Equatorial Pacific Ocean Sea Surface Temperature Anomaly ENSO Forecasts from the LDEO Climate Data Library

"Forecast sea surface temperature fields are produced on a monthly
basis using the Zebiak and Cane (1987) coupled atmosphere-ocean
model.

At present, two forecast products are available: The standard, or
LDEO, forecasts (consistent with those issued in the NOAA Diagnostic
Bulletin over the past several years), and a newer product,
referred to as LDEO2, that utilizes a different forecast initialization
scheme.

In the standard initialization, FSU pseudo-stress anomalies (with some
filtering and smoothing as described in Cane et al, 1986, Nature) are
used to "spin up" the ocean model from 1964 until the beginning of the
forecast period; the atmosphere model is similarly spun up using the
simulated SSTA from the forced ocean run. Thus initialized, the
coupled model runs ahead in time with no data insertion, producing a
forecast for the evolution of the coupled atmosphere-ocean system.

For the standard product, SSTA fields from individual forecasts are
composited by lag-averaging the results from six consecutive monthly
initial conditions. The composited forecasts for lead times of 3,6,9,
and 12 months are then post-processed using a singular value
decomposition analysis, to remove systematic spatial pattern errors
and to map the idealized model domain onto the real one. The LDEO
forecast results are archived from January 1972 (verification time) to
the most recent month available. Also archived are forecasts of NINO3
(the average SSTA in the region 90W-150W, 5N-5S), a commonly used
index of El Nino and the Southern Oscillation (ENSO). LDEO NINO3
forecast results are available at selected lead times as are the SSTA
fields.

For the LDEO2 product, a nudging algorithm as described in Chen et al,
1995, Science, is used to initialize forecasts. In effect, the ocean
is spun up with a weighted average of FSU and model-derived
winds. This scheme results in much reduced "initialization shock",
considerably improved forecast skill (.1 - .2 increase in correlation
at all lead times from 0 to 18 months) and reduced seasonality of
skill. For the LDEO2 product, no lag-averaging is used, although small
corrections for systematic errors are made using a singular value
decomposition analysis. LDEO2 forecast results are available at
selected lead times as are the LDEO2 NINO3 forecasts as are the SSTA
fields."

[from: "http://ingrid.ldeo.columbia.edu/SOURCES/.ENSOFORECAST/"]