Trends In Precipitation Extremes Research Articles

An analysis of observed and predicted extreme heat and precipitation trends across four pulse producing regions in North America: North Dakota, Montana, Saskatchewan, and Northeastern United States

Abstract The consumption of plant-based proteins in leu of animal proteins is the most important dietary shift that would be needed to keep the world under 2 C of warming, and this shift would require a dramatic increase in the percentage of cropland devoted to nuts and pulses (Peters et al. 2016). As the demand for plant-based proteins, like pulse crops, continues to grow, it is critical to understand the impact of climate change on crop production. In this paper, we study two climate-related stressors for pulse production in North America: extreme heat and excess moisture during harvest. Pulses must be dried on the plant before harvest, requiring a 7-day dry spell before harvest or the use of Roundup (glyphosate) to kill the plants quickly. However, little is known about the changes in frequency of hot extremes or dry spells during harvest in pulse-growing regions. We analyze climate trends using the Unprecedented Simulated Extreme Ensemble (UNSEEN) method and an analysis of the Coupled Model Intercomparison Project (CMIP6) in four pulse growing regions across North America: Montana, North Dakota, Saskatchewan, and the Northeast USA. We find that temperature extremes have increased in all regions, with extreme events 3-4 times more likely today than in 1981, increasing the risk of crop loss. August and September rainfall during the harvest months has been decreasing in the Midwestern regions and it is projected to continue to decrease in the future; however, the likelihood of a wet August in the Northeast has nearly doubled. Even with this drying trend, farmers cannot assume that they will have a 7-day consecutive dry spell that would enable natural drying of pulses without synthetic drying agents like glyphosate. Future expansion of pulse production should incorporate adaptation measures to manage extreme heat and the potential for rain events during harvest.

Does ERA5-Land Effectively Capture Extreme Precipitation in the Yellow River Basin?

ERA5-Land is a valuable reanalysis data resource that provides near-real-time, high-resolution, multivariable data for various applications. Using daily precipitation data from 301 meteorological stations in the Yellow River Basin from 2001 to 2013 as benchmark data, this study aims to evaluate ERA5-Land’s capability of monitoring extreme precipitation. The evaluation study is conducted from three perspectives: precipitation amount, extreme precipitation indices, and characteristics of extreme precipitation events. The results show that ERA5-Land can effectively capture the spatial distribution patterns and temporal trends in precipitation and extreme precipitation; however, it also exhibits significant overestimation and underestimation errors. ERA5-Land significantly overestimates total precipitation and indices for heavy precipitation and extreme precipitation (R95pTOT and R99pTOT), with errors reaching up to 89%, but underestimates the Simple Daily Intensity Index (SDII). ERA5-Land tends to overestimate the duration of extreme precipitation events but slightly underestimates the total and average precipitation of these events. These findings provide a scientific reference for optimizing the ERA5-Land algorithm and for users in selecting data.

The analysis of the long-term trend of extreme precipitation and discharge in Burundi

The analysis of the long-term trend of extreme precipitation and discharge in Burundi

Spatial and temporal analysis and trends of extreme precipitation over the Mississippi River Basin, USA during 1988–2017

Study regionMississippi River Basin. Study focusUsing daily precipitation records of 769 meteorological stations over the Mississippi River Basin (MRB), the spatial-temporal variability and trend of nine extreme precipitation indices were estimated and statistically assessed using the Mann-Kendall test. Factors likely to influence the spatial pattern and trends of precipitation extremes indices were also checked. New hydrological insights for the regionThe spatial pattern of the extreme precipitation indices exhibits a southeast to Northwest dipole, with the maximum values recorded over the southeastern part of the domain (exception being for Consecutive Dry Days, CDD which shows otherwise) driven by the southerly moisture transport toward the southeast. The spatial pattern of the extreme precipitation is controlled by the topography. The results also show that, on average, almost all the indices (except CDD) exhibit an increasing trend. The total wet day precipitation exhibits a significant increasing trend. Spatially, most of the significant increasing (decreasing) trends of the extreme's precipitation-except CDD- are located over the Upper (South) MRB where there is a significant sign toward cooling (warming) conditions. This supports the view that changing climate towards warming (cooling) conditions is significantly affecting precipitations extremes over the MRB. The relationships between large-scale teleconnections and extreme precipitation show that Pacific North America significantly increases (decreases) frequency and intensity indices over the Northwest (southeast) MRB, whereas the Pacific Decadal Oscillation does increase the frequency and intensity indices over the southeast. El Niño Southern Oscillation significantly increases the frequency and intensity indices over the entire MRB, with consequences to infrastructure failures, increasing vulnerable populations, risk zones and relocations populations.

