This study investigated the influence of five El Niño–Southern Oscillation (ENSO) types on rainy-season precipitation in China: central Pacific warming (CPW), eastern Pacific cooling (EPC), eastern Pacific warming (EPW), conventional ENSO and ENSO Modoki. The multi-scale moving t test was applied to determine the onset and withdrawal of rainy season. Results showed that the precipitation anomaly can reach up to 30 % above average precipitation during decaying CPW and EPW phases. Developing EPW could cause decreasing precipitation over large areas in China with 10–30 % lower than average precipitation in most areas. Conventional El Niño in the developing phase had the largest influence on ENSO-related precipitation among developing ENSO and ENSO Modoki regimes. Decaying ENSO also showed a larger effect on precipitation anomalies, compared to decaying ENSO Modoki. The difference between rainy-season precipitation under various ENSO regimes may be attributed to the combined influence of anti-cyclone in the western North Pacific and the Indian monsoon. Stronger monsoon and anti-cyclone are associated with enhanced rainy-season precipitation. The results suggest a certain predictability of rainy-season precipitation related to ENSO regimes.

Understanding the spatiotemporal variability of seasonal extreme precipitation and its linkage with climate patterns is of great importance for water resource management over the Yangtze River Basin. Hence, this study examined the spatiotemporal variability of seasonal extreme precipitation through the archetypal analysis (AA), by which observations were decomposed and characterized as several extreme modes. Six archetypes were identified and can obviously exhibit the features of events with above average or below average precipitation. Summer precipitation is the most variable compared to the winter, spring, and autumn precipitation through the trend analysis. It ranged from extremely dry (A6) to normal (A1 and A2) to extremely wet (A4). Climate teleconnections to the four archetypes for summer precipitation and relative importance of climate patterns were thus investigated. Results show that El Niño Southern Oscillation index is the strongest determinant of the ensuing archetypes representing the events with above average precipitation, while the Atlantic Multi-decadal Oscillation (AMO) contributes most to the events with below-average precipitation. A warm phase of the Pacific Decadal Oscillation (PDO) is significantly correlated with the above-average precipitation.

In terms of climate change and precipitation, there is large interest in how large-scale climatic features affect regional rainfall amount and rainfall occurrence. Large-scale climate elements need to be downscaled to the regional level for hydrologic applications. Here, a new Nonhomogeneous Hidden Markov Model (NHMM) called the Bayesian-NHMM is presented for downscaling and predicting of multisite daily rainfall during rainy season over the Huaihe River Basin (HRB). The Bayesian-NHMM provides a Bayesian method for parameters estimation. The model avoids the risk to have no solutions for parameter estimation, which often occurs in the traditional NHMM that uses point estimates of parameters. The Bayesian-NHMM accurately captures seasonality and interannual variability of rainfall amount and wet days during the rainy season. The model establishes a link between large-scale meteorological characteristics and local precipitation patterns. It also provides a more stable and efficient method to estimate parameters in the model. These results suggest that prediction of daily precipitation could be improved by the suggested new Bayesian-NHMM method, which can be helpful for water resources management and research on climate change.

The paper explores the impact of El Niño-Southern Oscillation (ENSO) on rainy season precipitation properties over the Yangtze River Basin. The multi-scale moving t-test was used to determine the onset and withdrawal of the rainy season. Results showed the following: (1) Onset and withdrawal of the averaged rainy season over the Yangtze River Basin showed a similar distribution and both progressed northwards and westwards. There is a trend for delayed onset of rainy season precipitation over the Yangtze River Basin. A similar trend in the withdrawal of rainy season precipitation was not found. (2) The decaying Central and Eastern Pacific Warming are indicative of wet signals in the Yangtze River Basin, with precipitation anomalies up to 25% above normal. The decaying Eastern Pacific Cooling and developing Eastern Pacific Warming are indicative of dry signals over the Yangtze River Basin, with 5–20% lower than average precipitation (3) ENSO Modoki in the developing phase is more important than the developing ENSO when it comes to present wetter or drier signals. Conversely, the decaying ENSO shows more prominent wet or dry signals than the decaying ENSO Modoki.

Precipitation is a significant parameter in many aspects such as agriculture, water management and climate variability. To characterize rainy season variations is important to understand precipitation variability under the effect of climate change. In this study, rainy season features (i.e., onset, retreat and rainy‐season precipitation) over the Huaihe River basin (HRB) and the response to different types of El Niño–Southern Oscillation (ENSO), that is, central Pacific warming (CPW), eastern Pacific warming (EPW), eastern Pacific cooling (EPC), conventional ENSO and ENSO Modoki in the developing and decaying phases are evaluated. The multi‐scale moving t test was used to capture onset and retreat of rainy season. The possible dynamic causes of ENSO‐induced precipitation over the HRB, such as monsoon and atmospheric circulation, were also explored. Results show that (a) onset (retreat) of rainy season progressed northwards (westwards), with rainy‐season precipitation increasing from north to south; (b) rainy‐season precipitation showed a strong correlation to Sea Surface Temperature (SST) in Niño regions. Dry and wet signals were identified in different regions of the HRB in the developing and decaying phases of CPW, EPC and EPW. Special attention should be paid on decaying EPW, where totally dry signals were found, which can reach down to 25% below average precipitation; (c) developing El Niño Modoki and decaying El Niño showed totally dry signals, with decaying El Niño Modoki and conventional La Niña demonstrating overall increasing precipitation; (d) different performances of ENSO‐induced precipitation during rainy season over the HRB are attributable to the combined influences of the monsoon from the India Ocean and the anticyclonic flow in the western North Pacific (WNP). Stronger anticyclone and monsoon are generally associated with increasing rainy‐season precipitation. These results can improve predictability of rainy season features and ENSO‐induced precipitation over the Huaihe River basin.

Monthly precipitation data at regular grids of 0.5° × 0.5° derived from observations during June‐August 1961‐2016 by the China Meteorological Administration were used to reveal characteristics of large‐scale circulations associated with rainy season precipitation over the source region of the Yangtze River (SRYR). The integrated impact of major influencing circulation patterns was examined by composites. Results showed that the first rainy season precipitation mode associates with the Southern Oscillation Index (SOI) and the Pacific Decadal Oscillation (PDO), explaining 64% of spatial and temporal rainy season precipitation variance in the region. Composites of precipitation pattern under different phases of SOI and PDO revealed that the effect of PDO on precipitation varies with the SOI phase. When in phase with the SOI, PDO‐induced precipitation anomalies are magnified with as quantified by the canonical correlation pattern. When out‐of‐phase, anomalies weaken or even disappear. Composites of moisture flux patterns show that large‐scale atmospheric circulation affects the strength of westerlies that transport moisture to the study area and formation of convergence. In coming decades, the PDO is likely to continue in a negative phase with La Niña (positive SOI) events, implying more precipitation during the rainy season. Consequently, this knowledge can be used to improve decision making regarding water supply and flood risk management in the SRYR.