Weather affects every aspect of the economy. It is estimated that weather and climate sensitive industries in the United States directly impacted by weather (such as agriculture, construction, energy distribution, and outdoor recreation) account for nearly 10 percent of GDP. To reduce risk associated with adverse weather and climate conditions, many companies are increasingly using weather derivatives as part of their risk management strategy. 

The most common types of weather derivatives are:

1. Heating degree day (HDD). This is an index designed to reflect the energy demand for heating. It is defined as the number of degrees that a day's average temperature is below 65°F (18°C). For example, if the day's average temperature is 50°F, its HDD value is 15. If the temperature is above 65°F, the HDD value is zero. Heating degree days can be accumulated over periods of time to provide an estimate of seasonal heating requirements.

2. Cooling degree day (CDD). This is an index used to relate the day's temperature to the energy demands of air conditioning. Cooling degree days are calculated by subtracting 65 from a day's average temperature. For example, on a day with an average temperature of 80°F, the CDD value is 15 (80 – 65 base = 15 CDD). If the temperature is lower than 65°F, the value of the CDD is zero. As with HDD, CDD can be added over periods of time to provide an estimate of seasonal cooling requirements.

3. Cumulative Average Temperature (CAT). In Europe, weather futures for the summer months are based on the CAT index. The CAT index is defined as cumulative daily average temperatures within the period covered by the derivative. For Canadian cities, both the CDD and CAT indices are used.

The weather derivatives forecasts provided here are based on our seasonal forecast maps for North America and Europe. Although these maps are produced primarily for the calendar seasons (e.g., December-January-February for winter), here we also use the extended seasons, such as November through March for winter, as well as other seasonal strips (November-December or January-February-March). The forecast accuracy is tested against other alternative forecasts.

Our forecasts can help energy and other weather- and climate-sensitive companies to improve their risk management strategies associated with climate fluctuations. They can also help professional traders to increase their profit from trading weather derivatives (see examples of how beneficial the climate forecast information can be). 

External Links

• Wikipedia articles on weather derivatives and heating degree day
• Introduction to Weather Derivatives
• The Weather Profits
• Making Climate Forecasts Matter (online book)
• Business Aspects of Seasonal Climate Forecasting
• Weather, Finance and Meteorology: Forecasting and Derivatives by Samuel Randalls
• CME Historical Weather Data
• An Introduction to CME Weather Products
• Weather Risk Management by Bob Dischel
• Vinod Kothari's securitization website contains a comprehensive list of weather derivatives-related links 
• Protecting Winter Profits