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. N. Holben , 2003 : Global monitoring of air pollution over land from the Earth Observing System- Terra Moderate Resolution Imaging Spectroradiometer (MODIS). J. Geophys. Res. , 108 , 4661 . doi:10.1029/2002JD003179 . Davis , K. J. , N. Gamage , C. R. Hagelberg , C. Kiemle , D. H. Lenschow , and P. P. Sullivan , 2000 : An objective method for deriving atmospheric structure from airborne lidar observations. J. Atmos. Oceanic Technol. , 17 , 1455 – 1468 . De Young
. N. Holben , 2003 : Global monitoring of air pollution over land from the Earth Observing System- Terra Moderate Resolution Imaging Spectroradiometer (MODIS). J. Geophys. Res. , 108 , 4661 . doi:10.1029/2002JD003179 . Davis , K. J. , N. Gamage , C. R. Hagelberg , C. Kiemle , D. H. Lenschow , and P. P. Sullivan , 2000 : An objective method for deriving atmospheric structure from airborne lidar observations. J. Atmos. Oceanic Technol. , 17 , 1455 – 1468 . De Young
the global system. 2. Daytime cirrus TOA cloud radiative forcing calculations at Greenbelt, Maryland a. 2012 MPLNET cirrus cloud subset at Greenbelt, Maryland One year of continuous lidar-based cloud observations was collected in 2012 at the NASA Goddard Space Flight Center (GSFC) in Greenbelt, Maryland (38.99°N, 76.84°W; 0.050 km MSL) using a 532-nm NASA Micro Pulse Lidar Network instrument (MPLNET; http://mplnet.gsfc.nasa.gov/ ; Welton et al. 2001 ; Campbell et al. 2002 ). Cirrus clouds were
the global system. 2. Daytime cirrus TOA cloud radiative forcing calculations at Greenbelt, Maryland a. 2012 MPLNET cirrus cloud subset at Greenbelt, Maryland One year of continuous lidar-based cloud observations was collected in 2012 at the NASA Goddard Space Flight Center (GSFC) in Greenbelt, Maryland (38.99°N, 76.84°W; 0.050 km MSL) using a 532-nm NASA Micro Pulse Lidar Network instrument (MPLNET; http://mplnet.gsfc.nasa.gov/ ; Welton et al. 2001 ; Campbell et al. 2002 ). Cirrus clouds were
spatial structure of flows in complex terrain at the local to mesoscale (1–100 km). Making these observations is an important but difficult challenge. Much progress has been made in obtaining observational information on the spatial wind structure for meteorological and environmental applications by Doppler lidars that were developed in the late 1960s [see Huffaker and Hardesty (1996) for a review]. Ground-based Doppler lidars have provided the research community with important new insights of
spatial structure of flows in complex terrain at the local to mesoscale (1–100 km). Making these observations is an important but difficult challenge. Much progress has been made in obtaining observational information on the spatial wind structure for meteorological and environmental applications by Doppler lidars that were developed in the late 1960s [see Huffaker and Hardesty (1996) for a review]. Ground-based Doppler lidars have provided the research community with important new insights of
application considered. 4. LCS over Hong Kong International Airport We now use the FDFTLE method described above to locate LCS in wind velocity data from coherent Doppler radar and lidar observations over Hong Kong International Airport. For such observational datasets, two constraints limit the straightforward extraction of LCS using the FTLE field Eq. (5) . First, remote sensing only recovers the line-of-sight velocity component relative to the instrument, and hence the cross-beam components of the
application considered. 4. LCS over Hong Kong International Airport We now use the FDFTLE method described above to locate LCS in wind velocity data from coherent Doppler radar and lidar observations over Hong Kong International Airport. For such observational datasets, two constraints limit the straightforward extraction of LCS using the FTLE field Eq. (5) . First, remote sensing only recovers the line-of-sight velocity component relative to the instrument, and hence the cross-beam components of the
difficult to know how representative they are. Even studies with routine aircraft observations ( Vogelmann et al. 2012 ) still only have a relatively small number of flights. Other studies have utilized tower data to examine w statistics (e.g., Wyngaard et al. 1971 ; Wood et al. 2010 ; Liu et al. 2011 ). The short height of the towers (relative to the depth of the daytime boundary layer), however, has caused some researchers to focus on the analysis of shallow internal boundary layers (e
difficult to know how representative they are. Even studies with routine aircraft observations ( Vogelmann et al. 2012 ) still only have a relatively small number of flights. Other studies have utilized tower data to examine w statistics (e.g., Wyngaard et al. 1971 ; Wood et al. 2010 ; Liu et al. 2011 ). The short height of the towers (relative to the depth of the daytime boundary layer), however, has caused some researchers to focus on the analysis of shallow internal boundary layers (e
