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Summary of ENSO Model Forecasts

14 September 2005

Note on interpreting model forecasts

The following graph and table show forecasts made by dynamical and statistical models for SST in the Nino 3.4 region for nine overlapping 3-month periods. Note that the expected skills of the models, based on historical performance, are not equal to one another. The skills also generally decrease as the lead time increases. Thirdly, forecasts made at some times of the year generally have higher skill than forecasts made at other times of the year--namely, they are better when made between June and December than when they are made between February and May. Differences among the forecasts of the models reflect both differences in model design, and actual uncertainty in the forecast of the possible future SST scenario.

Discussion of current forecasts

The set of dynamical and statistical model forecasts issued during late August and early September 2005 shows a faily narrow range of possible sea surface temperature conditions for the coming 2 to 10 months (September - October - December 2005 through May - June - July 2006). Most models are indicating above-average, but neutral, conditions over the coming few months. A couple indicate a developing weak El Nino during the coming few months, and a few forecast cool but neutral conditions. At the time of preparing this, SST observations in the NINO3.4 region are very close to their average. Overall tropical Pacific oceanic and atmospheric conditions point to a continuation of neutral ENSO conditions.

Table 1. Forecast SST Anomalies (deg C) in the Nino 3.4 Region

	Seasons (2005-2006)
Model	SON	OND	NDJ	DJF	JFM	FMA	MAM	AMJ	MJJ
Dynamical models
NASA/NSIPP model	-0.1	-0.1	0	0.2	0.3	0.4	0.4	0.6	0.7
NCEP Coupled Fcst Sys	-0.1	-0.1	-0.1	-0.3	-0.3	-0.2	-0.2	-0.1
Japan Met. Agency model	0.2	0.1	0.1	0.1	0.3
Scripps Inst. HCM	0.8	0.9	1	1.1	1.1	1	0.9	0.7	0.6
Lamont-Doherty model	0.6	0.8	0.8	0.9	0.8	0.7	0.6	0.5	0.4
POAMA (Austr) model	-0.8	-0.7	-0.5	-0.4	-0.2	-0	0.2
ECMWF model	0.2	0.2	0.2
UKMO model	0.6	0.6	0.3
SNU (Korea) model	0.2	0.1	0.1	0.1	0	0	-0	-0	-0
Average, dynamical models	0.2	0.2	0.2	0.2	0.3	0.3	0.3	0.3
Statistical models
NCEP/CPC Markov model	0.1	0.1	0.2	0.2	0.2	0.2	0.2	0.2	0.2
NOAA/CDC Linear Inverse	-0.1	-0.2	-0.3	-0.3	-0.3	-0.3	-0.4	-0.3	-0.3
Dool Constructed Analog	0.2	0.3	0.3	0.3	0.4	0.4	0.4	0.5	0.4
NCEP/CPC Can Cor Anal	0.5	0.5	0.6	0.6	0.6	0.5	0.4	0.4	0.3
Landsea/Knaff CLIPER	0.2	0.3	0.4	0.5	0.4	0.3	0.2	0.1	0.1
Univ. BC Neural Network	0.1	0	0.2	0.4	0.6	0.6	0.6	0.6	0.6
FSU Regression	0.3	0.3	0.3	0.4	0.3	0.2	0.2	0.1	0.1
TDC - UCLA	0.3	0.3	0.2	0.2	0.1	0.1	0.1	0.1	0.1
Average, statistical models	0.2	0.2	0.3	0.3	0.3	0.2	0.2	0.2	0.2
Average, all models	0.2	0.2	0.2	0.3	0.3	0.3	0.3	0.3	0.3

Notes on the data 

Only models producing forecasts on a monthly basis are included. This means that some models whose forecasts appear in the Experimental Long-Lead Forecast Bulletin (produced by COLA) do not appear in the table.

The SST anomaly forecasts are for the 3-month periods shown, and are for the Nino 3.4 region (120-170W, 5N-5S). Often, the anomalies are provided directly in a graph or a table by the respective forecasting centers for the Nino 3.4 region. In some cases, however, they are given for 1-month periods, for 3-month periods that skip some of the periods in the above table, and/or only for a region (or regions) other than Nino 3.4. In these cases, the following means are used to obtain the needed anomalies for the table:

• Temporal averaging, 
• Linear temporal interpolation 
• Visual averaging of values on a contoured map 
• Regional SST anomaly adjustment using the climatological variances of one region versus that of another 

As an example of the last case, suppose only the Nino 3 anomaly is provided. The Nino 3.4 anomaly is then obtained by decreasing the Nino 3 anomaly by the factor defined by the ratio of the year-to-year variabilities of Nino 3.4 to the year-to-year variance of Nino 3 SST, for the 3-month season in question. 

The anomalies shown are those with respect to the base period used to define the normals, which vary among the groups producing model forecasts. They have not been adjusted to anomalies with respect to a common base period. Discrepancies among the climatological SST resulting from differing base periods may be as high as a quarter of a degree C in the worst cases. Forecasters are encouraged to use the standard 1971-2000 period as the base period, or a period not very different from it.