Number Of Extreme Precipitation Events Research Articles

Spatiotemporal Variability of Extreme Precipitation Events and Associated Atmospheric Processes Over Dronning Maud Land, East Antarctica

AbstractWe investigate the spatial and temporal variability of extreme precipitation events (EPEs) in the Dronning Maud Land (DML) sector of Antarctica using high‐resolution ECMWF ERA5 reanalysis data. This study examines the spatial occurrence of EPEs across DML, focusing particularly on six locations spanning the coastal and interior parts of the area. The largest snowfall amounts are usually found on eastward‐facing slopes in the coastal zone. EPEs occur predominantly in north‐easterly to easterly flows, leading to enhanced precipitation on the windward side of the orographic features with a steep gradient. Wind during EPEs was found to be more directionally consistent in the coastal area than in the interior. An east‐west couplet of a mid‐tropospheric ridge and low‐pressure center is essential for steering warm moist maritime airmasses into the DML region before EPEs. Approximately 40% of EPEs result from atmospheric rivers (ARs), narrow bands of moist air originating at subtropical latitudes, which provide the greatest daily precipitation amounts. From 1979 to 2018, much of the DML experienced a statistically significant (p < 0.05) increase in the number of EPEs per year, along with increased precipitation from the EPEs. These trends were associated with significant changes in moisture availability and poleward meridional winds in the Atlantic sector of the Southern Ocean. The inter‐annual variability in the number of EPEs is primarily dictated by regional atmospheric variability, while the influence of the Southern Oscillation Index and Southern Annular Mode is limited.

Spatiotemporal analysis of extreme precipitation events in the United States at mesoscale: Complex network theory

Analyzing the complex behavior of extreme precipitation events (EPEs) is essential to better understand the effect of climate change on surface and subsurface water resources and forecast extreme hydrologic events. In this study, we applied complex network theory to analyze precipitation data in the contiguous United States (CONUS) and investigate synchronization patterns of EPEs across the nation. We constructed the complex network of EPEs using the CPC database, including the precipitation time series available at 3,276 grid points all over the CONUS. To compute the level of similarity between any two grid points, we analyzed their EPE series using two methods: (i) event synchronization (ES) and (ii) time warp edit distance (TWED). The constructed precipitation networks (PNs) for the summer and winter seasons were analyzed, and network measures i.e., degree centrality (DC), partial degree (PD), and mean geographic distance (MGD) were determined. By analyzing the precipitation data from 1979 to 2021, we found that the number of EPEs in the CONUS has been increasing over the past four decades with similar slopes in the summer and winter seasons. We also observed both local and regional connections as well as teleconnections demonstrating EPE synchronizations across scales. Results of the network measures revealed important geographic locations in terms of their connection patterns to other locations for both seasons. Using the Louvain method, we detected seven communities in the network for the summer season and five for the winter season by means of the ES. Similar results were obtained using the TWED.

Spatial and Temporal Variability of Extreme Precipitation Events in the Southeastern United States

Much of the Southeastern United States (SeUS) has experienced an increasing number of extreme precipitation events in recent decades. Characterizing these extreme precipitation events is critical for assessing risk from future hydroclimatic extremes and potential flash flooding. A threshold of one inch per hour (1IPH) was used to indicate an extreme precipitation event. Non-parametric tests were run to identify trends in 1IPH event frequency and locate time series change points. In the last 20 years, 1IPH events increased by 53 percent in the SeUS, and 21/61 stations recorded significant increasing trends. A change point is identified in 15/61 stations. June, July, and August are generally the peak time for 1IPH events, but Florida, Louisiana, and Mississippi recorded longer peak seasons. For the time between events, 17/61 stations recorded significant decreasing trends, implying that 1IPH events are increasing in frequency. Four teleconnection indices were positively correlated with 1IPH events. The SeUS experiences considerable tropical cyclone-induced extreme precipitation, yet only seven percent of 1IPH events overlapped with tropical cyclones. Therefore, the increasing frequency of 1IPH events is likely the result of a combination of baroclinic frontal zones or regional and mesoscale convective features. Causes for the increasing frequency of 1IPH events require further research.

