Extreme Precipitation Processes Research Articles

Meteorological, impact and climate perspectives of the 29 June 2017 heavy precipitation event in the Berlin metropolitan area

Abstract. Extreme precipitation is a weather phenomenon with tremendous damaging potential for property and human life. As the intensity and frequency of such events is projected to increase in a warming climate, there is an urgent need to advance the existing knowledge on extreme precipitation processes, statistics and impacts across scales. To this end, a working group within the Germany-based project, ClimXtreme, has been established to carry out multidisciplinary analyses of high-impact events. In this work, we provide a comprehensive assessment of the 29 June 2017 heavy precipitation event (HPE) affecting the Berlin metropolitan region (Germany), from the meteorological, impacts and climate perspectives, including climate change attribution. Our analysis showed that this event occurred under the influence of a mid-tropospheric trough over western Europe and two shortwave surface lows over Britain and Poland (Rasmund and Rasmund II), inducing relevant low-level wind convergence along the German–Polish border. Over 11 000 convective cells were triggered, starting early morning 29 June, displacing northwards slowly under the influence of a weak tropospheric flow (10 m s−1 at 500 hPa). The quasi-stationary situation led to totals up to 196 mm d−1, making this event the 29 June most severe in the 1951–2021 climatology, ranked by means of a precipitation-based index. Regarding impacts, it incurred the largest insured losses in the period 2002 to 2017 (EUR 60 million) in the greater Berlin area. We provide further insights on flood attributes (inundation, depth, duration) based on a unique household-level survey data set. The major moisture source for this event was the Alpine–Slovenian region (63 % of identified sources) due to recycling of precipitation falling over that region 1 d earlier. Implementing three different generalised extreme value (GEV) models, we quantified the return periods for this case to be above 100 years for daily aggregated precipitation, and up to 100 and 10 years for 8 and 1 h aggregations, respectively. The conditional attribution demonstrated that warming since the pre-industrial era caused a small but significant increase of 4 % in total precipitation and 10 % for extreme intensities. The possibility that not just greenhouse-gas-induced warming, but also anthropogenic aerosols affected the intensity of precipitation is investigated through aerosol sensitivity experiments. Our multi-disciplinary approach allowed us to relate interconnected aspects of extreme precipitation. For instance, the link between the unique meteorological conditions of this case and its very large return periods, or the extent to which it is attributable to already-observed anthropogenic climate change.

Analysis of Extreme Rain and Snow Weather Dynamic and Water Vapor Conditions in Northeast China from 17 to 19 November 2020

Based on hourly precipitation data from 2413 national ground observation stations in China and ERA5 (0.25° × 0.25°), this study analyzes the characteristics and causes of extreme rainfall and snow in northeast China from 17–19 November 2020. The results show that extreme precipitation is mainly attributed to the abnormally strong large-scale low vortex and ground cyclone. The significant high-level and low-level coupling in areas with strong rain and snow is conducive to the continuous upward motion, which provides favorable dynamic conditions for the generation and development of extreme precipitation. The frontogenesis effect below the 850 hPa level is obvious, and the extreme precipitation period corresponds to the meeting of the north and south front areas. The symmetrical unstable atmosphere of 925 hPa~700 hPa is forced by the frontogenesis, which strengthens the oblique rising of the low layer and increases the instability, leading to the strengthened development of precipitation. For heavy rainfall and snow in early winter in China, water vapor transport is crucial. The extremely strong low-level jet also provides extremely strong water vapor conditions for the occurrence of heavy rain and snow. The analysis of the extreme rain and snow characteristics and formation mechanism of this weather process can deepen the understanding of extreme weather processes, and provide a useful reference for the research and prediction of extreme precipitation processes.

