Trends In Precipitation Extremes Research Articles

Influence of teleconnections on observations and projections of hydroclimatic extremes caused by tropical cyclones in the arid climate of Baja California Sur

This study focuses on identifying modulations by large-scale synoptic, inter-annual, and decadal oscillations on the extreme rainfall in the state of Baja California Sur, and provides statistical models to forecast future evolution. The region is arid, with 70% of precipitation from July to October, and is affected by tropical systems that may lead to moderate and even intense precipitation. Seven clusters were obtained using the Ward method applied to quality-controlled climatological data from 1950 to 2014. Normalized extreme precipitation (95th percentile) shows an overall increase in the last decades (1995-2004 and 2005-2014), with total values much larger than in any of the previous 50 years. Multivariate linear models (MLMs) were developed based on indices for the Pacific Decadal Oscillation (PDO) and El Niño-Southern Oscillation (ENSO) in Region 3.4, which were shown to modulate extreme precipitation. The MLM based on PDO, ENSO, and the fraction of tropical cyclones (TC) within a radius of 300 km to the peninsula (M4), has a better correlation with observed rainfall than the historical simulations of the Coupled-Model Inter-comparison Project version 5 (CMIP5) models; moreover, M4 outperforms all other MLMs in six of the seven clusters. Projections were evaluated based on the MLMs and CMIP5 simulations under scenarios RCP4.5 and RCP8.5 for mid- and long-term horizons. Model M4 projects more extreme events than CMIP5, and all MLM projects negative trends in extreme precipitation from 2041 to 2100 under RCP8.5. This study provides valuable information on future extreme precipitation in an arid region in the presence of steep topography, which could result in potential damage to ecosystems and infrastructure.

ANALYSIS OF CLIMATE CHANGE EFFECT ON EXTREME PRECIPITATION EVENT IN CONSTANTINE ALGERIA

Extreme precipitation events are critical climatic indicators that offer substantial insights into climate change and its variability. This study aims to investigate whether climate change has impacted precipitation frequencies in the Constantine region of Algeria, known for its semi-arid climate with hot-dry summers and cold-wet winters. Temporal variations of monthly air temperature and precipitation were analyzed from 1981 to 2014. Statistical analysis identified a threshold for estimating monthly extreme precipitation during the period from 1981 to 2005 using the Gumbel distribution method. Additionally, a climatic projection of precipitation for return periods of 50 (t = 50) and 100 (t = 100) years was conducted to forecast extreme precipitation values in the future. The results indicate a gradual increase in precipitation levels during the study period, with values generally remaining below extreme thresholds. This suggests no significant escalation in the occurrence of extreme precipitation events. Furthermore, the findings highlight that climate change has had a more pronounced impact on altering air temperature than on influencing extreme precipitation trends.

Projected Changes in Mean and Extreme Precipitation over Northern Mexico

Abstract Northern Mexico is home to more than 32 million people and is of significant agricultural and economic importance for the country. The region includes three distinct hydroclimatic regions, all of which regularly experience severe dryness and flooding and are highly susceptible to future changes in precipitation. To date, little work has been done to characterize future trends in either mean or extreme precipitation over northern Mexico. To fill this gap, we investigate projected precipitation trends over the region in the NA-CORDEX ensemble of dynamically downscaled simulations. We first verify that these simulations accurately reproduce observed precipitation over northern Mexico, as derived from the Multi-Source Weighted-Ensemble Precipitation (MSWEP) product, demonstrating that the NA-CORDEX ensemble is appropriate for studying precipitation trends over the region. By the end of the century, simulations forced with a high-emissions scenario project that both mean and extreme precipitation will decrease to the west and increase to the east of the Sierra Madre highlands, decreasing the zonal gradient in precipitation. We also find that the North American monsoon, which is responsible for a substantial fraction of the precipitation over the region, is likely to start later and last approximately three weeks longer. The frequency of extreme precipitation events is expected to double throughout the region, exacerbating the flood risk for vulnerable communities in northern Mexico. Collectively, these results suggest that the extreme precipitation-related dangers that the region faces, such as flooding, will increase significantly by the end of the century, with implications for the agricultural sector, economy, and infrastructure. Significance Statement Northern Mexico regularly experiences severe flooding and its important agricultural sector can be heavily impacted by variations in precipitation. Using high-resolution climate model simulations that have been tested against observations, we find that these hydroclimate extremes are likely to be exacerbated in a warming climate; the dry (wet) season is projected to receive significantly less (more) precipitation (approximately ±10% by the end of the century). Simulations suggest that some of the changes in precipitation over the region can be related to the North American monsoon, with the monsoon starting later in the year and lasting several weeks longer. Our results also suggest that the frequency of extreme precipitation will increase, although this increase is smaller than that projected for other regions, with the strongest storms becoming 20% more frequent per degree of warming. These results suggest that this region may experience significant changes to its hydroclimate through the end of the century that will require significant resilience planning.

