Lidar remote sensing of cloud formation caused by low‐level jets

Jia, Suotang; Felton, Melvin; Lei, Liqiao; McCormick, M. P.; Delgado, Rubén; Pé, Alexandra St.

doi:10.1002/2015jd024590

Cited by 5 publications

(4 citation statements)

References 29 publications

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“…Doppler lidar measurements provide sufficient temporal and spatial resolution for observing turbulent mixing in the ABL (e.g., Tucker et al, ) but have typically concentrated on particular quantities (O'Connor et al, ; Smalikho & Banakh, ; Vakkari et al, ) or processes (Barlow et al, ; Hogan et al, ; Su et al, ; Träumner et al, ) or deriving the mixing level height (Baars et al, ; Emeis et al, ; Pearson et al, ; Schween et al, ). To better comprehend the complex structure and evolution of the ABL, Harvey et al () introduced a profile‐based Doppler lidar method for determining specific ABL types concentrating on whether the cloud‐topped ABL was coupled to the surface.…”

Section: Introductionmentioning

confidence: 99%

Atmospheric Boundary Layer Classification With Doppler Lidar

et al. 2018

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We present a method using Doppler lidar data for identifying the main sources of turbulent mixing within the atmospheric boundary layer. The method identifies the presence of turbulence and then assigns a turbulent source by combining several lidar quantities: attenuated backscatter coefficient, vertical velocity skewness, dissipation rate of turbulent kinetic energy, and vector wind shear. Both buoyancy-driven and shear-driven situations are identified, and the method operates in both clear-sky and cloud-topped conditions, with some reservations in precipitation. To capture the full seasonal cycle, the classification method was applied to more than 1 year of data from two sites, Hyytiälä, Finland, and Jülich, Germany. Analysis showed seasonal variation in the diurnal cycle at both sites; a clear diurnal cycle was observed in spring, summer, and autumn seasons, but due to their respective latitudes, a weaker cycle in winter at Jülich, and almost non-existent at Hyytiälä. Additionally, there are significant contributions from sources other than convective mixing, with cloud-driven mixing being observed even within the first 500 m above ground. Also evident is the considerable amount of nocturnal mixing within the lowest 500 m at both sites, especially during the winter. The presence of a low-level jet was often detected when sources of nocturnal mixing were diagnosed as wind shear. The classification scheme and the climatology extracted from the classification provide insight into the processes responsible for mixing within the atmospheric boundary layer, how variable in space and time these can be, and how they vary with location.

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Section: Introductionmentioning

confidence: 99%

Atmospheric Boundary Layer Classification With Doppler Lidar

et al. 2018

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“…It was found that the boundary layer aerosol increased after 21:30 caused by night low-level jets at HU campus. HU campus is adjacent to the confluence of the Chesapeake Bay and Earth and Space Science the Atlantic Ocean where LLJs often form in the boundary layer during the spring and summer [Su et al, 2016]. Moreover, the nearby weather station (HAMPTON ROADS EXECUTIVE AIRPORT station) ground observation was shown in Figure 5.…”

Section: Earth and Space Sciencementioning

confidence: 99%

New Technique to Retrieve Tropospheric Temperature Using Vibrational and Rotational Raman Backscattering

Jia

McCormick

Lei

2020

Earth and Space Science

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A new technique is advanced to obtain tropospheric temperature profile using vibrational Raman (VR) and rotational Raman (RR) backscattering. The proposed technique can obtain tropospheric temperature and decrease retrieval errors caused by insufficient suppression of the Mie backscattering in the RR detection channels. The retrieval equations are obtained using VR and RR lidar equations. The feasibility of this technique is demonstrated by applying the algorithm to the Hampton University VR and RR lidar signals. Intercomparisons of these atmospheric temperature retrievals from the Hampton University lidar show good agreement with local radiosonde measurements. Moreover, the proposed technique is applied to a cloudy case and is further validated by showing the good agreements with radiosonde measurements of cloud temperature.

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“…LLJs can also be associated with local transport of aerosols and water vapor, controlling the evolution of clouds and precipitation by horizontal convergence and uplifting of atmospheric constituents (Su et al 2016). The transferring motions and moisture transport between the surface and the atmosphere also directly affect synoptic-scale systems, leading to changes in precipitation patterns (Higgins et al 1997).…”

Section: Introductionmentioning

confidence: 99%

Long-Term Observations and High-Resolution Modeling of Midlatitude Nocturnal Boundary Layer Processes Connected to Low-Level Jets

Marke

Crewell

Schemann

et al. 2018

Journal of Applied Meteorology and Climatology

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Low-level-jet (LLJ) periods are investigated by exploiting a long-term record of ground-based remote sensing Doppler wind lidar measurements supported by tower observations and surface flux measurements at the Jülich Observatory for Cloud Evolution (JOYCE), a midlatitude site in western Germany. LLJs were found 13% of the time during continuous observations over more than 4 yr. The climatological behavior of the LLJs shows a prevailing nighttime appearance of the jets, with a median height of 375 m and a median wind speed of 8.8 m s−1 at the jet nose. Significant turbulence below the jet nose only occurs for high bulk wind shear, which is an important parameter for describing the turbulent characteristics of the jets. The numerous LLJs (16% of all jets) in the range of wind-turbine rotor heights below 200 m demonstrate the importance of LLJs and the associated intermittent turbulence for wind-energy applications. Also, a decrease in surface fluxes and an accumulation of carbon dioxide are observed if LLJs are present. A comprehensive analysis of an LLJ case shows the influence of the surrounding topography, dominated by an open pit mine and a 200-m-high hill, on the wind observed at JOYCE. High-resolution large-eddy simulations that complement the observations show that the spatial distribution of the wind field exhibits variations connected with the orographic flow depending on the wind direction, causing high variability in the long-term measurements of the vertical velocity.

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Lidar remote sensing of cloud formation caused by low‐level jets

Cited by 5 publications

References 29 publications

Atmospheric Boundary Layer Classification With Doppler Lidar

Atmospheric Boundary Layer Classification With Doppler Lidar

New Technique to Retrieve Tropospheric Temperature Using Vibrational and Rotational Raman Backscattering

Long-Term Observations and High-Resolution Modeling of Midlatitude Nocturnal Boundary Layer Processes Connected to Low-Level Jets

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