air masses ending in Candillargues at different altitudes levels are coming and are originated from different geographical regions.</p><p>The four distinct humidity layers observed by BASIL are also identified in the water vapour mixing ratio profiles collected by the air-borne DIAL LEANDRE 2 on-board of the French research aircraft ATR42. The exact correspondence, in terms of back-trajectories computation and water budget, between the humidity layers observed by BASIL and those identified in LEANDRE2 measurements has been verified based on a dedicated simulation effort.</p><p>In this research work we also try to identify the presence of dry layers and cold pools and assess their role in the genesis of the mesoscale convective systems and the heavy precipitation events observed on 29 September 2012 based on the combined use of water vapour mixing ratio and temperature profile measurements from BASIL and water vapour mixing ratio profile measurements from LEANDRE 2, again supported by MESO-NH simulations.</p>

scholarly journals Temperature and water vapour measurements in the framework of the Network for the Detection of Atmospheric Composition Change (NDACC)

2020 ◽  
Vol 13 (2) ◽  
pp. 405-427 ◽  
Author(s):  
Benedetto De Rosa ◽  
Paolo Di Girolamo ◽  
Donato Summa
Keyword(s):  
Temperature Profile ◽  
Water Vapour ◽  
Research Effort ◽  
Atmospheric Composition ◽  
Integration Time ◽  
Mixing Ratio ◽  
Composition Change ◽  
Raman Lidar ◽  
Model Data ◽  
Sensor Model

Abstract. The BASIL Raman lidar system entered the International Network for the Detection of Atmospheric Composition Change (NDACC) in 2012. Since then, measurements have been carried out routinely on a weekly basis. This paper reports specific measurement results from this effort, with a dedicated focus on temperature and water vapour profile measurements. The main objective of this research effort is to provide a characterisation of the system performance. The results illustrated in this publication demonstrate the ability of BASIL to perform measurements of the temperature profile up to 50 km and of the water vapour mixing ratio profile up to 15 km, when considering an integration time of 2 h and a vertical resolution of 150–600 m; the mean measurement accuracy, determined based on comparisons with simultaneous and co-located radiosondes, is 0.1 K (for the temperature profile) and 0.1 g kg−1 (for the water vapour mixing ratio profile) up to the upper troposphere. The relative humidity profiling capability up to the tropopause is also demonstrated by combining simultaneous temperature and water vapour profile measurements. Raman lidar measurements are compared with measurements from additional instruments, such as radiosondes and satellite sensors (IASI and AIRS), as well as with model reanalyses data (ECMWF and ECMWF-ERA). We focused our attention on six case studies collected during the first 2 years of system operation (November 2013–October 2015). Comparisons between BASIL and the different sensor/model data in terms of the water vapour mixing ratio indicate biases in the altitudinal interval between 2 and 15 km that are always within ±1 g kg−1 (or ±50 %), with minimum values being observed in the comparison between BASIL and radiosonde measurements (±20 % up to 15 km). Results also indicate a vertically averaged mean mutual bias of −0.026 g kg−1 (or −3.8 %), 0.263 g kg−1 (or 30.0 %), 0.361 g kg−1 (or 23.5 %), −0.297 g kg−1 (or −25 %) and −0.296 g kg−1 (or −29.6 %) when comparing BASIL with radiosondes, IASI, AIRS, ECMWF and ECMWF-ERA respectively. The vertically averaged mean absolute mutual biases are somewhat higher, i.e. 0.05 g kg−1(or 16.7 %), 0.39 g kg−1 (or 23.0 %), 0.57 g kg−1 (or 23.5 %), 0.32 g kg−1 (or 29.6 %) and 0.52 g kg−1 (or 53.3 %), when comparing BASIL with radiosondes, IASI, AIRS, ECMWF and ECMWF-ERA respectively. The comparisons in terms of temperature measurements indicate mutual biases in the altitudinal interval between 3 and 30 km that are always within ±3 K, with minimum values being observed in the comparison between BASIL and radiosonde measurements (±2 K within this same altitudinal interval). Results also reveal mutual biases within ±3 K up to 50 km for most sensor/model pairs. Furthermore, a vertically averaged mean mutual bias of −0.03, 0.21, 1.95, 0.14 and 0.43 K is found between BASIL and the radiosondes, IASI, AIRS, ECMWF and ECMWF-ERA respectively. The vertically averaged absolute mean mutual biases between BASIL and the radiosondes, IASI, AIRS, ECMWF and ECMWF-ERA are 1.28, 1.30, 3.50, 1.76 and 1.63 K respectively. Based on the available dataset and benefiting from the fact that the BASIL Raman lidar could be compared with all other sensor/model data, it was possible to estimate the overall bias of all sensors/datasets: −0.04 g kg−1 ∕ 0.19 K, 0.20 g kg−1 ∕ 0.22 K, −0.31 g kg−1 ∕ −0.02 K, −0.40 g kg−1 ∕ −1.76 K, 0.25 g kg−1 ∕ 0.04 K and 0.25 g kg−1 ∕ −0.24 K for the water vapour mixing ratio/temperature profile measurements carried out by BASIL, the radiosondes, IASI, AIRS, ECMWF and ECMWF-ERA respectively.