Contributions of Tropical Cyclones and Atmospheric Rivers to Extreme Precipitation Trends Over the Northeast US

AbstractThe Northeast United States (NEUS) has faced the most rapidly increasing occurrences of extreme precipitation within the US in the past few decades. Understanding the physics leading to long‐term trends in regional extreme precipitation is essential but the progress is limited partially by the horizontal resolution of climate models. The latest fully coupled 25‐km GFDL (Geophysical Fluid Dynamics Laboratory) SPEAR (Seamless system for Prediction and EArth system Research) simulations provide a good opportunity to study changes in regional extreme precipitation and the relevant physical processes. Here, we focus on the contributions of changes in synoptic‐scale events, including atmospheric rivers (AR) and tropical cyclone (TC)‐related events, to the trend of extreme precipitation in the fall season over the Northeast US in both the recent past and future projections using the 25‐km GFDL‐SPEAR. In observations, increasing extreme precipitation over the NEUS since the 1990s is mainly linked to TC‐related events, especially those undergoing extratropical transitions. In the future, both AR‐related and TC‐related extreme precipitation over the NEUS are projected to increase, even though the numbers of TCs in the North Atlantic are projected to decrease in the SPEAR simulations using the SSP5‐8.5 projection of future radiative forcing. Factors such as enhancing TC intensity, strengthening TC‐related precipitation, and/or westward shift in Atlantic TC tracks may offset the influence of declining Atlantic TC numbers in the model projections, leading to more frequent TC‐related extreme precipitation over the NEUS.

Extreme precipitation trends in Northeast China based on a non-stationary generalized extreme value model

AbstractNortheast China is the main food production base of China. Extreme precipitation (EP) events can seriously impact agricultural production and socioeconomics, but the understanding of EP in Northeast China is still limited. In this study, using the non-stationary generalized extreme value (GEV) model, we investigate the trend and potential risk of EP in Northeast China during 1959–2017, especially in early and mid-summer (periods of high frequency of EP). Then, the relationships between EP and large-scale circulation over Northeast China in early and mid-summer are analyzed separately. The EP in Northeast China mainly presents positive trends in early summer but negative trends in mid-summer. Meanwhile, the EP with all the return periods presents apparently increasing trends in early summer, corresponding to more frequent EP events. Nevertheless, in mid-summer, the EP with 2-year return period decreases with location parameter, and the EP with 20-year, 50-year, and 100-year return periods slightly increases with scale parameter. The EP with 2-year return period occurs frequently in Liaoning Province, while the EP with 100-year return period is more likely to occur in Jilin Province and Heilongjiang Province. Moreover, the increase of the EP in early summer is mainly influenced by the northeast cold vortex; the effect of cold air on the EP is stronger in mid-summer, giving a clear explanation why the EP in mid-summer does not increase significantly. Overall, the outcomes of this study would be beneficial for the disaster prevention and mitigation in Northeast China.