The Influence of Weather Patterns and the Madden‐Julian Oscillation on Extreme Precipitation Over Sri Lanka

AbstractSri Lanka is affected by extreme precipitation events every year, which cause floods, landslides and tremendous economic losses. We use the ERA5 reanalysis data set to understand the association of extreme precipitation events with 30 weather patterns, which were originally derived to represent the variability of the Indian climate during January–December 1979–2016. We find that weather patterns that are most common during the northeast monsoon (December–February) and second intermonsoon (October–November) seasons produce the highest number of extreme precipitation events. Furthermore, extreme precipitation events occurring during these two seasons are more persistent than those during the southwest monsoon (May–September) and first intermonsoon (March–April) seasons. We analyze the modulation of extreme precipitation events by the Madden‐Julian Oscillation, and find that their frequency is enhanced (suppressed) in phases 1–4 (5–8) for most weather patterns.

ConvMOS: climate model output statistics with deep learning

Climate models are the tool of choice for scientists researching climate change. Like all models they suffer from errors, particularly systematic and location-specific representation errors. One way to reduce these errors is model output statistics (MOS) where the model output is fitted to observational data with machine learning. In this work, we assess the use of convolutional Deep Learning climate MOS approaches and present the ConvMOS architecture which is specifically designed based on the observation that there are systematic and location-specific errors in the precipitation estimates of climate models. We apply ConvMOS models to the simulated precipitation of the regional climate model REMO, showing that a combination of per-location model parameters for reducing location-specific errors and global model parameters for reducing systematic errors is indeed beneficial for MOS performance. We find that ConvMOS models can reduce errors considerably and perform significantly better than three commonly used MOS approaches and plain ResNet and U-Net models in most cases. Our results show that non-linear MOS models underestimate the number of extreme precipitation events, which we alleviate by training models specialized towards extreme precipitation events with the imbalanced regression method DenseLoss. While we consider climate MOS, we argue that aspects of ConvMOS may also be beneficial in other domains with geospatial data, such as air pollution modeling or weather forecasts.

Water vapor isotopes indicating rapid shift among multiple moisture sources for the 2018–2019 winter extreme precipitation events in southeastern China

Abstract. In the East Asian monsoon region, winter extreme precipitation events occasionally occur and bring great social and economic losses. From December 2018 to February 2019, southeastern China experienced a record-breaking number of extreme precipitation events. In this study, we analyzed the variation in water vapor isotopes and their controlling factors during the extreme precipitation events in Nanjing, southeastern China. The results show that the variations in water vapor isotopes are closely linked to the change in moisture sources. Using a water vapor d-excess-weighted trajectory model, we identified the following five most important moisture source regions: South China, the East China Sea, the South China Sea, the Bay of Bengal, and continental regions (northwestern China and Mongolia). Moreover, the variations in water vapor d excess during a precipitation event reflect rapid shifts in the moisture source regions. These results indicate that rapid shifts among multiple moisture sources are important conditions for sustaining wintertime extreme precipitation events over extended periods.

Influence of Climate Change on the Flood Disasters in Bursa, Turkey

The recent increase in the frequency and intensity of the floods resulted from huge precipitation events in Bursa Province, Turkey, is the main motivation of this study. For this purpose, the daily precipitation values from the historical data recorded between 1971 and 2000 together with the projected data of the NorESM1-M general circulation model under RCP4.5 and RCP8.5 scenarios between 2031 and 2100 were used to calculate eight extreme precipitation events. The Spearman's rho and the Mann-Kendall trend tests were used to detect the trend in the indices. The results of the trend tests showed that any change is not expected in the total amount of the yearly precipitation amount, whereas the occurrence of the intense and short duration precipitation events is expected to be more probable by the end of the current century, compared to the last 30 years of the previous century. The positive significant trends were detected in some indices. However, the magnitude of the change in the climatic parameters and the increase in the number of extreme precipitation events cannot solely explain the increase in the number of destroying flood events in the province. Other parameters such as the dramatic increase in urbanization as a result of rapid population growth during the past years (since 1960) may have a more prominent effect on the increase of the flood risk in the province which is in need of comprehensive modeling and investigation.

