Seasonal Extreme Precipitation Research Articles

Role of Natural Climate Variability in the Detection of Anthropogenic Climate Change Signal for Mean and Extreme Precipitation at Local and Regional Scales

Abstract Climate change will impact both mean and extreme precipitation, having potentially significant consequences on water resources. The implementation of efficient adaptation measures must rely on the development of reliable projections of future precipitation and on the assessment of their related uncertainty. Natural climate variability is a key uncertainty component, which can result in apparent decadal trends that may be greater or lower than the long-term underlying anthropogenic climate change trend. The goal of the present study is to assess how natural climate variability affects the ability to detect the climate change signal for mean and extreme precipitation. Annual and seasonal total precipitation are used as indicators of the mean, whereas annual and seasonal maximum daily precipitation are used as indicators of extremes. This is done using the CanESM2 50-member and CESM1 40-member large ensembles of simulations over the 1950–2100 period. At the local scale, results indicate that natural climate variability will dominate the uncertainty for annual and seasonal extreme precipitation going up to the end of the century in many parts of the world. The climate change signal can, however, be reliably detected much earlier at the regional scale for extreme precipitation. In the case of annual and seasonal total precipitation, the climate change signal can be reliably detected at the local scale without resorting to a regional analysis. Nonetheless, natural climate variability can impede the detection of the anthropogenic climate change signal until the middle to late century in many parts of the world for mean and extreme precipitation.

Spatial Seasonal Distribution of Climatological Precipitation over the Middle of the Indochina Peninsula

Rainfall intensity and frequency are important parameters in agricultural development and water resource management. The middle of the Indochina peninsula climate is characterized by rainfall variability associated with complex terrains. The present study focuses on spatial seasonal extreme precipitation trends over the middle of the Indochina Peninsula for the 30 year period from 1978-2007. Daily gridded precipitation data obtained at 0.5° horizontal grid resolution from APHRODITE (Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources) was used to detect the spatial trends with the use of the Man-Kendall and Theil-Sen approach. Extreme precipitation indices were selected from the WMO–CCL/CLIVAR list of extreme precipitation indices focusing on intensity and frequency. The study shows a consistently increasing upward trend at 10.04 dfrom the WDAY index. In seasonal analysis, the pre-monsoon trend shows a significant upward trend in the PRCTOT index, while the WDAY index for pre-monsoon season has the highest correlation coefficient in downward trend. Spatial analysis of extreme precipitation indices shows that the PRCTOT index of the pre-monsoon season has the largest percentage change in significant upward trend over the northern Basins that are consistent with MAX and Mean but not for WDAY. In addition, the inter-annual relationship between the Oceanic Nino Index and PRCTOT is shown in relation with the La Niña phase for both April and May.

Spatiotemporal Variability of Extreme Summer Precipitation over the Yangtze River Basin and the Associations with Climate Patterns

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.

Statistical analyses of extreme rainfall events in Thessaloniki, Greece

Concern about climate change has amplified the need for accurate information about variations in statistical characteristics of extreme rainfall events in both smaller temporal and spatial scale. For this reason, in this paper the hourly precipitation measurements obtained at the Department of Meteorology and Climatology of the Aristotle University of Thessaloniki meteorological station, during the period 1947–2003, are used. A new threshold determining method is proposed, in order to define the extreme rainfall event in Thessaloniki, based upon the polynomial trends of the cumulative distribution functions, retrieved from hourly precipitation measurements. Through this approach, three statistical goodness-of-fit tests were carried out, in order to come up with the best fitting probability distributions, for annual and seasonal extreme precipitation conditions. Based upon this fitting distribution procedure, return periods for different precipitation extreme values were calculated. Results indicate that the value of 6.5mm/h is the hourly threshold of extreme precipitation in Thessaloniki over the studied period. Furthermore, the Generalized Pareto, and the Johnson SB, the log-Gamma and the Lognormal are the best fitted probability models for the description of annual and seasonal extreme rainfall events, respectively. Last but not least, the contribution of hourly data in the accuracy of the results is discussed.

