Extreme Precipitation Response Research Articles

Quantitative analysis of the sensitivity and spatial stratified heterogeneity of extreme precipitation across river basins

Global warming is expected to lead to a continuous increase in extreme precipitation. However, the response of extreme precipitation to climate change remains not entirely clear. This study quantitatively analyzes extreme precipitation in multiple river basins of China over the past nearly 60 years using high spatial resolution data. Both extreme precipitation and mean precipitation exhibit a spatial distribution pattern of higher values in the southeast and lower values in the northwest. However, their sensitivity to temperature shows an asymmetric spatial pattern, with higher sensitivity in the northwest and lower sensitivity in the southeast. Overall, the sensitivity of extreme precipitation to temperature (9.6 %/K) is 1.1 times that of mean precipitation (8.8 %/K). Additionally, the sensitivity of extreme precipitation in relatively dry areas (Continental River Basin) is about five times that in relatively wet areas (other river basins). Vegetation has the highest explanatory power (i.e., q-value) for the spatial stratified heterogeneity of extreme precipitation, ranging from 0.61 to 0.72, with the explanatory power of natural factors exceeding that of societal factors. Furthermore, the interaction between vegetation and elevation enhances the explanatory power for the spatial stratified heterogeneity of extreme precipitation, reaching values between 0.74 and 0.82.

Intensified response of extreme precipitation to rising temperature over the Tibetan Plateau from CMIP6 multi-model ensembles

This study conducted bias correction of the high-performing general circulation model (GCM) data in combination with observed data based on the latest GCM data released by the Coupled Model Intercomparison Project Phase 6 (CMIP6). The ability of GCMs to simulate the characteristics of extreme precipitation over the Tibetan Plateau (TP) was systematically assessed, and the CMIP6 multi-model ensemble was used to accurately project extreme precipitation. Furthermore, the response of extreme precipitation over the TP to global warming was explored. The results demonstrated that daily translation efficiently addressed the issue of apparent overestimation in the model’s raw output, and CMIP6 multi-model ensemble mean exhibited better simulation performance for all extreme precipitation indices over the TP. Additionally, the simulation performance of each index exhibited a divergence across various elevation bands as altitude increased, with the best and worst performance observed at the altitude bands of 1500–2000 m and above 5000 m, respectively. For future changes in extreme precipitation, the indices representing the amount and intensity of extreme precipitation increase significantly, whereas the indices representing the duration of precipitation decrease. Moreover, the plateau will show a spatial pattern of “wet regions becoming dry and dry regions becoming wet”. The relationship between extreme precipitation and temperature follows a positive and peak pattern over most areas of the plateau, while the response of extreme precipitation to temperature will increase by 0.6 %–52.6 % with rising temperature. The present results have important implications for investigating the impacts of climate change on the water cycle in alpine regions.

Understanding extreme precipitation scaling with temperature: insights from multi-spatiotemporal analysis in South Korea

With global warming, the intensification of extreme precipitation events is anticipated to follow an exponential growth pattern aligned with the Clausius–Clapeyron (CC) scaling rate (approximately 7% per degree Celsius). However, the regional-scale response of extreme precipitation shows significant variability, deviating from the expected CC rate. This deviation is likely caused by diverse weather patterns and local fluctuations in thermodynamic influences, resulting in differences across seasons and within the region of interest. In this study, we examine the spatial distribution of scaling relationships between extreme precipitation and temperature in South Korea, considering daily and sub-daily scales, both annually and seasonally. For a thorough analysis, we utilize multiple precipitation accumulation periods, temperatures, and different conditional quantiles. Our results reveal that, at the annual scale, most scaling patterns exhibit a peak-like structure, with significant variations in breakpoints observed across temperature variables and regions. However, the southern area presents a notable exception with a positive scaling pattern, particularly with the dew point temperature. At the seasonal scale, we observe more variability, with notable shifts occurring during the wet season across different temperatures and regions. Lastly, we explore the long-term historical changes in the peak value in extreme precipitation and find significant increases at high quantiles in the southern area of South Korea. It informs that the observed peak like pattern does not impose a potential upper limit for extreme precipitation. Overall, our findings emphasize the need for cautious interpretation of precipitation scaling within specific spatiotemporal contexts, which could provide a solid basis for better understanding future extreme precipitation events in a changing climate.

