Analysis of Mesoscale Atmospheric Flows above Mature Deep Convection Using Super Rapid Scan Geostationary Satellite Data

Super Rapid Scan Operations for the Geostationary Operational Environmental Satellite (GOES) R series (SRSOR) using GOES-14 have made experimentation with 1-min time-step data possible prior to the launch of the new satellite. A mesoscale atmospheric motion vector (mAMV) program is utilized in SRSOR...

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Bibliographic Details
Published in:Journal of applied meteorology and climatology 2016-09, Vol.55 (9), p.1859-1887
Main Authors: Apke, Jason M., Mecikalski, John R., Jewett, Christopher P.
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Atmospheric flows
Atmospheric motion
Bubbling
Case studies
Clouds
Convection
Convective clouds
Divergence
Doppler radar
Doppler sonar
Fields
Geostationary satellites
GOES satellites
Mesoscale phenomena
Meteorological satellites
Methods
Regions
Satellite data
Satellites
Signatures
Storms
Supercells
Synchronous satellites
Thunderstorms
Vorticity
Weather
Weather forecasting
Wind
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Summary:Super Rapid Scan Operations for the Geostationary Operational Environmental Satellite (GOES) R series (SRSOR) using GOES-14 have made experimentation with 1-min time-step data possible prior to the launch of the new satellite. A mesoscale atmospheric motion vector (mAMV) program is utilized in SRSOR with a Barnes analysis to produce objectively analyzed flow fields at the cloud tops of deep convection. Two nonsupercell and four supercell storm cases are analyzed. Data from the SRSOR mAMV analysis are compared with both multi-Doppler analyses when available and idealized convection cases within the Weather Research and Forecasting (WRF) Model framework. It is found that using SRSOR data provides several additional trackable targets to produce mAMVs in rapidly "bubbling" regions at the deep convective cloud-top level not previously available at lower temporal resolutions (
ISSN:1558-8424
1558-8432
DOI:10.1175/jamc-d-15-0253.1