Detection and attribution of extreme precipitation changes from 1961 to 2012 in the Yangtze River Delta in China

Radley Horton,1,a Daniel Bader,1,a Yochanan Kushnir,2 Christopher Little,3 Reginald Blake,4 and Cynthia Rosenzweig5 1Columbia University Center for Climate Systems Research, New York, NY. 2Ocean and Climate Physics Department, Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY. 3Atmospheric and Environmental Research, Lexington, MA. 4Physics Department, New York City College of Technology, CUNY, Brooklyn, NY. 5Climate Impacts Group, NASA Goddard Institute for Space Studies; Center for Climate Systems Research, Columbia University Earth Institute, New York, NY

Contribution of extreme daily precipitation to total rainfall over the Arabian Peninsula

Introduction: Several studies have shown associations between an increase in precipitation and a higher frequency of traffic accidents; a few have examined the relationship between high temperatures and motor vehicle crashes. However, to our knowledge, no studies exist assessing how extreme events, projected to grow in frequency, intensity, and duration in response to our changing climate, will impact the risk of injury from motor vehicle accidents. Our study quantified the association between frequency of extreme heat and precipitation events and change in injury risk from motor vehicle accident in Maryland between 2000 and 2012. Methods: Motor vehicle accident data was obtained from the Maryland Automated Accident Reporting System. Each observation in the data set corresponded to a unique collision event. A time-stratified case-crossover design was utilized to assess the association between exposure to extreme heat and precipitation events and risk of injury or death from motor vehicle accident. Additional stratified analyses examined risk by road type and season. Results: Over the study period, there were 461,009 motor vehicle accidents that resulted in injury or death. We observed an 18% increase (OR: 1.18; 95% CI: 1.17, 1.19) in risk of motor vehicle injury for every 1-day increase in extreme precipitation event, with the highest risk (29%) observed during autumn (OR: 1.29; 95% CI: 1.27, 1.32). Extreme precipitation related increase in motor vehicle injury was considerably higher when a road defect or obstruction was present (OR: 1.42, 95% CI: 1.32, 1.52). Changes in risk associated with extreme heat events were generally marginal. Conclusion: Extreme precipitation events, particularly in conjunction with a road defect or obstruction, are associated with an increased risk of injury from motor vehicle accidents in Maryland. Our results suggest that projected increases in frequency of extreme precipitation event will have a significant impact on public health.

Extreme precipitation events are climatic hazard phenomena that can lead to riverine floods, flash floods, and landslides, posing significant threats to society and the environment. In this study, we examine the effects of climate change on the frequency and intensity of extreme precipitation events in the Middle East and North Africa (MENA) region. Our analysis focuses on daily precipitation simulations at a spatial resolution of approximately 50 km, provided by both regional and global climate models. Detecting changes in extreme precipitation events is challenging due to their high variability in time and space. Therefore, we employ the Simplified Meta-statistical Extreme Value (SMEV) method, an advanced extreme precipitation frequency analysis approach that enables a more robust frequency analysis of extreme precipitation by reducing uncertainty compared to traditional methods. We find that, while average precipitation levels exhibit heterogeneous changes across the MENA region, a general intensification of extreme precipitation is expected. Notably, the intensification is stronger for rarer events. Our results also indicate that changes in both average and extreme precipitation across the MENA region are spatially non-uniform, with some areas experiencing intensification while others show a downward change, with regional variability in change strength. The strongest intensification in extreme precipitation is projected over central Africa and the northern Arabian Sea region. We also find that the regional patterns in extreme and average precipitation changes are not always aligned. Notably, mean annual precipitation is expected to decline over the Mediterranean, while extreme precipitation return levels are projected to intensify in much of the area.

