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The atmospheric moisture transport processes are of great importance to the occurrence and intensity of precipitation extremes. In this paper, we review the linkage between processes, including the large‐scale atmospheric circulation, atmospheric moisture transport, and extreme precipitation events. We first summarize the thermodynamic and dynamic processes and moisture transport trackings for historical precipitation extremes. We then focus on the contribution of three major atmospheric moisture transport pathways, that is, atmospheric rivers, low‐level jets, and tropical cyclones, to the occurrence and intensity of regional precipitation extremes. Studies on large‐scale atmospheric circulation driving water vapor transport for precipitation extremes over East Asia and North America were specifically reviewed for the understanding of physical mechanisms and predictability of moisture transport and extreme precipitation events. We then pay more attention to the effects of global warming on atmospheric moisture transport, and thus regional precipitation extremes from the perspectives of thermodynamic and dynamic changes of the atmosphere. In the end, we summarize future research challenges on the physical mechanisms of atmospheric moisture transport that are associated with regional precipitation extremes, especially under a warming climate. This article is categorized under: Science of Water > Water ExtremesScience of Water > Hydrological Processes [ABSTRACT FROM AUTHOR]

Changes in precipitation seasonality or redistribution of precipitation could exert significant influences on regional water resources availability and the well-being of the ecosystem. However, due to the nonuniform distribution of precipitation stations and intermittency of precipitation, precise detection of changes in precipitation seasonality on the global scale is absent. This study identifies and inter-compares trends in precipitation seasonality within seven precipitation datasets during the past three decades, including two gauge-based datasets derived from the Climatic Research Unit (CRU) and the Global Precipitation Climatology Centre (GPCC), one remote sensing-retrieval obtained from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), three reanalysis datasets obtained from National Centers for Environmental Prediction reanalysis II (NCEP2), European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim), and Modern Era Reanalysis for Research and Applications Version 2 (MERRA2), and one precipitation dataset merged from above three types, Multi-Source Weighted Ensemble Precipitation Version 1.2 (MSWEP_V1.2). Values of two indices representing the precipitation seasonality, the normal seasonality index (SI) and the dimensionless seasonality index (DSI), are estimated for each land grid in each precipitation dataset. The results show that DSI is more sensitive to changes in the temporal distribution of precipitation as it considers both annual amount and monthly fluctuations of precipitation, compared to SI that only considers monthly fluctuations of precipitation. There are large differences in precipitation seasonality at annual and climatologic scales between precipitation datasets for both SI and DSI. Within the seven precipitation datasets, PERSIANN-CDR SI and DSI show high precipitation seasonality while CRU SI, and ERA-Interim and MERRA2 DSI show the low precipitation seasonality in all continental regions. During 1988–2013, PERSIANN-CDR, NCEP2 and ERA-Interim show more widespread, statistically significant trends in precipitation seasonality than other four precipitation datasets. PERSIANN-CDR and NCEP2 show statistically significant decreases in SI over Middle East and Central Asia, while ERA-Interim, MERRA2 and MSWEP_V1.2 SI increase over Central and South Africa. Increases in SI over the most of South America are significant. Regions of Canada/Greenland/Iceland, East and South Africa show significant increases in precipitation seasonality, while South Europe/Mediterranean and Central Africa show significant decreases in precipitation seasonality in most datasets. Although time series of seasonality indices values fluctuate correlatively in recent three decades, there are no regions on which all precipitation datasets show a consistent, statistically significant, positive or negative trend in indices of precipitation seasonality. These inconsistent changes in precipitation seasonality within various precipitation datasets imply the importance of choosing dataset when studying changes in regional precipitation seasonality. [ABSTRACT FROM AUTHOR]