Austral summer Southern Africa precipitation extremes forced by the El Niño-Southern oscillation and the subtropical Indian Ocean dipole

Southern Africa, defined here as the African continent south of 15°S latitude, is prone to seasonal precipitation extremes during December–March that have profound effects on large populations of people. The intensity of summertime precipitation extremes can be remarkable, with wet seasons experiencing up to a doubling of the seasonal average precipitation. Recognizing the importance of understanding the causes of Southern Africa precipitation extremes for the purpose of improved early warning, an 80-member ensemble of atmospheric model simulations forced by observed time-varying boundary conditions during 1979–2016 is used to examine the mechanisms by which December–March precipitation extremes are delivered to Southern Africa and whether the El Nino-Southern Oscillation (ENSO) and the Subtropical Indian Ocean Dipole (SIOD) modify the probabilities of extreme seasonal precipitation occurrences. The model simulations reveal that the synchronous ENSO and SIOD phasing conditions the probability of December–March extreme precipitation occurrences. The probability of extreme wet seasons is greatly increased by La Nina, especially so when combined with a positive SIOD, and greatly decreased by El Nino regardless of SIOD phasing. By contrast, the probability of extreme dry seasons is increased by El Nino and is decreased by La Nina. The mechanisms by which extreme precipitation are delivered are the same regardless of ENSO and SIOD phase. Extreme wet seasons are a result of an anomalous lower tropospheric cyclone over Southern Africa that increases convergence and moisture fluxes into the region while extreme dry seasons are a result of an anomalous lower tropospheric anticyclone that decreases convergence and moisture fluxes into the region.

Paleogene monsoons across India and South China: Drivers of biotic change

Monsoonal climates at low latitudes (<32°N) are an inevitable consequence of seasonal migrations of the Inter-tropical Convergence Zone (ITCZ), but the character of these monsoons depends on continental configuration, orographic expression and the strength of Hadley circulation. To explore the evolution of monsoon systems across southern Asia we compare climate signatures archived in ten Paleogene floras from northern India, Tibet and southern China, occupying low palaeolatitudes at a time of extreme global warmth and elevated CO2. Fossil leaf form reveals that under such 'hothouse' conditions megathermal early Eocene to earliest Miocene forests were exposed to strong monsoonal climates typical of those experienced today arising from annual migrations of the ITCZ, possibly enhanced by a lower equator-to-pole temperature gradient. Throughout the Paleogene an elevated Tibetan highland produced no discernable modification of this ITCZ monsoon, although rainfall seasonality similar to that of the modern South Asia Monsoon (SAM) is observed in northern India as early as the beginning of the Eocene, despite its near-equatorial palaeoposition. In South China rainfall seasonality increased progressively achieving modern monsoon-like wet season/dry season precipitation ratios by the early Oligocene. Despite evidencing weak rainfall seasonality overall, fossil leaves from South China have exhibited monsoon-adapted morphologies, comparable to those seen in today's Indonesia-Australia Monsoon, for at least 45millionyears. Together, the Indian and South China fossil leaf assemblages show that the evolution of megathermal ecosystems across southern Asia has been influenced profoundly by monsoonal climates for at least the last 56millionyears. The Paleogene ITCZ-driven monsoon system strongly impacted India as it transited the Equator likely eliminating Gondwanan taxa not able to adapt to seasonal precipitation extremes. Furthermore, powerful seasonally-reversing winds, and associated surface ocean currents, are likely to have facilitated two-way biotic transfer between India and Eurasia long before closure of the Tethys Ocean.

Potential Predictability of Seasonal Extreme Precipitation Accumulation in China

Abstract The potential predictability of seasonal extreme precipitation accumulation (SEPA) across mainland China is evaluated, based on daily precipitation observations during 1960–2013 at 675 stations. The potential predictability value (PPV) of SEPA is calculated for each station by decomposing the observed SEPA variance into a part associated with stochastic daily rainfall variability and another part associated with longer-time-scale climate processes. A Markov chain model is constructed for each station and a Monte Carlo simulation is applied to estimate the stochastic part of the variance. The results suggest that there are more potentially predictable regions for summer than for the other seasons, especially over southern China, the Yangtze River valley, the north China plain, and northwestern China. There are also regions of large PPVs in southern China for autumn and winter and in northwestern China for spring. The SEPA series for the regions of large PPVs are deemed not entirely stochastic, either with long-term trends (e.g., increasing trends in inland northwestern China) or significant correlation with well-known large-scale climate processes (e.g., East Asian winter monsoon for southern China in winter and El Niño for the Yangtze River valley in summer). This fact not only verifies the claim that the regions have potential predictability but also facilitates predictive studies of the regional extreme precipitation associated with large-scale climate processes.