Analysis of The Occurrence of Extreme Events in The City of Rio de Janeiro/RJ

Objective: To investigate the trends of extreme rainfall and temperature indices in the city of Rio de Janeiro, as measures to assess climate change. Theoretical benchmark: Extreme climatic events have been observed more frequently than has become a concern all over the world, so the investigation of trends in extreme precipitation and temperature indices makes it necessary to enter how this dynamic in climatic conditions affects the city of Rio de Janeiro. Method: The methodology for assessing climate change will be used from the indicators defined by the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI) panel, but of the 27 indicators proposed by the panel, 12 indicators were used that were more adapted to the reality of the city of Rio de Janeiro, for the simulation of climate data, data from the stations of the National Institute of Meteorology (INMET) and for the simulation of the indicators in the RClimdex software. Daily data of 53 years of 19 (six) stations obtained from the historical series of the period between 1970 and 2023 were analyzed, for the precipitation indices: PRCPTOT, R10, R20, R95p and R99p, and for the temperature indices: TX90p, TN90p, TMAXmean, TMINmean and DTR. Results and conclusion: The results indicate a trend of decreasing rainfall of low rainfall and a significant increase of extreme rainfall, the data also show a decrease of thermal amplitude, with the increase of minimum temperatures and a moderate decrease of maximum temperatures. Implications of the research: The study in question presents internationally validated indicators that demonstrate how extreme events are intensifying in the city of Rio de Janeiro. Originality/value: The data demonstrated in this research are of extreme importance as a source of research for future works that address this theme, besides serving as a subsidy to decision makers to propose adaptive measures to the territory, in the face of the intensification of extreme events in the city of Rio de Janeiro.

Spatial Variation and Trend of Extreme Precipitation in Africa during 1981-2019 and Its Projected Changes at the End of 21<sup>st</sup> Century

Spatial Variation and Trend of Extreme Precipitation in Africa during 1981-2019 and Its Projected Changes at the End of 21<sup>st</sup> Century

Spatio‐temporal analysis of trends in annual maximum rainfall in the North‐West of Algeria: Comparative analysis of recent and old non‐parametric methods

AbstractThis article examines the spatial variability of extreme precipitation trends in northwestern Algeria (Macta) and compares the results obtained from the four recent and old non‐parametric methods. A dataset of annual maximum precipitation consisting of 41 observation years (1970–2010) and 41 rain gauges was used. The results of the four old and new methods used to detect trends, Mann–Kendall (MK), Bravais–Pearson (BP), Spearman (SR) and innovative trend analysis (ITA), show good agreement. They revealed that a decrease in the trend of annual maximum precipitation was detected during the first period (1970–1992) with −44% (MK), −61% (BP), −68% (SR) and −76% (ITA). On the other hand, in the second period (1993–2010), a total shift occurred in which a significant increase in annual maximum precipitation trends was observed with +63% (BP), +34% (MK and SR) and +93% (ITA). These results show the ability of ITA to detect partial trends that the other three tests do not allow. Our results allow decision‐makers to properly design adaptation strategies in the face of the intensification of these extreme events.

Patterns and Teleconnection Mechanisms of Extreme Precipitation in Ethiopia during 1990–2020

The occurrence of extreme precipitation events always leads to a mass of disasters. In this study, based on daily precipitation data from 20 meteorological stations in Ethiopia, we performed a detailed analysis of patterns and trends of ten extreme precipitation indices during 1990–2020. Our study revealed that different topographic conditions on the Ethiopian Plateau, Ethiopian savanna and Ethiopian desert resulted in great differences in patterns and trends of extreme precipitation. Notably, extreme precipitation intensity indices (Rx1day, Rx5day, SDII) and amount indices (R95pTOT) showed significant downward trends in the eastern desert (averagely −1.0 mm/year, −3.0 mm/year, −0.25 mm day−1/year, −6.0 mm/year) and upward trends in the northern plateau and southern savanna (averagely 0.3 mm/year, 0.4 mm/year, 0.05 mm day−1/year, 3.0 mm/year). These implied that extreme precipitation events decreased in the eastern desert and increased in the northern plateau and southern savanna during the past thirty years. Annual trends of the CDD index were upward (0.5 to 1.9 days/year) in most of Ethiopia while those of the CWD index were close to zero in most of Ethiopia, indicating that Ethiopia faced a longer duration of drought in the past thirty years. Moreover, we revealed that the local mean temperature, local mean precipitation, Southwest Asian summer monsoon and West African summer monsoon have significant impacts on the intensity, amount and duration of extreme precipitations in Ethiopia.