This study inter-compares the spatiotemporal features of precipitation extremes at global and regional scales within six daily precipitation datasets, i.e., gauge-based (Global Precipitation Climatology Center dataset, GPCC), satellite-retrieval (Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record, PERSIANN-CDR), three reanalysis datasets (ERA-Interim, ERAI; the National Center for Atmospheric Research Reanalysis 2, NCEP2; and the WATCH-Forcing-Data-ERA-Interim, WFDEI), and products merged from the three type datasets (the Multi-Source Weighted-Ensemble Precipitation, MSWEP). All datasets reproduce similar spatial patterns of both annual and seasonal precipitation extremes over the period from 1979 to 2017. Compared to the reference dataset gauge-based GPCC, the reanalysis WFDEI outperforms among six products with spatial correlation coefficients of 0.89 and 0.80 for the annual extreme indices (i.e., annual total amount of 95th precipitation and maximum 1-day precipitation), respectively. The satellite-based product PERSIANN-CDR performs better than reanalyses and merged datasets in capturing the temporal variability of the intensity and amount of precipitation extremes with similar changing tendencies and magnitudes of about 45 mm day−1 and 230 mm at the global scale, respectively. The reanalyses and merged products underestimate the intensity of precipitation extremes. The selected six datasets behave differently in various regions. For the percentile-based frequency of precipitation extremes, NCEP2 performs well in regions of the Southeast Asian (SEA) and Amazon (AMZ), while WFDEI better matches GPCC over East North America (ENA) and North Australia (NAU) in both spatial patterns and temporal changes with correlation coefficients of 0.84 and 0.90, respectively. For the intensity features of annual precipitation extremes, NCEP2 performs better than other four datasets over regions of SEA, AMZ and West Africa (WAF). ERAI and WFDEI are consistent with GPCC in ENA and NAU with correlations coefficients of the intensity between ERAI (WFDEI) and GPCC are 0.82 (0.77) and 0.78 (0.64) for ENA and NAU, respectively. For the intensity of seasonal precipitation extremes, GPCC shows the highest estimates in regions of SEA, AMZ, ENA and WAF. ERAI and WFDEI perform better in reproducing the spatial patterns of seasonal precipitation extremes in all regions. NCEP2 (ERAI and WFDEI) show(s) consistent temporal variability of seasonal precipitation extremes with GPCC in regions of AMZ and WAF (ENA and NAU). Overall, there are large discrepancies in the absolute values of daily precipitation among datasets, and performances of non-gauged-based precipitation datasets in capturing the spatiotemporal variability of precipitation extremes are dependent on seasons, regions, and time periods. [ABSTRACT FROM AUTHOR]

Both large-scale atmospheric circulation and moisture content in the atmosphere govern regional precipitation. We partition recent changes in mean, heavy, and extreme precipitation for all seasons over Canada to changes in synoptic circulation patterns (dynamic changes) and in atmospheric moisture conditions (thermodynamic changes) using 500-hPa geopotential height and precipitation data over 1979–2014. Using the self-organizing map (SOM) cluster analysis, we identify statistically significant trends in occurrences of certain synoptic circulation patterns over the Canadian landmass, which have dynamically contributed to observed changes in precipitation totals and occurrence of heavy and extreme precipitation events over Canada. Occurrences of circulation patterns such as westerlies and ridges over western North America and the North Pacific have considerably affected regional precipitation over Canada. Precipitation intensity and occurrences of precipitation extremes associated with each SOM circulation pattern also showed statistically significant trends resulting from thermodynamic changes in the atmospheric moisture supply for precipitation events. A partition analysis based on the thermodynamic–dynamic partition method indicates that most (~90%) changes in mean and extreme precipitation over Canada resulted from changes in precipitation regimes occurring under each synoptic circulation pattern (thermodynamic changes). Other regional precipitation changes resulted from changes in occurrences of synoptic circulation patterns (dynamic changes). Because of the high spatial variability of precipitation response to changes in thermodynamic and dynamic conditions, dynamic contributions could offset thermodynamic contributions to precipitation changes over some regions if thermodynamic and dynamic contributions are in opposition to each other (negative or positive), which would result in minimal changes in precipitation intensity and occurrences of heavy and extreme precipitation events. [ABSTRACT FROM AUTHOR]