The CORDEX Flagship Pilot Study in southeastern South America: a comparative study of statistical and dynamical downscaling models in simulating daily extreme precipitation events

The aim of this work is to present preliminary results of the statistical and dynamical simulations carried out within the framework of the Flagship Pilot Study in southeastern South America (FPS-SESA) endorsed by the Coordinated Regional Climate Downscaling Experiments (CORDEX) program. The FPS-SESA initiative seeks to promote inter-institutional collaboration and further networking with focus on extreme rainfall events. The main scientific aim is to study multi-scale processes and interactions most conducive to extreme precipitation events through both statistical and dynamical downscaling techniques, including convection-permitting simulations. To this end, a targeted experiment was designed considering the season October 2009 to March 2010, a period with a record number of extreme precipitation events within SESA. Also, three individual extreme events within that season were chosen as case studies for analyzing specific regional processes and sensitivity to resolutions. Four dynamical and four statistical downscaling models (RCM and ESD respectively) from different institutions contributed to the experiment. In this work, an analysis of the capability of the set of the FPS-SESA downscaling methods in simulating daily precipitation during the selected warm season is presented together with an integrated assessment of multiple sources of observations and available CORDEX Regional Climate Model simulations. Comparisons among all simulations reveal that there is no single model that performs best in all aspects evaluated. The ability in reproducing the different features of daily precipitation depends on the model. However, the evaluation of the sequence of precipitation events, their intensity and timing suggests that FPS-SESA simulations based on both RCM and ESD yield promising results. Most models capture the extreme events selected, although with a considerable spread in accumulated values and the location of heavy precipitation.

Nature‐based solutions for urban pluvial flood risk management

AbstractUrban pluvial flooding now occurs more frequently than it has in past decades, mainly due to an increasing number of extreme precipitation events occurring in the context of a changing climate. To limit the evolving risks of urban pluvial flooding in a more environmentally friendly manner, the research community has recently paid increasing attention to Nature‐Based Solutions (NBS), which are based on new green technologies. To meet the urgent demand for a comprehensive review of the most recent literature, this review conducts a systematic survey of the literature to characterize various NBS adopted in different regions of the world and to elaborate on the benefits and limitations of such NBS. The review highlights the role of NBS in urban flood risk management under ongoing climate change and rapid urbanization. It shows that NBS could effectively mitigate urban flooding caused by high‐frequency precipitation events, with additional economic, ecological, and social benefits. However, NBS are less effective at helping cope with pluvial flooding caused by extreme precipitation events over a short period of time, while gray infrastructures also have limitations as a mitigation measure against extreme pluvial flooding. We thus recommend identifying flood risk management strategies by evaluating the performance of alternative combinations of NBS with gray infrastructures in preventing pluvial flooding in the cities. Finally, recent advances made in the applications of NBS are presented with suggestions (e.g., long‐term monitoring) to improve urban flood adaptive management.This article is categorized under: Engineering Water > Planning Water Engineering Water > Sustainable Engineering of Water Science of Water > Water Extremes