Increased flood risk in Indian sub-continent under the warming climate

This study assessed the past changes in extreme precipitation and temperature events across the Himalayan Mountains of Pakistan. This cold and mountainous environmental region has witnessed a significant increase in climate-related disasters over the past few decades. Spatiotemporal changes in extreme temperature and precipitation events were analyzed using 24 indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI). For this study, in situ data of 16 national meteorological stations were obtained from the Pakistan Meteorological Department (PMD) for the past three decades (1991–2020). The significance of the trends was assessed using the modified Mann–Kendall (MMK) test, and the Theil–Sen (TS) slope estimator was used to estimate the slope of the trend. The results showed that there has been a consistent decline in the total precipitation amount across the Himalayan Mountains of Pakistan. The trend exhibited a decrease in the annual average precipitation at a rate of −6.56 mm/year. Simultaneously, there was an increasing trend in the annual average minimum and maximum temperatures at rates of 0.02 °C/year and 0.07 °C/year, respectively. The frequencies of consecutive wet days (CWDs) and maximum 5-day precipitation (RX5day) have decreased significantly, with decreasing rates of −0.40 days/year and −1.18 mm/year, respectively. The amount of precipitation during very wet days (R95p) and extremely wet days was decreased by −19.20 and −13.60 mm/decade, respectively. The warm spell duration (WSDI) and the frequency of warm days (TX90p) across the Himalayan Range both increased by 1.5 and 1.4 days/decade. The number of cold days (TX10p) and cold nights (TN10p) decreased by 2.9 and 3.4 days/decade. The average temperature of the hottest nights (TXn) and the diurnal temperature range (DTR) were increased by 0.10 and 0.30 °C/decade. The results indicated an increasing tendency of dry and warm weather in the Himalayan region of Pakistan, which could have adverse consequences for water resources, agriculture, and disaster management in the country. Therefore, it is essential to prioritize the implementation of localized adaptation techniques in order to enhance sustainable climate resilience and effectively address the emerging climate challenges faced by these mountainous regions.

The climate in Africa is very diverse ranging from tropical rainforest to deserts. Also, East Africa is covered by different climate zones and is very dry compared to other tropical regions. This is owed to various large-scale drivers, such as the complex topography, large water bodies such as Lake Victoria and vicinity to the Indian Ocean. The southern part of East Africa is characterized by two rainy seasons, which are separated by dry periods. The long rains from March to May feature more continuous precipitation, while the short rains from October to November show high interannual variability with days of high precipitation intensities and drier intervals.The CMIP5 and CMIP6 models project a general wetting of East Africa in the future, with a high model agreement. To obtain a better understanding of what this means for extreme precipitation and changes in the hydrological cycle we performed three different regional downscaling simulations using WRF: one for the present period from 1981–2010, and two for the end of the century (2071–2100). The latter two simulations are driven by, the RCP2.6 and the RCP8.5 scenarios, and the respective global forcing fields are based on CESM model runs. The regional model covers four different domains, whereby the first extends from the Sahara down to Madagascar with 27 km horizontal resolution, the second domain focuses on East Africa with 9 km resolution, the third domain at 3 km resolution zooms into the western part of Kenya, covering land with complex topography, and the last domain centers on Mount Kenya and surroundings at 1 km resolution.Preliminary results show that the rainy seasons are difficult to capture by WRF, when driven by a global climate model. This might be related to the fact that some of the atmospheric circulation is misrepresented in the global model and cannot be corrected by the regional model dynamics. While the long rains are underestimated in the present compared to a downscaling of ERA5, the short rains show an overestimation. A sensitivity study with adjusted SSTs to overcome some of the circulation issues in the global climate model only weakly improves the results. The projections for the future show an increase in extreme precipitation days, but also in the extreme daily precipitation amounts compared to present extreme (p99) precipitation. While the rainy seasons are projected to be more intense, the dry seasons tend to become drier, leaving some months without precipitation at all. The results further suggest that the extreme precipitation events do not differ for the RCP2.6 and RCP8.5. Thus, extreme precipitation events in Kenya might be limited by an upper bound, but this is subject of ongoing research.