Amplifying Flood Risk Across the Lower Yellow River Basin, China, Under Shared Socioeconomic Pathways

The ecological conservation and high-quality development of the Yellow River basin (YRB) has been adopted as a major national strategy of China. However, the YRB is still afflicted by floods. Here, we proposed a flood risk indicator using direct economic loss degree and improved the SNRD (station-based nonlinear regression downscaling model) and simulated extreme precipitation processes. The correlation coefficient of downscaled average extreme precipitation of CMORPH and CMIP6 data reached 0.817. Moreover, we evaluated flood risk and flood hazard across the YRB based on the sixth phase Coupled Model Intercomparison Project (CMIP6) data under different SSPs. Under SSP126, SSP245, and SSP585 scenarios, the areas with increasing flood hazards during 2015–2045 accounted for 65.2, 69.0, and 64.5% of the entire YRB. In the spatial pattern, flood hazards decreased from southeastern to northwestern parts of the YRB. When compared with the spatial pattern of flood risks in 2015, regions with high flood risks expanded slightly and regions with low flood risks shrunk slightly. Higher flood risks can be observed in the middle and lower YRB and particularly in the lower YRB. These findings are critical for the mitigation of flood risk across the YRB under warming climate.

Improvement of an Extreme Heavy Rainfall Simulation Using Nudging Assimilation

From 21 to 22 July 2012, Beijing and its surrounding areas suffered from an extreme precipitation event that was unprecedented relative to the past 61 years, and the event caused 79 deaths and reported direct economic losses of 11.64 billion Yuan. However, current models have difficulty to simulate the spatial and temporal distribution characteristics of such events. Therefore, improved simulations of these extreme precipitation processes are needed. In this study, nudging methods, including grid nudging (GN) and spectral nudging (SN), and more accurate surface type data retrieved from remote sensing were used in the Weather Research and Forecasting (WRF) model to simulate this extreme precipitation case. When the default city underlay surface of the WRF model was replaced by a more accurate urban surface (NU), the precipitation intensity could be better simulated, but the peak moment of precipitation seriously lagged. Although the peak precipitation intensity simulated by the GN experiment was weak, the simulated precipitation time was basically consistent with the observations. Using GN in only the outside domain could better simulate precipitation peaks, while using GN in both the inside and outside domains could better simulate the spatial distribution characteristics of precipitation. Additionally, the precipitation from GN could be better simulated than that from SN. Overall, the two nudging methods could contribute to better simulations of this case because the nudging methods could improve the simulations of 500-hPa geopotential height, 850-hPa water vapor transport, and low-level weather systems, which are the key factors in adjusting the spatial and temporal distributions of precipitation. This study is the basis for the investigation of the mechanism and attribution of extreme precipitation processes, and the results are of great significance for promoting understanding of and mitigating disasters caused by extreme precipitation.

Multivariate properties of extreme precipitation events in the Pearl River basin, China: Magnitude, frequency, timing, and related causes

AbstractDaily precipitation/temperature data collected at 74 weather stations across the Pearl River basin of China (PRBC), for the years 1952–2013, were used to analyse extreme precipitation (EP) processes at annual and seasonal scales in terms of precipitation magnitude, occurrence rates, and timing. Peak‐over‐threshold sampling, modified Mann‐Kendall trend tests, and Poisson regression model were utilized in this study. Causes driving the observed statistical behaviours of EP were investigated, focusing particularly on the impacts of temperature change and the El Niño–Southern Oscillation (ENSO). EP events, which occur mainly during April and September, are most frequent in June. At an annual scale, they are subject to relatively even interannual distributions during the wet season. Significant trends were observed in the magnitude, frequency, and timing of EP events during the dry seasons, although no such trends were seen during the wet seasons. Seasonal shifts in EP can easily trigger sudden flood or drought events and warming temperatures, and ENSO events also have significant impacts on EP processes across the PRBC, as reflected by their increased magnitude and frequency in the western PRBC and decreased precipitation magnitudes in the eastern PRBC during ENSO periods. These results provide important evidence of regional hydrological responses to global climate changes in terms of EP regimes in tropical and subtropical zones.

皖西大别山区暴雨洪涝致灾因素分析与措施建议

通过分析六安市近30年的历史气象资料和社会调查，结果表明：皖西大别山区的极端降水事件主要由梅雨型暴雨和台风型暴雨造成；暴雨洪涝的致灾因素可分为自然因素和社会因素两类，自然因素主要是极端降水过程和特殊地形的影响，社会成因主要包括承灾体脆弱、预警防御机制不健全和科普宣传不到位等，并针对不同的致灾因素提出相应的措施建议。 Based on the analysis of historical meteorological data and social survey in the last 30 years in Lu’an City, the results show that extreme precipitation events in Dabie Mountain area are mainly caused by Meiyu-type rainstorm and Typhoon-type rainstorm; the disaster-causing factors of rainstorm and flood can be divided into natural factors and social factors: the natural factors are mainly the impact of extreme precipitation processes and special topography; the social causes include the vulnerability of hazard-affected bodies, unsound early warning and defense mecha-nisms and the lack of dissemination for popular science knowledge and so on, and measures or suggestions are proposed for the different factors of the disaster.

