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.

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.

scholarly journals Inter-Comparison of AIRS Temperature and Relative Humidity Profiles with AMMA and DACCIWA Radiosonde Observations over West Africa

2020 ◽  
Vol 12 (16) ◽  
pp. 2631
Author(s):  
Marian Amoakowaah Osei ◽  
Leonard Kofitse Amekudzi ◽  
Craig R. Ferguson ◽  
Sylvester Kojo Danuor
Keyword(s):  
Relative Humidity ◽  
West Africa ◽  
Water Vapour ◽  
Radiosonde Data ◽  
Weather Information ◽  
Significant Difference ◽  
High Impact Weather ◽  
Mean Square Difference ◽  
June July ◽  
Humidity Profiles

The vertical profiles of temperature and water vapour from the Atmospheric InfraRed Sounder (AIRS) have been validated across various regions of the globe as an effort to provide a substitute for radiosonde observations. However, there is a paucity of inter-comparisons over West Africa where local convective processes dominate and radiosonde observations (RAOBs) are limited. This study validates AIRS temperature and relative humidity profiles for selected radiosonde stations in West Africa. Radiosonde data were obtained from the AMMA and DACCIWA campaigns which spanned 2006–2008 and June–July 2016 respectively and offered a period of prolonged radiosonde observations in West Africa. AIRS performance was evaluated with the bias and root mean square difference (RMSD) at seven RAOB stations which were grouped into coastal and inland. Evaluation was performed on diurnal and seasonal timescales, cloud screening conditions and derived thunderstorm instability indices. At all timescales, the temperature RMSD was higher than the AIRS accuracy mission goal of ±1 K. Relative humidity RMSD was satisfactory with deviations <20% and <50% for both lower and upper troposphere respectively. AIRS retrieval of water vapour under cloudy and cloud-free conditions had no significant difference whereas cloud-free temperature was found to be more accurate. The seasonal evolution of some thunderstorm convective indices were also found to be comparable for AIRS and RAOB. The ability of AIRS to capture the evolution of these indices imply it will be a useful dataset for the African Science for Weather Information and Forecasting Techniques (SWIFT) high impact weather studies.

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

&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;

One year of water vapour Raman Lidar measurements at the Andalusian Centre for Environmental Studies (CEAMA)

2008 ◽  
Vol 29 (17-18) ◽  
pp. 5437-5453 ◽  
Author(s):  
J. L. Guerrero‐Rascado ◽  
B. Ruiz ◽  
G. Chourdakis ◽  
G. Georgoussis ◽  
L. Alados‐Arboledas
Keyword(s):  
Water Vapour ◽  
Environmental Studies ◽  
Raman Lidar ◽  
Lidar Measurements ◽  
One Year

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

&lt;p&gt;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 (C&amp;#233;vennes-Vivarais Southern France Lat: 43&amp;#176;37&amp;#8242; N; Long: 04&amp;#176;04&amp;#8242; 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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;

scholarly journals Evaluation of upper tropospheric humidity forecasts from ECMWF using AIRS and CALIPSO data

2008 ◽  
Vol 8 (5) ◽  
pp. 17907-17937 ◽  
Author(s):  
N. Lamquin ◽  
K. Gierens ◽  
C. J. Stubenrauch ◽  
R. Chatterjee
Keyword(s):  
Relative Humidity ◽  
Satellite Observation ◽  
Correction Method ◽  
Radiosonde Data ◽  
Atmospheric Infrared Sounder ◽  
Weather Forecasts ◽  
Medium Range ◽  
Upper Tropospheric Humidity ◽  
One Year ◽  
Humidity Profiles

Abstract. An evaluation of the upper tropospheric humidity from the European Centre of Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) is presented. We first make an analysis of the spinup behaviour of ice supersaturation in weather forecasts. It shows that a spinup period of at least 12 h is necessary before using forecast humidity data from the upper troposphere. We compare the forecasted upper tropospheric humidity with coincident relative humidity fields retrieved from the Atmospheric InfraRed Sounder (AIRS) and with cloud vertical profiles from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). The analysis is made over one year, from October 2006 to September 2007, and we discuss how relative humidity and cloud features appear both in the IFS and in the observations. In a last part, we investigate the presence of ice supersaturation within low vertical resolution pressure layers by comparing the IFS outputs for high-resolution and low-resolution humidity profiles and by simulating the interpolation of humidity over radiosonde data. A new correction method is proposed and tested with these data.

scholarly journals Water vapour profiles from Raman lidar automatically calibrated by microwave radiometer data during HOPE

2015 ◽  
Vol 15 (5) ◽  
pp. 6567-6599 ◽  
Author(s):  
A. Foth ◽  
H. Baars ◽  
P. Di Girolamo ◽  
B. Pospichal
Keyword(s):  
Water Vapour ◽  
Continuous Measurement ◽  
Microwave Radiometer ◽  
Calibration Method ◽  
Calibration Factor ◽  
Raman Lidar ◽  
Clear Sky ◽  
Lidar Measurements ◽  
Integrated Water Vapour ◽  
Good Agreement

