Climate Prediction Center - seasonal Outlook
Skip Navigation Links 
NOAA logo - Click to go to the NOAA home page National Weather Service   NWS logo - Click to go to the NWS home page
Climate Prediction Center

CPC Search
Map Explanations
   Official Fcsts
   Fcst Tools

Outlooks (Forecasts)

About Us
   Our Mission
   Who We Are

Contact Us
   CPC Information
   CPC Web Team

Official 90-day Outlooks are issued once each month near mid-month at 8:30am Eastern Time. Please consult the schedule of 30 & 90-day outlooks for exact release dates.
HOME > Outlook Maps > Monthly to Seasonal Outlooks > Seasonal Outlooks
Seasonal Forecast Tool Description

Ensemble Canonical Correlation Analysis (ECCA)

The Ensemble Canonical Correlation Analysis (ECCA) forecast is one of the statistical seasonal tools that predict US surface temperature and precipitation. The ECCA uses Canonical Correlation Analysis (CCA), an empirical statistical method that finds patterns of predictors (variables used to make the prediction) and predictands (variables to be predicted) that maximize the correlation between them. The most recent available predictor data for different atmospheric/oceanic variables are projected onto the loading patterns to create forecasts. The ensemble refers to forecasts produced by using each predictor separately to create a forecast. The final forecast is an equally weighted average of the ensemble of forecasts. The model is trained from 1953 to the year before the present year to create the loading patterns.

Graphical Information
Colors on the ECCA forecast maps denote the following :
Temperature :
Orange - above normal temperature ; Blue - below normal temperature
Precipitation :
Green - above normal precipitation ; Brown - below normal precipitation

Predictor Selection :
The pool of possible predictors used in the forecasts are:

  • 200mb global velocity potential
  • global sea surface temperatures
  • sea level pressure (north of 40N)
  • US soil moisture

  • The predictors selected to be used in the ECCA are based on factors such as :
    a) which climate signals/atmospheric variables play a large role in US temperature/precipitation for a certain season (ie. soil moisture is included in summer forecasts
    b) status or strength of climate signals that impact US temperature and precipitation. For example, seasons with current or expected relatively strong ENSO years typically include sea level pressure as one of the ECCA predictors because of its ability to represent the ENSO signal.

    The list of predictors used to make a certain lead forecast are listed above the forecast images on the ECCA forecast pages

    Mo, K.C., 2003: Ensemble Canonical Correlation Prediction of Surface Temperature over the United States. J. Climate , 16, 1665-1683.
    Barnston, A.G.: Linear Statistical Short-Term Climate Predictive Skill in the Northern Hemisphere. J. Climate , 7, 1513-1564.

    (Comments/Suggestions? Send to: Melissa Ou)

    Ensemble Canonical Correlation Analysis Forecasts

    NOAA/ National Weather Service
    National Centers for Environmental Prediction
    Climate Prediction Center
    5200 Auth Road
    Camp Springs, Maryland 20746
    Page Author: Climate Prediction Center Internet Team
    Page last modified: December 12, 2005
    Information Quality
    Privacy Policy
    Freedom of Information Act (FOIA)
    About Us
    Career Opportunities