Extreme Heavy Precipitation Events Research Articles

Evaluation of the RF-MEP Method for Merging Multiple Gridded Precipitation Products in the Chongqing City, China

Precipitation is a major component of the water cycle. Accurate and reliable estimation of precipitation is essential for various applications. Generally, there are three main types of precipitation products: satellite based, reanalysis, and ground measurements from rain gauge stations. Each type has its advantages and disadvantages. Recent efforts have been made to develop various merging methods to improve precipitation estimates by combining multiple precipitation products. This study evaluated for the first time the performance of the random forest-based merging procedure (RF-MEP) method in enhancing the accuracy of daily precipitation estimates in Chongqing city, China with a complex terrain and sparse observational data. The RF-MEP method was used to merge three widely used gridded precipitation products (CHIRPS, ERA5-Land, and GPM IMERG) with ground measurements from a limited number of rain gauge stations to produce the merged precipitation dataset. Eight stations (approximately 70% of the available stations) were used to train the RF-MEP approach, while four stations (30%) were used for independent testing. Various statistical metrics were employed to assess the performance of the merged precipitation dataset and the three existing precipitation products against the ground measurements. Our results demonstrated that the RF-MEP approach significantly enhances the accuracy of daily precipitation estimates, surpassing the performance of the individual precipitation products and two other merging methods (the simple linear regression model and the simple averaging). Among the three existing products, ERA5-Land exhibited the best performance in capturing daily precipitation, followed by GPM IMERG, while CHIRPS performed the worst. Regarding precipitation intensity, all three existing products and the RF-MEP merged dataset performed well in capturing light precipitation events with an intensity of less than 1 mm/day, which accounts for the majority (more than 70%) of occurrences. However, all datasets showed rather poor capability in capturing precipitation events beyond 1 mm/day, with the worst performance observed for extreme heavy precipitation events exceeding 50 mm/day. The RF-MEP approach significantly improves the detection ability for all precipitation intensities, except for the most extreme intensity (>50 mm/day), where only marginal improvement is observed. Analysis of the spatial pattern of precipitation estimates and the temporal bias of daily precipitation estimates further confirms the superior performance of the RF-MEP merged precipitation dataset over the three existing products.

Projected Changes in Extreme Wet and Dry Conditions in Greece

Earth’s changing climate may have different effects around the planet. Regional changes in temperature and precipitation extremes are associated with damaging natural hazards. Decreases in precipitation are expected to occur in some places at mid-latitudes, for instance the Mediterranean, which has been classified as a climate change hotspot. Droughts are among the most damaging natural hazards with severe consequences in the socio-economic sectors, the environment, and living beings. In contrast, extreme heavy precipitation events may become more frequent. This study aims to project changes in precipitation extremes and assess drought variability and change across Greece. A better knowledge of the potential changes in drought variability under climate change is vital for managing potential risks and impacts associated with dry conditions. The spatiotemporal characteristics of heavy precipitation and drought events in Greece are investigated using extreme precipitation indices such as consecutive wet/dry days, total wet-day precipitation, fraction of total wet-day rainfall, maximum daily precipitation, and heavy precipitation days. The standardized precipitation index and the standardized precipitation and evapotranspiration index are also calculated to assess seasonal dryness variability. The analysis is performed using a sub-set of high-resolution simulations from EURO-CORDEX, under two different representative concentration pathway scenarios. The results show that the region is subject to future dry conditions. Total annual precipitation is found to decrease in most of the country, with western and southern parts tending to be the most vulnerable areas. The annual precipitation is estimated to decrease by 5–20% and 5–25% (RCP4.5 and RCP8.5 respectively) toward the period 2041–2070 and by 10–25% and 15–40% (RCP4.5 and RCP8.5) toward 2071–2100. Drought-related indices reveal positive trends, particularly under the high greenhouse-gas emission scenario, with the number of consecutive dry days increasing by 20–50% and 40–80% (during 2041–2070 and 2071–2100, respectively). On the contrary, extreme precipitation events tend to decrease in the future.

