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Numerous circulation indices have been applied in practical climate services focused on regional precipitation. It is beneficial to identify the most influential or decisive indices, but this is difficult with conventional correlation analyses because of the underlying nonlinear mechanisms for precipitation. This paper demonstrates a set of the most influential indices for July–August precipitation in North China, based on the recursive random forest (RRF) method. These decisive circulation indices include the Polar–Eurasia teleconnection, North African subtropical high ridge position, India–Burma trough, Antarctic Oscillation, Northern Hemisphere polar vortex central latitude, North Atlantic Oscillation, and western Pacific subtropical high northern boundary position. Some of these factors have been recognized as directly influential to the regional precipitation, for example, those of the northwestern Pacific subtropical high; however, some are not easily understood. Decision tree (DT) models using these indices were developed to facilitate composite analyses to explain the RRF results. Taking one of the most interesting DT rules as an example, when the North African subtropical high ridge position is sufficiently far south, an anomalous anticyclone occurs in the upstream and an anomalous cyclone in the downstream of North China. This is unfavorable for northward moisture transport in eastern China and hence causes less precipitation in North China than climatology. The present results are not only helpful for improving diagnostic models of regional precipitation, but also enlightening for exploring how global climate change could impact a region by modulating large-scale circulation patterns. [ABSTRACT FROM AUTHOR]

In the past few decades, there have been more extreme climate events occurring worldwide, including Canada, which has also suffered from many extreme precipitation events. In this paper, trend analysis, probability distribution functions, principal component analysis, and wavelet analysis were used to investigate the spatial and temporal patterns of extreme precipitation events of Canada. Ten extreme precipitation indices were calculated using long-term daily precipitation data (1950–2012) from 164 Canadian gauging stations. Several large-scale climate patterns such as El Niño–Southern Oscillation (ENSO), Pacific decadal oscillation (PDO), Pacific–North American (PNA), and North Atlantic Oscillation (NAO) were selected to analyze the relationships between extreme precipitation and climate indices. Convective available potential energy (CAPE), specific humidity, and surface temperature were employed to investigate potential causes of trends in extreme precipitation. The results reveal statistically significant positive trends for most extreme precipitation indices, which means that extreme precipitation of Canada has generally become more severe since the mid-twentieth century. The majority of indices display more increasing trends along the southern border of Canada while decreasing trends dominated the central Canadian Prairies. In addition, strong teleconnections are found between extreme precipitation and climate indices, but the effects of climate patterns differ from region to region. Furthermore, complex interactions of climate patterns with synoptic atmospheric circulations can also affect precipitation variability, and changes to the summer and winter extreme precipitation could be explained more by the thermodynamic impact and the combined thermodynamic and dynamic effects, respectively. The seasonal CAPE, specific humidity, and temperature are correlated to Canadian extreme precipitation, but the correlations are season dependent, which could be positive or negative. [ABSTRACT FROM AUTHOR]

This paper investigates how atmospheric circulation and orography affect the spatial variability of extreme precipitation in terms of depth-duration-frequency (DDF) curve parameters. To this aim, the Italian territory was considered because it is characterized by a complex orography and different precipitation dynamics and regimes. A database of 1494 time series with more than 20 years of maximum annual precipitation data was collected for the durations of 1, 3, 6, 12, and 24 h. For each data series, the parameters of DDF curves were estimated using a statistical simple scale invariance model. Hence, the combined effect of orography and atmospheric fields on parameter variability was investigated considering the spatial distribution of the parameters and their relation with elevation. The vertically integrated atmospheric moisture flux J was used as a measurement of the principal direction of the vapor transport at a given location. The analysis highlights the variability of DDF parameters and quantiles according to orography and precipitation climatology. This is confirmed by the evaluation of J modal direction over the study area. The variability of DDF parameters with mere elevation shows that maxima at high elevations seem to be upper bounded and more variable than those at lower elevations. Moreover, the mean of maximum annual precipitation of unit duration decreases with elevation. This last phenomenon is defined as 'reverse orographic effect' on extreme precipitation of short durations. [ABSTRACT FROM AUTHOR]