scholarly journals A novel post-processing algorithm for Halo Doppler lidars

2019 ◽  
Vol 12 (2) ◽  
pp. 839-852 ◽  
Author(s):  
Ville Vakkari ◽  
Antti J. Manninen ◽  
Ewan J. O'Connor ◽  
Jan H. Schween ◽  
Pieter G. van Zyl ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Radial Velocity ◽  
Planetary Boundary Layer ◽  
Data Availability ◽  
Processing Algorithm ◽  
Stream Line ◽  
Limiting Factor ◽  
High Temporal Resolution ◽  
Post Processing ◽  
Uncertainty Estimates

Abstract. Commercially available Doppler lidars have now been proven to be efficient tools for studying winds and turbulence in the planetary boundary layer. However, in many cases low signal-to-noise ratio is still a limiting factor for utilising measurements by these devices. Here, we present a novel post-processing algorithm for Halo Stream Line Doppler lidars, which enables an improvement in sensitivity of a factor of 5 or more. This algorithm is based on improving the accuracy of the instrumental noise floor and it enables longer integration times or averaging of high temporal resolution data to be used to obtain signals down to −32 dB. While this algorithm does not affect the measured radial velocity, it improves the accuracy of radial velocity uncertainty estimates and consequently the accuracy of retrieved turbulent properties. Field measurements using three different Halo Doppler lidars deployed in Finland, Greece and South Africa demonstrate how the new post-processing algorithm increases data availability for turbulent retrievals in the planetary boundary layer, improves detection of high-altitude cirrus clouds and enables the observation of elevated aerosol layers.

scholarly journals A novel post-processing algorithm for Halo Doppler lidars

2018 ◽  
Author(s):  
Ville Vakkari ◽  
Antti J. Manninen ◽  
Ewan J. O'Connor ◽  
Jan H. Schween ◽  
Pieter G. van Zyl
Keyword(s):  
Boundary Layer ◽  
Radial Velocity ◽  
Planetary Boundary Layer ◽  
Field Measurements ◽  
Data Availability ◽  
Processing Algorithm ◽  
Limiting Factor ◽  
High Temporal Resolution ◽  
Post Processing ◽  
Uncertainty Estimates

Abstract. Commercially available Doppler lidars have now been proven to be efficient tools for studying winds and turbulence in the planetary boundary layer. However, in many cases low signal-to-noise ratio is still a limiting factor for utilising measurements by these devices. Here, we present a novel postprocessing algorithm for Halo Streamline Doppler lidars, which enables an improvement in sensitivity of a factor of five or more. This algorithm is based on improving the accuracy of the instrumental noise floor and it enables using longer integration times or averaging of high temporal resolution data to obtain signals down to −32 dB. While this algorithm does not affect the measured radial velocity, it improves the accuracy of radial velocity uncertainty estimates and consequently the accuracy of retrieved turbulent properties. Field measurements with three different Halo Doppler lidars deployed in Finland, Greece and South Africa demonstrate how the new post-processing algorithm increases data availability for turbulent retrievals in the planetary boundary layer, improves detection of high-altitude cirrus clouds, and enables the observation of elevated aerosol layers.

scholarly journals A generalised background correction algorithm for a Halo Doppler lidar and its application to data from Finland

2015 ◽  
Vol 8 (10) ◽  
pp. 11139-11170
Author(s):  
A. J. Manninen ◽  
E. J. O'Connor ◽  
V. Vakkari ◽  
T. Petäjä
Keyword(s):  
Background Noise ◽  
Signal To Noise Ratio ◽  
Background Correction ◽  
Data Availability ◽  
Horizontal Wind ◽  
Limiting Factor ◽  
High Temporal Resolution ◽  
Signal To Noise ◽  
Uncertainty Estimates ◽  
Noise Ratio

Abstract. Current commercially available Doppler lidars provide an economical and robust solution for measuring vertical and horizontal wind velocities, together with the ability to provide co- and cross-polarised backscatter profiles. The high temporal resolution of these instruments allow turbulent properties to be obtained from studying the variation in velocities. However, the instrument specifications mean that certain characteristics, especially the background noise behaviour, become a limiting factor for the instrument sensitivity in regions where the aerosol load is low. Turbulent calculations require an accurate estimate of the contribution from velocity uncertainty estimates, which are directly related to the signal-to-noise ratio. Any bias in the signal-to-noise ratio will propagate through as a bias in turbulent properties. In this paper we present a method to correct for artefacts in the background noise behaviour of commercially available Doppler lidars and reduce the signal-to-noise ratio threshold used to discriminate between noise, and cloud or aerosol signals. We show that, for Doppler lidars operating continuously at a number of locations in Finland, the data availability can be increased by as much as 50 % after performing this background correction and subsequent reduction in the threshold. The reduction in bias also greatly improves subsequent calculations of turbulent properties in weak signal regimes.

scholarly journals A generalised background correction algorithm for a Halo Doppler lidar and its application to data from Finland