Climatological trends of mean and extreme daily precipitation in Arizona (USA)

Precipitation in Arizona, USA, represents a fundamental resource for the needs of agriculture, people, and the environment. However, due to the risk associated with flash flooding, extreme precipitation also constitutes a natural hazard. Available research on precipitation in Arizona has been limited in scope and focus and there currently exists no comprehensive assessment of statewide, historical, mean, and extreme precipitation. We use daily precipitation records from 43 Global Historical Climate Network daily (GHCNd) weather stations to examine trends in mean and extreme precipitation across Arizona from 1950 to 2020. We use a suite of standardized precipitation indices and explore the statistical significance of historical changes at the annual, monthly, and seasonal scales. Our analysis returns a motley collection of results displaying a great degree of spatial variability and sensitivity to the temporal scale of analysis. Mean total precipitation at the statewide scale underwent a small decreasing trend of 0.15 mm year−1, with considerable interannual variability being a dominant feature. The majority of stations experienced no statistically significant change in extreme precipitation at the annual scale. Monsoon season mean precipitation followed a similar pattern to annual means, with an overall reduction of 0.14 mm year−1 across the state. One fourth of stations, all located at elevations lower than 650 m, recorded decreases in monsoon precipitation intensity. Winter season analysis presents a different picture, displaying a positive statewide trend of 0.11 mm year−1 in mean precipitation. One tenth of stations recorded increases in extreme precipitation intensity and decreases in the number of consecutive dry days. Results of our observational analysis indicate a lack of a clear consensus on the climatological trends of mean/extreme precipitation in Arizona during the study period. Our findings are in contrast to those from other similarly arid areas across the world and highlight the role of regional differences in modulating the potential hydrometeorological impacts associated with climate change. However, while we do not find widespread, significant, modification in the spectrum of precipitation changes examined, the hydrologic system of the state has been – and will continue to be - impacted by the ongoing temperature increase associated with the buildup of greenhouse gases and continued population growth.

Are the magnitude and frequency of floods increasing in Iran due to climate change? Implications from a 50-year analysis

ABSTRACT The correlation between extreme precipitation and flood magnitude is still poorly understood because of the complex mechanisms controlling flood generation. In this study, we used 50 years of precipitation and streamflow data across Iran to analyse the spatial distribution, slope, and significance of long-term trends in extreme precipitation compared to the spatial distribution of long-term trends for flood magnitude and frequency. Despite the decreasing trend of extreme precipitation in 60% of Iran’s sub-basins, the flood magnitude showed an increasing trend. In particular, the number of flooding days with a return period of 25~50 years and >50 years in 2010s has increased by 1.3 and 2.2 times, respectively, compared to that in 2000s. We attributed the above contrasting relationship between extreme precipitation and flood magnitude to the influence of an increase in short-duration extreme precipitations, extensive land use and land cover change, and reduced soil infiltration due to long-term droughts.

Predictive Study on Extreme Precipitation Trends in Henan and Their Impact on Population Exposure

This study employs precipitation data sets from historical trials on 20 CMIP6 global climate models and four shared socioeconomic pathway scenario trials (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) to predict trends in extreme precipitation changes in Henan Province quantitatively, while ascertaining the risk of population exposure to extreme precipitation in this area. The capacity of the CMIP6 models to simulate extreme precipitation indices from 1985 to 2014 is assessed using CN05.1 daily precipitation observational data. The correlation coefficients of the multi-model ensemble median’s simulation of the extreme precipitation indices are approximately 0.8, with a standard deviation ratio closer to 1 compared with the single models, demonstrating superior modeling ability. Analyses using the multi-model ensemble median demonstrate an overall increase in the total amount, frequency, and intensity of extreme precipitation in Henan throughout this century, particularly in its southern regions; in the mid-century high-emission scenario (SSP5-8.5), the maximum increase in annual total precipitation exceeds 150 mm, and it can be over 250 mm in the late-century period. For the entire province, the maximum five-day precipitation increase relative to the historical period is nearly 25 mm in the late-century SSP5-8.5 scenario. The spatiotemporal concentration of precipitation will significantly increase, heightening the risk of flood disasters. Comparative analysis reveals that, under the same population prediction, the total population exposure will be higher in high radiative forcing scenarios than in low radiative forcing scenarios, especially in Kaifeng City, where the total population exposure in SSP1 and SSP5-8.5 exceeds that in SSP1-2.6 by 2 million person-days. However, in the same radiative forcing scenario, the total population exposure in the development pathway dominated by traditional fossil fuels (SSP5) will not be significantly higher than that in the sustainable development pathway (SSP1), indicating that population activity in this century will not be the main contributor to changes in total exposure. Overall, for Henan, in the same population forecast scenario, population exposure to extreme precipitation will gradually rise with global warming.