Future Joint Probability Characteristics of Extreme Precipitation in the Yellow River Basin

The relationship between climate change and extreme precipitation is extremely complex. From a probabilistic perspective, a proper understanding of the response of extreme precipitation to climate change is of significant importance. This study was based on daily precipitation provided by CMIP6 climate models and employed copula functions to construct joint distributions of precipitation amount and precipitation intensity indices at different quantile levels. A spatial–temporal assessment of the susceptibility areas for extreme precipitation in the Yellow River Basin was conducted while considering bivariate return periods and design values. The results indicate that there were significant spatial differences in the bivariate return periods. Taking the R90P-SDII (90) index for a 20a return period as an example, the difference between the maximum and minimum joint return periods within the Yellow River Basin was 1.4 times, while the co-occurring return period was 7.0 times, and the Kendall return period was 4 times. Moreover, this difference increased with the increase in the return period. The magnitude order of the four return periods is as follows: TAnd > TKendall > TSingle-variable > TOr. Joint return periods (Or) and co-occurring return periods (And) could be considered as the extreme cases under single-variable return periods, serving as an estimation interval for actual return periods. Under the influence of climate change, the bivariate design values for future periods exhibited a variability increase of 6.76–28.8% compared to historical periods, and this increase grew with higher radiative forcing scenarios, ranking as SSP126 < SSP245 < SSP585. The bivariate design values showed a noticeable difference in variability compared to the single-variable design values, ranging from −0.79% to 18.67%. This difference increased with higher quantile values, with R95P-SDII (95) > R90P-SDII (90) > PRCPTOT-SDII.

Asymmetrical Precipitation Sensitivity to Temperature Across Global Dry and Wet Regions

AbstractGlobal warming is expected to increase precipitation extremes. However, the response of extreme precipitation to global warming in various climates remains unclear. Here, we analyzed changes in the sensitivities of extreme and mean precipitation to temperature across the dry and wet regions of the world during 1960–1999 and 2060–2099 using global climate models. Both extreme and mean precipitation exhibited similar spatial patterns; however, the magnitude of sensitivity for extreme precipitation was approximately three times higher (19%/K) than for mean precipitation (6%/K). A higher precipitation sensitivity to temperature was observed in the dry regions than in the wet regions. Dry regions exhibited a four‐ to five‐fold higher temperature sensitivity for mean precipitation, and marginally higher temperature sensitivity for extreme precipitation than wet regions. These findings highlight the importance of implementing adaptive strategies to alleviate the effects of global warming on dryland ecosystems.

Response of extreme precipitation to climatic warming in the Weihe river basin, China and its mechanism

Abstract As global warming continues, extreme precipitation events occur frequently in inland areas, seriously affecting human security and the ecological environment. Spatiotemporal evolution of extreme precipitation as well as response of extreme precipitation to climatic warming and its mechanism were investigated by considering the Weihe river basin in a monsoon transition zone of China as a research object. The results indicate that while the annual average temperature of the Weihe river basin increased with fluctuations from 1966 to 2017, except for the consecutive dry days (CDD) and simple daily intensity index that increased slightly, the other extreme precipitation indices (consecutive wet days, R25, and Rx5day) tended to decrease. Moreover, except for the CDD, the other four indices gradually increased from the northwest to the southeast, showing a similar trend to the temperature. The relationship between the 95th percentile threshold and temperature (hereinafter referred to as the P 95d–T relationship) in the Weihe river basin demonstrates the hook structure and its strength in terms of response is mainly dominated by the super-Clausius–Clapeyron (C–C) and C–C scaling. Furthermore, the peak temperature rises gradually from the northwest to the southeast. The results can provide important reference for the prediction of climate change and future studies of disaster risk in the Weihe river basin.

