The new Version 2.3 of the Global Precipitation Climatology Project (GPCP) Monthly analysis is described in terms of changes made to improve the homogeneity of the product, especially after 2002. These changes include corrections to cross-calibration of satellite data inputs and updates to the gauge analysis. Over-ocean changes starting in 2003 resulted in an overall precipitation increase of 1.8% after 2009. Updating the gauge analysis to its final, high-quality version increases the global land total by 1.8% for the post-2002 period. These changes correct a small, incorrect dip in the estimated global precipitation over the last decade given by the earlier Version 2.2. The GPCP analysis is also used to describe global precipitation in 2017. The general La Niña pattern for 2017 is noted and the evolution from the early 2016 El Niño pattern is described. The 2017 global value is one of the highest for the 1979–2017 period, exceeded only by 2016 and 1998 (both El Niño years), and reinforces the small positive trend. Results for 2017 also reinforce significant trends in precipitation intensity (on a monthly scale) in the tropics. These results for 2017 indicate the value of the GPCP analysis, in addition to research, for climate monitoring.

El Niño‐Southern Oscillation (ENSO) is an important driver of interannual climate variability with increasing attention for its impacts on water and flood management. The impact of ENSO on basin‐scale floods during the TRMM period (1998–2013) is examined by using the streamflow outputs from the Dominant river Routing Integrated with VIC Environment model (DRIVE). Significant simultaneous correlations between flood indices and Niño 3.4 appear in many flood‐prone river basins during peak flood months across both the tropics and midlatitudes especially for flood frequency and flood duration. Gauged by significant lag‐correlations between floods and Niño 3.4, significant ENSO‐leading‐floods relations are found as well in many river basins in South America, south and southeastern Asia, and northern Africa. These ENSO‐floods‐relations can greatly enhance understanding of physical mechanisms relevant to the ENSO impact and may also improve the skills of basin‐scale monthly‐to‐seasonal flood forecast, thus allowing for better preparedness and management of flood risks.

Tropical (30°N–30°S) interdecadal precipitation changes and trends are explored for the satellite era using GPCP monthly analyses and CMIP5 outputs and focusing on precipitation intensity distributions represented by percentiles (Pct) and other parameters. Positive trends occur for the upper percentiles (Pct ≥ 70th), and become statistically significant for Pct ≥ 80th. Negative trends appear for the middle one-half percentiles (~20th–65th) and are statistically significant for the 20th–40th percentiles. As part of these trends there is a decadal shift around 1998, indicating the presence of an interdecadal [Pacific decadal oscillation (PDO)] signal. For the lower percentiles (Pct ≤ 10th), positive trends occur, although weakly. The AMIP-type simulations generally show similar trend results for their respective time periods. Precipitation intensity changes are further examined using four precipitation categories based on the climatological percentiles: Wet (Pct ≥ 70th), Intermediate (70th > Pct ≥ 30th), Dry (30th > Pct ≥ 5th), and No Rain (5th > Pct ≥ 0th). Epoch differences of occurrence frequency between 1988–97 and 1998–2015 have spatial features generally reflecting the combined effect of the PDO and external forcings, specifically the anthropogenic greenhouse gas (GHG)-related warming based on comparisons with both AMIP and CMIP results. Furthermore, precipitation intensity over Wet zones shows much stronger changes than mean precipitation including a more prominent change around 1998 associated with the PDO phase shift. Trends also appear in the sizes of Intermediate and Dry zones, especially over ocean. However, changes in the sizes of Wet and No Rain zones are generally weak. AMIP simulations reproduce these changes relatively well. Comparisons with the CMIP5 historical experiments further confirm that the observed changes and trends are a combination of the effect of the PDO phase shift and the impact of anthropogenic GHG-related warming.