Linking Historical and Projected Trends in Extreme Precipitation with Cumulative Carbon Dioxide Emissions

Extreme weather events are expected to increase in frequency and intensity in response to higher global temperatures, augmenting societal exposure to these events. While the magnitude of projected changes in extremes varies considerably among future emission scenarios, a large part of this uncertainty is driven by the choice of scenario, rather than by the climate response to a particular emission scenario. A growing body of research has identified robust linear relationships between climate changes and cumulative carbon emissions; for global average temperature change, this relationship is known as the transient climate response to cumulative carbon emissions (TCRE). Extensions of the TCRE framework to other variables, such as regional and seasonal temperature and precipitation changes, have also shown to be effective, raising the possibility that changes in weather extremes could be linked to cumulative carbon dioxide (CO2) emissions. Here, we estimate changes in historical and projected trends in one-day (Rx1day) and five-day maximum precipitation (Rx5day) events as a function of cumulative carbon emissions across a range of future emission scenarios and global climate models. Our results show that median Rx1day and Rx5day generally increases linearly with increasing cumulative emissions, consistent with studies that have previously employed the TCRE framework to estimate changes in precipitation extremes, as well as other climate indicators. Overall, we show that a linear response to cumulative CO2 emissions is a good approximation for both historical and future trends in precipitation extremes.

An increasing trend in daily monsoon precipitation extreme indices over Pakistan and its relationship with atmospheric circulations

This study assessed spatiotemporal trends in daily monsoon precipitation extremes at seasonal and sub-seasonal scales (June, July, August, and September) and their links with atmospheric circulations over Pakistan. The study used observed precipitation data from fifty in-situ stations and reanalysis products from the European Centre for Medium-Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction/the National Center for Atmospheric Research (NCEP/NCAR) during 1981–2018. A suite of seven extreme precipitation indices and non-parametric statistical techniques were used to infer trends in the frequency and intensity of extreme precipitation indices. An increase in frequency and intensity of overall extreme indices was evident, with a maximum tendency in the country’s northwestern (z-score=>2.5), central, and eastern (z-score > 4) monsoon-dominant parts. The northern and southwestern parts of the country exhibited a slight decrease (z-score <–2) in frequency and intensity. The Sen’s Slope estimator (SSE) shows an increase in western parts (0.20 days) indicating a shift in the maxima of the monsoon precipitation. The regional precipitation shows an increase in wet days (R1 mm) with higher values of mMK (3.71) and SSE (0.3) in region 2 Similar results of moderate regional increase are evident for extreme indices except regions 1 and 3. The extreme 1-day maximum precipitation increased in region 3 (mMK: 1.39, SSE: 2.32). The extremely wet days (R99p TOT) precipitation has a moderate increase in all regions with a decrease in region 1. The temporal mutations showed dynamic changes, clearly reflecting the country’s historical extreme events. The frequency and intensity of precipitation extremes negatively correlated with the altitude (R = −0.00039). The probability density function (PDF) showed a significant increase in the density during June and September with a probabilistic positive shift during July and August. The intensified mid-latitude westerlies and subtropical zonal easterlies teleconnections, strengthening of the monsoon trough, and land-ocean thermal contrast are the potential drivers of the increasing trend in precipitation extremes. The current study could serve as a benchmark for future researchers and policymakers to devise effective mitigation strategies for sustainable development.