Synoptic and Mesoscale Forcing of Southern California Extreme Precipitation

AbstractSouthern California water resources are heavily dependent on a small number of extreme precipitation events each winter season, which dictate the region's highly variable interannual accumulations. In the Santa Ana River Watershed, on average, three extreme events per year contribute half of annual precipitation, yet there are relatively few studies of the synoptic to mesoscale processes that drive precipitation during these events. This study uses an ingredient‐based approach in identifying the contributions of orographic forcing, dynamical forcing, and convective instability to extreme precipitation in the watershed in 107 storms that produced roughly 50% of all precipitation from 1981 to 2017. The influence of dynamical forcing and convective instability on event precipitation distributions is investigated relative to the dominant influence of orographic forcing that is typically found in landfalling atmospheric rivers. Case studies of two high‐impact events from the 2017 winter season demonstrate differences in the roles of synoptic ascent and mesoscale convective features in modifying precipitation location, rate, and accumulation over the watershed. The 17 and 18 February 2017 case study included a narrow cold‐frontal rainband that produced high‐intensity short‐duration precipitation over low elevations of the watershed. In the 107 extreme event records, similar modification of the precipitation distribution toward non‐orographic rainfall was related to significant changes in the synoptic‐scale circulation that favored enhanced dynamics and upstream ascent associated with frontogenesis. Variability in precipitation mechanisms is of primary interest to weather forecasters and water managers as it modifies event impacts and predictability.

Features of Extreme Precipitation at Progress Station, Antarctica

AbstractObserved daily precipitation data were used to investigate the characteristics of precipitation at Antarctic Progress Station and synoptic patterns associated with extreme precipitation events during the period 2003–16. The annual precipitation, annual number of extreme precipitation events, and amount of precipitation during the extreme events have positive trends. The distribution of precipitation at Progress Station is heavily skewed with a long tail of extreme dry days and a high peak of extreme wet days. The synoptic pattern associated with extreme precipitation events is a dipole structure of negative and positive height anomalies to the west and east of Progress Station, respectively, resulting in water vapor advection to the station. For the first time, we apply self-organizing maps (SOMs) to examine thermodynamic and dynamic perspectives of trends in the frequency of occurrence of Antarctic extreme precipitation events. The changes in thermodynamic (noncirculation) processes explain 80% of the trend, followed by the changes in the interaction between thermodynamic and dynamic processes, which account for nearly 25% of the trend. The changes in dynamic processes make a negative (less than 5%) contribution to the trend. The positive trend in total column water vapor over the Southern Ocean explains the change of thermodynamic term.

VERSATILE MOBILE AND STATIONARY LOW-COST APPROACHES FOR HYDROLOGICAL MEASUREMENTS

Abstract. In the last decades, an increase in the number of extreme precipitation events has been observed, which leads to increasing risks for flash floods and landslides. Thereby, conventional gauging stations are indispensable for monitoring and prediction. However, they are expensive in construction, management, and maintenance. Thus, density of observation networks is rather low, leading to insufficient spatio-temporal resolution to capture hydrological extreme events that occur with short response times especially in small-scale catchments. Smaller creeks and rivers require permanent observation, as well, to allow for a better understanding of the underlying processes and to enhance forecasting reliability. Today’s smartphones with inbuilt cameras, positioning sensors and powerful processing units may serve as wide-spread measurement devices for event-based water gauging during floods. With the aid of volunteered geographic information (VGI), the hydrological network of water gauges can be highly densified in its spatial and temporal domain even for currently unobserved catchments. Furthermore, stationary low-cost solutions based on Raspberry Pi imaging systems are versatile for permanent monitoring of hydrological parameters. Both complementary systems, i.e. smartphone and Raspberry Pi camera, share the same methodology to extract water levels automatically, which is explained in the paper in detail. The annotation of 3D reference data by 2D image measurements is addressed depending on camera setup and river section to be monitored. Accuracies for water stage measurements are in range of several millimetres up to few centimetres.