Simulation of ENSO Teleconnections to Precipitation Extremes over the United States in the High-Resolution Version of E3SM

Abstract We evaluate the simulated teleconnection of El Niño–Southern Oscillation (ENSO) to winter season precipitation extremes over the United States in a long (98 years) 1950 control high-resolution version (HR; 25-km nominal atmosphere model horizontal resolution) of the U.S. Department of Energy’s (DOE) Energy Exascale Earth System Model version 1 (E3SMv1). The model bias and spatial pattern of ENSO teleconnections to mean and extreme precipitation in HR overall are similar to the low-resolution model’s (LR; 110 km) historical simulation (four-member ensemble, 1925–59). However, over the southeastern United States (SE-U.S.), HR produces stronger El Niño–associated extremes, reducing LR’s model bias. Both LR and HR produce weaker than observed increase in storm track activity during El Niño events there, but HR improves the ENSO-associated variability of moisture transport over SE-U.S. During El Niño, stronger vertical velocities in HR produce stronger large-scale precipitation, causing larger latent heating of the troposphere that pulls in more moisture from the Gulf of Mexico into the SE-U.S. This positive feedback also contributes to the stronger mean and extreme precipitation response in HR. Over the Pacific Northwest, LR’s bias of stronger than observed La Niña associated extremes is amplified in HR. Both models simulate stronger than observed moisture transport from the Pacific Ocean into the region during La Niña years. The amplified HR bias there is due to stronger orographically driven vertical updrafts that create stronger large-scale precipitation, despite weaker La Niña–induced storm track activity. Significance Statement New high-resolution Earth system models (ESMs) solve mathematical equations of fluid flow at much smaller spatial scales than prevalent ESMs, and thus are prohibitively expensive to compute. However, they can be useful for simulating accurate details of regional climate extremes that are driven by naturally occurring climate oscillations like El Niño–Southern Oscillation (ENSO). Here, we evaluate the simulation of ENSO-driven precipitation extremes over the United States in the high-resolution version of the U.S. Department of Energy’s new Energy Exascale Earth System Model version 1. We find that the high-resolution model improves upon its low-resolution counterpart over the southeastern United States by producing a better transport of moisture into the region from the Gulf of Mexico during El Niño. Over the U.S. Pacific Northwest, the high-resolution model simulates the atmospheric flow in more detail over the complex mountainous terrain. However, it also brings in more moisture from the Pacific Ocean just like the low-resolution model. This causes it to produce precipitation extremes during La Niña years there that are stronger than that observed in the real world.

Increased Risk of Extreme Precipitation Over an Urban Agglomeration With Future Global Warming

AbstractUnderstanding the response of extreme precipitation (EP) at a city scale to global warming is critical to reducing the respective risk of urban flooding. Yet, current knowledge on this issue is limited. Here, focusing on an urban agglomeration in the tropics, Singapore, we reveal that future global warming enhances both frequency and intensity of EP, based on simulations with a state‐of‐the‐art convection‐permitting regional climate model. EP intensification can reach maximum “super” Clausius‐Clapeyron rate (+7% per K warming) rate, implying a “new normal” of “extreme events get more extreme,” which is consistently for both Representative Concentration Pathways 8.5 and 4.5. The intensification is lower for moderate and light precipitation. Also, global warming was found to dampen the urban effect on EP events. The EP enhancement is attributed to the increased atmospheric moisture and convective inhibition due to enhanced low‐level stratification that delays a convection to develop until it becomes more intense.

Response of extreme precipitation to increasing extratropical cyclonic vortex frequency