Association of precipitation extremes and crops production and projecting future extremes using machine learning approaches with CMIP6 data.

Precipitation extremes have surged in frequency and duration in recent decades, significantly impacting various sectors, including agriculture, water resources, energy, and public health worldwide. Pakistan, being highly susceptible to climate change and extremes, has experienced adverse events in recent times, emphasizing the need for a comprehensive investigation into the relationship between precipitation extremes and crops production. This study focuses on assessing the association between precipitation extremes on crops production, with a particular emphasis on the Punjab province, a crucial region for the country's food production. The initial phase of the study involved exploring the associations between precipitation extremes and crops production for the duration of 1980-2014. Notably, certain precipitation extremes, such as maximum CDDs (consecutive dry days), R99p (extreme precipitation events), PRCPTOT (precipitation total) and SDII (simple daily intensity index) exhibited strong correlations with the production of key crops like wheat, rice, garlic, dates, moong, and masoor. In the subsequent step, four machine learning (ML) algorithms were trained and tested using observed daily climate data (including maximum and minimum temperatures and precipitation) alongside model reference data (1985-2014) as predictors. Gradient boosting machine (GBM) was selected for its superior performance and employed to project precipitation extremes for three distinct future periods (F1: 2025-2049, F2: 2050-2074, F3: 2075-2099) under the SSP2-4.5 and SSP5-8.5 derived from the CMIP6 (Coupled Model Intercomparison Project Phase 6) archive. The projection results indicated an increasing and decreasing trend in CWDs (maximum consecutive wet days) and CDDs, respectively, at various meteorological stations. Furthermore, R10mm (the number of days with precipitation equal to or exceeding 10mm) and R25mm displayed an overall increasing trend at most of the stations, though some exhibited a decreasing trend. These trends in precipitation extremes have potential consequences, including the risk of flash floods and damage to agriculture and infrastructure. However, the study emphasizes that with proper planning, adaptation measures, and mitigation strategies, the potential losses and damages can be significantly minimized in the future.

Analysis of Change in Summer Extreme Precipitation in Southwest China and Human Adaptation

This study analyzed the change in and mechanisms of summer extreme precipitation in Southwest China (SWC) during 1979–2021. The trend in summer extreme precipitation showed an evident interdecadal mutation in the late 1990s; it decreased during 1979–1996 (P1) and increased during 1997–2021 (P2). It is observed that the moisture flux in SWC is more abundant in P2 than in P1. The South Asian high (SAH) and western Pacific subtropical high (WPSH) contributed to the change in extreme precipitation in SWC. Both the SAH and WPSH weakened in 1979–1996 and enhanced in 1997–2021. The enhanced SAH and WPSH are conducive to forming updrafts in SWC and transporting moisture from the Bay of Bengal (BOB) and South China Sea (SCS) into SWC. Further research found that the causes for the interdecadal variation of the SAH and WPSH are the anomalies of sensible heat flux (SSH) over the Tibetan Plateau (TP) and sea surface temperature (SST) in the tropical western Pacific–Indian Oceans. The SSH is the main energy source of troposphere air and an essential component of the surface heat balance because it can maintain the intensity and influence range of the SAH. The increasing SST stimulated strong upward motion and thus maintained the strength of the WPSH, which also made the WPSH extend westward into mainland China. This study also summarized local human adaptation to climate change. The use of advanced science and technology to improve monitoring and forecasting ability is an important measure for human society to adapt to climate change. At the same time, increasing the participation of individuals and social organizations is also an indispensable way to increase human resilience to climate change.

