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controlling the direction of the lidar beam with a hemispheric scanner (see Banta et al. 2002 ; Banta et al. 2006 ). The NOAA/ESRL Doppler lidars use coherent detection to measure the radial velocity component of atmospheric scatterers (typically aerosol) relative to the velocity of the lidar; “radial” refers to the direction along the instantaneous lidar beam. Since 1998, the systems have performed wind measurements from seagoing research vessels during eight field studies described in Bretherton et
controlling the direction of the lidar beam with a hemispheric scanner (see Banta et al. 2002 ; Banta et al. 2006 ). The NOAA/ESRL Doppler lidars use coherent detection to measure the radial velocity component of atmospheric scatterers (typically aerosol) relative to the velocity of the lidar; “radial” refers to the direction along the instantaneous lidar beam. Since 1998, the systems have performed wind measurements from seagoing research vessels during eight field studies described in Bretherton et
, data were collected during seven IOPs with a duration of 2–3 days, respectively. The Raman lidar systems measured mainly during nighttime, which resulted in 10 nights of data collected in Germany. Prior to the supply of all network lidar data to the assimilation centers at the universities of L’Aquila, Italy, and Hohenheim, Germany, all water vapor profiles were prepared by using the same signal processing software and by securing data quality using collocated radiosondes at each of the different
, data were collected during seven IOPs with a duration of 2–3 days, respectively. The Raman lidar systems measured mainly during nighttime, which resulted in 10 nights of data collected in Germany. Prior to the supply of all network lidar data to the assimilation centers at the universities of L’Aquila, Italy, and Hohenheim, Germany, all water vapor profiles were prepared by using the same signal processing software and by securing data quality using collocated radiosondes at each of the different
. 2002 ). Using this multiyear lidar aerosol data, interannual, intraseasonal, and long-term trends in aerosol loading, the aerosol–cloud–precipitation relationship, and the air quality over the experimental station have all been investigated ( Devara et al. 2003 ). Although a considerable number of studies have been done on the effects on weather and climate of direct radiative forcing due to aerosols, studies of aerosol-related semidirect and indirect radiative forcing are very sparse ( Houghton et
. 2002 ). Using this multiyear lidar aerosol data, interannual, intraseasonal, and long-term trends in aerosol loading, the aerosol–cloud–precipitation relationship, and the air quality over the experimental station have all been investigated ( Devara et al. 2003 ). Although a considerable number of studies have been done on the effects on weather and climate of direct radiative forcing due to aerosols, studies of aerosol-related semidirect and indirect radiative forcing are very sparse ( Houghton et
automated quality control (QC) to remove suspect data points that did not pass tests for internal and vertical consistency, gross limit checks, and rate-of-change limits for temperature, pressure, and ascension rate. Measurements of wind, moisture, and temperature fluctuations with temporal sampling ranging from 1 to 60 min were available from a collection of surface mesonetworks. Other remote sensing systems were in place at Homestead, but they were not used in the present study either because the
automated quality control (QC) to remove suspect data points that did not pass tests for internal and vertical consistency, gross limit checks, and rate-of-change limits for temperature, pressure, and ascension rate. Measurements of wind, moisture, and temperature fluctuations with temporal sampling ranging from 1 to 60 min were available from a collection of surface mesonetworks. Other remote sensing systems were in place at Homestead, but they were not used in the present study either because the
low clouds, because such instruments are more efficient and precise for this task ( Clothiaux et al. 2000 ). With a FMCW system, the vertical resolution is controlled by the quality of the system phase noise, the continuous-wave slew rate, and the sampling speed of the detected signal, while fast Fourier transform effects tend to place a limit on the minimum detection height. For a pulsed system the minimum height is predominantly determined by the length of the transmitted pulse, with no
low clouds, because such instruments are more efficient and precise for this task ( Clothiaux et al. 2000 ). With a FMCW system, the vertical resolution is controlled by the quality of the system phase noise, the continuous-wave slew rate, and the sampling speed of the detected signal, while fast Fourier transform effects tend to place a limit on the minimum detection height. For a pulsed system the minimum height is predominantly determined by the length of the transmitted pulse, with no
that are not resolvable are assumed to carry only a small fraction of the total energy of the flow and are parameterized with a subgrid (or subfilter) closure scheme. In the LES of the atmospheric CBL, the environmental parameters such as surface heating, stratification, and shear can be precisely controlled. Retrieval of spatial turbulence statistics in LES does not necessarily rely on additional assumptions like the Taylor (1938) frozen turbulence hypothesis: thermodynamic and kinematic
that are not resolvable are assumed to carry only a small fraction of the total energy of the flow and are parameterized with a subgrid (or subfilter) closure scheme. In the LES of the atmospheric CBL, the environmental parameters such as surface heating, stratification, and shear can be precisely controlled. Retrieval of spatial turbulence statistics in LES does not necessarily rely on additional assumptions like the Taylor (1938) frozen turbulence hypothesis: thermodynamic and kinematic
.1126/science.272.5265.1121 Smirnov, A. , Holben B. N. , Eck T. F. , Dubovik O. , and Slutsker I. , 2000 : Cloud screening and quality control algorithms for aerosol data base. Remote Sens. Environ. , 73 , 337 – 349 . 10.1016/S0034-4257(00)00109-7 Tafuro, A. M. , Barnaba F. , De Tomasi F. , Perrone M. R. , and Gobbi G. P. , 2006 : Saharan dust properties over the central Mediterranean. J. Atmos. Res. , 81 , 67 – 93 . 10.1016/j.atmosres.2005.11.008 Tegen, I. , Hollrigl P
.1126/science.272.5265.1121 Smirnov, A. , Holben B. N. , Eck T. F. , Dubovik O. , and Slutsker I. , 2000 : Cloud screening and quality control algorithms for aerosol data base. Remote Sens. Environ. , 73 , 337 – 349 . 10.1016/S0034-4257(00)00109-7 Tafuro, A. M. , Barnaba F. , De Tomasi F. , Perrone M. R. , and Gobbi G. P. , 2006 : Saharan dust properties over the central Mediterranean. J. Atmos. Res. , 81 , 67 – 93 . 10.1016/j.atmosres.2005.11.008 Tegen, I. , Hollrigl P
