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312 JOURNAL OF APPLIED METEOROLOGY VOLUME30Lidar Observations of Banded Convection during BLX83 R. A. FERRARE,* J. L. SCHOLS~' AND F.. W. ELORANTA Department of Meteorology, University of Wisconsin, Madison, Wisconsin R. COULTEREnvironmental Research Dgvision, Argonne National Laboratory, Argonne, Illinois(Manuscript received 23 April 1990, in final form 21 August 1990
312 JOURNAL OF APPLIED METEOROLOGY VOLUME30Lidar Observations of Banded Convection during BLX83 R. A. FERRARE,* J. L. SCHOLS~' AND F.. W. ELORANTA Department of Meteorology, University of Wisconsin, Madison, Wisconsin R. COULTEREnvironmental Research Dgvision, Argonne National Laboratory, Argonne, Illinois(Manuscript received 23 April 1990, in final form 21 August 1990
of cirrus occurrence of nearly 50% all year-round ( Goldfarb et al. 2001 ). This is consistent with visual investigations performed on board aircraft ( Clodman 1957 ). Lidar observations give access to several cirrus characteristics such as the cloud absolute geometric height, cloud thickness, backscattering ratio (called here intensity, which is related to the number of particles, their size, and their mean backscattering efficiencies), and its temporal variability (related to the horizontal
of cirrus occurrence of nearly 50% all year-round ( Goldfarb et al. 2001 ). This is consistent with visual investigations performed on board aircraft ( Clodman 1957 ). Lidar observations give access to several cirrus characteristics such as the cloud absolute geometric height, cloud thickness, backscattering ratio (called here intensity, which is related to the number of particles, their size, and their mean backscattering efficiencies), and its temporal variability (related to the horizontal
backscatter power close to the flight level shows that there is a cloud layer that extends to ~600 m above the flight level. Above this altitude, lidar backscatter power is dominated by the background molecular backscatter, which slowly decreases with height. Figures 1c and 1d show more clearly the impact of overlap correction based on 10-min WCL-I observations from the same flight. A narrow band of measurements near the flight level in Fig. 1c is biased low because of the incomplete overlap, which is
backscatter power close to the flight level shows that there is a cloud layer that extends to ~600 m above the flight level. Above this altitude, lidar backscatter power is dominated by the background molecular backscatter, which slowly decreases with height. Figures 1c and 1d show more clearly the impact of overlap correction based on 10-min WCL-I observations from the same flight. A narrow band of measurements near the flight level in Fig. 1c is biased low because of the incomplete overlap, which is
the Physical Sciences Division of the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (online at http://www.esrl.noaa.gov/psd/data/gridded/reanalysis ). Upper-air observations from Kelowna, British Columbia (255 km east of Whistler), were acquired from the University of Wyoming’s radiosonde data archive (online at http://weather.uwyo.edu/upperair/ ). 3. Results Backscatter ratio data from the CORALNet lidar provide depictions of relative aerosol
the Physical Sciences Division of the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (online at http://www.esrl.noaa.gov/psd/data/gridded/reanalysis ). Upper-air observations from Kelowna, British Columbia (255 km east of Whistler), were acquired from the University of Wyoming’s radiosonde data archive (online at http://weather.uwyo.edu/upperair/ ). 3. Results Backscatter ratio data from the CORALNet lidar provide depictions of relative aerosol
AUGUST 1986 W.S. LEWELLEN AND R. I. SYKES 1145Analysis of Concentration Fluctuations from Lidar Observations of Atmospheric Plumes W. S. LEWELLEN AND R. I. SYKESAeronautical Research Associates of Princeton, Inc., Princeton, NJ 08540(Manuscript received 14 September 1985, in final form 13 Ja~luary 1986)ABSTRACT A series of nearly instantaneous vertical cross sections of power
AUGUST 1986 W.S. LEWELLEN AND R. I. SYKES 1145Analysis of Concentration Fluctuations from Lidar Observations of Atmospheric Plumes W. S. LEWELLEN AND R. I. SYKESAeronautical Research Associates of Princeton, Inc., Princeton, NJ 08540(Manuscript received 14 September 1985, in final form 13 Ja~luary 1986)ABSTRACT A series of nearly instantaneous vertical cross sections of power