Historical and future extreme climate events in highly vulnerable small Caribbean Islands

Small Caribbean islands are on the frontline of climate change because of sea level rise, extreme rainfall and temperature events, and heavy hurricanes. The Archipelago of San Andrés, Providencia, and Santa Catalina (SAI), are Caribbean islands belonging to Colombia and declared a Biosphere Reserve by UNESCO. SAI is highly vulnerable to climate change impacts but no hydroclimatological study quantified the extreme climatic changes yet. This study analyzes historical (1960s-2020, 7 stations) and future (2071–2100, CMIP6 multi-model ensemble, for four scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) trends in mean and extreme precipitation and temperature duration, frequency, and intensity. We find that heatwaves have more than tripled in frequency and doubled their maximum duration since the end of the ‘80 s. Precipitation is historically reduced by 5%, with a reduction recorded in 5 stations and an increase in 2, while extreme rainfall events significantly increased in frequency and intensity in most stations. The hotter-and-drier climate is amplified in the future for all scenarios, with much drier extremes (e.g., -0.5─-17% wet days, +8%─30% consecutive dry days, and +60%─89% in hot days). Although we show that hurricanes Categories IV and V near SAI (< 600 km) more than doubled since the’60 s, only a small fraction of extreme rainfall in the archipelago is associated with hurricanes or tropical storms. La Niña events also have no substantial influence on extreme precipitation. Interestingly, opposite and heterogeneous historical extreme rainfall trends are found across such small territory (< 30 km2). Thus, downscaled hydrometeorological data and model simulations are essential to investigate future extreme climatic events and strengthen small Caribbean islands' climate change adaptation efforts.

Past and future joint return period of precipitation extremes over South Asia and Southeast Asia

Climate change is one of the major reasons for the increased intensity and frequency of precipitation extremes in tropical regions. This will have a significant impact on underdeveloped countries in South Asia and Southeast Asia. Therefore, this study analyzes changes in spatiotemporal patterns and the joint behavior of precipitation extremes across South Asian and Southeast Asian countries for the historical period (1975 to 2014) and future periods (2021–2060 (F1) and 2061–2100 (F2)). This study develops bias-corrected precipitation data and ranks General Circulation Models (GCMs) using the Empirical Quantile Mapping method and TOPSIS method, respectively. A multi-model ensemble of precipitation extremes is created using the top five GCMs. The Mann Kendall test is used to analyze trends in precipitation extremes. Joint probabilistic analysis is also conducted for different combinations of ETCCDI precipitation-based indices using Archimedes and Elliptical copulas. The results of the trend analysis indicate significant positive trends for R20mm (19.26%), R95pTOT (18.40%), Rx5Day (11.53%), and CWD (10.46%), while CDD (5.07%) shows a significant negative trend across the study area during historical period (1975–2014). The results of R20mm, R95pTOT, and Rx5Day under SSP585 shows almost 19 to 39% of area comes under significant positive trend during the F1 period. This becomes more evident in F2, with trends under SSP585 rising between 32% and 61%. The high-emissions scenario SSP585 reveals an increase in these positive trends compared to SSP126 in both the future periods (F1 and F2). These results indicating a noticeable rise in extreme precipitation events. The analysis of changes in the joint return period of precipitation extremes indicates that the South Peninsular India, North East India, West Central India and Central Northeast India, as well as most parts of Southeast Asian countries, will experience very heavy intensify precipitations in the future. In addition, persistent co-occurrence of dry and wet conditions will be observed in Pakistan, North West India, and Central Northeast India. This study provides useful information on the distribution of precipitation extremes in different regions of the study area.

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&amp;lt;sup&amp;gt;st&amp;lt;/sup&amp;gt; Century

Spatial Variation and Trend of Extreme Precipitation in Africa during 1981-2019 and Its Projected Changes at the End of 21&amp;lt;sup&amp;gt;st&amp;lt;/sup&amp;gt; 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.