User-driven Climate Forecasts User-driven Climate Forecasts in the Southeast U.S.in the Southeast U.S.

David F. ZierdenDavid F. ZierdenAssistant State ClimatologistAssistant State Climatologist

Center for Ocean-Atmospheric Center for Ocean-Atmospheric Prediction StudiesPrediction Studies

The Florida State University The Florida State University

Tallahassee, FLTallahassee, FL

World MapWorld Map

ENSO Impacts in the ENSO Impacts in the SoutheastSoutheast

La Niña

• Dry Fall, Winter, and Spring• Greatly increases Atlantic hurricanes• Increases tornadoes in the deep south• Greatly increases wildfire activity

EL Niño

• Very wet winter and spring• Greatly reduces Atlantic hurricanes• decreases tornadoes in the tornado alley

Neutral ENSO phase increases the risk of severe freezes by 3:1 odds.

ENSO Effects on ENSO Effects on PrecipitationPrecipitation

ENSO Effects on ENSO Effects on TemperatureTemperature

Impact Freezes of the last Impact Freezes of the last centurycentury

Freeze Date ENSO State *Dec 1894 Neutral Feb 1899 Neutral Dec 1934 Neutral Jan 1940 Neutral *Dec 1961 Neutral Jan 1977 El Nino Jan 1981 Neutral *Dec 1983 Neutral Jan 1985 Neutral *Dec 1989 Neutral Jan 1997 Neutral

* High Impact

ENSO and Florida FreezeENSO and Florida FreezeProbabilitesProbabilites

Return Return FrequenciesFrequencies

Extended Freeze EventsExtended Freeze Events

Late Season FreezesLate Season Freezes

La Niña and La Niña and WildfiresWildfires

La Niña brings drier than La Niña brings drier than normal conditions (30%-normal conditions (30%-40%) and warmer 40%) and warmer temperatures from temperatures from November through April.November through April.

Wildfire activity is increased Wildfire activity is increased throughout the wildfire throughout the wildfire season.season.

The increased activity can The increased activity can be expected during nearly be expected during nearly all La Niña episodes.all La Niña episodes.

Anomalous Wildfire activity

(acres burned) during La Niña

episodes

April

Mallory Swamp Fire during the last La Niña

Forecasting Potential Forecasting Potential Wildfire ActivityWildfire Activity

Forecast based on the Keetch-Byram Drought Forecast based on the Keetch-Byram Drought Index (KBDI).Index (KBDI).

Historical weather observations from the NWS Historical weather observations from the NWS Coop network provides coverage at nearly county Coop network provides coverage at nearly county level.level.

Forecast is presented in probabilistic terms.Forecast is presented in probabilistic terms.

““Bootstrapping” used to generate probability Bootstrapping” used to generate probability distributions for each station.distributions for each station.

KBDI Forecast MethodKBDI Forecast Method

Wildfire Wildfire Threat Threat

forecastforecast

•The end product is a The end product is a monthly, monthly, county-by-county-by-countycounty forecast of the forecast of the KBDI.KBDI.

•Graphic shows the Graphic shows the probability of probability of at least 7 at least 7 daysdays in the month being in the month being above or below critical above or below critical thresholds.thresholds.

•Thresholds were Thresholds were determined with input determined with input from forestry and wildfire from forestry and wildfire experts.experts.

•Forecast was based on Forecast was based on the Neutral ENSO phase.the Neutral ENSO phase.

More uses for climate More uses for climate forecasts that just wildfireforecasts that just wildfire

Harvesting - cannot harvest in low Harvesting - cannot harvest in low areas during El Nino winters.areas during El Nino winters.

Planting - Survival rate low during Planting - Survival rate low during La NinaLa Nina

Managed Forests - Herbicides, Managed Forests - Herbicides, pesticides, prescribed burnspesticides, prescribed burns

For More Information:For More Information:

Visit Our WebsitesVisit Our Websites

COAPS: COAPS: www.coaps.fsu.eduwww.coaps.fsu.edu

Florida Climate Center:Florida Climate Center:

www.coaps.fsu.edu/climate_centerwww.coaps.fsu.edu/climate_center

Florida Automated Weather Florida Automated Weather Network:Network:

fawn.ifas.ufl.edufawn.ifas.ufl.edu

Determining Probability Determining Probability Distributions using Distributions using

“Bootstrapped” Data“Bootstrapped” Data

Begin with the CURRENT KBDI Begin with the CURRENT KBDI value at the beginning of the value at the beginning of the forecast cycle.forecast cycle.

Use over 50 years of DAILY Use over 50 years of DAILY observations at each station (13 observations at each station (13 El Nino, 13 La Nina, and 28 El Nino, 13 La Nina, and 28 neutral).neutral).

Constuct a “bootstrapped” Constuct a “bootstrapped” month by month by randomlyrandomly selecting selecting temperature and precipitation temperature and precipitation values each day from the group values each day from the group with similar ENSO phase.with similar ENSO phase.

Repeat until you have 1,000 Repeat until you have 1,000 realizations of the specific ENSO realizations of the specific ENSO phase in each month.phase in each month.