2016 ◽  
Vol 9 (2) ◽  
pp. 817-827 ◽  
Author(s):  
Antti J. Manninen ◽  
Ewan J. O'Connor ◽  
Ville Vakkari ◽  
Tuukka Petäjä
Keyword(s):  
Background Noise ◽  
Signal To Noise Ratio ◽  
Background Correction ◽  
Data Availability ◽  
Horizontal Wind ◽  
Limiting Factor ◽  
High Temporal Resolution ◽  
Signal To Noise ◽  
Uncertainty Estimates ◽  
Noise Ratio

Abstract. Current commercially available Doppler lidars provide an economical and robust solution for measuring vertical and horizontal wind velocities, together with the ability to provide co- and cross-polarised backscatter profiles. The high temporal resolution of these instruments allows turbulent properties to be obtained from studying the variation in radial velocities. However, the instrument specifications mean that certain characteristics, especially the background noise behaviour, become a limiting factor for the instrument sensitivity in regions where the aerosol load is low. Turbulent calculations require an accurate estimate of the contribution from velocity uncertainty estimates, which are directly related to the signal-to-noise ratio. Any bias in the signal-to-noise ratio will propagate through as a bias in turbulent properties. In this paper we present a method to correct for artefacts in the background noise behaviour of commercially available Doppler lidars and reduce the signal-to-noise ratio threshold used to discriminate between noise, and cloud or aerosol signals. We show that, for Doppler lidars operating continuously at a number of locations in Finland, the data availability can be increased by as much as 50 % after performing this background correction and subsequent reduction in the threshold. The reduction in bias also greatly improves subsequent calculations of turbulent properties in weak signal regimes.

A New Generation of Ground-Based Mobile Platforms for Active and Passive Profiling of the Boundary Layer

2019 ◽  
Vol 100 (1) ◽  
pp. 137-153 ◽  
Author(s):  
Timothy J. Wagner ◽  
Petra M. Klein ◽  
David D. Turner
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Lower Troposphere ◽  
Mobile Systems ◽  
Lower Atmosphere ◽  
Stream Line ◽  
High Temporal Resolution ◽  
Great Success ◽  
Mobile Platforms ◽  
Atmospheric Phenomena

AbstractMobile systems equipped with remote sensing instruments capable of simultaneous profiling of temperature, moisture, and wind at high temporal resolutions can offer insights into atmospheric phenomena that the operational network cannot. Two recently developed systems, the Space Science and Engineering Center (SSEC) Portable Atmospheric Research Center (SPARC) and the Collaborative Lower Atmosphere Profiling System (CLAMPS), have already experienced great success in characterizing a variety of phenomena. Each system contains an Atmospheric Emitted Radiance Interferometer for thermodynamic profiling and a Halo Photonics Stream Line Doppler wind lidar for kinematic profiles. These instruments are augmented with various in situ and remote sensing instruments to provide a comprehensive assessment of the evolution of the lower troposphere at high temporal resolution (5 min or better). While SPARC and CLAMPS can be deployed independently, the common instrument configuration means that joint deployments with well-coordinated data collection and analysis routines are easily facilitated.In the past several years, SPARC and CLAMPS have participated in numerous field campaigns, which range from mesoscale campaigns that require the rapid deployment and teardown of observing systems to multiweek fixed deployments, providing crucial insights into the behavior of many different atmospheric boundary layer processes while training the next generation of atmospheric scientists. As calls for a nationwide ground-based profiling network continue, SPARC and CLAMPS can play an important role as test beds and prototype nodes for such a network.

scholarly journals Measurements of wind turbulence parameters by a conically scanning coherent Doppler lidar in the atmospheric boundary layer

2017 ◽  
Author(s):  
Igor N. Smalikho ◽  
Viktor A. Banakh
Keyword(s):  
Boundary Layer ◽  
Kinetic Energy ◽  
Radial Velocity ◽  
Dissipation Rate ◽  
Stream Line ◽  
Lidar Data ◽  
Doppler Lidar ◽  
Integral Scale ◽  
Coherent Doppler Lidar ◽  
Turbulence Parameters

Abstract. The method and results of lidar studies of spatiotemporal variability of wind turbulence in the atmospheric boundary layer are reported. The measurements were conducted by a Stream Line pulsed coherent Doppler lidar with the use of conical scanning by a probing beam around the vertical axis. Lidar data are used to estimate the kinetic energy of turbulence, turbulent energy dissipation rate, integral scale of turbulence, and momentum fluxes. The dissipation rate was determined from the azimuth structure function of radial velocity within the inertial subrange of turbulence. When estimating the kinetic energy of turbulence from lidar data, we took into account the averaging of radial velocity over the sensing volume. The integral scale of turbulence was determined on the assumption that the structure of random irregularities of the wind field is described by the von Karman model. The domain of applicability of the used method and the accuracy of estimation of turbulence parameters were determined. Turbulence parameters estimated from Stream Line lidar measurement data and from data of a sonic anemometer were compared.

scholarly journals Measurements of wind turbulence parameters by a conically scanning coherent Doppler lidar in the atmospheric boundary layer

