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HOME > Outlooks > Monthly to Seasonal Outlooks > Probability of Exceedance Forecast > Degree Day Introduction
Degree Day Outlook for Major United States Cities

Outlook for Monthly Total Degree Days State and Regional Population Weighted Totals.


Weather variations are one of the most important factors influencing energy demand for heating and cooling. The degree day is one measure of the weather related energy demand. The heating degree day (hdd) is used to help estimate heating requirements at a given location for a given day. It is defined as the difference between 65 degrees F and the daily mean temperature, m:

hdd=(65 - m) .

The higher the daily hdd value, the more heating energy is required for that day. When the mean daily temperature exceeds 65 degrees F, there are no heating degree days (hdd=0).

A cooling degree day (cdd) can be used to help estimate the energy required for cooling and is defined as the difference between the mean daily temperature and 65 degrees F:

cdd=(m - 65).

When the mean daily temperature is lower than 65 degrees F, there are no cooling degree days. (cdd=0).

The energy demand for a given period of time is related to the simple sum of the daily heating and cooling degree day values, or the degree day accumulation. Since many people require monthly statistics, the heating and cooling degree day accumulations for monthly time periods are a convenient measure of weather related energy usage.

The energy demand for a region, such as a state, depends on where people live. Temperatures in sparsely populated regions, such as the mountains, have less impact on regional energy demand than temperatures within large cities. Thus, regional energy demand is often estimated by population weighted statistics, rather than area averages.

Explanation of tables

The tables gives the expected monthly totals of populated weighted degree days for various regions of the country and individual states. These are derived from the most recent CPC seasonal temperature outlooks issued around mid-month. Because monthly temperatures are heavily influenced by daily weather systems that are unpredictable beyond about 10 days, the degree day outlook is expressed as a range rather than a single number. The lower end of the range shows a value that is expected to be exceeded 90 percent of the time. In other words, the monthly degree day totals are forecast to be higher than the "90%" value in the table about 90 percent of the time, and lower than that value 10 percent of the time. Likewise, the degree day totals for a given month is expected to exceed the "10%" value about 10 percent of the time. There is an 80 percent chance that the monthly degree day accumulation will be between the 90% and 10% values. The forecast mean degree day total is given in the column labeled "MEAN". The long-term monthly means of heating and cooling degree days for the 1971-2000 period is listed under the "NORMALS" columns. The mean difference between the normals and the mean value expected for a given month is shown in the "FORECAST DEPARTURE" columns. Note that the forecast departure of heating degree days is opposite that of the expected temperature departure, so a negative departure for hdd occurs when above normal temperatures are expected for that month. The sign of the departures of cooling degree days from normal is the same as the expected temperature anomaly, so negative departures in cdd's correspond to cooler than average temperatures.

The mean value for heating and cooling degree days for periods longer than one month can be obtained by summing the monthly mean values for the desired time period. The 90% and 10% degree day range for periods longer than a month, however, cannot be estimated by the simple sum of the corresponding monthly values.

The rows in the table display the year and month of the that the forecast is valid, with 1=January, 2 = February, and so on. The collection of 15 monthly degree day totals are grouped for each state or region defined just above the heading. The outlook was issued at the time shown on the top of the set of tables.
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