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Global Gridded Standardized Precipitation Index (SPI) from CMORPH Daily

Associated Agencies

National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Center (CPC)

The Standardized Precipitation Index, or SPI, is a drought index that captures how observed precipitation deviates from the climatological average over a given time period. This global SPI is derived from the NOAA CMORPH dataset, using the Climate Engine tool, and includes timescales of 1, 2, 3, 6, 9 and 12 months.

The NOAA CMORPH precipitation dataset is a gridded dataset derived from combining numerous microwave-based estimates from low orbiter satellites.  The dataset is also archived and managed through the NOAA Climate Data Record program at NOAA's National Centers for Environmental Information (NCEI).

Interactive Map: Standardized Precipitation Index (SPI)

Dry Conditions
Wet Conditions
Dry Conditions
Wet Conditions
Dry Conditions
Wet Conditions
Dry Conditions
Wet Conditions
Dry Conditions
Wet Conditions
Dry Conditions
Wet Conditions

HOW TO

How to use this site:

  • Datasets are in GeoTIFF, readable by GIS software and many meteorological tools.

ACCESS

SPI from CMORPH in GeoTIFF: available for download from NOAA/NIDIS 

Related Publications

Joyce, R. J., J. E. Janowiak, P. A. Arkin, and P. Xie, 2004: CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution.. J. Hydromet., 5, 487-503.   https://ftp.cpc.ncep.noaa.gov/precip.orig/CMORPH_V1.0/REF/Joyce_et_al_2004_JHM_CMORPHP.pdf

Guttman, N. B., 1999: Accepting the standardized precipitation index: A calculation algorithm. J. Amer. Water Resour. Assoc., 35, 311–322, https://doi.org/10.1111/j.1752-1688.1999.tb03592.x.

Wu, H., M. J. Hayes, D. A. Wilhite, and M. D. Svoboda, 2005: The effect of length of record on the standardized precipitation index. Int. J. Climatol., 25, 505–520, https://doi.org/10.1002/joc.1142.

Wu, H., M. D. Svoboda, M. J. Hayes, D. A. Wilhite, and F. Wen, 2007: Appropriate application of the standardized precipitation index in arid locations and dry seasons. Int. J. Climatol., 27, 65–79, https://doi.org/10.1002/joc.1371.

Cumbie-Ward, R. V., and R. P. Boyles, 2016: Evaluation of a high-resolution SPI for monitoring local drought severity. J. Appl. Meteor. Climatol., 55, 2247–2262, https://doi.org/10.1175/JAMC-D-16-0106.1.

Vose, R. S., and et al, 2014a: NOAA’s Gridded Climate Divisional Dataset (CLIMDIV). NOAA National Climatic Data Center, accessed 4 June 2018, https://doi.org/10.7289/V5M32STR.