Standardized Precipitation Index (SPI)
Index name: Standardized Precipitation Index (SPI).
Ease of use: Green.
Origins: The result of research and work done in 1992 at Colorado State University, United States, by McKee et al. The outcome of their work was first presented at the 8th Conference on Applied Climatology, held in January 1993. The basis of the index is that it builds upon the relationships of drought to frequency, duration and timescales.
In 2009, WMO recommended SPI as the main meteorological drought index that countries should use to monitor and follow drought conditions (Hayes, 2011). By identifying SPI as an index for broad use, WMO provided direction for countries trying to establish a level of drought early warning.
Characteristics: Uses historical precipitation records for any location to develop a probability of precipitation that can be computed at any number of timescales, from 1 month to 48 months or longer. As with other climatic indicators, the time series of data used to calculate SPI does not need to be of a specific length. Guttman (1998, 1999) noted that if additional data are present in a long time series, the results of the probability distribution will be more robust because more samples of extreme wet and extreme dry events are included. SPI can be calculated on as little as 20 years’ worth of data, but ideally the time series should have a minimum of 30 years of data, even when missing data are accounted for.
SPI has an intensity scale in which both positive and negative values are calculated, which correlate directly to wet and dry events. For drought, there is great interest in the ‘tails’ of the precipitation distribution, and especially in the extreme dry events, which are the events considered to be rare based upon the climate of the region being investigated.
Drought events are indicated when the results of SPI, for whichever timescale is being investigated, become continuously negative and reach a value of -1. The drought event is considered to be ongoing until SPI reaches a value of 0. McKee et al. (1993) stated that drought begins at an SPI of -1 or less, but there is no standard in place, as some researchers will choose a threshold that is less than 0, but not quite -1, while others will initially classify drought at values less than -1.
Owing to the utility and flexibility of SPI, it can be calculated with data missing from the period of record for a location. Ideally, the time series should be as complete as possible, but SPI calculations will provide a ‘null’ value if there are insufficient data to calculate a value, and SPI will begin calculating output again as data become available. SPI is typically calculated for timescales of up to 24 months, and the flexibility of the index allows for multiple applications addressing events that affect agriculture, water resources and other sectors.
Input parameters: Precipitation. Most users apply SPI using monthly datasets, but the computer programs have the flexibility to produce results when using daily and weekly values. The methodology of SPI does not change based upon using daily, weekly or monthly data.
Applications: The ability of SPI to be calculated at various timescales allows for multiple applications. Depending on the drought impact in question, SPI values for 3 months or less might be useful for basic drought monitoring, values for 6 months or less for monitoring agricultural impacts and values for 12 months or longer for hydrological impacts. SPI can also be calculated on gridded precipitation datasets, which allows for a wider scope of users than those just working with station-based data.
Strengths: Using precipitation data only is the greatest strength of SPI, as it makes it very easy to use and calculate. SPI is applicable in all climate regimes, and SPI values for very different climates can be compared. The ability of SPI to be computed for short periods of record that contain missing data is also valuable for those regions that may be data-poor or lacking long-term, cohesive datasets. The program used to calculate SPI is easy to use and readily available. NDMC provides a program for use on personal computers that has been distributed to more than 200 countries around the world. The ability to be calculated over multiple timescales also allows SPI to have a wide breadth of application. Many articles relating to SPI are available in the science literature, giving novice users a multitude of resources to rely on for assistance.
Weaknesses: With precipitation as the only input, SPI is deficient when accounting for the temperature component, which is important to the overall water balance and water use of a region. This drawback can make it more difficult to compare events of similar SPI values but different temperature scenarios. The flexibility of SPI to be calculated for short periods of record, or on data that contain many missing values, can also lead to misuse of the output, as the program will provide output for whatever input is provided. SPI assumes a prior distribution, which may not be appropriate in all environments, particularly when examining short-duration events or entry into, or exit out of, drought. There are many versions of SPI available, implemented within various computing software packages other than that found in the source code distributed by NDMC. It is important to check the integrity of these algorithms and the consistency of output with the published versions.
Resource: The SPI program can be run on Windows-based personal computers. Download at: National Drought Mitigation Center – Monitoring Tools. Global SPI data at 3-, 6-and 12-moth scales is available at NCAR/UCAR Research Data Archive. Additional resources are available at the Flood and Drought portal developed by GEF, UN Environment, IWA and DHI.
Guttman, N.B., 1998: Comparing the Palmer Drought Index and the Standardized Precipitation Index. Journal of the American Water Resources Association, 34: 113–121. DOI: 10.1111/j.1752-1688.1998.tb05964.x. (For more information on this paper, please contact the IDMP HelpDesk).
Guttman, N.B., 1999: Accepting the Standardized Precipitation Index: A Calculation Algorithm. Journal of the American Water Resources Association, 35: 311–322. DOI: 10.1111/j.1752-1688.1999.tb03592.x. (For more information on this paper, please contact the IDMP HelpDesk).
Hayes, M., M. Svoboda, N. Wall and M. Widhalm, 2011: The Lincoln Declaration on Drought Indices: Universal Meteorological Drought Index Recommended. Bulletin of the American Meteorological Society, 92(4): 485–488. DOI: 10.1175/2010BAMS3103.1.
McKee, T.B., N.J. Doesken and J. Kleist, 1993: The Relationship of Drought Frequency and Duration to Time Scales. Proceedings of the 8th Conference on Applied Climatology, 17–22 January 1993, Anaheim, CA. Boston, MA, American Meteorological Society.
World Meteorological Organization, 2012: Standardized Precipitation Index User Guide, (WMO-No. 1090), World Meteorological Organization, Geneva, Switzerland.
Wu, H., M.J. Hayes, D.A. Wilhite and M.D. Svoboda, 2005: The Effect of the Length of Record on the Standardized Precipitation Index Calculation. International Journal of Climatology, 25(4): 505–520. DOI: 10.1002/joc.1142.
Currently used by: Argentina, Austria, Belize, Bosnia and Herzegovina, Brazil, Bulgaria, Canada, Chile, Croatia, Cyprus, Dominican Republic, Germany, Greece, Hong Kong, Iran, Israel, Jamaica, Jordan, Kazakhstan, Libya, Lithuania, Macedonia, New Zealand, Pakistan, Peru, Slovenia, Spain, Sri Lanka, Switzerland, Tanzania, Thailand, Trinidad and Tobago, Turkey, Ukraine, USA.