Since the 2000s, extratropical extremes have been more frequent, which are closely related to anomalies of planetary-scale and synoptic-scale systems. This study focuses on a key synoptic system, the extratropical cyclonic vortex (ECV) over land, to investigate its relations with extreme precipitation. It was found that ECVs have been more active post-2000, which has induced more extreme precipitation, and such variation is projected to persist along with increasing temperature within 1.5°C of global warming. An enhanced quasi-stationary vortex (QSV) primarily contributes to the ECV, rather than inactive synoptic-scale transient eddies (STEs). Inactive STEs respond to a decline in baroclinicity due to the tendency of the homogeneous temperature gradient. However, such conditions are helpful to widening the westerly jet belt, favoring strong dynamic processes of quasi-resonant amplification and interaction of STEs with the quasi-stationary wave, and the result favors an increasing frequency and persistence of QSVs, contributing to extreme precipitation.摘要自21世纪以来, 热带外极端降水频次增加. 随着中高纬度的显著增温, 经向温度梯度减弱导致低层大气斜压性减小, 由此产生的气旋型瞬变涡天气系统等活动减弱. 然而, 热力分布导致西风急流带变宽, 经向环流加大, 有助于行星尺度波动相关的涡旋异常增加, 如东北冷涡, 中亚涡, 东欧-地中海涡, 北美涡等, 进而增加了气旋涡影响范围的极端降水频次. 在未来变暖背景和1.5°C增温的目标内, 热带外气旋涡增强会进一步促进极端降水发生.

Dominant change pattern of extreme precipitation and its potential causes in Shandong Province, China

Due to global warming, global and regional extreme precipitation events occur frequently, causing severe drought and flood disasters. This has a significant impact on productivity and human life. Therefore, it is of great significance to study the characteristics of extreme precipitation and its spatiotemporal variation. In this study, we investigate the dominant variation patterns of extreme precipitation (EP), which is characterized by indices, and also analyze its potential causes in the Shandong province of China during 1961–2015 using the daily precipitation data from 123 metrological stations. The results show that there has been a dry trend in the Shandong Province in the past 55 years, that is, with the decrease in precipitation, most of the extreme precipitation index has basically showed a downward trend to varying degrees. In particular, the increase in the number of consecutive dry days (CDD) and the decrease in the number of consecutive wet days (CWD) can better explain the drought in this region. After the 1980s, the extreme precipitation index basically showed an upward trend to varying degrees, indicating that extreme precipitation events have shown an increasing trend in recent years. The spatial distribution of each extreme precipitation index generally increased from north to south. The mutation of each extreme precipitation index occurred in the 1970s and 1990s, and there was a main period of 0.9–2.2 years. In terms of influencing factors, the NINO3 area can be used as the critical sea area for the response of extreme precipitation to SSTAs in the Shandong Province. The research results are helpful to understand the temporal and spatial variations of extreme precipitation and have very important reference value for the prediction of and response to climate change and extreme events in the future.

Quantifying the Human Influence on the Intensity of Extreme 1- and 5-Day Precipitation Amounts at Global, Continental, and Regional Scales

Abstract This study provides a comprehensive analysis of the human contribution to the observed intensification of precipitation extremes at different spatial scales. We consider the annual maxima of the logarithm of 1-day (Rx1day) and 5-day (Rx5day) precipitation amounts for 1950–2014 over the global land area, four continents, and several regions, and compare observed changes with expected responses to external forcings as simulated by CanESM2 in a large-ensemble experiment and by multiple models from phase 6 of the Coupled Model Intercomparison Project (CMIP6). We use a novel detection and attribution analysis method that is applied directly to station data in the areas considered without prior processing such as gridding, spatial or temporal dimension reduction, or transformation to unitless indices and uses climate models only to obtain estimates of the space–time pattern of extreme precipitation response to external forcing. The influence of anthropogenic forcings on extreme precipitation is detected over the global land area, three continental regions (the western Northern Hemisphere, western Eurasia, and eastern Eurasia), and many smaller IPCC regions, including central North America, East Asia, east-central Asia, eastern Europe, eastern North America, northern Europe, and western Siberia for Rx1day, and central North America, eastern Europe, eastern North America, northern Europe, the Russian Arctic region, and western Siberia for Rx5day. Consistent results are obtained using forcing response estimates from either CanESM2 or CMIP6. Anthropogenic influence is estimated to have substantially decreased the approximate waiting time between extreme annual maximum events in regions where anthropogenic influence has been detected, which has important implications for infrastructure design and climate change adaptation policy. Significance Statement All previous detection and attribution studies of observed changes in extreme precipitation (i) use station data that has been heavily processed via gridding, transformation, and spatial and temporal averaging or other dimension reduction approaches, as well as using climate models to estimate the responses to external forcing, and (ii) also use models to estimate the unforced natural variability of extreme precipitation. Both aspects reduce user confidence in detection and attribution results. This study uses station data directly and avoids difficult to verify model-based estimates of the unforced variability of precipitation extremes. Results confirm findings from previous studies, and extend them to a number of subcontinental regions, thus substantially increasing confidence in detection and attribution findings precipitation.