Moisture sources and pathways associated with the spatial variability of seasonal extreme precipitation over Canada

Nine regions with spatially coherent seasonal 3-day total precipitation extremes across Canada were identified using a clustering method that is compliant to the extreme value theory. Using storm back-trajectory analyses, we then identified possible moisture sources and pathways that are conducive to occurrences of seasonal extreme precipitation events in four seasons for the nine regions identified. Moisture pathways for all extreme precipitation events were clustered to nine dominant moisture pathway patterns using the self-organizing map method. Results show that horizontal moisture pathway patterns and their occurrences were not evidently different between seasons. However, warm (summer and fall) and cold (winter and spring) seasons show considerable differences in the spreading of moisture sources in all nine regions, even though many sources do not frequently contribute to extreme precipitation events. In all four seasons, terrestrial evapotranspiration had provided major moisture sources to many extreme precipitation events occurred in inland regions. Central Canada had received more widespread moisture sources over surrounding oceans of North America than western and eastern Canada, because of more diverse moisture pathway patterns for central Canada that transport moisture from all surrounding oceans to central Canada. Extreme precipitation in southwestern Canada mainly resulted from atmospheric rivers over the North Pacific Ocean. For northwestern Canada, moisture pathway patterns were from the northern Pacific, Arctic and northern Atlantic oceans, even though more than 78% of trajectories for northwestern Canada were from the North Pacific. Westerlies from the North Pacific Ocean and northern polar jet streams controlled dominant pathways to central and eastern Canada. More extreme precipitation events over Canada were fed by the Arctic Ocean in warm than in cold seasons.

Spatiotemporal patterns of annual and seasonal precipitation extreme distributions across China and potential impact of tropical cyclones

ABSTRACTStatistical properties of annual and seasonal daily maximum precipitation in terms of nonstationarity, upper tail properties, and impact of tropical cyclones (TCs) were analysed, using data from 728 meteorological stations across China and TCs tracks data covering a period of 1951–2014. The change points and trends detected by stepwise regression method and modified Mann–Kendall, respectively, provide limited evidence of the violation of the stationarity assumption in both annual and seasonal extreme precipitation, and we cannot make conclusive statements about the presence of a possible climate change signal. For stationary stations, the ratio of scale to location parameters of generalized extreme value (GEV) distribution shows exponential for annual and seasonal extreme precipitation in some sub‐regions. On the other hand, annual and seasonal maxima point to an unbounded‐above and heavy‐tail behaviour, and discussion of these upper tail properties in light of mixtures of different rainfall‐generating mechanisms is provided. In addition, anomalous values of the GEV shape parameter are associated with TCs in controlling the upper tail of annual maxima on China's coastal areas with strong spatial heterogeneities.

Assessing the Spatial and Temporal Patterns of Seasonal Precipitation Extremes and the Potential Influencing Factors in Dongting Lake Basin, China

The Dongting Lake Basin (DTLB) of China is a flood prone area. Knowledge of the spatiotemporal characteristics and risks of precipitation extremes is essential for flood mitigation. Based on the precipitation amount (R), precipitation intensity (Ri), max 1 day precipitation amount (Rx1) and max 5 day precipitation amount (Rx5), this study analyzed the spatial-temporal patterns, risks and investigated the influences of the precipitation extremes at seasonal scale. The distributed high values of R, Ri, Rx1, Rx5 and their 5-year return levels (R5, Ri5, Rx15, Rx55) indicated high flood risks in the eastern and northern parts of the basin, and the general upward trends of these indices suggested increasing flood risks, except for some areas in southwestern part in spring and autumn. The precipitation extremes were related to the topographic and circulation factors, within which the latter might have greater roles. Furthermore, the trend directions of the 5-year return levels (R5, Ri5, Rx15, Rx55) were not always the same as the initial indices (R, Ri, Rx1, Rx5), suggesting that overall decreasing (increasing) precipitation extremes do not always represent decreasing (increasing) risks of floods. Hence, policy makers should pay more attention to the risks of precipitation extremes rather than their overall tendencies.

Synoptic and quantitative attributions of the extreme precipitation leading to the August 2016 Louisiana flood

AbstractThe catastrophic August 2016 flood in the U.S. state of Louisiana was a result of intense precipitation produced by a slow‐moving tropical low‐pressure system interacting with an eastward traveling baroclinic trough to the north. While tropical‐midlatitude interactions of this nature are rare, they are not unprecedented. Analyses presented point toward the tendency for more and perhaps stronger upper level troughs propagating out of the western U.S. in summer; these then have an increasing potential to cross paths with low‐pressure systems that form around the Gulf Coast. Combined with the projected increase in precipitable water, resulting precipitation magnitude would increase. Large‐ensemble modeling indicates that the prospect of future tropical‐midlatitude interactions is a scenario that Louisiana will face in the future, while regional simulations estimate that the climate warming since 1985 may have increased the event precipitation (11–14 August 2016) on the order of 20%, all of which allude to a conceivable forecast of nonhurricane‐related, warm season extreme precipitation in the Gulf Coast states.