Revisiting extreme storms of the past 100 years for future safety of large water management infrastructures

AbstractHistorical extreme storm events are widely used to make Probable Maximum Precipitation (PMP) estimates, which form the cornerstone of large water management infrastructure safety. Past studies suggest that extreme precipitation processes can be sensitive to land surface feedback and the planetary warming trend, which makes the future safety of large infrastructures questionable given the projected changes in land cover and temperature in the coming decades. In this study, a numerical modeling framework was employed to reconstruct 10 extreme storms over CONUS that occurred during the past 100 years, which are used by the engineering profession for PMP estimation for large infrastructures such as dams. Results show that the correlation in daily rainfall for such reconstruction can range between 0.4 and 0.7, while the correlation for maximum 3‐day accumulation (a standard period used in infrastructure design) is always above 0.5 for post‐1948 storms. This suggests that current numerical modeling and reanalysis data allow us to reconstruct big storms after 1948 with acceptable accuracy. For storms prior to 1948, however, reconstruction of storms shows inconsistency with observations. Our study indicates that numerical modeling and data may not have advanced to a sufficient level to understand how such old storms (pre‐1948) may behave in future warming and land cover conditions. However, the infrastructure community can certainly rely on the use of model reconstructed extreme storms of the 1948‐present period to reassess safety of our large water infrastructures under assumed changes in temperature and land cover.

Dominant Large-Scale Atmospheric Circulation Systems for the Extreme Precipitation over the Western Sichuan Basin in Summer 2013

The western Sichuan Basin (WSB) is a rainstorm center influenced by complicated factors such as topography and circulation. Based on multivariable empirical orthogonal function technique for extreme precipitation processes (EPP) in WSB in 2013, this study reveals the dominant circulation patterns. Results indicate that the leading modes are characterized by “Saddle” and “Sandwich” structures, respectively. In one mode, a TC from the South China Sea (SCS) converts into the inverted trough and steers warm moist airflow northward into the WSB. At the same time, WPSH extends westward over the Yangtze River and conveys a southeasterly warm humid flow. In the other case, WPSH is pushed westward by TC in the Western Pacific and then merges with an anomalous anticyclone over SCS. The anomalous anticyclone and WPSH form a conjunction belt and convey the warm moist southwesterly airflow to meet with the cold flow over the WSB. The configurations of WPSH and TC in the tropic and the blocking and trough in the midhigh latitudes play important roles during the EPPs over the WSB. The persistence of EPPs depends on the long-lived large-scale circulation configuration steady over the suitable positions.

Max-stable based evaluation of impacts of climate indices on extreme precipitation processes across the Poyang Lake basin, China

Monthly precipitation extremes defined by monthly maximum one-day precipitation amount (Rx1day) and maximum consecutive five-day precipitation amount (Rx5day) were analyzed based on daily precipitation data covering a period of 1957 to 2010 across the Poyang Lake basin, the largest freshwater lake basin in the lower Yangtze River basin, China. Based on the max-stable, impacts of El Niño–Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO) on the annual and seasonal Rx1day and Rx5day regimes in the Poyang Lake basin were evaluated. Results indicated that annual Rx1day and Rx5day were influenced mainly by the ENSO events a year earlier and the relations between annual Rx1day and Rx5day and ENSO were statistically positive. However, influences of climate indices on the seasonal Rx1day and Rx5day are complicated when compared with the influences on annual Rx1day and Rx5day regimes. ENSO and PDO can enhance the spring Rx1day regime of the subsequent year and the same year, respectively, but IOD weakens spring Rx1day in the same year. In summer, ENSO can enhance Rx1day of the subsequent year. However, Rx1day in summer had a decreasing tendency. IOD and NAO influenced the autumn Rx1day in another way, i.e., IOD decreases autumn Rx1day of the subsequent year; while NAO enhances autumn Rx1day of the same year. Meanwhile, ENSO can amplify the summer Rx1day in terms of variability, while IOD and NAO can, respectively, influence autumn and winter Rx1day in terms of mean. Influences of climate indices on annual and seasonal Rx5day are similar to those on Rx1day. Results of this study are of great theoretical as well as practical merit in terms of evaluation of droughts and floods under the influences of climate indices.

