using anomalies to forecast high impact events david l. beachler noaa/national weather service...
TRANSCRIPT
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Using Anomalies to Forecast High Impact Events
David L. Beachler NOAA/National Weather Service Forecast Office Chicago IL
14-16 Mar 2012 Great Lakes Operational Meteorology Workshop Chicago IL
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An anomalous outline…
• Salient Points:– Anomalies– EPS
• Cases:– Eastern United States Winter Storm: 1-2Feb2011– Western Great Lakes Flood (Ridge Roller): 21-
23July2010
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Why such an outlier?• Outliers in a data set can pose significant
problems– Visually examine data…aids in identifying outliers
• Envelope of possibilities• Clustering
– NWP outliers at times are difficult
• Operational Solutions at times offer chaos– EPS at times offers focus & generally less chaos
• Once identified then what? – Forecasters leverage the significance
• Tempted to eliminate…to simplify the forecast
Outliers have their place• Forecasters hone their skills along the fringes
– Live on the edge through NWP forecasts• Aid in fine-tuning EPS• Eliminate the noise
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EPS: Big Picture• EPS provides the forest amongst the trees!– PATTERN RECOGNITION
• Quick assessment of basic parameters– U-wind :FGEN/Trowal/Potential temp gradient
• East-West– Positive between 180-360 C– Negative between 360-180 C
– V-wind :Moisture transport• North-South
– Positive between 90-270 C– Negative between 270-90 C
– PWAT– MFLUX
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Anomalous U-windStrengthening Easterly Jet
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Anomalous U-windStrengthening Easterly Jet
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GEFS: 24-hr QPF
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SREF: Snowfall Threats
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Impacts…
• Heavy Snow from OK to MI– Chicago 21.2” (72hr total)
• South of Low Ice– Southern Plains/New England– ~0.5” Ice Indiana
• Anomalous LLVL Easterly Jet• Inertial Gravity Wave (IGW)?– Likely resulted in Thunder/Blizzard conds from MO/IL• 15Dec1987 Observed IGW similar to 31Jan-
2Feb2011
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Western Great Lakes Flood: 21-23July2010
• Dominant Subtropical Ridge– Galarneau & Bosart 2006 coined “ridge rollers”
• Flooding aligned with Anomalous PWAT/Ridge– 23-24July2010: Heavy Rainfall (flooding)
IA > 15”• Failure of Lake Delhi Dam (Eastern IA)
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Composite: 17-26July2010
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Plume Forecast
• Offer point based analysis • Probabilistic approach to DSS • Visualize clustering and outliers with
mean
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Service Assessment: Record Floods Middle Tennessee & Western Kentucky 1-4 May
2010
• At the time of this report, a paper under peer review entitled “The Devastating Mid-Mississippi Valley Floods of 1-2 May 2010”, by Richard H. Grumm, National Weather Service, noted the following:“The event of 1-2 May 2010 had …key ingredients for a significant heavy rainfall event (Doswell 1996), and for historic events (Bodner 2011); This case is a classic case on the value ofanomalies in identifying a potentially significant heavy rainfall event... [which] clearly defined a threat of a Maddox Synoptic event type with a strong southerly jet and a surge of high PW [precipitable water] air into the region.”
• As the NWS focuses increasingly on Decision Support Services, offices and operational staff at all levels should place more attention on anomalies and pattern recognition in advance of potentially significant events.
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Closing…
• All events demonstrate some anomaly• Noise amongst EPS suggests lower
confidence– Forecasters live on the edge and can improve
through operational envelope of solutions
• Minimal spread provides better vision into the future– Ability to provide high-confidence forecast for
DSS
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References
• Web resources: http://cms.met.psu.edu/sref/– SREF/GEFS options and Ensemble Threats Page
• Forsythe, J.M., S.Q. Kidder, S.J. Kusselson, A.S. Jones, T.H. Vonder Haar, 2009: Increasing the land coverage of blended multisensory total precipitable water products for weather analysis. 16th Conference on Satellite Meteorology and Oceanography, Phoenix, Arizona. http://ams.confex.com/ams/89annual/techprogram/paper 149348.htm
• Grumm, R.H. and R. Hart. 2001: Standardized Anomalies Applied to Significant Cold Season Weather Events: Preliminary Findings. Wea. and Fore., 16,736–754.
• Hart, R. E., and R. H. Grumm, 2001: Using normalized climatological anomalies to rank synoptic scale events objectively. Mon. Wea. Rev., 129, 2426–2442.
• Junker, N. W., R. H. Grumm, R. Hart, L. F. Bosart, K. M. Bell, and F. J. Pereira, 2008: Use of standardized anomaly fields to anticipate extreme rainfall in the mountains of northern California. Wea. Forecasting,23, 336–356.
• Kusselson, S.J., S.Q. Kidder, J.M. Forsythe, A.J Jones, L. Zhao, 2009: An update on the operational implementation of blended total precipitable water products. 23rd Conference on Hydrology, Phoenix, AZ. http://ams.confex.com/ams/89annual/techprogram/paper_142967.htm
• http://www.nws.noaa.gov/os/assessments/pdfs/Tenn_Flooding.pdf NWS Service Assessment Tennessee Flood
• THE USE OF ENSEMBLE AND ANOMALY DATA TO ANTICIPATE EXTREME FLOOD EVENTS IN THE NORTHEASTERN U.S. – Neil A. Stuart(1), Richard H. Grumm(2), John Cannon(3), and Walt Drag(4)