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  • Author or Editor: P. A. Miller x
  • Journal of Applied Meteorology and Climatology x
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Virendra P. Ghate
,
Bruce A. Albrecht
,
Mark A. Miller
,
Alan Brewer
, and
Christopher W. Fairall

Abstract

Observations made during a 24-h period as part of the Variability of the American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study Regional Experiment (VOCALS-REx) are analyzed to study the radiation and turbulence associated with the stratocumulus-topped marine boundary layer (BL). The first 14 h exhibited a well-mixed (coupled) BL with an average cloud-top radiative flux divergence of ~130 W m−2; the BL was decoupled during the last 10 h with negligible radiative flux divergence. The averaged radiative cooling very close to the cloud top was −9.04 K h−1 in coupled conditions and −3.85 K h−1 in decoupled conditions. This is the first study that combined data from a vertically pointing Doppler cloud radar and a Doppler lidar to yield the vertical velocity structure of the entire BL. The averaged vertical velocity variance and updraft mass flux during coupled conditions were higher than those during decoupled conditions at all levels by a factor of 2 or more. The vertical velocity skewness was negative in the entire BL during coupled conditions, whereas it was weakly positive in the lower third of the BL and negative above during decoupled conditions. A formulation of velocity scale is proposed that includes the effect of cloud-top radiative cooling in addition to the surface buoyancy flux. When scaled by the velocity scale, the vertical velocity variance and coherent downdrafts had similar magnitude during the coupled and decoupled conditions. The coherent updrafts that exhibited a constant profile in the entire BL during both the coupled and decoupled conditions scaled well with the convective velocity scale to a value of ~0.5.

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Eugene E. Clothiaux
,
Thomas P. Ackerman
,
Gerald G. Mace
,
Kenneth P. Moran
,
Roger T. Marchand
,
Mark A. Miller
, and
Brooks E. Martner

Abstract

The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Program is deploying sensitive, millimeter-wave cloud radars at its Cloud and Radiation Test Bed (CART) sites in Oklahoma, Alaska, and the tropical western Pacific Ocean. The radars complement optical devices, including a Belfort or Vaisala laser ceilometer and a micropulse lidar, in providing a comprehensive source of information on the vertical distribution of hydrometeors overhead at the sites. An algorithm is described that combines data from these active remote sensors to produce an objective determination of hydrometeor height distributions and estimates of their radar reflectivities, vertical velocities, and Doppler spectral widths, which are optimized for accuracy. These data provide fundamental information for retrieving cloud microphysical properties and assessing the radiative effects of clouds on climate. The algorithm is applied to nine months of data from the CART site in Oklahoma for initial evaluation. Much of the algorithm’s calculations deal with merging and optimizing data from the radar’s four sequential operating modes, which have differing advantages and limitations, including problems resulting from range sidelobes, range aliasing, and coherent averaging. Two of the modes use advanced phase-coded pulse compression techniques to yield approximately 10 and 15 dB more sensitivity than is available from the two conventional pulse modes. Comparison of cloud-base heights from the Belfort ceilometer and the micropulse lidar confirms small biases found in earlier studies, but recent information about the ceilometer brings the agreement to within 20–30 m. Merged data of the radar’s modes were found to miss approximately 5.9% of the clouds detected by the laser systems. Using data from only the radar’s two less-sensitive conventional pulse modes would increase the missed detections to 22%–34%. A significant remaining problem is that the radar’s lower-altitude data are often contaminated with echoes from nonhydrometeor targets, such as insects.

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Ben C. Bernstein
,
Frank McDonough
,
Marcia K. Politovich
,
Barbara G. Brown
,
Thomas P. Ratvasky
,
Dean R. Miller
,
Cory A. Wolff
, and
Gary Cunning

Abstract

The “current icing potential” (CIP) algorithm combines satellite, radar, surface, lightning, and pilot-report observations with model output to create a detailed three-dimensional hourly diagnosis of the potential for the existence of icing and supercooled large droplets. It uses a physically based situational approach that is derived from basic and applied cloud physics, combined with forecaster and onboard flight experience from field programs. Both fuzzy logic and decision-tree logic are applied in this context. CIP determines the locations of clouds and precipitation and then estimates the potential for the presence of supercooled liquid water and supercooled large droplets within a given airspace. First developed in the winter of 1997/98, CIP became an operational National Weather Service and Federal Aviation Administration product in 2002, providing real-time diagnoses that allow users to make route-specific decisions to avoid potentially hazardous icing. The CIP algorithm, its individual components, and the logic behind them are described.

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David B. Mechem
,
Carly S. Wittman
,
Matthew A. Miller
,
Sandra E. Yuter
, and
Simon P. de Szoeke

Abstract

Marine boundary layer clouds are modified by processes at different spatial and temporal scales. To isolate the processes governing aerosol–cloud–precipitation interactions, multiday synoptic variability of the environment must be accounted for. Information on the location of low clouds relative to the ridge–trough pattern gives insight into how cloud properties vary as a function of environmental subsidence and stability. The technique of self-organizing maps (SOMs) is employed to objectively classify the 500-hPa geopotential height patterns for 33 years of reanalysis fields (ERA-Interim) into pretrough, trough, posttrough, ridge, and zonal-flow categories. The SOM technique is applied to a region of prevalent marine low cloudiness over the eastern North Atlantic Ocean that is centered on the Azores island chain, the location of a long-term U.S. Department of Energy observation site. The Azores consistently lie in an area of substantial variability in synoptic configuration, thermodynamic environment, and cloud properties. The SOM method was run in two ways to emphasize multiday and seasonal variability separately. Over and near the Azores, there is an east-to-west sloshing back and forth of the western edge of marine low clouds associated with different synoptic states. The different synoptic states also exhibit substantial north–south variability in the position of high clouds. For any given month of the year, there is large year-to-year variability in the occurrence of different synoptic states. Hence, estimating the climatological behavior of clouds from short-term field campaigns has large uncertainties. This SOM approach is a robust method that is broadly applicable to characterizing synoptic regimes for any location.

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