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Precipitation is an important climatic parameter, and its variability severely affects regional hydrological processes and water resource management. In order to explore the changing spatial and temporal characteristics of precipitation-related indices, including precipitation amounts indices, extreme precipitation indices, and precipitation concentration indices, in Hubei province, central China during 1961-2010, several precipitation-related indices series were analyzed using the Mann-Kendall test, Pettitt test, and inverse distance weighted interpolation method in this paper. The results are as follows: (1) A clear south-north gradient is apparent in the spatial distribution of the majority of precipitation-related indices, while the distribution of other indices (i.e., CDD, PCD, and PCP) is just the opposite. Most part of Hubei province can experience mixed positive and negative trends in precipitation-related indices. (2) The majority of precipitation-related indices exhibit an increasing trend, but most of which are not significant. July has the largest positive trend, with a regional average of 14.76 mm/decade. As for extreme precipitation indices, there exist large variations in Hubei, especially in R95pTOT. Besides, no obvious trends are shown in precipitation concentration indices. (3) With the exception of consecutive dry days (CDD), most of extreme precipitation indices are strongly correlated with annual mean precipitation (AMP) in Hubei. And the extreme precipitation indices are well correlated with each other except CDD and consecutive wet days (CWD). For six precipitation-related indices (i.e., SDII, RX1day, RX5day, R95pTOT R99pTOT, and PCD), there are significant positive relationships with Northern Hemisphere Subtropical High (NHSH) but significant negative relationships with Northern Hemisphere Polar Vortex (NHPV). Furthermore, the majority of precipitation-related indices have significant negative correlations with East Asian summer monsoon index (EASMI) and South China Sea summer monsoon index (SCSSMI), and the correlation coefficient with EASMI is higher than that with SCSSMI. [ABSTRACT FROM AUTHOR]