Topography-based spatial patterns of precipitation extremes in the Poyang Lake basin, China: Changing properties and causes

Summary The Poyang Lake is the largest freshwater lake in China. Monthly precipitation extremes defined by maximum one-day precipitation amount (Rx1day) and maximum consecutive five-day precipitation amount (Rx5day) regimes were analyzed for precipitation data covering a period of 1957–2010. How the spatial patterns of these precipitation extremes are impacted by topographic characteristics was investigated using the max-stable method. Results indicated that a better performance of model can be identified if topographical influences were considered, showing the critical role of topography in the spatial distribution of precipitation extremes. Seasonal shifts of extreme precipitation events can be identified within the Poyang Lake basin: the Rx1day generally increases from the west to the east parts during spring, from the south to the north parts during summer, from the east to the west parts during autumn and from the northwest to the southeast parts during winter. Besides, details and subtle traits of spatial patterns of precipitation extremes can be attained when altitude was taken into consideration. However, complex influences of topographical properties or the mountains on changes of Rx1day and Rx5day were also detected: higher altitude tends to increase the Rx1day in summer and autumn while decrease the Rx1day in winter and spring, which should be attributed to propagation direction of water vapor flux and also different relations between water vapor flux and extreme precipitation processes during different seasons. When compared to Rx1day, the seasonal Rx5day regimes shift along the east–west direction and which may be attributed to the different seasonal movements of precipitation center for Rx5day when compared to those of Rx1day. Results of this study may help to better understand the possible influence of topography on the spatial patterns of precipitation extremes.

Drought evolution characteristics and precipitation intensity changes during alternating dry–wet changes in the Huang–Huai–Hai River basin

Abstract. Abrupt drought–flood change events caused by atmospheric circulation anomalies have occurred frequently and widely in recent years, which has caused great losses and casualties in China. In this paper, we focus on investigating whether there will be a rainfall occurrence with higher intensity after a drought period in the Huang–Huai–Hai River basin. Combined with the Chinese climate divisions and the basin's DEM (digital elevation model), the basin is divided into seven sub-regions by means of cluster analysis of the basin meteorological stations using the self-organizing map (SOM) neural network method. Based on the daily precipitation data of 171 stations for the years 1961–2011, the changes of drought times with different magnitudes are analyzed, and the number of consecutive days without precipitation is used to identify the drought magnitudes. The first precipitation intensity after a drought period is analyzed with the Pearson-III frequency curve, then the relationship between rainfall intensity and different drought magnitudes is observed, as are the changes of drought times for different years. The results of the study indicated that the occurrence times of different drought levels show an overall increasing trend; there is no clear interdecadal change shown, but the spatial difference is significant. (2) As the drought level increases, the probability of extraordinary rainstorm becomes lower, and the frequency of occurrence of spatial changes in different precipitation intensities vary. In the areas I and II, as the drought level increases, the occurrence frequency of different precipitation intensities first shows a decreasing trend, which becomes an increasing trend when extraordinary drought occurs. In the area III, IV and V, the probability of the different precipitation intensities shows an overall decreasing trend. The areas VI and VII are located at the mountains with high altitudes where the variation of different precipitation intensities with the increase in drought level is relatively complex. (3) As the drought times increase, areas I, II and V, which are located on the coastal and in the valley or basin, are vulnerable to extreme precipitation processes; areas III, IV, VI and VII are located in the inland area, where heavier precipitation is not likely to occur. (4) The local rainfall affected by multiple factors is closely related with drought occurrence. The characteristics between the first rainfall intensity after a drought period and different drought magnitudes (or drought occurrence times) are preliminarily examined in this paper, but its formation mechanism still requires further research.