IRI Multi-model Probability Forecasts for Precipitation and Temperature: Oct-Nov-Dec 2010 and Jan-Feb-Mar 2011 Tony Barnston International Research Institute for Climate and Society

Observed Precipitation Jun-Jul-Aug 2010 Observed Precipitation Normal based on 1971-2000

Jul-Aug-Sep 2010

Jun-Jul-Aug 2010 Observed Temperature Normal based on 1971-2000

95F 86F 77F 68F Jul-Aug-Sep 2010 104F 95F 86F 77F 68F

Departure from normal La Nina

Departure from normal La Nina

A strong key to seasonal climate forecasting: Departures from normal of Sea Surface Temperature (SST), especially in the tropics, influence seasonal climate.

Stronger El Niño El Nino Aug La Nina StrongerLa Niña Nino3.4

Tropical Pacific oceanic and atmospheric conditions: Normally during El Nino

Circulation pattern over North America for El Nino and La Nina El Nino La Nina

Lead time and forecast skill Temperature and precipitation forecasts Weather forecasts (from initial conditions) Forecast Skill (correlation) good fair poor zero Seasonal forecasts (from boundary conditions like SST) 10 20 30 60 80 90 Forecast lead time (days)

El Nino La Nina El Nino La Nina El Nino/ La Nina situation over the last 12 months El Nino La Nina El Nino La Nina ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;

El Nino

La Nina

La Nina

Nino3.4 SST anomaly predictions from September

from September

La Nina Forecast for late autumn 2010

How do we make a seasonal climate forecast?

IRI DYNAMICAL CLIMATE FORECAST SYSTEM 2-tiered OCEAN ATMOSPHERE GLOBAL ATMOSPHERIC MODELS ECPC(Scripps) ECHAM4.5(MPI) CCM3.6(NCAR) NCEP(MRF9) NSIPP(NASA) COLA2 GFDL PERSISTED GLOBAL SST ANOMALY Persisted SST Ensembles 3 Mo. lead 10 POST PROCESSING MULTIMODEL ENSEMBLING 24 24 10 FORECAST SST TROP. PACIFIC: THREE (multi-models, dynamical and statistical) TROP. ATL, INDIAN (ONE statistical) EXTRATROPICAL (damped persistence) 12 Forecast SST Ensembles 3/6 Mo. lead 24 24 30 12 30 30 GFDL has 10 to PSST

Forecasts of the climate The tercile category system: Below, near, and above normal Probability: 33% 33% 33% Below| Near | Below| Near | Above  Data: | || ||| ||||.| || | | || | | | . | | | | | | | | | | 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 Rainfall Amount (tenths of inch) (30 years of historical data for a particular location & season)

Historical distribution Forecast distribution: tilt of the odds A typical shift of the odds in a seasonal precipitation forecast Historical distribution Forecast distribution: tilt of the odds toward “above” P R O B A I L T Y Below Normal Above Normal Near Normal Historically, the probabilities of “above” and “below” are 0.33. Shifting the mean by half a standard-deviation (to 69%ile) and reducing the variance by 20% changes the probability of below to 0.15 and of above to 0.53.

El Nino and Rainfall and Temperature

Correlation Skill for NINO3 forecasts Predictability of El Nino and La Nina – and consequently, predictability of the climate deviations from normal over parts of the world Skill bonus Northern Spring barrier useless low fair good Correlation between forecast and obs

Atlantic Hurricane Tracks for the 1982 season El Nino was in prog- ress.

2004 (El Nino) From http://weather.unisys.com

2005 (neutral)

2006 (El Nino)

2007 (La Nina)

2008 (neutral)

2009 (El Nino)

2010 (La Nina) [incomplete]

Traditionally we have used a recent 30-year What should be defined as the NORMAL climate? Traditionally we have used a recent 30-year period. (Currently it is 1971-2000.) But if the “normal” is changing, using 30 past years gives us an old climate. How can we define the average current climate?

From NASA/GISS (Goddard Institute for Space Studies) Where has it been warming at the highest rate?

Phoenix, Arizona urban growth ↔ Yuma, Arizona