Abstract. In this paper, we present a method to derive water vapour profiles from Raman lidar measurements calibrated by the integrated water vapour (IWV) from a collocated microwave radiometer during the intense observation campaign HOPE in the frame of the HD(CP)2 initiative. The simultaneous observation of a microwave radiometer and a Raman lidar allowed an operational and continuous measurement of water vapour profiles also during cloudy conditions. The calibration method provides results in a good agreement with conventional methods based on radiosondes. The calibration factor derived from the proposed IWV method is very stable with a relative uncertainty of 6%. This stability allows to calibrate the lidar even in the presence of clouds using the calibration factor determined during the closest in time clear sky interval. Based on the application of this approach, it is possible to retrieve water vapour profiles during all non-precipitating conditions. A statistical analysis shows a good agreement between the lidar measurements and collocated radiosondes. The relative biases amount to less than 6.7% below 2 km.

scholarly journals Quantifying the value of redundant measurements at GCOS Reference Upper-Air Network sites

2014 ◽  
Vol 7 (11) ◽  
pp. 3813-3823 ◽  
Author(s):  
F. Madonna ◽  
M. Rosoldi ◽  
J. Güldner ◽  
A. Haefele ◽  
R. Kivi ◽  
...  
Keyword(s):  
Time Series ◽  
Water Vapour ◽  
Global Climate ◽  
Microwave Radiometer ◽  
Raman Lidar ◽  
Mutual Correlation ◽  
Random Uncertainty ◽  
Lidar Measurements ◽  
Integrated Water Vapour ◽  
Microwave Radiometers

Abstract. The potential for measurement redundancy to reduce uncertainty in atmospheric variables has not been investigated comprehensively for climate observations. We evaluated the usefulness of entropy and mutual correlation concepts, as defined in information theory, for quantifying random uncertainty and redundancy in time series of the integrated water vapour (IWV) and water vapour mixing ratio profiles provided by five highly instrumented GRUAN (GCOS, Global Climate Observing System, Reference Upper-Air Network) stations in 2010–2012. Results show that the random uncertainties on the IWV measured with radiosondes, global positioning system, microwave and infrared radiometers, and Raman lidar measurements differed by less than 8%. Comparisons of time series of IWV content from ground-based remote sensing instruments with in situ soundings showed that microwave radiometers have the highest redundancy with the IWV time series measured by radiosondes and therefore the highest potential to reduce the random uncertainty of the radiosondes time series. Moreover, the random uncertainty of a time series from one instrument can be reduced by ~ 60% by constraining the measurements with those from another instrument. The best reduction of random uncertainty is achieved by conditioning Raman lidar measurements with microwave radiometer measurements. Specific instruments are recommended for atmospheric water vapour measurements at GRUAN sites. This approach can be applied to the study of redundant measurements for other climate variables.

Calibration of water vapor Raman lidar measurements by use of radiosonde and microwave radiometer measurements

2021 ◽  
Author(s):  
Dietrich Althausen ◽  
Clara Seidel ◽  
Ronny Engelmann ◽  
Hannes Griesche ◽  
Martin Radenz ◽  
...  
Keyword(s):  
Water Vapor ◽  
Microwave Radiometer ◽  
The Arctic ◽  
Radiosonde Data ◽  
Lidar Data ◽  
Mixing Ratio ◽  
Raman Lidar ◽  
Vertical Column ◽  
Linear Fit ◽  
Water Vapor Mixing Ratio

&lt;p&gt;Water vapor profiles with high vertical and temporal resolution were determined by use of the Raman lidar PollyXT within the MOSAiC campaign in the Arctic during the winter time 2019 &amp;#8211; 2020. These measurements need a calibration. Usually, radiosonde data are utilized to calibrate the lidar data by the profile or the linear fit method, respectively. The radiosonde is drifting with the wind; thus, it is often measuring different atmospheric volumes compared to the lidar observations.&lt;/p&gt; &lt;p&gt;The period 5-7 February 2020 is used to demonstrate the results. The correlation coefficient of the linear fit between the radiosonde and the lidar data varies with the different atmospheric conditions.&amp;#160;The calibration results from the profile method coincide with those of the linear fit method, but the selection of the appropriate calibration setup is not straightforward. The varying correlation of the calibration results is attributed to the partly too low data-variability of the water vapor mixing ratio in the respective heights. &amp;#160;Moreover, the drift of the radiosondes with the wind and hence measurements of atmospheric volumes with lateral distances will have decreased the correlation between the lidar and the radiosonde measurements.&lt;/p&gt; &lt;p&gt;During MOSAiC a microwave radiometer was collocated close to the lidar. This system was measuring the same atmospheric vertical column. Its product, the integrated water vapor, might be useful for the calibration of the lidar.&lt;/p&gt; &lt;p&gt;Hence, the contribution will analyze the error of the lidar retrieved water vapor mixing ratio that includes the calibration with the radiosonde data and the microwave radiometer product.&lt;/p&gt; &lt;p&gt;&amp;#160;&lt;/p&gt;

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