Using the observed daily precipitation data across East China, this paper analyzes spatiotemporal changes of annual and seasonal extreme precipitation indices during 1960–2015. Effects of changes in atmospheric circulation on seasonal extremes were also detected by using the singular value decomposition method. Results show that amount of annual, spring and summer extreme precipitation over East China showed a significant increase with a maximum changing rate of 7.2, 3.2 and 5.4 mm decade−1, and the stations with upward tendency mainly located in the southern part of East China. Preceding sea surface temperature of the Indian Ocean and the Equatorial Pacific Ocean shows great influences on spring extreme precipitation over East China through modulating anomalous anticyclones and winds, especially over the downstream of the south of East China. Summer extreme precipitation is statistically significantly correlated with the western North Pacific subtropical high (WPSH) and positive anomalies of 500 hPa geopotential heights. Anomalously strong WPSH combining with two blocking highs in mid-latitude regions tends to trigger more extreme precipitation events in the Yangtze River Basin but less in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Climate change and large-scale climate patterns may result in changes in probability distributions of climate variables that are associated with changes in the mean and variability, and severity of extreme climate events. In this paper, we applied a flexible framework based on the Bayesian spatiotemporal quantile (BSTQR) model to identify climate changes at different quantile levels and their teleconnections to large-scale climate patterns such as El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO) and Pacific-North American (PNA). Using the BSTQR model with time (year) as a covariate, we estimated changes in Canadian winter precipitation and their uncertainties at different quantile levels. There were some stations in eastern Canada showing distributional changes in winter precipitation such as an increase in low quantiles but a decrease in high quantiles. Because quantile functions in the BSTQR model vary with space and time and assimilate spatiotemporal precipitation data, the BSTQR model produced much spatially smoother and less uncertain quantile changes than the classic regression without considering spatiotemporal correlations. Using the BSTQR model with five teleconnection indices (i.e., SOI, PDO, PNA, NP and NAO) as covariates, we investigated effects of large-scale climate patterns on Canadian winter precipitation at different quantile levels. Winter precipitation responses to these five teleconnections were found to occur differently at different quantile levels. Effects of five teleconnections on Canadian winter precipitation were stronger at low and high than at medium quantile levels. [ABSTRACT FROM AUTHOR]

Extreme precipitation event is rare and mostly occurs on a relatively small local scale, which presents marked uncertainties when analyzing its characteristics. Using daily precipitation data covering 1959-2009 from 62 stations over the Pearl River Basin, the percentile method (PM) and the absolute critical value method (ACVM) are applied to define extreme precipitation thresholds (EPT), and their different impacts on the spatial-temporal distribution of extreme precipitation event were analyzed in this study. The findings of this study show: (1) Using the K-means clustering algorithm in terms of precipitation indices and the topography, longitude and latitude of each station, the whole basin is divided into eight precipitation zones. (2) The extreme indices, including extreme precipitation frequency, extreme precipitation proportion and proportion of extremely n-day precipitation, calculated by PM are markedly higher than those calculated by ACVM during five decades, which is particularly obvious in the low precipitation area such as the west-northern of the basin since more daily precipitation events are treated as extreme precipitation in this region if EPT is defined by PM. (3) The spatial distributions of extreme frequencies respectively calculated by these two methods are quite different across the basin. The spatial distribution of extreme frequencies calculated by ACVM shows a high-value center in the southeast coastal areas and a low-value center in the northwest mountain areas. However, the extreme frequencies calculated by PM distribute evenly over the basin, which is obviously inconsistent with the empirical results, an area with heavy precipitation usually has a high extreme precipitation frequency, and vice versa. [ABSTRACT FROM AUTHOR]

The change structures of precipitation and precipitation intensity and rainy days are analyzed for the Pearl River Basin (from 1959 to 2009) on the basis of a suite of 24 climatic indices derived from daily precipitation data at 62 meteorological stations with the help of the Mann-Kendall test. Contributions of seasonal precipitation and precipitation intensity class to the annual precipitation are also examined using the inverse distance weighted method. The following four conclusions can be drawn: (1) although the average annual precipitation of the entire basin does not show obvious variation, the number of annual rainy days has decreased significantly in 98.3 % of the stations. These two factors result in an obvious increase in precipitation intensity at 64.5 % of the stations. (2) No clear change trend has been found for seasonal precipitation over the entire area; however, the number of rainy days in each season has decreased significantly. In particular, the number of rainy days in the entire year and in the fall season has decreased in 98.3 and 100 % of the stations, respectively. (3) Although the number of rainy days in drizzle has decreased in 83.9 % of the stations, the number of rainy days where heavy rain and extremely heavy rain occurred increased in nearly 75.8 and 82.3 % of the stations, respectively. (4) The number of rainy days in fall and winter contributes more to the change in the number of annual rainy days than the number of rainy days in spring and summer. Heavy rain and extremely heavy rain contribute more to the change in total annual precipitation than drizzle; however, they contribute less to the change in the number of annual rainy days than drizzle. The findings in this study can provide important information for formulating water resource and eco-environment management strategies in the Pearl River Basin to policymakers and stakeholders. [ABSTRACT FROM AUTHOR]

