1. “Effects of Pacific Sea Surface Temperature (SST) Anomalies on the Climate of Southern South Carolina and Northern Coastal Georgia ” Whitney Albright Joseph Calderone Frank Alsheimer NWS Forecast Office Charleston

2. 2 Outline Introduction/Objectives Background Methodology Results Summary Acknowledgements

3. 3 Introduction/Objectives Purpose: Quantify the effects of above or below normal Pacific SSTs on winter climatology in the southern South Carolina and northern coastal Georgia region Big Picture: Notify water managers and other weather sensitive industries to the potential of moderate to high impact weather as far in advance as possible

4. 4 Background The fluctuation of equatorial SSTs between the eastern and western Pacific, and the associated pressure fluctuation, is known as the El Niño Southern Oscillation (ENSO). SSTs above normal are considered El Niño events, while SSTs below normal are considered La Niña events. This atmospheric phenomenon is a result of the combination of several atmospheric and oceanic factors including changes in surface easterly winds, jet stream location, and subsurface oceanic temperatures. http://www.bom.gov.au/lam/climate/levelthree/analclim/elnino.htm

5. Neutral conditions El Niño conditions La Niña conditions http://www.cpc.noaa.gov/products/analysis_monitoring/ensocycle/meansst.shtml http://www.cpc.noaa.gov/products/analysis_monitoring/ensocycle/ensocycle.shtml

6. Background: Current Accepted Impacts _______________________________________ SOUTH CAROLINA & GEORGIA

7. 7 Background (Cont.) Anomalies in Pacific Equatorial Sea Surface Temperatures are known to have an impact on winter weather and climate in the southern United States. As previously mentioned, this project determines exactly what some of these impacts are in parts of South Carolina and Georgia

8. 8 Methodology: Procedure Step 1: Acquired raw SST anomaly values from the Climate Prediction Center (CPC) for 1950 to 2006 (values from the Nino 3.4 region) http://www.cpc.noaa.gov/products/analysis_monitoring/ensostuff/nino_regions.shtml

9. 9 Methodology: Procedure Step 2: Defined El Niño(EN)/La Niña(LN) Categories –Took average of monthly SST anomaly values for December to April from 1950 to 2006 –Then classified each year as a certain event based on its average anomaly value The categories were defined as follows: Strong EN≥+0.65 Weak EN+0.30 to +0.64 Neutral-0.29 to +0.29 Weak LN-0.64 to -0.30 Strong LN≤-0.65

10. 10 Methodology: Procedure Step 3: –Acquired monthly maximum, minimum, and average temperatures, and precipitation amounts from 1950 to 2006 for Charleston SC, Savannah GA, Walterboro SC and Fort Stewart GA from the National Climate Data Center (NCDC) –Sorted data based on EN/LN category. Average Max Temp Values CHS DECJANFEBMARAPR Strong EN60.355.257.163.871.5 Weak EN58.855.757.764.773.2 Neutral59.857.860.36672.8 Weak LN58.257.560.165.473.3 Strong LN60.5 6266.773.6 Average59.557.359.465.372.9

11. 11 Methodology: Procedure –Found all days since 1950 when the minimum temperature was below 17 degrees and when the maximum temperature was below 32 degrees. –Classify these days as having occurred during one of the defined categories. CHS DECJANFEBMARAPR Strong EN23400 Weak EN07210 Neutral88000 Weak LN64100 Strong LN15100 Total1727810 Average3.45.41.60.20.0 # OF DAYS WITH MIN TEMP 17 DEGREES OR BELOW Step 4: Retrieved “extreme” temperature data for the 4 locations from NCDC

12. 12 Methodology: Procedure Step 5: Acquired severe hail, tornado, and severe wind data for the Charleston Weather Forecast Office County Warning Area from the NCDC Storm Events Database –Found total number of days in each month for each year that the above conditions took place and sorted them by category. ___________________________________________________________ NUMBER OF DAYS PER MONTH ON WHICH HAIL OCCURRED FOR GEORGIA AND SOUTH CAROLINA COUNTIES DECJANFEBMARAPR Strong EN0741723 Weak EN0041128 Neutral011711 Weak LN490520 Strong LN0021216 Average0.83.42.210.419.6

13. 13 Results: Defined ENSO Categories Maximum Daily Temperatures: considerably below average during EN years due to lower pressures aloft suppressing jet stream and storm track across the southern U.S. above average during Strong LN events due to higher pressure in the mid and upper atmosphere forcing jet stream and storm track north.

14. 14 Results: Defined ENSO Categories Minimum Daily Temperatures: minimum daily temperatures show a similar trend to the maximums, although not as pronounced.

15. 15 Results: Defined ENSO Categories Average Precipitation: Precipitation amounts are well above average during all EN events due to the increased frequency of storm systems. Precipitation amounts are well below average during LN events due to higher pressure and fewer storms.

16. 16 Results: Defined ENSO Categories Strong El Niño Temperature Departures: max and min departures are negative for January through April max departures are more negative than min departures, indicating increased cloud cover

17. 17 Results: Defined ENSO Categories Strong La Niña Temperature Departures: max and min departures are positive max departures are greater than min departures due to decreased cloud cover.

18. 18 Results: CHS Extremes CHS Minimum Temperature Extremes: Dec and January show the most neutral influence The later winter months are dominated by EN events as strong late season storms bring cold air southward behind them.

19. 19 Results: Severe Hail Data Total CWA hail days: Most late winter and early spring hail events take place during EN years, likely due to: lower pressure aloft introducing colder air, destabilizing the atmosphere. stronger jet stream winds increasing upper level divergence and shear.

20. 20 Summary For the Charleston, SC County Warning Area: Maximum, minimum, and average temperatures are generally below normal during El Niño events and above normal during La Niña events. Precipitation is well above normal during El Niño events and well below normal during La Niña events.

21. 21 Summary (Cont.) During El Niño, the maximum temperature anomalies are significantly colder than the minimum temperature anomalies. During La Niña, the maximum temperature anomalies are significantly warmer than the minimum temperature anomalies. Extreme cold is more likely in late winter during El Niño events. Severe Hail is more likely during El Niño events.

22. 22 Acknowledgements Data for this project was taken from NOAA archives. –SST values were gathered from the Climate Prediction Center at: http://www.cpc.noaa.gov/products/analysis_monitoring/enso stuff/ensoyears.shtml –Temperature, Precipitation, Tornado, wind, hail, and extreme weather data was taken from the Northeast Regional Climate Center at: http://xmacis.nrcc.cornell.edu/CHS/xmacis_options

23. Thank you!