Climatology of the extreme heavy precipitation events in Slovakia in the 1951–2020 period

Climatology of the extreme heavy precipitation events in Slovakia in the 1951–2020 period

A network of water vapor Raman lidars for improving heavy precipitation forecasting in southern France: introducing the WaLiNeAs initiative

Extreme heavy precipitation events (HPEs) pose a threat to human life but remain difficult to predict because of the lack of adequate high frequency and high-resolution water vapor (WV) observations in the low troposphere (below 3 km). To fill this observational gap, we aim at implementing an integrated prediction tool, coupling network measurements of WV profiles, and a numerical weather prediction model to precisely estimate the amount, timing, and location of rainfall associated with HPEs in southern France (struck by ~ 7 HPEs per year on average during the fall). The Water vapor Lidar Network Assimilation (WaLiNeAs) project will deploy a network of 6 autonomous Raman WV lidars around the Western Mediterranean to provide measurements with high vertical resolution and accuracy to be assimilated in the French Application of Research to Operations at Mesoscale (AROME-France) model, using a four-dimensional ensemble-variational approach with 15-min updates. This integrated prediction tool is expected to enhance the model capability for kilometer-scale prediction of HPEs over southern France up to 48 h in advance. The field campaign is scheduled to start early September 2022, to cover the period most propitious to heavy precipitation events in southern France. The Raman WV lidar network will be operated by a consortium of French, German, Italian, and Spanish research groups. This project will lead to recommendations on the lidar data processing for future operational exploitation in numerical weather prediction (NWP) systems.

Assessment of WRF-ARW model parameterization schemes for extreme heavy precipitation events associated with atmospheric rivers over West Coast of India

This study attempts to investigate the simulation of heavy precipitation events (HPEs) over the West Coast of India associated with atmospheric rivers (ARs) using the Advanced Research Weather Research and Forecasting (ARW-WRF) model. The study evaluates the sensitivity of five microphysical (Lin, WSM6, Goddard, Thompson, and Morrison) and cumulus (KF, BMJ, Grell3D, Tidtke, and GD) parameterization schemes to explore the capability to reproduce the AR associated HPEs. The model simulations were reasonably successful at reproducing key structural and synoptic characteristics of atmospheric rivers, including well-defined corridors of strong water vapor transport, meteorological variables and circulation features. Deviations in Rainfall and Wind profiles were observed in simulations among the different parameterization schemes. The model better simulated the AR related precipitation using the Lin, Thompson MP and KF, Grell3D CU schemes when compared to observations, and attributed to the moisture laden tendency of the schemes. Nonetheless, differences in precipitation distribution and overestimation of winds among the model runs using different microphysical and cumulus physics schemes were noted. The study highlights that simulation of AR associated HPEs using high-resolution mesoscale mode with suitable representations of physical parameterization schemes are useful for disaster management and to minimize the loss of fatalities and property.

Linkage of future regional climate extremes to global warming intensity

Changes in extreme climate have caused widespread concern, and it is important to understand how climate extremes will link to global warming intensity at the regional scale. Based on the daily minimum and maximum temperature and precipitation outputs from 25 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models under the Representative Concentration Pathways 8.5 (RCP8.5) scenario, we project the linkage of future regional climate extremes to the global mean temperature increase above preindustrial levels. Results show that regionally averaged changes in absolute temperature extremes (the coldest night and the warmest day) scale linearly with global warming intensity. In contrast, changes in cold nights and cold days in all regions, warm nights in low latitudes, and warm days in Southeast Asia exhibit nonlinear relationships with the global mean temperature increase, which manifests rapid changes in early warming stages and weak changes in late warming stages. The percentile-based temperature extremes vary at large magnitudes as global warming intensifies in low latitudes, while large values are seen in middle and high latitudes for the coldest night and warmest day, respectively; large intermodel spread occurs in the strong scaling areas, except for cold days and cold nights. Regional mean changes in extreme precipitation show consistent linear trends with global warming, and different indices vary in magnitude with region. Extreme heavy precipitation events increase linearly with global warming in high latitudes with larger magnitudes. The intermodel spread is generally large in low latitudes and will increase with warming. The work presented here can provide effective support to decision makers for developing adaptation and mitigation measures.

Projected regional responses of precipitation extremes and their joint probabilistic behaviors to climate change in the upper and middle reaches of Huaihe River Basin, China

Abstract The objective of this paper is to investigate the projected regional responses of univariate and bivariate behaviors of extreme precipitation to climate change over the upper-middle Huaihe River Basin. Based on twelve GCM outputs under historical, RCP4.5 and the observations at 32 rainfall stations, the equidistant cumulative distribution function matching method (EDCDFm) was utilized to bias correct daily precipitation during the historical (1961–2005) and future (2021–2080) periods. Four precipitation indices combinations were introduced based on eight precipitation indices to characterize the regional-scale changes of precipitation events, which designate the duration, intensity and amount of heavy and weak precipitation in a year. Their dependence structures were captured by Copulas. Kendall return period (KRP) were applied to discuss hazard scenarios and we quantified the spatial variability of KRPs under different marginal values. The results indicated that projected precipitation characteristics including the average intensity, the amount of annual precipitation, the intensity and amount of extreme precipitation together with annual extremes displayed increasing trends, while the changes of consecutive wet and dry days did not present pronounced trends. Decreased KRPs in the vast majority of the territory manifested that the frequency of simultaneous floods and droughts in a year as well as that of extreme heavy precipitation events would augment. Obvious spatial heterogeneity of the changes of KRP was partly attributed to the topography difference, especially the coastal areas along the main stream of the Huaihe River. Consequently, there will be a higher risk of water resources-related issues in this region for upcoming decades.

