Reliable drought monitoring requires long-term and continuous precipitation data. High
resolution satellite measurements provide valuable precipitation information on a quasi-global
scale. However, their short lengths of records limit their applications in drought monitoring. In
addition to this limitation, long-term low resolution satellite-based gauge-adjusted data sets
such as the Global Precipitation Climatology Project (GPCP) one are not available in near
real-time form for timely drought monitoring. This study bridges the gap between low
resolution long-term satellite gauge-adjusted data and the emerging high resolution satellite
precipitation data sets to create a long-term climate data record of droughts. To accomplish
this, a Bayesian correction algorithm is used to combine GPCP data with real-time satellite
precipitation data sets for drought monitoring and analysis. The results showed that the
combined data sets after the Bayesian correction were a significant improvement compared to
the uncorrected data. Furthermore, several recent major droughts such as the 2011 Texas, 2010
Amazon and 2010 Horn of Africa droughts were detected in the combined real-time and
long-term satellite observations. This highlights the potential application of satellite
precipitation data for regional to global drought monitoring. The final product is a real-time
data-driven satellite-based standardized precipitation index that can be used for drought
monitoring especially over remote and/or ungauged regions.