Response of extreme precipitation to uniform surface warming in quasi-global aquaplanet simulations at high resolution

Projections of precipitation extremes in simulations with global climate models are very uncertain in the tropics, in part because of the use of parameterizations of deep convection and model deficiencies in simulating convective organization. Here, we analyse precipitation extremes in high-resolution simulations that are run without a convective parameterization on a quasi-global aquaplanet. The frequency distributions of precipitation rates and precipitation cluster sizes in the tropics of a control simulation are similar to the observed distributions. In response to climate warming, 3 h precipitation extremes increase at rates of up to [Formula: see text] in the tropics because of a combination of positive thermodynamic and dynamic contributions. The dynamic contribution at different latitudes is connected to the vertical structure of warming using a moist static stability. When the precipitation rates are first averaged to a daily timescale and coarse-grained to a typical global climate-model resolution prior to calculating the precipitation extremes, the response of the precipitation extremes to warming becomes more similar to what was found previously in coarse-resolution aquaplanet studies. However, the simulations studied here do not exhibit the high rates of increase of tropical precipitation extremes found in projections with some global climate models. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'.

Response of summer extreme precipitation over East Asia during the mid-Holocene versus future global warming

Changes in extreme precipitation have significant impacts on society and the environment. In recent years, the response of extreme precipitation over East Asia to global warming has received considerable attention; however, few studies have focused on the extreme precipitation in geological warm periods, especially the mid-Holocene—the most recent warm period on the orbital timescale. In this study, the outputs of mid-Holocene, pre-industrial and CO2-induced warming experiments using a coupled climate model (MPI-ESM-P) were employed to examine the changes in extreme precipitation over East Asia in the mid-Holocene and under future warming scenario, respectively. The results show that, during the mid-Holocene, summer extreme precipitation increases over the east of China but decreases over Japan and the surrounding oceans. However, under CO2-induced warming, summer extreme precipitation increases over the southeast of China, Japan, and the surrounding oceans, but decreases over the north of East Asia. Moisture budget analysis shows that these distinct responses come from different changes in moisture and circulation during the two periods. During the mid-Holocene, higher insolation over the Northern Hemisphere leads to a larger ocean–land thermal contrast and a stronger East Asian summer monsoon (EASM). The strengthened EASM brings more moisture to continental East Asia, resulting in an increase in both mean and extreme precipitation. In contrast, the CO2-induced warming facilitates an anomalous heating center in the upper troposphere over the tropical part of Northwestern Pacific ocean, which weakens the EASM. However, enhanced atmospheric moisture counterbalances the effect of the weakened EASM, resulting in more extreme precipitation over the south of East Asia.

Responses of Mean and Extreme Precipitation to Different Climate Forcing Under Radiative-Convective Equilibrium

Understanding the responses of mean and extreme precipitation to climate change is of great importance. Previous studies have mainly focused on the responses to prescribed sea surface warming or warming due to increases of CO2. This study uses a cloud-resolving model under the idealization of radiative–convective equilibrium to examine the responses of mean and extreme precipitation to a variety of climate forcings, including changes in prescribed sea surface temperature, CO2, solar insolation, surface albedo, stratospheric volcanic aerosols, and several tropospheric aerosols. The different responses of mean precipitation are understood by examining the changes in the surface energy budget. It is found that the cancellation between shortwave scattering and longwave radiation leads to a small dependence of the mean precipitation response on forcings. The responses of extreme precipitation are decomposed into three components (thermodynamic, dynamic, and precipitation efficiency). The thermodynamic components for all climate forcings are similar. The dynamic components and the precipitation-efficiency components, which have large spreads among the cases, are negatively correlated, leading to a small dependence of the extreme precipitation response on the forcings.

