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The Standardized Precipitation Index (SPI) is a probability
index that can be calculated for different time periods to indicate periods of abnormal
wetness or dryness.
SPI is derived solely from monthly precipitation and
can be compared across regions with different climates.
The SPI is an index
based on the probability of recording a given amount of precipitation, and the probabilities
are standardized so that an index of zero indicates the median precipitation amount (half of
the historical precipitation amounts are below the median, and half are above the median).
This dataset shows the average 12-month SPI
(in classes ranging from extremely wet to extremely dry) for the three-month
forecast period indentified in the dataset title. Negative (i.e.,
dry) values of the 12-month SPI are closely associated with a high potential
for wildland fire.
SPI was calculated from the
long-term precipitation record up to the last observed month and from projected monthly precipitation values provided by the weather model identified
in the dataset title.
Future climate forecasts are available through cooperation with the
International Research Institute for Climate Prediction (IRI) of Columbia University
which provides monthly updates of 7-month future climate forecasts from
five different general circulation models (GCMs) of the global
atmosphere. GCM results come from the University of Maryland
(COLA), the University of Hamburg (ECHAM4.5), the National Weather
Service’s Climate Prediction Center (NCEP), NASA’s Goddard Institute of
Space Studies (NSIPP), and the Scripps Oceanographic Institute (ECPC).
Data Provided By:
United States Forest Service, MAPSS team--Raymond Drapek
Layers in this dataset are based on combinations of the following options.
You may choose from these options to select a specific layer on the map page.