Climate Variability and Forecasting in the Southeast U.S. David F. Zierden Center for Ocean-Atmospheric Prediction Studies The Florida State University Tallahassee, FL Alabama Water Resources Conference October 13, 2005

SECC Partners Florida State Univeristy – climate studies, coupled modeling, climate forecasts, forestry University of Florida – extension, crop modeling, decision support tools University of Miami – climate, economics, water resources, assessment University of Georgia – climate, extension, crop modeling University of Auburn – extension, economics, insurance University of Alabama Huntsville – climate, water resources

World Map

Global Sea Surface Temperatures

Monitoring the Pacific Ocean

Japan Meteorological Agency (JMA) ENSO Index SST Anomalies averaged over the red shaded portion of the equatorial Pacific Ocean Smoothed with a five- month running average to reduce noise

Tracking ENSO with the JMA Index

How El Niño/La Niña Effect the Atmospheric Circulation

Winter Jet Stream Patterns during El Niño and La Niña

ENSO Effects on Precipitation

ENSO Effects on Temperature

Probabilistic Nature of Forecasts

Predicting El Nino/La Nina Warm/Cold events are tied to the seasonal cycle Events and their climate impacts tend to peak in NH winter Phase can be forecast as early as late summer for the next 6-9 months Phase is difficult to forecast in Spring for the following seasons

Climate Forecast from NOAA TemperaturePrecipitation

El Niño/La Niña and Hurricanes El Niño La Niña

Probability of Hurricane Strikes

Impact Freezes of the last century Freeze Date ENSO State *Dec 1894 Neutral Feb 1899 Neutral Dec 1934 Neutral Jan 1940 Neutral *Dec 1962 Neutral Jan 1977 Neutral Jan 1981 Neutral *Dec 1983 Neutral Jan 1985 Neutral *Dec 1989 Neutral Jan 1997 Neutral * High Impact

ENSO and Southeast Freeze Probabilities

Mallory Swamp Fire during the last La Niña

ENSO and Wildfires  La Niña typically increases acreage burned in Florida from around 60,000 acres to 200,000 or more. (Jones, Shriver, and O’Brien, 1999; Brenner, 1999).  Effective mitigation (supression, contolled burns, herbicides) has bias historical burn records.  Foresters need downscaled predictions in time and space to effectively manage resources. Anomalous Wildfire activity (acres burned) during La Niña episodes April Percent Change

Wildfire Threat forecast The end product is a monthly, county-by-county forecast of the KBDI.The end product is a monthly, county-by-county forecast of the KBDI. Graphic shows the probability of at least 7 days in the month being above or below critical thresholds.Graphic shows the probability of at least 7 days in the month being above or below critical thresholds. Thresholds were determined with input from forestry and wildfire experts.Thresholds were determined with input from forestry and wildfire experts. Forecast was based on the Neutral ENSO phase.Forecast was based on the Neutral ENSO phase.

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