Decreasing precipitation occurs in daily extreme precipitation intervals across China in observations and model simulations

Extreme precipitation response to increasing temperature includes not only changes of frequency and intensity, but also changes of extreme precipitation interval (EPIV) and the precipitation during the neighboring daily extreme precipitations interval (EPIP). These changes have not been fully evaluated yet in observations or climate model simulations although they are very useful to understand variations of extreme precipitation. We used daily precipitation data from 669 meteorological stations during the past five decades across China and projections of 19 general circulation models from CMIP5 under the RCP4.5 and RCP8.5 scenarios to investigate variations of EPIV and EPIP. We found the national average annual EPIV increased across China during the last five decades, while annual EPIP significantly decreased. The decreases mainly occurred in southwest China, east China, and southeast China. At national and regional scales, the average annual EPIV and EPIP showed greater decreases under the RCP8.5 scenario than those under the RCP4.5 scenario from 2006 to 2100. Annual EPIP showed a stronger correlation with extreme precipitation intensity than EPIV. The national average annual EPIP had a significant positive correlation with the Western Pacific Subtropical High Area Index. The abnormal geopotential heights over western Mongolia and the western Pacific at 500 hpa as well as the abnormal SSTs in Japan Sea and the western of Pacific in rainy seasons would result in abnormal annual EPIVs and EPIPs in China. This study may provide references for flooding prediction, water resources management, and disaster prevention and mitigation.

Quantifying spatiotemporal influences of climate index on seasonal extreme precipitation based on hierarchical Bayesian method

AbstractQuantifying spatiotemporal influence of climate index on extreme precipitation will help to better understand the variability of extreme precipitation. The extreme precipitation is usually influenced by different climate indices, and mutual offset is unavoidable to occur, thus the rotated empirical orthogonal function was used to identify the different influences of climate indices on extreme precipitation in space and time. The variation of extreme precipitation in data‐scarce region is also concerned, hence, an improved spatiotemporal regional frequency analysis model was further developed, therein the identified spatiotemporal influences of climate indices on extreme precipitation were quantified using Bayesian hierarchical method. In this study, the in situ seasonal maximum one‐day precipitation amount (Rx1day) was used to represent seasonal precipitation extremes from 1957 to 2010 in the Poyang Lake basin, and spatiotemporal influences of El Niño‐Southern Oscillation (ENSO), North Atlantic oscillation (NAO) and Indian Ocean Dipole (IOD) on seasonal Rx1day were quantified. Results indicated that the seasonal Rx1day was influenced by different climate indices in the Poyang Lake basin, ENSO tends to affect spring and autumn Rx1day, IOD tends to affect summer Rx1day, and NAO tends to affect spring and winter Rx1day. The response of extreme precipitation on climate index is varied in different regions, and this was well distinguished and verified, such as negative ENSO (in the same year) events tends to cause spring Rx1day slight decrease in the southern part of the basin while increase about 15% in the northern part with center around the Poyang lake.

Nonlinear Response of Extreme Precipitation to Warming in CESM1

AbstractThe response of extreme precipitation to warming varies widely among climate models, especially in the tropics. In some models, there have been indications that the rate of response increases with warming—that the response is not linear. We investigate the evolution of extreme precipitation, quantified by the maximum accumulated precipitation in a day each year, in CESM1. We find that tropical‐ and global‐average extreme precipitation is related to global‐mean surface temperature quadratically. This behavior is associated with an increase in the large‐scale fraction of extreme precipitation and also strengthening circulation on extreme precipitation days. Compared to other CMIP5 models, the nonlinearity in CESM1 is among the largest. One implication is that the difference between CESM1 simulations with full forcing and with fixed aerosols cannot be used to isolate the response of extreme precipitation to aerosols, as the resulting climates are not equally warm.