Biotic and abiotic controls in determining exceedingly variable responses of ecosystem functions to extreme seasonal precipitation in a mesophytic alpine grassland

As a result of global climate change, frequent and intensive extreme climate events are observed and predicted. These extreme climate events can change ecosystem functions through driving plant growth and mortality, as well as ecological and evolutionary processes into different directions. We simulated a 1-in-100-year extreme precipitation event in different plant growth seasons (i.e. spring, summer, or autumn) to investigate the functional responses of a mesophytic alpine grassland ecosystem to climate change in the Tibetan plateau. The results demonstrated that the seasonal distribution of extreme precipitation is a critical factor in determining soil microbial- and plant-productivity. The response of vegetation net primary productivity (NPP) to extreme precipitation depends on the growth seasons and plant types. Total NPP in the treatments experienced extreme precipitation in the early (spring), mid- (summer) and late- (autumn) plant growth seasons were significant lower, higher, and no difference, respectively, compared with the control. Soil temperature and moisture were the key abiotic factors that affected ecosystem functions. For example, in the early plant growth season, no changes of soil moisture and the decreased temperature in response to the extreme precipitation resulted in a substantial decline in NPP. By contrast, in the mid-plant growth season, higher temperature and soil moisture elicited positive synergistic effects on plant growth and soil microbial processes. The increased sensitivity of above-ground NPP and the shift of dominant species from sedges to less palatable forbs might inevitably exaggerate the degradation of this grassland. Nevertheless, a high resilience index in the related ecological processes could potentially contribute to the grassland acclimation and stability, as most parameters returned to the similar levels as in the control after the extreme events ceased. Therefore, several synergistic or antagonistic mechanisms are hypothesized to operate in parallel or at different levels of organization and timescales. Further studies involving a range of different potential scenarios and longer periods are needed to predict the future climate change impacts on mesophytic grassland.

Trends in atmospheric patterns conducive to seasonal precipitation and temperature extremes in California.

Recent evidence suggests that changes in atmospheric circulation have altered the probability of extreme climate events in the Northern Hemisphere. We investigate northeastern Pacific atmospheric circulation patterns that have historically (1949-2015) been associated with cool-season (October-May) precipitation and temperature extremes in California. We identify changes in occurrence of atmospheric circulation patterns by measuring the similarity of the cool-season atmospheric configuration that occurred in each year of the 1949-2015 period with the configuration that occurred during each of the five driest, wettest, warmest, and coolest years. Our analysis detects statistically significant changes in the occurrence of atmospheric patterns associated with seasonal precipitation and temperature extremes. We also find a robust increase in the magnitude and subseasonal persistence of the cool-season West Coast ridge, resulting in an amplification of the background state. Changes in both seasonal mean and extreme event configurations appear to be caused by a combination of spatially nonuniform thermal expansion of the atmosphere and reinforcing trends in the pattern of sea level pressure. In particular, both thermal expansion and sea level pressure trends contribute to a notable increase in anomalous northeastern Pacific ridging patterns similar to that observed during the 2012-2015 California drought. Collectively, our empirical findings suggest that the frequency of atmospheric conditions like those during California's most severely dry and hot years has increased in recent decades, but not necessarily at the expense of patterns associated with extremely wet years.

Simulating multimodal seasonality in extreme daily precipitation occurrence

Summary Floods pose multi-dimensional hazards to critical infrastructure and society and these hazards may increase under climate change. While flood conditions are dependent on catchment type and soil conditions, seasonal precipitation extremes also play an important role. The extreme precipitation events driving flood occurrence may arrive non-uniformly in time. In addition, their seasonal and inter-annual patterns may also cause sequences of several events and enhance likely flood responses. Spatial and temporal patterns of extreme daily precipitation occurrence are characterized across the UK. Extreme and very heavy daily precipitation is not uniformly distributed throughout the year, but exhibits spatial differences, arising from the relative proximity to the North Atlantic Ocean or North Sea. Periods of weeks or months are identified during which extreme daily precipitation occurrences are most likely to occur, with some regions of the UK displaying multimodal seasonality. A Generalized Additive Model is employed to simulate extreme daily precipitation occurrences over the UK from 1901 to 2010 and to allow robust statistical testing of temporal changes in the seasonal distribution. Simulations show that seasonality has the strongest correlation with intra-annual variations in extreme event occurrence, while Sea Surface Temperature (SST) and Mean Sea Level Pressure (MSLP) have the strongest correlation with inter-annual variations. The north and west of the UK are dominated by MSLP in the mid-North Atlantic and the south and east are dominated by local SST. All regions now have a higher likelihood of autumnal extreme daily precipitation than earlier in the twentieth century. This equates to extreme daily precipitation occurring earlier in the autumn in the north and west, and later in the autumn in the south and east. The change in timing is accompanied by increases in the probability of extreme daily precipitation occurrences during the autumn, and in the number of days with a very high probability of an extreme event. These results indicate a higher probability of several extreme occurrences in succession and a potential increase in flooding.

