NCAR Auto-Nowcast System
Cynthia K. Mueller,Thomas R. Saxen,Rita D. Roberts,James W. Wilson,T. Betancourt,Susan Dettling,Niles Oien,J. Yee +7 more
TLDR
The Auto-Nowcast System, a software system that produces time- and space-specific, routine short-term nowcasts of storm location, is presented and statistical verification shows that ANC is able to routinely improve over extrapolation and persistence.Abstract:
The Auto-Nowcast System (ANC), a software system that produces time- and space-specific, routine (every 5 min) short-term (0‐1 h) nowcasts of storm location, is presented. A primary component of ANC is its ability to identify and characterize boundary layer convergence lines. Boundary layer information is used along with storm and cloud characteristics to augment extrapolation with nowcasts of storm initiation, growth, and dissipation. A fuzzy logic routine is used to combine predictor fields that are based on observations (radar, satellite, sounding, mesonet, and profiler), a numerical boundary layer model and its adjoint, forecaster input, and feature detection algorithms. The ANC methodology is illustrated using nowcasts of storm initiation, growth, and dissipation. Statistical verification shows that ANC is able to routinely improve over extrapolation and persistence.read more
Citations
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Journal ArticleDOI
Summary of Convective Storm Initiation and Evolution during IHOP: Observational and Modeling Perspective
James W. Wilson,Rita D. Roberts +1 more
TL;DR: The data-rich International H2O Project (IHOP_2002) experiment is used to study convective storm initiation and subsequent evolution for all days of the experiment.
Journal ArticleDOI
Forecasting Convective Initiation by Monitoring the Evolution of Moving Cumulus in Daytime GOES Imagery
TL;DR: In this paper, the precursor signals of convective initiation were identified within sequences of 1-km-resolution visible (VIS) and 4-8-km infrared (IR) imagery from the Geostationary Operational Environmental Satellite (GOES) instrument.
Journal ArticleDOI
Nowcasting Storm Initiation and Growth Using GOES-8 and WSR-88D Data
TL;DR: In this article, the authors examined the evolution of cumulus clouds over a variety of radar-detected, boundary layer convergence features in eastern Colorado using Geostationary Operational Environmental Satellite (GOES) imagery and Weather Surveillance Radar-1988 Doppler (WSR-88D) data.
Journal ArticleDOI
A Review of High Impact Weather for Aviation Meteorology
Ismail Gultepe,Robert Sharman,Paul Williams,Binbin Zhou,Gary P. Ellrod,Patrick Minnis,Stanley B. Trier,Sarah M. Griffin,Seong Soo Yum,Bahram Gharabaghi,Wayne F. Feltz,Marouane Temimi,Zhaoxia Pu,Luke N. Storer,Philipp Kneringer,Michael Weston,Hui-ya Chuang,Ludovic Thobois,A. P. Dimri,Sebastian J. Dietz,Gutemberg Borges França,Manoel Valdonel de Almeida,F. L. Albquerque Neto +22 more
TL;DR: In this paper, the authors summarized current knowledge available for aviation operations related to meteorology and provided suggestions for necessary improvements in the measurement and prediction of weather-related parameters, new physical methods for numerical weather predictions (NWP), and next-generation integrated systems.
References
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Journal ArticleDOI
A Theory for Strong, Long-Lived Squall Lines
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TL;DR: In this article, three algorithms extract information on precipitation type, structure, and amount from operational radar and rain gauge data, and statistically summarize the vertical structure of the radar echoes, and determine precipitation rates and amounts on high spatial resolution.
Journal ArticleDOI
TITAN: Thunderstorm Identification, Tracking, Analysis, and Nowcasting—A Radar-based Methodology
Michael Dixon,Gerry Wiener +1 more
TL;DR: In this paper, a real-time automated identification, tracking, and short-term forecasting of thunderstorms based on volume-scan weather radar data is presented, with the emphasis on the concepts upon which the methodology is based.
Journal ArticleDOI
The Storm Cell Identification and Tracking Algorithm: An Enhanced WSR-88D Algorithm
J. T. Johnson,Pamela L. MacKeen,Arthur Witt,E. De Wayne Mitchell,Gregory J. Stumpf,Michael D. Eilts,Kevin W. Thomas +6 more
TL;DR: The SCIT algorithm, a centroid tracking algorithm with improved methods of identifying storms (both isolated and clustered or line storms), correctly identified 68% of all cells with maximum reflectivities over 40 dB Z and 96% ofall cells withmaximum reflectivities of 50 dBZ or greater.
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