Barbara E. Mayes and Joshua M. Boustead – NWS WFO Omaha/Valley, NE

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Utilizing Standardized Utilizing Standardized Anomalies to Assess Synoptic Anomalies to Assess Synoptic Scale Weather Events in the Scale Weather Events in the

Central United StatesCentral United States

Barbara E. Mayes and Joshua M. Boustead – NWS WFO Omaha/Valley, NE

Mark O’Malley and Suzanne M. Fortin – NWS WFO Pleasant Hill, MO

Richard H. Grumm – NWS WFO State College, PA

13th High Plains AMS/NWA ConferenceAugust 27, 2009North Platte, NE

NATIONAL WEATHER SERVICE

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Presentation OutlinePresentation Outline

• Background– Eastern U.S. and Western U.S. studies

• Methodology• Results:

– Ranking of 20 “total” standardized anomalies– Ranking of 10 most anomalous events by

meteorological variable– Example: 11 January 1975– Return periods


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PurposePurpose

• Rank synoptic-scale systems by standardized anomalies– Put past events in

context

• Determine range of anomalies for “typical” and “significant” events– Provide a tool for

forecasters to identify “how anomalous” events may be


What does +4 to +5 mean? -4 to -5? Are these What does +4 to +5 mean? -4 to -5? Are these significant? significant?

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Previous StudiesPrevious Studies

• Eastern U.S.– Hart and Grumm 2001– Many coastal low systems,

with a few interior events

• Western U.S.– Graham and Grumm 2009– Many Pacific cutoff lows,

with some interior events

• But… what about the middle?!– Central U.S. domain– Eliminates impact of

coastal events


Eastern U.S.Eastern U.S.Western U.S.Western U.S.Gap between:Gap between:

Central U.S.Central U.S.

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MethodologyMethodology

• Data:– NCEP/NCAR Reanalysis Data (2.5° X 2.5°, 17 pressure levels)– 1/01/1948 through 12/31/2008, 6-hr time steps– Domain: 82°W to 110°W, 26°N to 55°N

• Meteorological variables:– Geopotential height, temperature, specific humidity, u and v wind components,

mean sea level pressure, and precipitable water

• Calculations, for each variable at each time step:– Calculated departure (standard deviation) from 21-day running climatological

mean, using 1971-2000 climatology, across the domain and at all standard levels– Determined greatest standardized anomalies within the domain at all levels– Ranked each variable by departures from climatology

– Calculated total anomaly (MTOTAL) by averaging max anomalies of height, temperature, precipitable water, and wind

*Note: Found errors in the February specific humidity fields; replaced with precipitable water in the MTOTAL calculation and must use with caution in general.


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Top 20 Total Anomaly EventsTop 20 Total Anomaly Events


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Top 10 Precipitable Water Anomaly Top 10 Precipitable Water Anomaly EventsEvents


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Top 10 Wind Anomaly EventsTop 10 Wind Anomaly Events


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Top 10 Height Anomaly EventsTop 10 Height Anomaly Events


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Top 10 Temperature Anomaly EventsTop 10 Temperature Anomaly Events


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Top 10 Mean Sea Level Pressure Top 10 Mean Sea Level Pressure Anomaly EventsAnomaly Events


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Example: 11 January 1975Example: 11 January 1975“The Great Storm of 1975”“The Great Storm of 1975”

• Blizzard from Dakotas to MN

– Extremely cold wind chills (-70 to -80°F)

– Up to 2 feet of snow– Zero visibility for 24 hr– Low pressure records

• Severe weather IL/IN and southeast

– Jan. thunderstorms in Duluth

– 45 tornadoes– Record high

temperatures MI to mid-Atlantic


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Example: 11 January 1975Example: 11 January 1975“The Great Storm of 1975”“The Great Storm of 1975”

• 12 fatalities• Hundreds of

injuries• Tens of thousands

of livestock lost


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Example: 22 May 2008Example: 22 May 2008

• #2 ranked MSLP anomalous event

• Lead-off day to a week of high-impact severe weather as strong upper-level low ejected across the Plains


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Example: 22 May 2008Example: 22 May 2008

• High-impact tornadoes

– Greeley/Windsor, CO– Cheyenne, WY– Hoxie, KS


Greeley, Colorado

Hoxie, Kansas

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Return PeriodsReturn Periods

• Investigate frequency of occurrence of given anomaly values

• MTOTAL:– Most frequent anomaly: 2.2– Return period of most

frequent anomaly: 0.07 months

– Number of occurrences per month of most frequent anomaly: 13.5

– Max anomaly: 4.7– Min anomaly: 0.9


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Return PeriodsReturn Periods

• Investigate frequency of occurrence of given anomaly values

• Mean sea level pressure:– Most frequent anomaly: -2.0– Return period of most

frequent anomaly: 0.22 months

– Number of occurrences per month of most frequent anomaly: 4.6

– Max anomaly (positive or negative): -13.02*

– Min anomaly (positive or negative): 0.7

* Includes tropical cyclones, which were not included in the rankings


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Summary and Future WorkSummary and Future Work

• Conclusions:– Most of the high-ranking events were indeed associated with high impact

weather– Ranked events included winter storms, severe weather and tornado

outbreaks, record cold, record high temperatures, record low pressures, and heavy rain and flooding

• Future Work:– Create clear tables relating return periods of each variable to frequency of

occurrence– Determine monthly rankings– Continue to investigate top-ranking events– Create a website with findings– Investigate connection between highly anomalous events and known

climate cycles (ENSO, MJO, NAO, etc.)– Investigate longer duration events (i.e. drought, heat outbreaks)


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Thank you!Thank you!

References

• Hart, R., and R.H. Grumm, 2001: Using normalized climatological anomalies to objectively rank extreme synoptic-scale events. Mon. Wea. Rev., 129, 2426-2442.

• Graham, R.A., and R.H. Grumm, 2009: Utilizing standardized anomalies to assess synoptic scale weather events in the western United States. Wea. Forecasting, in review.

• Eastern U.S. Anomalies Website: http://eyewall.met.psu.edu/ranking/ranking.html • Western U.S. Anomalies Website: http://ww2.slc.noaa.gov/slc/projects/anomalies/index.htm


Questions?

Email: [email protected]

WFO OAX: (402) 359-5166

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Top 20 Total Anomaly Events (Q)Top 20 Total Anomaly Events (Q)


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Top 10 Specific Humidity Anomaly Top 10 Specific Humidity Anomaly EventsEvents


Documents

Barbara E. Mayes and Joshua M. Boustead – NWS WFO Omaha/Valley, NE