Seasonal Weather Forecasts

The AER Seasonal Forecast sCast is the most comprehensive seasonal forecasting service in the industry. sCast provides detailed regional HDD* and CDD forecasts that are population-weighted for electricity, gas and oil for energy and weather derivatives traders. This six-month seasonal forecast also provides extensive temperature and precipitation information in both tabular and map formats, making these seasonal forecasts easy to understand. Clients receive forecasts for the U.S. and the Northern Hemisphere.

Based on over a decade of extensive atmospheric research, AER's seasonal forecasts have been used by the financial services and energy industries for years. Unlike other seasonal weather forecasts, our forecast uses a unique initialization scheme that combines snow cover in Siberia in addition to El Niño/Southern Oscillation (ENSO) and warming trends.

• AER's research on the Snow Advance Index demonstrates how this can be used to predict the Arctic Oscillation (AO) and provide more accurate predictions of winter weather.
• View the AER Model of How Snow Cover Impacts Winter Weather
• AER has shown that Siberian snow cover can be use to predict the strength of the polar vortex, which is highly correlated with the frequency of Arctic outbreaks in the mid-latitudes.

Extensive seasonal hindcasting, leveraging more than three decades of weather data, has validated that the AER suite of seasonal weather forecasts accurately predicts the temperature direction (higher or lower) 80% of the time, and the magnitude of the predicted temperature anomaly is a 30-50% improvement over using climatology as a predictor (e.g., improvement over forecasts based on average historical data).

• Read the forecast accuracy verification results published in the American Meteorological Society’s Journal of Climate in 2007
• View the National Science Foundation (NSF) special report “Predicting Seasonal Weather”which highlights AER's forecast approach.

The accuracy of the Seasonal Forecast approach is demonstrated by comparing observed and forecasted results. These images show: a) observed, and b) forecasted winter surface temperature anomalies (difference from normal) for the U.S. for Dec 2010-Jan-Feb 2010.

The model forecasted colder than normal for the Upper Midwest, Great Lakes, Northeast and Southeast, with warmer than normal in the Southwest. The model uses October Siberian snow cover and sea level pressure anomalies, and sea surface temperature anomalies in the equatorial Pacific in its winter forecast. October 2010 snow cover was observed to be above normal, which favors below normal temperatures for the Eastern U.S.

The accuracy of the Seasonal Forecast approach is demonstrated by comparing observed and forecasted results. These images show: a) observed, and b) forecasted winter surface temperature anomalies for the Northern Hemisphere including the North America and Eurasia for Dec 2010-Jan-Feb 2010.

The model forecasted colder than normal temperatures for the midlatitudes, with warmer than normal toward the Arctic. The model uses October Siberian snow cover and sea level pressure anomalies, and sea surface temperature anomalies in the equatorial Pacific in its winter forecast. October 2010 snow cover was observed to be above normal, which favors below normal temperatures for the Eastern US and Northern Eurasia.

* HDD: Heating degree day. CDD: Cooling degree day.