## Ways of computing Drought Monitor statistics

Statistics are calculated weekly for the U.S. Drought Monitor by two different methods that we refer to as “traditional,” which is how we did it from the beginning, or “categorical,” meaning we report on one category at a time. Below is an explanation of each method.

### Traditional Statistics

The traditional U.S. Drought Monitor statistic is a percent of an area that is in or worse than a certain drought category. These statistics are denoted by the inclusion of two drought categories in the label. For example the D0 or worse category is labeled as D0-D4 and shows the percent of the area that is in D0 or worse. Someone using or reporting on this type of information might say that on May 26, 2015, 90 percent of Utah was in moderate drought or worse (D1-4) and 34 percent of the state was in severe drought or worse (D2-4). Various forms of drought response and assistance are often pegged to drought that is at or above a certain level.

Note that with these statistics it is not possible to have a higher percent area for a higher drought category. For example the value of D1-D4 can be equal to the value of D0-D4 for a given week, but it can never be higher. Also note that these proportions do not automatically add up to 100 percent.

### Categorical Statistics

The categorical U.S. Drought Monitor statistic is the percent of the area in a certain drought category, and excludes areas that are better or worse. These statistics are denoted by only one drought category in each label. For example, the D0 category is labeled as D0 and only shows the percent of the area that is in D0. Someone using categorical statistics might say that as of May 26, 2015, 9.32 percent of Utah was in extreme (D3) drought, 25.07 percent was in severe drought, 56.24 percent was in moderate drought, and 9.37 percent of the state was abnormally dry.

Note that these statistics will add up to 100 percent for a given week. It is also possible to have a greater percent of the area in a higher drought category. For example, the percent of the area in D1 could be higher than the percent of the area in D0. However, it is not possible for all six values (including None) to have a total greater than 100 percent for a given week.