2017 ◽  
Vol 10 (11) ◽  
pp. 4191-4208 ◽  
Author(s):  
Igor N. Smalikho ◽  
Viktor A. Banakh
Keyword(s):  
Boundary Layer ◽  
Kinetic Energy ◽  
Radial Velocity ◽  
Dissipation Rate ◽  
Stream Line ◽  
Lidar Data ◽  
Doppler Lidar ◽  
Integral Scale ◽  
Coherent Doppler Lidar ◽  
Turbulence Parameters

Abstract. The method and results of lidar studies of spatiotemporal variability of wind turbulence in the atmospheric boundary layer are reported. The measurements were conducted by a Stream Line pulsed coherent Doppler lidar (PCDL) with the use of conical scanning by a probing beam around the vertical axis. Lidar data are used to estimate the kinetic energy of turbulence, turbulent energy dissipation rate, integral scale of turbulence, and momentum fluxes. The dissipation rate was determined from the azimuth structure function of radial velocity within the inertial subrange of turbulence. When estimating the kinetic energy of turbulence from lidar data, we took into account the averaging of radial velocity over the sensing volume. The integral scale of turbulence was determined on the assumption that the structure of random irregularities of the wind field is described by the von Kármán model. The domain of applicability of the used method and the accuracy of the estimation of turbulence parameters were determined. Turbulence parameters estimated from Stream Line lidar measurement data and from data of a sonic anemometer were compared.

scholarly journals Sensitivity of an Idealized Tropical Cyclone to the Configuration of the Global Forecast System–Eddy Diffusivity Mass Flux Planetary Boundary Layer Scheme

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 284
Author(s):  
Evan A. Kalina ◽  
Mrinal K. Biswas ◽  
Jun A. Zhang ◽  
Kathryn M. Newman
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Weather Prediction ◽  
Intensity Change ◽  
Rapid Intensification ◽  
Forecast System ◽  
Stability Functions ◽  
Non Local ◽  
The Stability ◽  
Heat And Moisture

The intensity and structure of simulated tropical cyclones (TCs) are known to be sensitive to the planetary boundary layer (PBL) parameterization in numerical weather prediction models. In this paper, we use an idealized version of the Hurricane Weather Research and Forecast system (HWRF) with constant sea-surface temperature (SST) to examine how the configuration of the PBL scheme used in the operational HWRF affects TC intensity change (including rapid intensification) and structure. The configuration changes explored in this study include disabling non-local vertical mixing, changing the coefficients in the stability functions for momentum and heat, and directly modifying the Prandtl number (Pr), which controls the ratio of momentum to heat and moisture exchange in the PBL. Relative to the control simulation, disabling non-local mixing produced a ~15% larger storm that intensified more gradually, while changing the coefficient values used in the stability functions had little effect. Varying Pr within the PBL had the greatest impact, with the largest Pr (~1.6 versus ~0.8) associated with more rapid intensification (~38 versus 29 m s−1 per day) but a 5–10 m s−1 weaker intensity after the initial period of strengthening. This seemingly paradoxical result is likely due to a decrease in the radius of maximum wind (~15 versus 20 km), but smaller enthalpy fluxes, in simulated storms with larger Pr. These results underscore the importance of measuring the vertical eddy diffusivities of momentum, heat, and moisture under high-wind, open-ocean conditions to reduce uncertainty in Pr in the TC PBL.

Assessing the Influence of Aerosol on Radiation and Its Roles in Planetary Boundary Layer Development

2021 ◽  
Vol 35 (2) ◽  
pp. 384-392
Author(s):  
Zhigang Cheng ◽  
Yubing Pan ◽  
Ju Li ◽  
Xingcan Jia ◽  
Xinyu Zhang ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Boundary Layer Development ◽  
Layer Development

A Modified CGM Algorithm Enhances Data Availability While Retaining iCGM Performance

2021 ◽  
pp. 193229682110075
Author(s):  
Rebecca A. Harvey Towers ◽  
Xiaohe Zhang ◽  
Rasoul Yousefi ◽  
Ghazaleh Esmaili ◽  
Liang Wang ◽  
...  
Keyword(s):  
Data Integration ◽  
Patient Experience ◽  
Real World ◽  
Data Availability ◽  
Post Processing ◽  
Sensor Error ◽  
The Mean ◽  
The Difference ◽  
Data Gap ◽  
Improve Patient

The algorithm for the Dexcom G6 CGM System was enhanced to retain accuracy while reducing the frequency and duration of sensor error. The new algorithm was evaluated by post-processing raw signals collected from G6 pivotal trials (NCT02880267) and by assessing the difference in data availability after a limited, real-world launch. Accuracy was comparable with the new algorithm—the overall %20/20 was 91.7% before and 91.8% after the algorithm modification; MARD was unchanged. The mean data gap due to sensor error nearly halved and total time spent in sensor error decreased by 59%. A limited field launch showed similar results, with a 43% decrease in total time spent in sensor error. Increased data availability may improve patient experience and CGM data integration into insulin delivery systems.

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