Extreme precipitation and phosphorus loads from two agricultural watersheds

AbstractPhosphorus runoff from agricultural land is a major cause of eutrophication in lakes and reservoirs. Frequency and intensity of extreme precipitation events are increasing in agricultural regions of the Upper Midwestern U.S., and these increases are projected to continue as climate warms. We quantified the linkage between extreme daily precipitation and extreme daily discharge, phosphorus (P) load, and P concentration for Pheasant Branch and the Yahara River, two tributaries of Lake Mendota, Wisconsin, U.S.A. using the generalized Pareto distribution. Although precipitation extremes have increased since 1940, over the shorter period of stream monitoring (1994–2015 for Pheasant Branch and 1991–2015 for Yahara) there is no significant trend in extreme precipitation. Nonetheless a disproportionate number of extreme precipitation events (for example seven of the 11 largest 24‐h events since 1901) occurred during the period of stream monitoring. Daily precipitation extremes were associated with extremes in daily discharge and P load. P load return levels increased steeply and almost linearly with precipitation on log‐log axes. The trend toward more frequent and intense precipitation extremes will increase P loading and intensify the eutrophication of the lake, unless the excessive P enrichment of the watershed is reversed.

An Independent Assessment of Anthropogenic Attribution Statements for Recent Extreme Temperature and Rainfall Events

The annual “State of the Climate” report, published in the Bulletin of the American Meteorological Society (BAMS), has included a supplement since 2011 composed of brief analyses of the human influence on recent major extreme weather events. There are now several dozen extreme weather events examined in these supplements, but these studies have all differed in their data sources as well as their approaches to defining the events, analyzing the events, and the consideration of the role of anthropogenic emissions. This study reexamines most of these events using a single analytical approach and a single set of climate model and observational data sources. In response to recent studies recommending the importance of using multiple methods for extreme weather event attribution, results are compared from these analyses to those reported in the BAMS supplements collectively, with the aim of characterizing the degree to which the lack of a common methodological framework may or may not influence overall conclusions. Results are broadly similar to those reported earlier for extreme temperature events but disagree for a number of extreme precipitation events. Based on this, it is advised that the lack of comprehensive uncertainty analysis in recent extreme weather attribution studies is important and should be considered when interpreting results, but as yet it has not introduced a systematic bias across these studies.

Contribution of large-scale circulation anomalies to changes in extreme precipitation frequency in the United States

The mean global climate has warmed as a result of the increasing emission of greenhouse gases induced by human activities. This warming is considered the main reason for the increasing number of extreme precipitation events in the US. While much attention has been given to extreme precipitation events occurring over several days, which are usually responsible for severe flooding over a large region, little is known about how extreme precipitation events that cause flash flooding and occur at sub-daily time scales have changed over time. Here we use the observed hourly precipitation from the North American Land Data Assimilation System Phase 2 forcing datasets to determine trends in the frequency of extreme precipitation events of short (1 h, 3 h, 6 h, 12 h and 24 h) duration for the period 1979–2013. The results indicate an increasing trend in the central and eastern US. Over most of the western US, especially the Southwest and the Intermountain West, the trends are generally negative. These trends can be largely explained by the interdecadal variability of the Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation (AMO), with the AMO making a greater contribution to the trends in both warm and cold seasons.

Examining moisture pathways and extreme precipitation in the U.S. Intermountain West using self‐organizing maps

AbstractSelf‐organizing maps (SOMs) were used to explore relationships between large‐scale synoptic conditions, especially vertically integrated water vapor transport (IVT), and extreme precipitation events in the U.S. Intermountain West (IMW). By examining spatial patterns in the IVT, pathways are identified where moisture can penetrate into the IMW. A substantial number of extreme precipitation events in the IMW are associated with infrequently occurring synoptic patterns. The transition frequency between each of the SOM nodes, which indicate temporal relationships between the patterns, identified two synoptic settings associated with extreme precipitation in the IMW: (1) a landfalling, zonally propagating trough that results in a concentrated IVT band that moves southward as the system moves inland and (2) a southwesterly storm track associated with strong ridging over the coast that results in persistent IVT transport into the Pacific Northwest that can last for several days.

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.

