Raman lidar in operational meteorology

2018 ◽  
Author(s):  
Todor Dinoev ◽  
Alexander Hafele ◽  
Giovanni Martucci ◽  
Valentin B. Simeonov ◽  
Bertrand Calpini ◽  
...  
Keyword(s):  
Raman Lidar

Synergy of Raman Lidar and Modeled Temperature for Relative Humidity Profiling: Assessment and Uncertainty Analysis

2021 ◽  
pp. 1-12
Author(s):  
Constantino Munoz-Porcar ◽  
Michael Sicard ◽  
Maria Jose Granados-Munoz ◽  
Ruben Barragan ◽  
Adolfo Comeron ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Uncertainty Analysis ◽  
Raman Lidar

A case study on the vertical distribution and characteristics of aerosols using ground-based raman lidar, satellite and model over Western India

2021 ◽  
Vol 42 (17) ◽  
pp. 6421-6436
Author(s):  
Sourita Saha ◽  
Som Sharma ◽  
K. Niranjan Kumar ◽  
Prashant Kumar ◽  
Vaidehi Joshi ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Western India ◽  
Raman Lidar ◽  
The Vertical Distribution

scholarly journals Hydrogen gas concentration measurement in small area using raman lidar measurement technnology

2018 ◽  
Vol 176 ◽  
pp. 01019 ◽  
Author(s):  
Sachiyo Sugimoto ◽  
Ippei Asahi ◽  
Tatuso Shiina
Keyword(s):  
Small Area ◽  
Gas Flow ◽  
Hydrogen Gas ◽  
Measurement Technology ◽  
Lidar Measurement ◽  
Measurement Point ◽  
Raman Lidar ◽  
Gas Concentration ◽  
Scattering Light ◽  
Temporal And Spatial

When change of hydrogen(H2) gas concentration in a certain point is measured, non-contact measurement technology with high temporal and spatial resolution is necessary. In this study, H2 concentration in the small area of <1cm2 under the gas flow was measured by using a Raman lidar. Raman scattering light at the measurement point of 750mm ahead was detected by the Raman lidar. As a result, it was proved that the H2 concentration of more than 100ppm could be successfully measured.

Regularized algorithm for Raman lidar data processing

2007 ◽  
Vol 46 (22) ◽  
pp. 4879 ◽  
Author(s):  
Valery Shcherbakov
Keyword(s):  
Data Processing ◽  
Lidar Data ◽  
Raman Lidar

scholarly journals One-year aerosol profiling with EUCAARI Raman lidar at Shangdianzi GAW station: Beijing plume and seasonal variations

2012 ◽  
Vol 117 (D13) ◽  
pp. n/a-n/a ◽  
Author(s):  
A. Hänel ◽  
H. Baars ◽  
D. Althausen ◽  
A. Ansmann ◽  
R. Engelmann ◽  
...  
Keyword(s):  
Seasonal Variations ◽  
Raman Lidar ◽  
One Year

scholarly journals EARLINET dust observations vs. BSC-DREAM8b modeled profiles: 12-year-long systematic comparison at Potenza, Italy

2014 ◽  
Vol 14 (16) ◽  
pp. 8781-8793 ◽  
Author(s):  
L. Mona ◽  
N. Papagiannopoulos ◽  
S. Basart ◽  
J. Baldasano ◽  
I. Binietoglou ◽  
...  
Keyword(s):  
Center Of Mass ◽  
Saharan Dust ◽  
Raman Lidar ◽  
Dust Layer ◽  
Systematic Comparison ◽  
Dust Extinction ◽  
Lidar Measurements ◽  
Order Of Magnitude ◽  
Lidar Ratio ◽  
532 Nm

Abstract. In this paper, we report the first systematic comparison of 12-year modeled dust extinction profiles vs. Raman lidar measurements. We use the BSC-DREAM8b model, one of the most widely used dust regional models in the Mediterranean, and Potenza EARLINET lidar profiles for Saharan dust cases, the largest one-site database of dust extinction profiles. A total of 310 dust cases were compared for the May 2000–July 2012 period. The model reconstructs the measured layers well: profiles are correlated within 5% of significance for 60% of the cases and the dust layer center of mass as measured by lidar and modeled by BSC-DREAM8b differ on average 0.3 ± 1.0 km. Events with a dust optical depth lower than 0.1 account for 70% of uncorrelated profiles. Although there is good agreement in terms of profile shape and the order of magnitude of extinction values, the model overestimates the occurrence of dust layer top above 10 km. Comparison with extinction profiles measured by the Raman lidar shows that BSC-DREAM8b typically underestimates the dust extinction coefficient, in particular below 3 km. Lowest model–observation differences (below 17%) correspond to a lidar ratio at 532 nm and Ångström exponent at 355/532 nm of 60 ± 13 and 0.1 ± 0.6 sr, respectively. These are in agreement with values typically observed and modeled for pure desert dust. However, the highest differences (higher than 85%) are typically related to greater Ångström values (0.5 ± 0.6), denoting smaller particles. All these aspects indicate that the level of agreement decreases with an increase in mixing/modification processes.

Narrow-band, narrow-field-of-view Raman lidar with combined day and night capability for tropospheric water-vapor profile measurements

1999 ◽  
Vol 38 (9) ◽  
pp. 1841 ◽  
Author(s):  
Scott E. Bisson ◽  
John E. M. Goldsmith ◽  
Mark G. Mitchell
Keyword(s):  
Water Vapor ◽  
Narrow Band ◽  
Field Of View ◽  
Raman Lidar

Raman lidar water vapor profiling over Warsaw, Poland

2017 ◽  
Vol 194 ◽  
pp. 258-267 ◽  
Author(s):  
Iwona S. Stachlewska ◽  
Montserrat Costa-Surós ◽  
Dietrich Althausen
Keyword(s):  
Water Vapor ◽  
Raman Lidar

scholarly journals Balloon-borne and Raman lidar observations of Asian dust and cirrus cloud properties over Tsukuba, Japan

2014 ◽  
Vol 119 (6) ◽  
pp. 3295-3308 ◽  
Author(s):  
Tetsu Sakai ◽  
Narihiro Orikasa ◽  
Tomohiro Nagai ◽  
Masataka Murakami ◽  
Takuya Tajiri ◽  
...  
Keyword(s):  
Asian Dust ◽  
Cirrus Cloud ◽  
Raman Lidar ◽  
Cloud Properties ◽  
Lidar Observations
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