Evaluation of NASA’s MERRA Precipitation Product in Reproducing the Observed Trend and Distribution of Extreme Precipitation Events in the United States

Abstract This study evaluates the performance of NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979–2010. The Climate Prediction Center (CPC) U.S. Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scale patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRA tends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1) MERRA shows a spurious negative trend in Nebraska and Kansas, which is most likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over the Gulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. In addition, the increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.

Discussing the role of tropical and subtropical moisture sources in cold season extreme precipitation events in the Mediterranean region from a climate change perspective

Abstract. This paper presents a review of a large number of research studies performed during the last few decades that focused on the investigation of cold season extreme precipitation events (EPEs) in the Mediterranean region (MR). The publications demonstrate the important role of anomalously intense transports of moist air from the tropical and subtropical Atlantic in the occurrence of EPEs in the MR. EPEs in the MR are directly or indirectly connected to narrow bands with a high concentration of moisture in the lower troposphere, i.e., atmospheric rivers, along which a large amount of moisture is transported from the tropics to midlatitudes. Whereas in a significant fraction of the EPEs in the western MR moisture is transported to the MR from the tropical Atlantic, EPEs in the central, and especially the eastern, MR are more often associated with intense tropical moisture transports over North Africa and the Red Sea. The moist air for the EPEs in the latter part of the MR also mainly originates from the tropical Atlantic and Indian oceans, and in many cases it serves as a temporary moisture reservoir for future development. The paper is supplemented by the results of a test for a possible connection between declining Arctic sea ice and the climatology of intense precipitation in the eastern MR. Based on the results of the evaluation supporting those from the earlier climate change analyses and modeling studies, it is concluded that a further anthropogenic global warming may lead a greater risk of higher rainfall totals and therefore larger winter floods in western and central parts of the MR as a consequence of stronger and more numerous Atlantic atmospheric rivers, possibly accompanied by a decline in the number of EPEs in the eastern part of the MR.

Analysis of Capabilities of Bias-corrected Precipitation Simulation from Ensemble of Downscaled GCMs in Reconstruction of Historical Wet and Dry Spell Characteristics

Precipitation outputs from downscaled GCMs are often used as input data for hydrological models to study the impact of climate change on hydrological cycles and water resources. However, precipitation outputs from downscaled GCMs may bear systematic errors, such as incorrect estimates of seasonal cycles and precipitation extremes and hence cannot be directly used as input to hydrological models. In this context, bias correction methods are often applied to post-process precipitation outputs from downscaled GCMs to adjust the statistics or distributions of the model output to those of historical observations. Though bias corrected precipitation outputs from downscaled GCMs show great improvements over the raw precipitation outputs in terms of reconstruction of seasonal cycles, extreme precipitation, etc., they might misrepresent the wet and dry spell characteristics of precipitation, which play an important role in climate impact studies on surface water quality, agriculture, domestic water use, etc. Therefore, this study presents a detailed analysis of the wet and dry spell characteristics of bias corrected precipitation outputs in Singapore region from a set of dynamically downscaled GCMs, and compare them with those of the historical observations during the baseline period between 1980 and 2009. The cumulative distribution functions of wet and dry spell characteristics (duration and magnitude), and the contributions of wet or dry spells of certain durations or magnitudes to total duration or total accumulated depth for bias corrected downscaled GCM precipitation simulation and historical observations are analysed and compared. The results show that the bias corrected precipitation simulations from the downscaled GCMs tend to overestimate the duration of wet and dry spells, as well as the magnitude of wet spells, in the upper tail of the distributions. Besides, frequencies and contributions of extreme wet and dry spells are also overestimated. The results have implications for evaluation of climate change impacts on water resources management.