Multi-Indicator Evaluation for Extreme Precipitation Events in the Past 60 Years over the Loess Plateau

The unique characteristics of topography, landforms, and climate in the Loess Plateau make it especially important to investigate its extreme precipitation characteristics. Daily precipitation data of Loess Plateau covering a period of 1959–2017 are applied to evaluate the probability features of five precipitation indicators: the amount of extreme heavy precipitation (P95), the days with extreme heavy precipitation, the intensity of extreme heavy precipitation (I95), the continuous dry days, and the annual total precipitation. In addition, the joint risk of different combinations of precipitation indices is quantitatively evaluated based on the copula method. Moreover, the risk and severity of each extreme heavy precipitation factor corresponding to 50-year joint return period are achieved through inverse derivation process. Results show that the precipitation amount and intensity of the Loess Plateau vary greatly in spatial distribution. The annual precipitation in the northwest region may be too concentrated in several rainstorms, which makes the region in a serious drought state for most of the year. At the level of 10-year return period, more than five months with no precipitation events would occur in the Northwest Loess Plateau. While, P95 or I95 events of 100-year level may be encountered in a 50-year return period and in the southeastern region, which means there are foreseeable long-term extreme heavy precipitation events.

Future joint probability behaviors of precipitation extremes across China: Spatiotemporal patterns and implications for flood and drought hazards

Observed daily precipitation from 527 meteorology stations in China during 1960–2005, and simulated daily precipitation from five Earth System Models (ESMs) under historical, RCP2.6 and RCP8.5 scenarios from Coupled Model Intercomparison Project Phase 5 (CMIP5) datasets are analyzed to investigate joint probability behaviors of precipitation extremes in China during 2021–2050 and 2071–2100. Five joint return periods based on six extreme precipitation indices are defined. These joint return periods consider co-occurrence of extreme heavy and weak precipitation, as well as joint extreme heavy precipitation events in terms of different combinations of extreme precipitation amount, intensity, fractional contribution to annual precipitation days, and consecutive wet periods. Weather Generator Model (WGEN) is used to downscale the outputs of ESMs, and Copula is applied to construct joint probability distributions. The variations of joint return periods with 5-year marginal values (marginal values larger than their 5-year return period values respectively) and 20-year marginal values are discussed to represent changes in joint probability behaviors. Results show that: (1) during 1960–2005, spatial distributions of joint return periods with 5-year marginal values are similar to those with 20-year marginal values; (2) changes in marginal distributions and bivariate relationships between extreme indices may be the causes of joint probability distribution shift; (3) in general, during 2021–2050 and 2071–2100, there is less co-occurrence of consecutive wet and dry days, and more joint extreme heavy precipitation events with various aspects, implying less risk of co-occurrence of floods and droughts in the same year but higher risk of floods in China. But north China may face higher risk of co-occurrence of severe floods and droughts in the same year; and (4) changes in joint return periods under RCP8.5 are more remarkable than under RCP2.6. Even under RCP2.6, a scenario 2°C global average warming target is met, the changes in joint return periods are still considerable.

Characteristics of extreme heavy precipitation events occurring in the area of Cracow (Poland)

The variability of extremely heavy precipitation events with duration of 120 min occurring in the area of Cracow, southern Poland was assessed. The analysis was performed using time series of maximum annual precipitation events with durations t = 5, 10, 15, 30, 60, and 120 min, recorded at the Botanical Garden station at the Jagiellonian University in the period of 1906–1990. The periodicity of precipitation was analyzed using the autocorrelation function and Fourier spectral density analysis. The Probable Maximum Precipitation (PMP) was calculated by Hershfield’s statistical method. The analysis of the autocorrelation function of sequences and the Fourier spectral density revealed a clear periodicity of the maximum precipitation. For precipitation with t = 60 min, the maximum values occur every 9 years, but also shorter periods (3-year) may be observed. The PMP values calculated for Cracow differ significantly from the values calculated using the probability distribution, as well as from the ones observed and they increase with increasing precipitation duration. The differences between the PMP and probable as well as observed precipitation tend to decrease with increasing duration of precipitation.