scholarly journals Temperature and water vapour measurements in the framework of NDACC

2019 ◽  
Author(s):  
Benedetto De Rosa ◽  
Paolo Di Girolamo ◽  
Donato Summa
Keyword(s):  
Temperature Profile ◽  
Water Vapour ◽  
Research Effort ◽  
Atmospheric Composition ◽  
Integration Time ◽  
Mixing Ratio ◽  
Raman Lidar ◽  
Model Data ◽  
Sensor Model ◽  
Absolute Bias

Abstract. The Raman Lidar system BASIL entered the International Network for the Detection of Atmospheric Composition Change (NDACC) in 2012. Since then measurements were carried out routinely on a weekly basis. This manuscript reports specific measurement results from this effort, with a dedicated focus on temperature and water vapour profile measurements. The main objective of this research effort is to provide a characterization of the system performance. Measurements illustrated in this manuscript demonstrate the ability of BASIL to perform measurements of the temperature profile up to 50 km and of the water vapour mixing ratio profile up to 15 km, when considering an integration time of 2 h and a vertical resolution of 150 m, with measurement bias not exceeding 0.1 K and 0.1 g kg−1, respectively. Relative humidity profiling capability up to the tropopause is also demonstrated by combining simultaneous temperature and water vapour profile measurements. Raman lidar measurements are compared with measurements from additional instruments, such as radiosondings and satellite sensors (IASI and AIRS), and with model re-analyses data (ECMWF and ECMWF-ERA). Comparisons in this paper cover the altitude region up to 15 km for water vapour mixing ratio and up to 50 km for the temperature. We focused our attention on four selected case studies collected during the first 2 years of operation of the system (November 2013–October 2015). Comparisons between BASIL and the different sensor/model data in terms of water vapour mixing ratio indicate a mean absolute/relative bias of −0.024 g kg−1 (or −3.9 %), 0.346 g kg−1 (or 37.5 %), 0.342 g kg−1 (or 36.8 %), −0.297 g kg−1 (or −25 %), −0.381 g kg−1 (or −31 %), when compared with radisondings, IASI, AIRS, ECMWF, ECMWF-ERA, respectively. For what concerns the comparisons in terms of temperature measurements, these reveal a mean absolute bias between BASIL and the radisondings, IASI, AIRS, ECMWF, ECMWF-ERA of −0.04, 0.48, 1.99, 0.14, 0.62 K, respectively. Based on the available dataset and benefiting from the circumstance that the Raman lidar BASIL could be compared with all other sensor/model data, it was possible to estimate the absolute bias of all sensors/datasets, this being 0.004 g kg−1/0.30 K, 0.021 g kg−1/−0.34 K, −0.35 g kg−1/0.18 K, −0.346 g kg−1/−1.63 K, 0.293 g kg−1/−0.16 K and 0.377 g kg−1/0.32 K for the water vapour mixing ratio/temperature profile measurements carried out by BASIL, the radisondings, IASI, AIRS, ECMWF, ECMWF-ERA, respectively.

scholarly journals A Calibration of the MeteoSwiss RAman Lidar for Meteorological Observations (RALMO)Water Vapour Mixing Ratio Measurements using a Radiosonde Trajectory Method

2018 ◽  
Vol 176 ◽  
pp. 08015
Author(s):  
Shannon Hicks-Jalali ◽  
R.J. Sica ◽  
Alexander Haefele ◽  
Giovanni Martucci
Keyword(s):  
Water Vapour ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Lidar Data ◽  
Data Sets ◽  
Mixing Ratio ◽  
Raman Lidar ◽  
Trajectory Method ◽  
Meteorological Observations ◽  
Improved Technique

With only 50% downtime from 2007-2016, the RALMO lidar in Payerne, Switzerland, has one of the largest continuous lidar data sets available. These measurements will be used to produce an extensive lidar water vapour climatology using the Optimal Estimation Method introduced by Sica and Haefele (2016). We will compare our improved technique for external calibration using radiosonde trajectories with the standard external methods, and present the evolution of the lidar constant from 2007 to 2016.

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