Dynamic and thermodynamic drivers of rainfall trends at the City of Buenos Aires, Argentina

AbstractSoutheastern South America (SESA) experienced some of the largest positive trends in total and extreme precipitation of the Southern Hemisphere during the last decades. The City of Buenos Aires, the second largest mega‐city of SESA, has been particularly hard‐hit by these trends due to its flat topography and poor natural drainage. Recent studies suggest that these precipitation extremes may exacerbate even further under global warming, but the physical mechanisms responsible for such events have not been documented for this region so far. This study quantifies the relative contributions of dynamics (atmospheric fronts) and thermodynamics (vertical stability) on the observed variations and trends of daily, seasonal and annual precipitation over the City of Buenos Aires between 1981 and 2020 by splitting the precipitation events into convective and stratiform. Results show that the relative contributions from dynamics and thermodynamics depend on the season under consideration: the positive trends in summer precipitation have been favoured by a net increase in vertical instability with a negligible contribution from dynamics, while the increased frequency of fronts in autumn and winter, when no changes in vertical instability have been observed, has contributed to the higher frequency of cold‐season convective events.

The Precipitation‐Recycling Process Enhanced Extreme Precipitation in Xinjiang, China

AbstractThe amount, frequency and intensity of extreme precipitation over Xinjiang have increased dramatically under the wetting trend in Northwest China, but long‐term trends in the precipitation‐recycling process remain largely unexplored. Based on dynamic recycling model and MERRA2 reanalysis, we revealed a mean recycling ratio for extreme precipitation in Xinjiang of 42.3% with a growth rate of 2.3% decade−1 during 1982–2019. The increasing trend of extreme precipitation was almost equally attributed to increased recycling precipitation (49%) and external precipitation (51%). The extreme precipitation in Xinjiang exhibited two peak centers, the Tianshan Mountains region (TS) and Kunlun Mountains region (KL), highlighting variations in the water cycle. Specifically, the external cycle predominated the increased extreme precipitation in TS (61%), while the recycling process mainly influenced the increase in KL (67%) due to markedly enhanced evapotranspiration. Moisture source attribution further proved the crucial role of evapotranspiration from Xinjiang and its vicinity in extreme precipitation.

Trends in Extreme Precipitation Indices in Northwest Ethiopia: Comparative Analysis Using the Mann–Kendall and Innovative Trend Analysis Methods

This study analyzed long-term extreme precipitation indices using 4 × 4 km gridded data obtained from the National Meteorological Agency of Ethiopia between 1981 and 2018. The study examined trends in extreme precipitation over three districts (Lay Gayint, Tach Gayint, and Simada) in the northwestern highlands of Ethiopia. Innovative Trend Analysis (ITA) and Mann–Kendall (MK) trend tests were used to study extreme precipitation trends. Based on the ITA result, the calculated values of nine indices (90% of the analyzed indices) showed significant increasing trends (p < 0.01) in Lay Gayint. In Tach Gayint, 70% (seven indices) showed significantly increasing trends at p < 0.01. On the other hand, 60% of the extreme indices showed significant downward trends (p < 0.01) in Simada. The MK test revealed that 30% of the extreme indices had significantly increasing trends (p < 0.01) in Lay Gayint. In Tach Gayint, 30% of the extreme indices showed significant increasing trends at p < 0.05, while 10% of the extreme indices exhibited significant increasing trends at p < 0.01. In Simada, 20% of the extreme indices showed significant increasing trends at p < 0.05. Overall, the results showed that the ITA method can identify a variety of significant trends that the MK test misses.

