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  • Author or Editor: G. Vaughan x
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J. C. Fankhauser
,
C. J. Biter
,
C. G. Mohr
, and
R. L. Vaughan

Abstract

Objective numerical techniques are applied in analyzing constant altitude aircraft measurements obtained from coordinated research flights in thunderstorm inflow regions. The approach combines meteorological and flight track data from dual or single aircraft missions in a common frame of reference and transforms the observations from original analogue format to horizontal two-dimensional Cartesian coordinates. Operational procedures guiding the data collection, intercomparison techniques for refining instrument calibrations and corrections for aircraft navigation errors are all considered.

Results of the interpolations are judged in the context of the storms' associated radar echo features. Primary applications include calculation of water vapor influx in cloud base updrafts. Evidence indicates that the fullest exploitation of the inflow mapping will come through combining kinematic fields observed concurrently by aircraft and multiple Doppler radars.

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Carl G. Mohr
,
L. Jay Miller
,
Robin L. Vaughan
, and
Harold W. Frank

Abstract

During the 1981 summer season within a 70 000 km2 area surrounding Miles City, Montana, researchers from approximately twenty institutions participated in the Cooperative Convective Precipitation Experiment (CCOPE). The measurements collected during this project comprise one of the most comprehensive datasets ever acquired in and around individual convective storms on the high plains of North America. Principal data systems utilized during CCOPE included 8 ground-based radar (7 of which had Doppler capability), 12 instrumented research aircraft, and a network of 123 surface stations.

A major data processing goal has been to combine these independently acquired mesoscale measurements into a numerical description of observed atmospheric conditions at any point in time. Using the CCOPE data archive as an example, this paper describes the procedures used to reduce these high resolution observations to a common spatial and temporal framework. The final product is a digital description of the environment similar to that employed by most modelers—a three-dimensional Cartesian coordinate system containing fields that represent the instantaneous state of the atmosphere at discrete times across the period of interest. A software package designed to facilitate the construction and analysis of these composite data structures will also be discussed.

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H. Chepfer
,
G. Cesana
,
D. Winker
,
B. Getzewich
,
M. Vaughan
, and
Z. Liu

Abstract

Two different cloud climatologies have been derived from the same NASA–Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP)-measured attenuated backscattered profile (level 1, version 3 dataset). The first climatology, named Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations–Science Team (CALIPSO-ST), is based on the standard CALIOP cloud mask (level 2 product, version 3), with the aim to document clouds with the highest possible spatiotemporal resolution, taking full advantage of the CALIOP capabilities and sensitivity for a wide range of cloud scientific studies. The second climatology, named GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP), is aimed at a single goal: evaluating GCM prediction of cloudiness. For this specific purpose, it has been designed to be fully consistent with the CALIPSO simulator included in the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) used within version 2 of the CFMIP (CFMIP-2) experiment and phase 5 of the Coupled Model Intercomparison Project (CMIP5).

The differences between the two datasets in the global cloud cover maps—total, low level (P > 680 hPa), midlevel (680 < P < 440 hPa), and high level (P < 440 hPa)—are frequently larger than 10% and vary with region.

The two climatologies show significant differences in the zonal cloud fraction profile (which differ by a factor of almost 2 in some regions), which are due to the differences in the horizontal and vertical averaging of the measured attenuated backscattered profile CALIOP profile before the cloud detection and to the threshold used to detect clouds (this threshold depends on the resolution and the signal-to-noise ratio).

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