shortwave radiation streams. The unique synergy of the A-Train constellation is due to the broad diversity of instrumentation that includes the active remote sensors Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ; Winker et al. 2009 ), including the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP), and the first cloud-sensing millimeter-wave radar in space ( CloudSat ; Im et al. 2006 ). The active remote sensors are complemented by passive measurements that
shortwave radiation streams. The unique synergy of the A-Train constellation is due to the broad diversity of instrumentation that includes the active remote sensors Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ; Winker et al. 2009 ), including the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP), and the first cloud-sensing millimeter-wave radar in space ( CloudSat ; Im et al. 2006 ). The active remote sensors are complemented by passive measurements that
mode by a factor of 5, the calculated depolarization histogram matches quite well with the observations as seen in Fig. 4 , with a median value and IQR of 9.2% and 5.2%, respectively. Using scaling factors of 2 or 10 leads to median calculated depolarization values of 6.0% and 11.8%, respectively (not shown). As shown in Fig. 5 , the observed vertical distribution of lidar depolarization below cloud base between 2200 and 0000 UTC is quite well matched by the simulations using the aerosol
mode by a factor of 5, the calculated depolarization histogram matches quite well with the observations as seen in Fig. 4 , with a median value and IQR of 9.2% and 5.2%, respectively. Using scaling factors of 2 or 10 leads to median calculated depolarization values of 6.0% and 11.8%, respectively (not shown). As shown in Fig. 5 , the observed vertical distribution of lidar depolarization below cloud base between 2200 and 0000 UTC is quite well matched by the simulations using the aerosol
1. Introduction Since the launch of CloudSat ( Stephens et al. 2002 , 2008 ) and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) ( Winker et al. 2003 , 2007 , 2009 ) in April 2006, when they joined the A-Train constellation, they have provided detailed information about cloud vertical structures. Both satellites are equipped with active sensors; CALIPSO carries the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar, and CloudSat carries the
1. Introduction Since the launch of CloudSat ( Stephens et al. 2002 , 2008 ) and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) ( Winker et al. 2003 , 2007 , 2009 ) in April 2006, when they joined the A-Train constellation, they have provided detailed information about cloud vertical structures. Both satellites are equipped with active sensors; CALIPSO carries the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar, and CloudSat carries the
, and E. E. Uthe , 1979 : An automated method for determining the mixing depth from lidar observations . Atmos. Environ. , 13 , 1051 – 1056 . Eresmaa , N. , A. Karppinen , S. M. Joffre , J. Räsänen , and H. Talvitie , 2006 : Mixing height determination by ceilometer . Atmos. Chem. Phys. , 6 , 1485 – 1493 . Haeffelin , M. , and Coauthors , 2011 : Evaluation of mixing-height retrievals from automatic profiling lidars and ceilometers in view of future integrated networks
, and E. E. Uthe , 1979 : An automated method for determining the mixing depth from lidar observations . Atmos. Environ. , 13 , 1051 – 1056 . Eresmaa , N. , A. Karppinen , S. M. Joffre , J. Räsänen , and H. Talvitie , 2006 : Mixing height determination by ceilometer . Atmos. Chem. Phys. , 6 , 1485 – 1493 . Haeffelin , M. , and Coauthors , 2011 : Evaluation of mixing-height retrievals from automatic profiling lidars and ceilometers in view of future integrated networks
M^RCH1974 NOONKESTER ET AL. 249Concurrent FM-CW Radar and Lidar Observations of the Boundary Layer V. R. NOONKESTER, D. R. JENSEN AND J. H. R~Ca~ER Naval Electronics Laboratory Center, San Diego, Calif. 92152 W. VIEZEE AND R. T. H. COnL~SStanford Research Institute, Menlo 2ark, Calif. 94025(Manuscript received 11 July 1973, in revised form 30 November 1973)ABSTRACT
M^RCH1974 NOONKESTER ET AL. 249Concurrent FM-CW Radar and Lidar Observations of the Boundary Layer V. R. NOONKESTER, D. R. JENSEN AND J. H. R~Ca~ER Naval Electronics Laboratory Center, San Diego, Calif. 92152 W. VIEZEE AND R. T. H. COnL~SStanford Research Institute, Menlo 2ark, Calif. 94025(Manuscript received 11 July 1973, in revised form 30 November 1973)ABSTRACT