Recent changes in daily precipitation and surface air temperature extremes in mainland Portugal, in the period 1941–2007

Changes in the climatology of precipitation and surface air temperature are being investigated worldwide, searching for changes in variability, the mean and extreme events (maximum and minimum). By exploring recent adjustments in the climate of mainland Portugal, particularly in the intensity, frequency and duration of extreme events, this study investigates trends in selected specific indices that are calculated from daily precipitation data from 57 and surface air temperature data from 23 measuring stations scattered across the territory. Special attention is paid to regional differences and variations in seasonality. The data cover the periods 1941–2007 for precipitation, and 1941–2006 for temperature. They are explored at the annual and seasonal scales and for different sub-periods.Results show that trends in annual precipitation indices are generally weak and, overall, not statistically significant at the 5% level. Nevertheless, a decreasing trend is revealed by regional indices of total wet-day precipitation and extreme precipitation (above the 99th percentile). Seasonal precipitation exhibits significant decreasing trends in spring precipitation, while extreme heavy precipitation events, in terms of both magnitude and frequency, have become more pronounced in autumn. Results for winter and summer suggest that the extremes have not suffered any significant aggravation.Trends for air temperature are statistically more significant and marked than for precipitation and indicate general warming across the territory. This warming trend is revealed very consistently by the time series of individual stations and regional mean temperature, and is also consistent with the findings reported in other studies for Portugal and at the European scale.

A spatial analysis of extreme hourly precipitation patterns in India

AbstractStation level hourly precipitation data from 1980 to 2002 spread across the Indian subcontinent were analysed for trends in extreme hourly precipitation events. The analyses were conducted for the main seasons of winter, dry‐summer, and wet‐summer monsoon seasons, respectively. The results of the study indicated rising trends in extreme heavy precipitation events, mostly in the high‐elevation regions of the northwestern Himalaya as well as along the foothills of the Himalaya extending south into the Indo‐Gangetic basin. In general, the lowest positive trends to slightly neutral to negative trends in extreme precipitation events were observed during the winter season, while stronger positive trends were found for both dry‐summer and wet‐summer monsoon seasons. Along the west coast, the southern part experienced a declining trend, whereas the northern section of the coast experienced an increasing trend of extreme precipitation events. Most of Deccan Plateau extending towards south central coastal regions of the subcontinent also experienced a positive trend in the occurrence of extreme heavy precipitation events. Furthermore, the trends affecting large, million‐plus‐population urban agglomerations were examined separately, and these trends were found to be pre‐dominantly positive during dry‐summer and wet‐summer monsoon seasons, but showed neutral to negative trends during the winter season. Copyright © 2008 Royal Meteorological Society

A numerical study of three catastrophic precipitating events over southern France. I: Numerical framework and synoptic ingredients

AbstractThis study examines the simulation of three torrential rain events observed on 13–14 October 1995 (the Cévennes case), 12–13 November 1999 (the Aude case) and 8–9 September 2002 (the Gard case) over the southeastern part of France using the Meso‐NH non‐hydrostatic mesoscale numerical model. These cases were associated with extreme Heavy Precipitation Events (HPEs) with significant precipitation amounts exceeding 500 mm in less than 24 hours. Several sets of numerical experiments were performed with 10 km and 2.5 km horizontal resolutions. In part I of this study, special attention is paid to the experimental design for obtaining realistic simulations of HPEs with the Meso‐NH model, as well as the evolution of the synoptic patterns in which the rainfall events are embedded.The best 2.5 km numerical simulations show the ability of the Meso‐NH model to reproduce significant quasi‐stationary rainfall events. Moreover, the model fairly reproduces the low‐level mesoscale environments associated with the three HPEs. The HPEs formed in a slow‐evolving synoptic environment favourable for the development of convective systems (diffluent upper‐level southerly flow, PV anomalies, etc.). At lower levels, a southerly to easterly moderate to intense flow provided conditionally unstable and moist air as it moved over the relatively warm Mediterranean Sea, typical for this time of the year (late summer and autumn). The two extreme cases (Gard and Aude) differ from the more classical event (Cévennes) in terms of larger low‐level moisture fluxes. Weaker values of conditional convective instability, as in the Aude case, is counterbalanced by a stronger warm and moist low‐level jet. The mesoscale triggering and/or sustaining ingredients for deep convection and the physical mechanisms leading to the stationarity of these rainfall events are presented and discussed in a companion paper. Copyright © 2008 Royal Meteorological Society