Changes in precipitation extremes in Romania

BackgroundSeveral studies have investigated the association between asthma exacerbations and exposures to ambient temperature and precipitation. However, limited data exists regarding how extreme events, projected to grow in frequency, intensity, and duration in the future in response to our changing climate, will impact the risk of hospitalization for asthma. The objective of our study was to quantify the association between frequency of extreme heat and precipitation events and increased risk of hospitalization for asthma in Maryland between 2000 and 2012.MethodsWe used a time-stratified case-crossover design to examine the association between exposure to extreme heat and precipitation events and risk of hospitalization for asthma (ICD-9 code 493, n = 115,923).ResultsOccurrence of extreme heat events in Maryland increased the risk of same day hospitalization for asthma (lag 0) by 3 % (Odds Ratio (OR): 1.03, 95 % Confidence Interval (CI): 1.00, 1.07), with a considerably higher risk observed for extreme heat events that occur during summer months (OR: 1.23, 95 % CI: 1.15, 1.33). Likewise, summertime extreme precipitation events increased the risk of hospitalization for asthma by 11 % in Maryland (OR: 1.11, 95 % CI: 1.06, 1.17). Across age groups, increase in risk for asthma hospitalization from exposure to extreme heat event during the summer months was most pronounced among youth and adults, while those related to extreme precipitation event was highest among ≤4 year olds.ConclusionExposure to extreme heat and extreme precipitation events, particularly during summertime, is associated with increased risk of hospitalization for asthma in Maryland. Our results suggest that projected increases in frequency of extreme heat and precipitation event will have significant impact on public health.Electronic supplementary materialThe online version of this article (doi:10.1186/s12940-016-0142-z) contains supplementary material, which is available to authorized users.

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.

Extreme precipitation events can trigger many natural disasters like floods, mudslides, and landslides. Understanding historical changes in extreme precipitation is critical for disaster prevention and risk assessment. The Mekong River Basin (MB) is vulnerable to natural disasters related to extreme precipitation. In the past ten years, the MB has experienced some destructive extreme precipitation events. Our concern is whether the historical extreme precipitation events in the MB have increased in a warming climate. This study investigates the spatiotemporal changes in extreme precipitation in the MB from 1951 to 2015 using a high-quality precipitation product and eight indices of extreme precipitation. These indices consistently indicate that the trend in extreme precipitation in the Upper Mekong Basin (UMB) is opposite to that in the Lower Mekong Basin (LMB). Extreme precipitation has generally decreased in the UMB but increased in the LMB. The areas with significant increasing extreme precipitation are mainly located in Laos, Vietnam, and Cambodia. The areas with a statistically significant decline in extreme precipitation primarily occur in the Lancang (China’s section of the Mekong river) and Thailand. Also, the magnitude of changes in extreme precipitation is significantly larger in the LMB than that in the UMB, which potentially increases flooding risks in the LMB. The findings from this study are useful for guiding disaster-prevention efforts in the MB.

We discuss equilibrium changes in daily extreme surface air temperature and precipitation events in response to doubled atmospheric CO2, simulated in an ensemble of 53 versions of HadSM3, consisting of the HadAM3 atmospheric general circulation model (GCM) coupled to a mixed layer ocean. By virtue of its size and design, the ensemble, which samples uncertainty arising from the parameterisation of atmospheric physical processes and the effects of natural variability, provides a first opportunity to quantify the robustness of predictions of changes in extremes obtained from GCM simulations. Changes in extremes are quantified by calculating the frequency of exceedance of a fixed threshold in the 2 × CO2 simulation relative to the 1 × CO2 simulation. The ensemble-mean value of this relative frequency provides a best estimate of the expected change while the range of values across the ensemble provides a measure of the associated uncertainty. For example, when the extreme threshold is defined as the 99th percentile of the 1 × CO2 distribution, the global-mean ensemble-mean relative frequency of extremely warm days is found to be 20 in January, and 28 in July, implying that events occurring on one day per hundred under present day conditions would typically occur on 20–30 days per hundred under 2 × CO2 conditons. However the ensemble range in the relative frequency is of similar magnitude to the ensemble-mean value, indicating considerable uncertainty in the magnitude of the increase. The relative frequencies in response to doubled CO2 become smaller as the threshold used to define the extreme event is reduced. For one variable (July maximum daily temperature) we investigate this simulated variation with threshold, showing that it can be quite well reproduced by assuming the response to doubling CO2 to be characterised simply as a uniform shift of a Gaussian distribution. Nevertheless, doubling CO2 does lead to changes in the shape of the daily distributions for both temperature and precipitation, but the effect of these changes on the relative frequency of extreme events is generally larger for precipitation. For example, around one-fifth of the globe exhibits ensemble-mean decreases in time-averaged precipitation accompanied by increases in the frequency of extremely wet days. The ensemble range of changes in precipitation extremes (relative to the ensemble mean of the changes) is typically larger than for temperature extremes, indicating greater uncertainty in the precipitation changes. In the global average, extremely wet days are predicted to become twice as common under 2 × CO2 conditions. We also consider changes in extreme seasons, finding that simulated increases in the frequency of extremely warm or wet seasons under 2 × CO2 are almost everywhere greater than the corresponding increase in daily extremes. The smaller increases in the frequency of daily extremes is explained by the influence of day-to-day weather variability which inflates the variance of daily distributions compared to their seasonal counterparts.

