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15 December 2011

> Note on interpreting model forecasts
> Figure of Nino3.4 SST forecasts
> Table of Nino3.4 SST forecasts
> Discussion of current forecasts
> Summary of forecasts, last 22 months
> Individual Model View, last 22 months
> Additional information on models
> Notes on the data

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.

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

  Seasons (2011-2012)
Model DJF JFM FMA MAM AMJ MJJ JJA JAS ASO
Dynamical models
NASA GMAO model -2.2 -2 -1.6 -1.3 -1.1 -0.9 -0.8    
NCEP Coupled Fcst Sys model -1.2 -1 -0.9 -0.8 -0.8 -0.8 -0.8    
Japan Met. Agency model -0.5 -0.3 -0.1 0.2 0.4        
Scripps Inst. HCM -1.2 -1.2 -1.2 -1 -0.9 -0.7 -0.4 -0.2 -0.1
Lamont-Doherty model -0.9 -0.7 -0.5 -0.2 0.1 0.5 0.8 0.9 0.9
POAMA (Austr) model -0.6 -0.3 -0.1 0.1 0.3 0.4      
ECMWF model -0.9 -0.7 -0.4 -0.2          
UKMO model -1.1 -0.9 -0.7 -0.6          
KMA (Korea) SNU model -0.6 -0.4 -0.2 -0.1 -0.1 0 0.1 0.2 0.3
ESSIC Intermed. Coupled model -0.7 -0.4 -0.3 -0.1 -0 0.1 0.1 0.1 0.1
ECHAM/MOM -0.6 -0.4 -0.1 0.1 0.4        
COLA ANOM -0.4 -0.4 -0.4 -0.4 -0.4 -0.5 -0.6 -0.7 -0.8
MÉTÉO FRANCE model -0.9 -0.7 -0.5 -0.3 -0.1        
COLA CCSM3 model -0.2 0.1 0.3 0.5 0.8 0.9 1 0.9 1
NCEP CFS version 2 -1.1 -1.1 -0.9 -0.8 -0.6 -0.4 -0.2 -0.1  
CSIR-IRI 3-model MME -1.2 -1.2 -0.9 -0.6 -0.4        
GFDL CM2.1 Coupled Climate model -0.9 -0.8 -0.5 -0.1 0.3 0.6 0.9 1 0.9
Average, dynamical models -0.9 -0.7 -0.5 -0.3 -0.1 -0.1 -0   
Statistical models
NCEP/CPC Markov model -1.1 -0.9 -0.7 -0.6 -0.4 -0.2 -0.1 0 0.1
NOAA/CDC Linear Inverse -0.6 -0.6 -0.6 -0.6 -0.5 -0.5 -0.4 -0.3 -0.2
NCEP/CPC Constructed Analog -0.9 -0.9 -0.8 -0.6 -0.4 -0.3 -0.3 -0.3 -0.3
NCEP/CPC Can Cor Anal -1.2 -1.1 -0.8 -0.6 -0.4 -0.2 0 0.1 0.1
Landsea/Knaff CLIPER 0 -0.1 -0.1 -0.2 -0.2 -0.1 -0.1 -0 0
Univ. BC Neural Network -1.1 -1.1 -1 -0.9 -0.7 -0.5 -0.3 -0.1 -0
FSU Regression -1 -1 -0.8 -0.8 -0.6 -0.5 -0.5 -0.5 -0.5
TDC - UCLA -1.2 -1.3 -1.2 -1 -0.8 -0.6 -0.6 -0.6 -0.6
Average, statistical models -0.9 -0.9 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.2
Average, all models -0.9 -0.8 -0.6 -0.4 -0.3 -0.2 -0.1 0 0

Discussion of current forecasts

Most of the set of dynamical and statistical model predictions issued during late November and early December 2011 predict La Nina conditions from the December 2011 to February 2012 season currently in progress, continuing into the early part of 2012 before transitioning back to neutral conditions during northern spring season. Based on the multi-model mean predictions, and the expected skill of the models by start time and lead time, the probabilities (X100) for La Nina, neutral and El Nino conditions (using -0.5C and 0.5C thresholds) over the coming 10 seasons are:
DJF 98 2 0.1
JFM 86 14 0.2
FMA 63 37 0.4
MAM 41 58 1
AMJ 32 62 6
MJJ 31 56 13
JJA 28 54 17
JAS 22 54 24
ASO 21 53 26
SON 21 52 27

Summary of forecasts issued over last 22 months

The following plots show the model forecasts issued not only from the current month (as in the plot above), but also from the 21 months previous to this month. The observations are also shown up to the most recently completed 3-month period. The plots allow comparison of plumes from the previous start times, or examination of the forecast behavior of a given model over time. The first plot shows forecasts for dynamical models, the second for statistical models, and the third for all models. For less difficult readability, forecasts are shown to a maximum of only the first five lead times. Below the third plot, we provide a mechanism for highlighting the forecasts of one model at a time against a background of more lightly colored lines for all other models.




Individual Model View over last 22 months

View individual models here.

Additional information on Models

Dynamical Models Statistical Models
NASA GMAO model NCEP/CPC Markov model
NCEP Coupled Fcst Sys model NOAA/CDC Linear Inverse
Japan Meteorological Agency NCEP/CPC Constructed Analog
Scripps Inst. HCM NCEP/CPC Can Cor Anal
Lamont-Doherty model Landsea/Knaff CLIPER
POAMA (Austr) model Univ. BC Neural Network
ECMWF model FSU Regression
UKMO model TDC - UCLA
KMA SNU (Korea) model  
ESSIC Intermed. Coupled model  
ECHAM/MOM  
COLA ANOM  
MÉTÉO FRANCE  
Japan Frontier Coupled model  

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 

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.

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