scholarly journals Notes on Temperature-Dependent Lidar Equations

2009 ◽  
Vol 26 (6) ◽  
pp. 1021-1039 ◽  
Author(s):  
Mariana Adam
Keyword(s):  
Water Vapor ◽  
Cross Sections ◽  
Differential Cross ◽  
Interference Filter ◽  
Transmission Efficiency ◽  
Mixing Ratio ◽  
Temperature Dependent ◽  
Howard University ◽  
Lidar Measurements ◽  
Water Vapor Mixing Ratio

Abstract The temperature dependence of molecular backscatter coefficients must be taken into account when narrowband interference filters are used in lidar measurements. Thus, the spectral backscatter differential cross section of the molecules involved in the backscattering of the radiation has to be calculated or measured and the interference filter transmission efficiency must be known. The present paper is intended to describe in an easily reproducible manner the procedure involved in calculating the temperature-dependent functions introduced in the lidar equations, including the computation of the differential cross sections for air, nitrogen, and water vapor. The temperature-dependent functions are computed for the Howard University Raman lidar (HURL). The interference filter efficiencies are given by the manufacturer. Error estimates in water vapor mixing ratio and aerosol backscatter ratio involved when temperature-dependent functions are omitted are given for measurements taken with HURL. For the data analyzed, it is found that errors in estimating the water vapor mixing ratio are up to ∼6% while in estimating the aerosol backscattering ratio the errors are up to ∼1.3% in the planetary boundary layer and ∼2.2% in cirrus clouds. Theoretical computations are performed to determine temperature-dependent functions for nitrogen, water vapor, and their ratio, using simulated Gaussian-shaped filters. The goal is to find the optimum combination of different filters that will determine the ratio profiles of the temperature-dependent functions that are either the closest to unity or the least variable. The analyses reveal that quite constant profiles can be obtained for several combinations of the filters.

scholarly journals A Remotely Operated Lidar for Aerosol, Temperature, and Water Vapor Profiling in the High Arctic

2012 ◽  
Vol 29 (2) ◽  
pp. 221-234 ◽  
Author(s):  
G. J. Nott ◽  
T. J. Duck ◽  
J. G. Doyle ◽  
M. E. W. Coffin ◽  
C. Perro ◽  
...  
Keyword(s):  
Water Vapor ◽  
Measurement Techniques ◽  
High Arctic ◽  
Interference Filter ◽  
Fine Tuning ◽  
The Arctic ◽  
Tropospheric Temperature ◽  
Mixing Ratio ◽  
Atmospheric Conditions ◽  
Water Vapor Mixing Ratio

Abstract A Rayleigh–Mie–Raman lidar has been installed and is operating in the Polar Environment Atmospheric Research Laboratory at Eureka in the High Arctic (79°59′N, 85°56′W) as part of the Canadian Network for the Detection of Atmospheric Change. The lidar operates in both the visible and ultraviolet and measures aerosol backscatter and extinction coefficients, depolarization ratio, tropospheric temperature, and water vapor mixing ratio. Variable field of view, aperture, and filtering allow fine-tuning of the instrument for different atmospheric conditions. Because of the remote location, operations are carried out via a satellite link. The instrument is introduced along with the measurement techniques utilized and interference filter specifications. The temperature dependence of the water vapor signal depends on the filter specifications, and this is discussed in terms of minimizing the uncertainty of the water vapor mixing ratio product. Finally, an example measurement is presented to illustrate the potential of this instrument for studying the Arctic atmosphere.

scholarly journals Water Vapor Measurements by Howard University Raman Lidar during the WAVES 2006 Campaign

2010 ◽  
Vol 27 (1) ◽  
pp. 42-60 ◽  
Author(s):  
M. Adam ◽  
B. B. Demoz ◽  
D. D. Venable ◽  
E. Joseph ◽  
R. Connell ◽  
...  
Keyword(s):  
Water Vapor ◽  
Relative Humidity ◽  
Relative Difference ◽  
Mixing Ratio ◽  
State Variables ◽  
Raman Lidar ◽  
Ensemble Averaging ◽  
Howard University ◽  
Validation Experiment ◽  
Water Vapor Mixing Ratio