Serial Analysis of Ten Precipitation-Based Indices by Land Use in Semiarid Regions

Open ecosystems in Mexico are under increasing pressure, due particularly to the expansion of cities and agricultural activities. These developments occur without integrating biodiversity concerns in land use planning and result in extensive fragmentation and transformation of the landscapes. The semiarid region of Mesa Central was characterized using ten precipitation-based indices. Using multivariate statistical and geostatistical spatial analysis techniques, the influence of those indices on five land use strata was explored. Land use analysis indicated that the maximum values of the five significant precipitation-based indices were found in Grasslands, Agricultural Use, and Shrubs; minimum values were characteristic of substrates Secondary Desert Vegetation and Other Use. Our results suggest that the greatest number of extreme precipitation events is likely to occur in open ecosystems and consequently will have a strong influence on landscaping and land use. The semivariogram analysis and geostatistical layers demand attention from research institutions, policy makers, researchers, and food producers to take the appropriate and coordinated actions to propose scenarios to deal with climate change. Perhaps this study can stimulate thought concerning research endeavours aimed at promoting initiatives for biodiversity conservation and planning programs for climate change mitigation.

Changes of precipitation intensity spectra in different regions of mainland China during 1961–2006

The spectral characteristics of precipitation intensity during warm and cold years are compared in six regions of China based on precipitation data at 404 meteorological stations during 1961–2006. In all of the studied regions except North China, with the increasing temperature, a decreasing trend is observed in light precipitation and the number of light precipitation days, while an increasing trend appears in heavy precipitation and the heavy precipitation days. Although changes in precipitation days in North China are similar to the changes in the other five regions, heavy precipitation decreases with the increasing temperature in this region. These results indicate that in most parts of China, the amount of precipitation and number of precipitation days have shifted towards heavy precipitation under the background of a warming climate; however, the responses of precipitation distributions to global warming differ from place to place. The number of light precipitation days decreases in the warm and humid regions of China (Jianghuai region, South China, and Southwest China), while the increasing amplitude of heavy precipitation and the number of heavy precipitation days are greater in the warm and humid regions of China than that in the northern regions (North China, Northwest China, and Northeast China). In addition, changes are much more obvious in winter than in summer, indicating that the changes in the precipitation frequency are more affected by the increasing temperature during winter than summer. The shape and scale parameters of the Γ distribution of daily precipitation at most stations of China have increased under the background of global warming. The scale parameter changes are smaller than the shape parameter changes in all regions except Northwest China. This suggests that daily precipitation shifts toward heavy precipitation in China under the warming climate. The number of extreme precipitation events increases slightly, indicating that changes in the Γ distribution fitting parameters reflect changes in the regional precipitation distribution structure.

Evaluating a mesoscale atmosphere model and a satellite-based algorithm in estimating extreme rainfall events in northwestern Turkey

Abstract. Quantitative precipitation estimates are obtained with more uncertainty under the influence of changing climate variability and complex topography from numerical weather prediction (NWP) models. On the other hand, hydrologic model simulations depend heavily on the availability of reliable precipitation estimates. Difficulties in estimating precipitation impose an important limitation on the possibility and reliability of hydrologic forecasting and early warning systems. This study examines the performance of the Weather Research and Forecasting (WRF) model and the Multi Precipitation Estimates (MPE) algorithm in producing the temporal and spatial characteristics of the number of extreme precipitation events observed in the western Black Sea region of Turkey. Precipitation derived from WRF model with and without the three-dimensional variational (3DVAR) data assimilation scheme and MPE algorithm at high spatial resolution (5 km) are compared with gauge precipitation. WRF-derived precipitation showed capabilities in capturing the timing of precipitation extremes and to some extent the spatial distribution and magnitude of the heavy rainfall events, whereas MPE showed relatively weak skills in these aspects. WRF skills in estimating such precipitation characteristics are enhanced with the application of the 3DVAR scheme. Direct impact of data assimilation on WRF precipitation reached up to 12% and at some points there is a quantitative match for heavy rainfall events, which are critical for hydrological forecasts.