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

1. Utilizing Standardized Anomalies to Assess Synoptic Scale Weather Events in the Central 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 Conference August 27, 2009 North Platte, NE NATIONAL WEATHER SERVICE

2. Presentation 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 NATIONAL WEATHER SERVICE

3. Purpose • 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 significant? NATIONAL WEATHER SERVICE

4. Previous 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. Western U.S. Gap between: Central U.S. NATIONAL WEATHER SERVICE

5. Methodology • 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. NATIONAL WEATHER SERVICE

6. Top 20 Total Anomaly Events NATIONAL WEATHER SERVICE

7. Top 10 Precipitable Water Anomaly Events NATIONAL WEATHER SERVICE

8. Top 10 Wind Anomaly Events NATIONAL WEATHER SERVICE

9. Top 10 Height Anomaly Events NATIONAL WEATHER SERVICE

10. Top 10 Temperature Anomaly Events NATIONAL WEATHER SERVICE

11. Top 10 Mean Sea Level Pressure Anomaly Events NATIONAL WEATHER SERVICE

12. Example: 11 January 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 NATIONAL WEATHER SERVICE

13. Example: 11 January 1975“The Great Storm of 1975” • 12 fatalities • Hundreds of injuries • Tens of thousands of livestock lost NATIONAL WEATHER SERVICE

14. Example: 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 NATIONAL WEATHER SERVICE

15. Example: 22 May 2008 • High-impact tornadoes • Greeley/Windsor, CO • Cheyenne, WY • Hoxie, KS Greeley, Colorado Hoxie, Kansas NATIONAL WEATHER SERVICE

16. Return 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 NATIONAL WEATHER SERVICE

17. Return 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 NATIONAL WEATHER SERVICE

18. Summary 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) NATIONAL WEATHER SERVICE

19. 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: Barbara.Mayes@noaa.gov WFO OAX: (402) 359-5166 NATIONAL WEATHER SERVICE

20. Top 20 Total Anomaly Events (Q) NATIONAL WEATHER SERVICE

21. Top 10 Specific Humidity Anomaly Events NATIONAL WEATHER SERVICE