Abstract Water vapor mixing ratio retrieval using the Howard University Raman lidar is presented with emphasis on three aspects: (i) comparison of the lidar with collocated radiosondes and Raman lidar, (ii) investigation of the relationship between atmospheric state variables and the relative performance of the lidar and sonde (in particular, their poor agreement), and (iii) comparison with satellite-based measurements. The measurements were acquired during the Water Vapor Validation Experiment Sondes/Satellites 2006 campaign. Ensemble averaging of water vapor mixing ratio data from 10 nighttime comparisons with Vaisala RS92 radiosondes shows, on average, an agreement within ±10%, up to ∼8 km. A similar analysis of lidar-to-lidar data of over 700 profiles revealed an agreement to within 20% over the first 7 km (10% below 4 km). A grid analysis, defined in the temperature–relative humidity space, was developed to characterize the lidar–radiosonde agreement and quantitatively localizes regions of strong and weak correlations as a function of altitude, temperature, or relative humidity. Three main regions of weak correlation emerge: (i) regions of low relative humidity and low temperature, (ii) regions of moderate relative humidity at low temperatures, and (iii) regions of low relative humidity at moderate temperatures. Comparison of Atmospheric Infrared Sounder and Tropospheric Emission Sounder satellite retrievals of moisture with those of Howard University Raman lidar showed a general agreement in the trend, but the satellites miss details in atmospheric structure because of their low resolution. A relative difference of about ±20% is usually found between lidar and satellite measurements for the coincidences available.

Ice clouds and Asian dust studied with lidar measurements of particle extinction-to-backscatter ratio, particle depolarization, and water-vapor mixing ratio over Tsukuba

2003 ◽  
Vol 42 (36) ◽  
pp. 7103 ◽  
Author(s):  
Tetsu Sakai ◽  
Tomohiro Nagai ◽  
Masahisa Nakazato ◽  
Yuzo Mano ◽  
Takatsugu Matsumura
Keyword(s):  
Water Vapor ◽  
Asian Dust ◽  
Mixing Ratio ◽  
Ice Clouds ◽  
Lidar Measurements ◽  
Water Vapor Mixing Ratio

scholarly journals Aircraft Evaluation of Ground-Based Raman Lidar Water Vapor Turbulence Profiles in Convective Mixed Layers

2014 ◽  
Vol 31 (5) ◽  
pp. 1078-1088 ◽  
Author(s):  
D. D. Turner ◽  
R. A. Ferrare ◽  
V. Wulfmeyer ◽  
A. J. Scarino
Keyword(s):  
Water Vapor ◽  
Great Plains ◽  
Mixing Ratio ◽  
Raman Lidar ◽  
Southern Great Plains ◽  
Lidar Measurements ◽  
Atmospheric Radiation Measurement ◽  
Convective Mixed Layer ◽  
Water Vapor Mixing Ratio ◽  
Mixed Layers

AbstractHigh temporal and vertical resolution water vapor measurements by Raman and differential absorption lidar systems have been used to characterize the turbulent fluctuations in the water vapor mixing ratio field in convective mixed layers. Since daytime Raman lidar measurements are inherently noisy (due to solar background and weak signal strengths), the analysis approach needs to quantify and remove the contribution of the instrument noise in order to derive the desired atmospheric water vapor mixing ratio variance and skewness profiles. This is done using the approach outlined by Lenschow et al.; however, an intercomparison with in situ observations was not performed.Water vapor measurements were made by a diode laser hygrometer flown on a Twin Otter aircraft during the Routine Atmospheric Radiation Measurement (ARM) Program Aerial Facility Clouds with Low Optical Water Depths Optical Radiative Observations (RACORO) field campaign over the ARM Southern Great Plains (SGP) site in 2009. Two days with Twin Otter flights were identified where the convective mixed layer was quasi stationary, and hence the 10-s, 75-m data from the SGP Raman lidar could be analyzed to provide profiles of water vapor mixing ratio variance and skewness. Airborne water vapor observations measured during level flight legs were compared to the Raman lidar data, demonstrating good agreement in both variance and skewness. The results also illustrate the challenges of comparing a point sensor making measurements over time to a moving platform making similar measurements horizontally.