Long series of Swiss seasonal precipitation: regionalization, trends and influence of large‐scale flow

Quantifying precipitation variability and trends is difficult and merits regular reassessment. In the present study, the seasonal homogenized precipitation series in Switzerland is investigated for the period 1901–2013 in terms of trends, inter-annual variability and the influence of large-scale flow. An objective clustering is applied, resulting in 32 distinct precipitation regions. Trends are analysed for all 32 regions with moving trend windows, and statistical significance (p < 0.05) is assessed with Theil–Sen trend estimates and nonparametric Mann–Kendall trend tests. Inter-annual precipitation varies considerably regionally and seasonally. Of 2720 analysed trend windows of 33–113 years in length, 194 (7.1%) show a significantly positive trend and 10 (0.4%) a significantly negative trend. Most of the significantly positive trends are found for 50+ year series for winter, autumn and the year. 81% of the annual and 72% of the winter series show positive trends (0–3% per decade) for the 1901–2013 period. The trends are significant for 34% (22%) of the annual (winter) series. Long-term trends are generally in line with earlier estimates in literature considering somewhat shorter time periods. Significantly negative trends are only found for winter in the most recent decades. No significant trends are found for inter-annual variability and changes in the 10th and 90th percentile seasonal extreme precipitation thresholds. The influence of large-scale flow on precipitation variability is strongest in winter. The leading pattern for northern Switzerland (nS) is the Euro-Atlantic blocking pattern. For southern Switzerland (sS), the Eastern Atlantic (Scandinavian) pattern is dominant in winter (autumn). In nS, wet (dry) seasons are linked to south-westerly (north-easterly) flow. In sS, wet (dry) seasons are linked to southerly (northerly) flow. Strong evidence for imprints of atmospheric blocking on seasonal precipitation variability is found in winter and autumn. In spring, a high pressure anomaly stretching from the mid-Atlantic to central Europe is indicative of dryness in nS.

Changing properties of precipitation extremes in the urban areas, Yangtze River Delta, China, during 1957–2013

The Yangtze River Delta (YRD) is one of largest river deltas and metropolitan areas in the world with strong human interference, so it is vulnerable to extreme weather events. Based on daily precipitation dataset of 16 rain gauges in Yangtze River Delta and Mann–Kendall trend detection techniques, the trend in annual and seasonal precipitation extremes has been investigated in the period 1957–2013. Possible links between changes in extreme precipitation and monsoon indices have also been explored. The results show that: (1) the increasing trends of consecutive wet days, maximum daily precipitation, maximum 5-day precipitation and maximum precipitation amount in the past 57 years in YRD can be detected. Much attention should be paid to higher risk of flash flood in these areas, especially in big cities of Shanghai, Nanjing, Hangzhou and Ningbo. (2) Both precipitation days and amount of heavy events (defined as over 90th, 95th and 99th) exhibit overwhelming upward tendency in summer and winter throughout YRD. The summer is to meet with heavier precipitation events as result of larger increasing magnitude in heavy rain days and amounts in the past 57 years. So, high importance should be placed on the relief for flood in summer in the large cites. (3) There is an abrupt change point for extreme precipitation events, and increased annual total precipitation has impact on the upward tendency of heavy rainfall events in YRD on great scale. In addition, the significant correlations between indices (P90, P95, R90 and R95) and monsoon indices (East Asian Summer Monsoon Index and South Asia Summer Monsoon Index) indicate that extreme precipitation events are related to the EASMI and SASMI. Therefore, these properties of precipitation extremes are of great significance to the control of natural hazards in YRD with high degree of human activities and understanding the impact of climate change on hydrologic processes.

Spatial variability of seasonal extreme precipitation in the western United States

AbstractWe examine the characteristics of 3 day total extreme precipitation in the western United States. Coherent seasonal spatial patterns of timing and magnitude are evident in the data, motivating a seasonally based analysis. Using a clustering method that is consistent with extreme value theory, we identify coherent regions for extremes that vary seasonally. Based on storm back trajectory analysis, we demonstrate unique moisture sources and dominant moisture pathways for each spatial region. In the winter the Pacific Ocean is the dominant moisture source across the west, but in other seasons the Gulf of Mexico, the Gulf of California, and the land surface over the midwestern U.S. play an important role. We find the El Niño–Southern Oscillation (ENSO) to not have a strong impact on dominant moisture delivery pathways or moisture sources. The frequency of extremes under ENSO is spatially coherent and seasonally dependent with certain regions tending to have more (less) frequent extreme events in El Niño (La Niña) conditions.