Changes in mean and extreme homogeneous precipitation in China during 1960–2020

This study aims to explore the observed national and regional changes in the seasonal mean and extreme precipitation in mainland China between 1960 and 2020 using data from 678 stations. Tests of homogeneity (e.g. standard normal homogeneity test, Pettitt's test and Buishand range test) are applied to identify homogeneous stations for the trend analysis. The non-parametric Mann-Kendall test and a modified Theil-Sen slope estimator were then used to examine changes in the precipitation characteristics. Our results show that despite a decreasing trend in the frequency of wet days, the mean precipitation has actually increased. Extreme precipitation has also increased, and in many locations, at greater rates than those of the mean. This is principally due to a greater rate of increase per degree of warming, of 8% for extreme precipitation compared to 7% for the mean. However, considerably regional and seasonal variability has been seen in the trends. Mean and extreme precipitation trends are positive throughout in western China for all seasons, but they vary in eastern China. Mean precipitation increased slightly in the southeast but decreased in the northeast of the country. Extreme precipitation increased in both regions, but the increases were greater in the southeast. Trends, additionally, also differed within regions, especially over eastern China. In southeast China, precipitation increased in the east and decreased in the west. In northeast China, precipitation increased in the north and decreased in the south. Using a multiple regression model, we found that changes during summer precipitation clearly dominate the overall annual changes in most regions. Most long-term changes over eastern China appear to be linked to those of the East-Asian and South-Asian Summer Monsoons.

More extreme precipitation over the Yangtze River Basin, China: Insights from historical and projected perspectives

Detecting and predicting extreme weather events are important for the risk management, human health and social economy. Here, we comprehensively investigate the historical and projected variations of extreme precipitation events in the Yangtze River Basin (YRB) using the observational data and the multi-model ensemble data under SSP245 and SSP585 scenarios provided by the newest round of the Coupled Model Inter-comparison Project phase 6 (CMIP6). Five extreme precipitation indices including RX1-day, RX5-day, R50mm, SDII, and R95pTOT are analyzed in this study. The observational results reveal that all extreme precipitation indices (except for RX5-day) show significant positive trends during 1961–2017. Spatially, the trends of extreme precipitation vary across the YRB, and the greater upward trends are observed in the eastern YRB (except for R50mm). The results from model simulations indicate that extreme precipitation events during 2023–2100 are projected to increase significantly relative to that in the reference period (1986–2005), and the average increase of the five extreme precipitation indices over the whole region reach approximately 20 and 35% under the SSP245 and SSP585 scenarios, respectively. Similar spatial distributions between SSP245 and SSP585 are observed, with more pronounced increases of the projected changes in the central and eastern YRB. Notably, the population exposure to extreme precipitation is also assessed and the results reveal that it would increase by nearly 4 × 108 people even though the population is projected to reduce sharply in the future. This study provides a comprehensive understanding of the historical and projected extreme precipitation variation across the YRB based on a series of analysis method, which is an important reference for the risk management and development of mitigation strategies.

Evaluation of CMIP6 Models and Multi-Model Ensemble for Extreme Precipitation over Arid Central Asia

Simulated historical extreme precipitation is evaluated for Coupled Model Intercomparison Project Phase 6 (CMIP6) models using precipitation indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). The indices of 33 Global Circulation Models (GCMs) are evaluated against corresponding indices with observations from the Global Climate Center Precipitation Dataset (GPCC V2020) over five sub-regions across Arid Central Asia (ACA), using the Taylor diagram, interannual variability skill score (IVS) and comprehensive rating index (MR). Moreover, we compare four multi-model ensemble approaches: arithmetic average multi-model ensemble (AMME), median multi-model ensemble (MME), pattern performance-based multi-model ensemble (MM-PERF) and independence weighted mean (IWM). The results show that CMIP6 models have a certain ability to simulate the spatial distribution of extreme precipitation in ACA and the best ability to simulate simple daily intensity (SDII), but it is difficult to capture the spatial bias of consecutive wet days (CWD). Almost all models represent different degrees of wet bias in the southern Xinjiang (SX). Most GCMs are generally able to capture extreme precipitation trends, but to reproduce the performance of interannual variability for heavy precipitation days (R10mm), SDII and CWD need to be improved. The four multi-model ensemble methods can reduce the internal system bias and variability within individual models and outperform individual models in capturing the spatial and temporal variability of extreme precipitation. However, significant uncertainties remain in the simulation of extreme precipitation indices in SX and Tianshan Mountain (TM). Comparatively, IWM simulations of extreme precipitation in the ACA and its sub-regions are more reliable. The results of this study can provide a reference for the application of GCMs in ACA and sub-regions and can also reduce the uncertainty and increase the reliability of future climate change projections through the optimal multi-model ensemble method.