The Global Precipitation Climatology Project (GPCP) has released the GPCP Version 1 Combined Precipitation Data Set, a global monthly precipitation dataset covering July 1987 to December 1995. The primary product is a merged analysis of precipitation estimates from low-orbit satellite microwave data, geosynchronous-orbit satellite infrared data, and rain gauge observations. The dataset also includes individual input fields, a combination of microwave and infrared satellite estimates, and error estimates for each field. The data are provided on a 2.5° × 2.5° latitude–longitude grid. Preliminary analyses show general agreement with prior studies of global precipitation and extend the study of El Niño–Southern Oscillation precipitation patterns. At the regional scale, there are systematic differences with standard climatologies. The GPCP combines the strengths of each input dataset to produce a merged global monthly precipitation field that is superior to any individual dataset. The combination technique involves matching microwave estimates with geo-IR observations to derive a calibration ratio for each grid box. The multisatellite estimate is formed from three satellite sources: AGPI estimates where available, a weighted combination of microwave and microwave-adjusted low-orbit IR elsewhere in the 40°N–S belt, and the microwave outside of this region. The satellite/gauge estimate is computed in two steps, first multiplying the multisatellite estimate by the ratio of the large-scale average gauge analysis to the large-scale average of the multisatellite estimate, and second combining the gauge-adjusted multisatellite estimate with the gauge analysis using inverse-error-variance weighting. The GPCP Version 1 Combined Precipitation Data Set shows fair agreement with standard climatologies, with a global annual-average precipitation rate of 2.5 mm day−1. On seasonal and regional scales, systematic differences start to appear. Validation over land shows that the multisatellite combination provides useful information, but the addition of even a few gauges greatly improves the estimate. Future releases of the GPCP combination will extend to earlier periods, improve error estimation, provide globally complete fields, and incorporate data from four-dimensional data assimilation models.The Global Precipitation Climatology Project (GPCP) has released the GPCP Version 1 Combined Precipitation Data Set, a global monthly precipitation dataset covering July 1987 to December 1995. The primary product is a merged analysis of precipitation estimates from low-orbit satellite microwave data, geosynchronous-orbit satellite infrared data, and rain gauge observations. The dataset also includes individual input fields, a combination of microwave and infrared satellite estimates, and error estimates for each field. The data are provided on a 2.5° × 2.5° latitude–longitude grid. Preliminary analyses show general agreement with prior studies of global precipitation and extend the study of El Niño–Southern Oscillation precipitation patterns. At the regional scale, there are systematic differences with standard climatologies. The GPCP combines the strengths of each input dataset to produce a merged global monthly precipitation field that is superior to any individual dataset. The combination technique involves matching microwave estimates with geo-IR observations to derive a calibration ratio for each grid box. The multisatellite estimate is formed from three satellite sources: AGPI estimates where available, a weighted combination of microwave and microwave-adjusted low-orbit IR elsewhere in the 40°N–S belt, and the microwave outside of this region. The satellite/gauge estimate is computed in two steps, first multiplying the multisatellite estimate by the ratio of the large-scale average gauge analysis to the large-scale average of the multisatellite estimate, and second combining the gauge-adjusted multisatellite estimate with the gauge analysis using inverse-error-variance weighting. The GPCP Version 1 Combined Precipitation Data Set shows fair agreement with standard climatologies, with a global annual-average precipitation rate of 2.5 mm day−1. On seasonal and regional scales, systematic differences start to appear. Validation over land shows that the multisatellite combination provides useful information, but the addition of even a few gauges greatly improves the estimate. Future releases of the GPCP combination will extend to earlier periods, improve error estimation, provide globally complete fields, and incorporate data from four-dimensional data assimilation models.