IRI/CPC Mid-Month Model-Based ENSO Forecast Probabilities
| Season | La Niña | Neutral | El Niño |
|---|---|---|---|
| OND 2016 | 57% | 43% | 0% |
| NDJ 2016 | 53% | 46% | 1% |
| DJF 2017 | 47% | 51% | 2% |
| JFM 2017 | 35% | 63% | 2% |
| FMA 2017 | 22% | 74% | 4% |
| MAM 2017 | 12% | 81% | 7% |
| AMJ 2017 | 10% | 74% | 16% |
| MJJ 2017 | 15% | 61% | 24% |
| JJA 2017 | 18% | 53% | 29% |
| Seasons (2016-2017) | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Model | OND | NDJ | DJF | JFM | FMA | MAM | AMJ | MJJ | JJA |
| Dynamical models | |||||||||
| NASA GMAO model | -0.6 | -0.5 | -0.4 | -0.1 | 0.1 | 0.3 | 0.5 | ||
| NCEP CFS version 2 | -0.9 | -1 | -1 | -0.7 | -0.3 | -0.1 | 0.2 | 0.4 | |
| Japan Met. Agency model | -0.6 | -0.8 | -0.9 | -0.9 | -0.6 | ||||
| Scripps Inst. HCM | -1.1 | -1.2 | -1.2 | -1.1 | -1 | -0.9 | -0.7 | -0.5 | -0.4 |
| Lamont-Doherty model | -0.3 | -0.2 | 0 | 0.2 | 0.4 | 0.3 | 0.2 | 0 | -0.3 |
| POAMA (Austr) model | -0.6 | -0.6 | -0.6 | -0.4 | -0.3 | -0.1 | 0.1 | ||
| ECMWF model | -0.3 | -0.2 | -0.1 | 0 | 0.1 | ||||
| UKMO model | -0.7 | -0.7 | -0.5 | -0.3 | |||||
| KMA (Korea) SNU model | -0.6 | -0.6 | -0.6 | -0.6 | -0.6 | -0.7 | -0.7 | -0.7 | -0.7 |
| IOCAS (China) Intermed. Coupled model | -0.8 | -0.9 | -0.8 | -0.7 | -0.5 | -0.5 | -0.5 | -0.5 | -0.6 |
| COLA CCSM4 model | -0.4 | -0.5 | -0.6 | -0.5 | -0.3 | -0.1 | 0.1 | 0.2 | 0.2 |
| MÉTÉO FRANCE model | -0.5 | -0.5 | -0.4 | -0.3 | -0.2 | ||||
| Japan Frontier Coupled model | -0.5 | -0.4 | -0.3 | -0.2 | -0.1 | -0.1 | 0 | 0.1 | 0.2 |
| CSIR-IRI 3-model MME | -0.2 | -0.3 | -0.5 | -0.5 | -0.4 | -0.3 | |||
| GFDL CM2.1 Coupled Climate model | -0.8 | -0.8 | -0.7 | -0.4 | -0.1 | 0.3 | 0.5 | 0.7 | 0.9 |
| Canadian Coupled Fcst Sys | -0.4 | -0.3 | -0.1 | -0.1 | 0.1 | 0.3 | 0.5 | 0.8 | 1.1 |
| GFDL CM2.5 FLOR Coupled Climate model | -0.6 | -0.5 | -0.4 | -0.2 | -0.1 | 0.1 | 0.3 | 0.6 | 0.8 |
| Average, dynamical models | -0.6 | -0.6 | -0.5 | -0.4 | -0.2 | -0.1 | 0 | 0.1 | 0.1 |
| Statistical models | |||||||||
| NCEP/CPC Markov model | -0.6 | -0.6 | -0.5 | -0.4 | -0.4 | -0.3 | -0.3 | -0.2 | -0.2 |
| NOAA/CDC Linear Inverse | -0.3 | -0.2 | -0.1 | -0.1 | 0 | 0 | 0.1 | 0.1 | 0.1 |
| NCEP/CPC Constructed Analog | -0.6 | -0.5 | -0.4 | -0.3 | -0.1 | 0 | 0.1 | -0.1 | -0.1 |
| NCEP/CPC Can Cor Anal | -0.4 | -0.5 | -0.6 | -0.5 | -0.3 | -0.1 | 0 | 0 | 0 |
| Landsea/Knaff CLIPER | -0.7 | -0.6 | -0.5 | -0.5 | -0.3 | -0.2 | 0 | -0.1 | -0.2 |
| Univ. BC Neural Network | -0.4 | -0.3 | -0.1 | 0.1 | 0.3 | 0.3 | 0.4 | 0.5 | 0.4 |
| FSU Regression | -1 | -1 | -1 | -0.8 | -0.5 | -0.3 | 0 | 0.2 | 0.4 |
| TCD – UCLA | -0.2 | 0 | 0.2 | 0.4 | 0.5 | 0.5 | 0.5 | 0.6 | 0.6 |
| UNB/CWC Nonlinear PCA | -0.4 | -0.3 | -0.2 | 0 | 0.1 | 0.1 | 0.1 | 0.1 | 0.2 |
| Average, statistical models | -0.5 | -0.4 | -0.4 | -0.2 | -0.1 | 0 | 0.1 | 0.1 | 0.1 |
| Average, all models | -0.6 | -0.5 | -0.5 | -0.3 | -0.2 | -0.1 | 0.1 | 0.1 | 0.1 |