Study of the statistics of water vapor mixing ratio determined from Raman lidar measurements

2007 ◽  
Vol 46 (33) ◽  
pp. 8170 ◽  
Author(s):  
Pierre Bosser ◽  
Olivier Bock ◽  
Christian Thom ◽  
Jacques Pelon
Keyword(s):  
Water Vapor ◽  
Mixing Ratio ◽  
Raman Lidar ◽  
Lidar Measurements ◽  
Water Vapor Mixing Ratio

Subcloud and Cloud-Base Latent Heat Fluxes during Shallow Cumulus Convection

2019 ◽  
Vol 77 (3) ◽  
pp. 1081-1100 ◽  
Author(s):  
Neil P. Lareau
Keyword(s):  
Boundary Layer ◽  
Water Vapor ◽  
Latent Heat ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Cloud Base ◽  
Cumulus Convection ◽  
Mixing Ratio ◽  
Convective Boundary ◽  
Water Vapor Mixing Ratio

Abstract Doppler and Raman lidar observations of vertical velocity and water vapor mixing ratio are used to probe the physics and statistics of subcloud and cloud-base latent heat fluxes during cumulus convection at the ARM Southern Great Plains (SGP) site in Oklahoma, United States. The statistical results show that latent heat fluxes increase with height from the surface up to ~0.8Zi (where Zi is the convective boundary layer depth) and then decrease to ~0 at Zi. Peak fluxes aloft exceeding 500 W m−2 are associated with periods of increased cumulus cloud cover and stronger jumps in the mean humidity profile. These entrainment fluxes are much larger than the surface fluxes, indicating substantial drying over the 0–0.8Zi layer accompanied by moistening aloft as the CBL deepens over the diurnal cycle. We also show that the boundary layer humidity budget is approximately closed by computing the flux divergence across the 0–0.8Zi layer. Composite subcloud velocity and water vapor anomalies show that clouds are linked to coherent updraft and moisture plumes. The moisture anomaly is Gaussian, most pronounced above 0.8Zi and systematically wider than the velocity anomaly, which has a narrow central updraft flanked by downdrafts. This size and shape disparity results in downdrafts characterized by a high water vapor mixing ratio and thus a broad joint probability density function (JPDF) of velocity and mixing ratio in the upper CBL. We also show that cloud-base latent heat fluxes can be both positive and negative and that the instantaneous positive fluxes can be very large (~10 000 W m−2). However, since cloud fraction tends to be small, the net impact of these fluxes remains modest.

scholarly journals A practical information-centered technique to remove a priori information from lidar optimal-estimation-method retrievals

2019 ◽  
Vol 12 (7) ◽  
pp. 3943-3961 ◽  
Author(s):  
Ali Jalali ◽  
Shannon Hicks-Jalali ◽  
Robert J. Sica ◽  
Alexander Haefele ◽  
Thomas von Clarmann
Keyword(s):  
Water Vapor ◽  
A Priori ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Mixing Ratio ◽  
A Priori Information ◽  
Fine Grid ◽  
Large Power ◽  
Priori Information ◽  
Water Vapor Mixing Ratio