Extreme Precipitation in China in Response to Emission Reductions under the Paris Agreement

To avoid more severe impacts from climate change, countries worldwide pledged to implement intended nationally determined contributions (INDCs) for emission reductions (as part of the Paris Agreement). However, it remains unclear what the resulting precipitation change in terms of regional extremes would be in response to the INDC scenarios. Here, we analyzed China’s extreme precipitation response of the next few decades to the updated INDC scenarios within the framework of the Paris Agreement. Our results indicate increases in the intensity and frequency of extreme precipitation (compared with the current level) in most regions in China. The maximum consecutive five-day precipitation over China is projected to increase ~16%, and the number of heavy precipitation days will increase as much as ~20% in some areas. The probability distributions of extreme precipitation events become wider, resulting in the occurrence of more record-breaking heavy precipitation in the future. We further considered the impacts of precipitation-related extremes and found that the projected population exposure to heavy precipitation events will significantly increase in almost all Chinese regions. For example, for heavy precipitation events that exceed the 20 year baseline return value, the population exposure over China increases from 5.7% (5.1–6.0%) to 15.9% (14.2–16.4%) in the INDC-pledge scenario compared with the present-day level. Limiting the warming to lower levels (e.g., 1.5 °C or 2.0 °C) would reduce the population exposure to heavy precipitation, thereby avoiding impacts associated with more intense precipitation events. These results contribute to an improved understanding of the future risk of climate extremes, which is paramount for the design of mitigation and adaptation policies in China.

Response of Extreme Precipitation to Urbanization over the Netherlands

AbstractKnowledge of the response of extreme precipitation to urbanization is essential to ensure societal preparedness for the extreme events caused by climate change. To quantify this response, this study scales extreme precipitation according to temperature using the statistical quantile regression and binning methods for 231 rain gauges during the period of 1985–2014. The positive 3%–7% scaling rates were found at most stations. The nonstationary return levels of extreme precipitation are investigated using monthly blocks of the maximum daily precipitation, considering the dependency of precipitation on the dewpoint, atmospheric air temperatures, and the North Atlantic Oscillation (NAO) index. Consideration of Coordination of Information on the Environment (CORINE) land-cover types upwind of the stations in different directions classifies stations as urban and nonurban. The return levels for the maximum daily precipitation are greater over urban stations than those over nonurban stations especially after the spring months. This discrepancy was found by 5%–7% larger values in August for all of the classified station types. Analysis of the intensity–duration–frequency curves for urban and nonurban precipitation in August reveals that the assumption of stationarity leads to the underestimation of precipitation extremes due to the sensitivity of extreme precipitation to the nonstationary condition. The study concludes that nonstationary models should be used to estimate the return levels of extreme precipitation by considering the probable covariates such as the dewpoint and atmospheric air temperatures. In addition to the external forces, such as large-scale weather modes, circulation types, and temperature changes that drive extreme precipitation, urbanization could impact extreme precipitation in the Netherlands, particularly for short-duration events.

Physical Responses of Convective Heavy Rainfall to Future Warming Condition: Case Study of the Hiroshima Event

An extreme precipitation event happened at Hiroshima in 2014. Over 200 mm of total rainfall was observed on the night of August 19th, which caused floods and many landslides. The rainfall event was estimated to be a rare event happening once in approximately 30 years. The physical response of this event to the change of the future atmospheric condition, which includes a temperature increase on average and convective stability change, is investigated in the present study using a 27-member ensemble experiment and pseudo global warming downscaling method. The experiment is integrated using the Japan Meteorological Research Institute non-hydrostatic regional climate model. A very high-resolution horizontal grid, 500 m, is used to reproduce dense cumulonimbus cloud formation causing heavy rainfall in the model. The future climate condition determined by a higher greenhouse gas concentration is prescribed to the model, in which the surface air temperature globally averaged is 4 K warmer than that in the preindustrial era. The total amounts of precipitation around the Hiroshima area in the future experiments are closer to or slightly lower than in the current experiments in spite of the increase in water vapor due to theatmospheric warming. The effect of the water vapor increase on extreme precipitation is found to be canceled out by the suppression of convection due to the thermal stability enhancement. The fact that future extreme precipitation like the Hiroshima event is not intensified is in contrast to the well-known result that extreme rainfall tends to be intensified in the future. The results in the present study imply that the response of extreme precipitation to global warming differs for each rainfall phenomenon.