turbulence parameterization in these situations is highly needed. The data and results from our case study can be used to develop and evaluate turbulence parameterizations for complex terrain. Among the many observations made during T-REX IOP 1, scanning aerosol lidar data proved to be particularly helpful in interpreting the results of the TKE budget analysis and in providing a more complete understanding of temporal and spatial variability of turbulence in mountainous terrain. Acknowledgments This work
turbulence parameterization in these situations is highly needed. The data and results from our case study can be used to develop and evaluate turbulence parameterizations for complex terrain. Among the many observations made during T-REX IOP 1, scanning aerosol lidar data proved to be particularly helpful in interpreting the results of the TKE budget analysis and in providing a more complete understanding of temporal and spatial variability of turbulence in mountainous terrain. Acknowledgments This work
1. Introduction The knowledge of the cloud properties has been recently identified as a mandatory step to reach if the operational weather and climate change forecasts are to be improved ( Stephens et al. 2002 ; Stephens 2005 ). In the framework of the space missions devoted to monitoring the microphysical, radiative, and dynamic properties of clouds at a global scale using cloud radar and lidar combinations [CloudSat/Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO
1. Introduction The knowledge of the cloud properties has been recently identified as a mandatory step to reach if the operational weather and climate change forecasts are to be improved ( Stephens et al. 2002 ; Stephens 2005 ). In the framework of the space missions devoted to monitoring the microphysical, radiative, and dynamic properties of clouds at a global scale using cloud radar and lidar combinations [CloudSat/Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO
measurements using a Doppler lidar have been presented in this paper. The lidar observations also show that near-surface winds often do not “see” many of the changes in the flow aloft, some of which were significant. Thus, near-surface measurements, or even low-resolution profile measurements, often produce misleading results when extrapolated to hub height. Such results can lead to significant error in estimates of turbine power output. Lidar datasets extending over multiweek periods, such as NEAQS and
measurements using a Doppler lidar have been presented in this paper. The lidar observations also show that near-surface winds often do not “see” many of the changes in the flow aloft, some of which were significant. Thus, near-surface measurements, or even low-resolution profile measurements, often produce misleading results when extrapolated to hub height. Such results can lead to significant error in estimates of turbine power output. Lidar datasets extending over multiweek periods, such as NEAQS and
JUNE 1969NOTES AND CORRESPONDENCE443NOTES AND CORRESPONDENCELidar Observations of the Diffusion and Rise of Stack Plumes1WARREN B. JOHNSON, JR.1. IntroductionThe lidar, or laser radar, which was developed formeteorological use by Stanford Research Institute in1963, has important applications in air pollution research (Johnson, 1969; Hamilton, 1966; Barrett andBen-Dov, 1967). A recent experimental program carriedout for the National Air Pollution Control Administration involved lidar
JUNE 1969NOTES AND CORRESPONDENCE443NOTES AND CORRESPONDENCELidar Observations of the Diffusion and Rise of Stack Plumes1WARREN B. JOHNSON, JR.1. IntroductionThe lidar, or laser radar, which was developed formeteorological use by Stanford Research Institute in1963, has important applications in air pollution research (Johnson, 1969; Hamilton, 1966; Barrett andBen-Dov, 1967). A recent experimental program carriedout for the National Air Pollution Control Administration involved lidar
both shallow and deep convection ( Fletcher and Bretherton 2010 ; Hohenegger and Bretherton 2011 ), there has been little evaluation of this framework using observations (e.g., limited evaluation in Lareau et al. 2018 ). As such, the goal of this paper is to seek observational evidence supporting, or refuting, the CIN/TKE framework as a discriminator between shallow and deep convective outcomes. This is accomplished using radar, lidar, and radiosonde observations to quantify subcloud and cloud
both shallow and deep convection ( Fletcher and Bretherton 2010 ; Hohenegger and Bretherton 2011 ), there has been little evaluation of this framework using observations (e.g., limited evaluation in Lareau et al. 2018 ). As such, the goal of this paper is to seek observational evidence supporting, or refuting, the CIN/TKE framework as a discriminator between shallow and deep convective outcomes. This is accomplished using radar, lidar, and radiosonde observations to quantify subcloud and cloud