Using the daily precipitation and temperature data at 153 stations in the karst area of Southwest China from 1959 to 2009, the long-term change characteristics of wet and dry climatic conditions are analyzed by the Mann–Kendall test. This study shows that: 1) the annual average temperature has increased at 88% of the stations with an average rate of + 0.16 °C/10-year. This increase rate is greater than + 0.30 °C/10-year in the southeastern, northeastern, and western parts of the study region. Very warm days and abnormally warm days were seen increased at 47% and 63% of the stations, respectively. Very cool days and abnormally cool days in a year have reduced at respectively 94% and 95% of the stations; 2) no clear change trend was found for average annual precipitation over the entire area as a whole, but regional and seasonal changes were quite obvious. The annual total precipitation has decreased by − 22.5 mm/10-year in the central part but increased by + 8.9 mm/10-year in the western part of the region, and summer and winter seemed to become wetter while spring and autumn became drier. Although the number of rainy days in a year has decreased at almost 53% of the total stations with an average rate of − 3.9 days/10-year over the entire area, the number of extremely heavy rainy days has increased by + 0.2, + 0.4 and + 0.4 days/10-year in the southern Sichuan Province, the central part of Yunnan Province, and the northeastern Hubei Province, respectively; and 3) the extreme drought became more serious. The consecutive dry days has increased significantly at nearly 46% of the stations, especially in the western Guangxi Autonomous Region, the southern Guizhou Province, and the eastern Chongqing Municipality. The extreme drought remained at a high frequency at the beginning of the 21st century. It has shifted gradually from the eastern and western parts to the south-central part which is characterized by medium-high rocky desertification. Hopefully findings from this study will help for a better understanding of the impacts to some eminent geological hazards such as rocky desertification, increased frequency of drought and storms, and landslides in recent years. [ABSTRACT FROM AUTHOR]

Highlights: [•] The non-parametric absolute critical value method is not applicable to large scale river basin. [•] The non-parametric percentile method is sensitive to data series and dependent on percentile. [•] The parametric method depends on the probability distribution and size of data series. [•] The detrended fluctuation analysis method provides unique threshold and reasonable solution. [ABSTRACT FROM AUTHOR]

Highlights • Thermodynamic changes are conducive to the increased occurrence of extreme spring fire weather over western Canada. • Human-induced climate changes are responsible for the increasing occurrences of extreme spring fire over western Canada. • The spring warming and drying trends over western Canada cannot be attributed to large-scale climate variability. Abstract On May 2016 an extreme large wildfire affected Fort McMurray of Canada, leading to the largest wildfire evacuation and the costliest natural disaster in Canadian history. This wildfire was caused by extremely warm and dry weather conditions in spring. Here we investigate thermodynamic and dynamic (atmospheric circulation) conditions, and teleconnections conducive to extreme wildfire climate of western Canada since 1871. Results show that the extreme wildfire was very likely an outcome of anthropogenic effects that increase the occurrence of a persistent upper ridge associated with a warm and dry weather over western Canada. Changes in dynamic conditions decreased temperature and increased precipitation, while changes in thermodynamic conditions increased temperature and decreased precipitation. Thus the observed increase in temperature and decrease in precipitation on 26 April–15 May over western Canada were caused by changes in thermodynamic conditions. Although the Pacific North American (PNA) pattern was teleconnected with the occurrence of certain synoptic circulation patterns over western Canada, changes in the occurrence of the synoptic circulation pattern associated with the extreme wildfire cannot be explained by increased occurrences of the positive phase of PNA. The El Niño-Southern Oscillation and the Pacific Decadal Oscillation have not been found to have contributed to wildfire weather in western Canada. The spring warming and drying trends since 1871 over western Canada cannot be attributed to changes in common teleconnections. [ABSTRACT FROM AUTHOR]