Monitoring extreme climate events is of great importance, mainly due to increasingly severe impacts of extreme climate on nature and humanity. However, the characteristics of extreme climate events, especially extreme precipitation, frequently show complex variations in the context of climate change. Taking the middle and lower reaches of the Yangtze River (MLR-YR) in China as a case study, extreme daily precipitation during 1961–2012 was analyzed from the aspects of frequency and intensity. The changes in extreme daily precipitation in the MLR-YR were further attributed to several factors, including large-scale circulation, hydrologic engineering and local topography. Our analyses indicate that both frequency and intensity of the extreme daily precipitation in the MLR-YR showed overall increasing trends from 1961 to 2012. The increase could be associated with weakened East Asian summer monsoon in past decades. In addition, inverse trends could also be found locally between the frequency and the intensity. For instance, extreme precipitation intensity revealed an enhanced trend in the western part of the middle reach of the Yangtze River, while extreme precipitation frequency showed decreasing trends in this region. These phenomena could be associated with the effects of some local factors (e.g., lake regulation, hydropower engineering, topography). Our study highlights the important role of local factors on extreme precipitation changes.

Extreme precipitation events are a major cause of economic damage and disruption, and need to be addressed for increasing resilience to a changing climate, particularly at the local scale. Practitioners typically want to understand local changes at spatial scales much smaller than the native resolution of most Global Climate Models, for which downscaling techniques are used to translate planetary-to-regional scale change information to local scales. However, users of statistically downscaled outputs should be aware that how the observational data used to train the statistical models is constructed determines key properties of the downscaled solutions. Specifically for one such downscaling approach, when considering seasonal return values of extreme daily precipitation, we find that the Localized Constructed Analogs (LOCA) method produces a significant low bias in return values due to choices made in building the observational data set used to train LOCA. The LOCA low biases in daily extremes are consistent across event extremity, but do not degrade the overall performance of LOCA-derived changes in extreme daily precipitation. We show that the low (negative) bias in daily extremes is a function of a time-of-day adjustment applied to the training data and the manner of gridding daily precipitation data. The effects of these choices are likely to affect other downscaling methods trained with observations made in the same way. The results developed here show that efforts to improve resilience at the local level using extreme precipitation projections can benefit from using products specifically created to properly capture the statistics of extreme daily precipitation events.

Based on daily measured data from 25 stations in Xinjiang Province from 1963 to 2017, we discuss the statistical characteristics, linear trends, and temporal concentration of slight precipitation (SP) and extreme precipitation (EP) events, and consider relationships between SP and EP events and daily mean temperature. The results show that SP events contribute strongly to the total annual number of wet days, and that EP events contribute strongly to the total annual precipitation amount. In consist with the decrease in SP events and the increase in EP events over the 55-year period, the contribution of SP events to total annual number of wet days has decreased significantly while the contribution of EP events to total annual precipitation amount has increased significantly. SP event usually distributes through most months of the year, whereas EP event usually concentrates in summer (JJA). Influenced by the negative trends for SP events frequency and positive trends of EP events frequency during recent decades, the concentration degree for SP and EP events have significantly increased and decreased, respectively. Distinct differences are found between the relationships of SP events and EP events to daily mean temperature. The daily mean temperature recorded at the stations in Northern Xinjiang on days with SP events was between –35°C and +34°C, and for EP events ranged from –21°C to +30°C. Regionally averaged curves for the change in SP and EP event frequency with temperature have bimodal and unimodal distributions, respectively. Trends for daily mean temperatures and for the frequency of SP events at different temperatures agree well over nearly the entire temperature range, while trends for daily mean temperatures and for the frequency of EP events at different temperatures are not always consistent. These results will help to improve our understanding of the characteristics and variability of precipitation in arid regions within the context of climate warming.