Abstract. Lidar retrievals of atmospheric temperature and water vapor mixing ratio profiles using the optimal estimation method (OEM) typically use a retrieval grid with a number of points larger than the number of pieces of independent information obtainable from the measurements. Consequently, retrieved geophysical quantities contain some information from their respective a priori values or profiles, which can affect the results in the higher altitudes of the temperature and water vapor profiles due to decreasing signal-to-noise ratios. The extent of this influence can be estimated using the retrieval's averaging kernels. The removal of formal a priori information from the retrieved profiles in the regions of prevailing a priori effects is desirable, particularly when these greatest heights are of interest for scientific studies. We demonstrate here that removal of a priori information from OEM retrievals is possible by repeating the retrieval on a coarser grid where the retrieval is stable even without the use of formal prior information. The averaging kernels of the fine-grid OEM retrieval are used to optimize the coarse retrieval grid. We demonstrate the adequacy of this method for the case of a large power-aperture Rayleigh scatter lidar nighttime temperature retrieval and for a Raman scatter lidar water vapor mixing ratio retrieval during both day and night.

Some features of water vapor mixing ratio in tropical upper troposphere and lower stratosphere: Role of convection

2012 ◽  
Vol 108 ◽  
pp. 86-103 ◽  
Author(s):  
V. Panwar ◽  
A.R. Jain ◽  
A. Goel ◽  
T.K. Mandal ◽  
V.R. Rao ◽  
...  
Keyword(s):  
Water Vapor ◽  
Lower Stratosphere ◽  
Mixing Ratio ◽  
Upper Troposphere ◽  
Water Vapor Mixing Ratio ◽  
Tropical Upper Troposphere

scholarly journals Quantifying the Imprint of a Severe Hector Thunderstorm during ACTIVE/SCOUT-O3 onto the Water Content in the Upper Troposphere/Lower Stratosphere

2009 ◽  
Vol 137 (8) ◽  
pp. 2493-2514 ◽  
Author(s):  
Charles Chemel ◽  
Maria R. Russo ◽  
John A. Pyle ◽  
Ranjeet S. Sokhi ◽  
Cornelius Schiller
Keyword(s):  
Water Vapor ◽  
Water Content ◽  
Lower Stratosphere ◽  
Horizontal Resolution ◽  
Convective Transport ◽  
Mixing Ratio ◽  
Field Campaign ◽  
Upper Troposphere ◽  
Ice Particles ◽  
Water Vapor Mixing Ratio

Abstract The development of a severe Hector thunderstorm that formed over the Tiwi Islands, north of Australia, during the Aerosol and Chemical Transport in Tropical Convection/Stratospheric-Climate Links with Emphasis on the Upper Troposphere and Lower Stratosphere (ACTIVE/SCOUT-O3) field campaign in late 2005, is simulated by the Advanced Research Weather Research and Forecasting (ARW) model and the Met Office Unified Model (UM). The general aim of this paper is to investigate the role of isolated deep convection over the tropics in regulating the water content in the upper troposphere/lower stratosphere (UT/LS). Using a horizontal resolution as fine as 1 km, the numerical simulations reproduce the timing, structure, and strength of Hector fairly well when compared with field campaign observations. The sensitivity of results from ARW to horizontal resolution is investigated by running the model in a large-eddy simulation mode with a horizontal resolution of 250 m. While refining the horizontal resolution to 250 m leads to a better representation of convection with respect to rainfall, the characteristics of the Hector thunderstorm are basically similar in space and time to those obtained in the 1-km-horizontal-resolution simulations. Several overshooting updrafts penetrating the tropopause are produced in the simulations during the mature stage of Hector. The penetration of rising towering cumulus clouds into the LS maintains the entrainment of air at the interface between the UT and the LS. Vertical exchanges resulting from this entrainment process have a significant impact on the redistribution of atmospheric constituents within the UT/LS region at the scale of the islands. In particular, a large amount of water is injected in the LS. The fate of the ice particles as Hector develops drives the water vapor mixing ratio to saturation by sublimation of the injected ice particles, moistening the air in the LS. The moistening was found to be fairly significant above 380 K and averaged about 0.06 ppmv in the range 380–420 K for ARW. As for UM, the moistening was found to be much larger (about 2.24 ppmv in the range of 380–420 K) than for ARW. This result confirms that convective transport can play an important role in regulating the water vapor mixing ratio in the LS.

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