Monthly, seasonal and interannual climate forecasts

Clima Futura provides state-of-the-art global climate forecast information for the public and private sector that needs to take into account future climate anomalies in order to take action ahead of time – such as insurance corporations, renewable energy generators and electrical grid operators. For example, seasonal climate anomalies in the tropical Pacific as well as interannual climate anomalies in the North Atlantic, predicted by our forecasts, tend to suppress or favour hurricane development in the North Atlantic. This means, that our forecasts predict the hurricane frequency in the next seasons, years. Since monthly and seasonal climate anomalies affect human health such as cardiovascular and respiratory diseases and dengue and malaria infection rates, our forecasts forecast the enhanced or decreased risk of these diseases in the next 12 months or 4 seasons.

Clima Futura provides monthly (coming 12 months), seasonal (coming 4 seasons) and interannual climate forecasts based on the Canadian seasonal to interannual climate prediction system (CanSIPS) and decadal system (CanCM4). An extensive set of global calibrated forecast probabilities and anomalies maps for 10 variables (Geopotential Height (m), Precipitation (mm/day), Sea Level Pressure (Pa), Temperature at 850 hPa (K), 2-metre Temperature (K), Eastward Wind at 200 hPa (m/s), Eastward Wind at 850 hPa (m/s), Northward Wind at 200 hPa (m/s), Northward Wind at 850 hPa (m/s), Sea Surface Temperature (K)) are updated on the 1st of each Month. This means the first forecasts are 0-lead. The monthly and seasonal forecast anomalies are departures from 1981-2010, whereas the interannual anomalies are departures from 1961-2013. The forecast ensemble-mean tend to have reduced variabilty, hence relatively small values can represent larger values.

CanSIPS comprises two coupled ocean-atmosphere-sea-ice-land-surface climate models, where the ocean, atmosphere, sea-ice and land are initialized in coupled mode. Many physical processes (El Niño Southern Oscillation, Madden-Julian Oscillation, Rossby Wave Breaking, Atmospheric Blocking, Sea Surface Temperature, Sea Ice Extention, Snow Coverage, etc.) are simulated at hourly or daily time scales and show up in monthly means if for example the anomaly is persistently negative or positive during 20 of 30 days. For ENSO skill in the Pacific, CanSIPS outperforms most European systems, except ECMWF S4, see Figure 22 on page 45 of CanSIPS documentation as well as the system at NCEP see Figure 23 on page 46 of CanSIPS documentation.


All the forecast maps are available for customers at:


Both probabilistic and deterministic skill maps are added to each forecast, where the quality of the prediction system is established by comparing its forecasts in the past 30 or 53 years to the observational dataset: Continuous Ranked Probability Skill Score, Ranked Probability Skill Score of terciles, Anomaly Correlation (with 1-p dotted lines to show confidence), Mean Square Skill Score.

Forecasts of climate indices for El Niño Southern Oscillation, a.k.a. ENSO (Niño 3.4, Southern Oscillation Index), Pacific North American Pattern,  a.k.a. PNA, North Atlantic Oscillation,  a.k.a. NAO, North Atlantic SST Anomaly are presented as boxplots (black line shows median, the box the lower and upper quartiles (50% in total), the whiskers min, max values or 1.5 times length of the box).