Climate Change Extreme Events Research Articles

Climate change extreme events and exposure of local communities to water scarcity: a case study of QwaQwa in South Africa

ABSTRACT The exposure of local communities to multiple climate change-related events is on the rise across the globe. Despite extensive disaster research on climate change, exposure and vulnerability, few studies have focused on the exposure of local communities to multiple climate change-related events. For over a decade QwaQwa, in South Africa, has experienced persistent water crises which have been attributed to climate change and socio-economic drivers. However, there is a lack of understanding of the risk drivers to provide a solid basis for disaster risk reduction and resilience-building. This paper; therefore, aims to conduct analyses of hazards and exposure as part of risk analysis of climate change-related events; notably drought, flooding, wildfires, and water scarcity in QwaQwa. Quantitative and qualitative data sources included key informant interviews, household surveys, and field observations. The study employed the indicator method to analyse both the hazard and exposure. Qualitative data were anlysed using thematic analysis. On a five-point scale, the findings showed high indices of multiple hazards (3.6) and exposure (3.2). Analysis results were validated at a stakeholders’ workshop. The study recommends efficiency in implementing risk-sensitive land use plans, improving early warning systems, and the use of unmanned aerial vehicles to mitigate disaster risks.

Analysis of Spatial and Temporal Distribution and Changes in Extreme Climate Events in Northwest China from 1960 to 2021: A Case Study of Xinjiang

Xinjiang, as a climate-sensitive region in Northwest China, holds significant importance in studying extreme climate events for agricultural production and socioeconomic development. Using data spanning from 1960 to 2021 from 52 meteorological stations across Xinjiang, encompassing 23 indices of extreme climate events, the 5-year moving average, linear trend fitting, and inverse distance weighting (IDW) are used to analyze the distribution patterns and temporal changes in extreme climatic phenomena within the region. The results indicate that, over the period from 1960 to 2021, the Amplitude Temperature Index, Heat Index, and Warm Spell Duration Index in Xinjiang exhibited a marked increasing trend, whereas the Cold Index and Cold Spell Duration Index displayed a significant decreasing trend. The range of changes in the extreme temperature indices from 1990 to 2021 is higher than that of 1960 to 1989. The areas with high values of amplitude temperature extreme indices are primarily concentrated in the southern part, while the areas with high values of cold indices are mainly distributed in the northern part. The upward/downward trends all account for over 80.00% of the entire region. The precipitation scale indices, precipitation day indices, intense precipitation index, and extreme precipitation index all showed a significant growth trend from 1960 to 2021, and the range of change in the extreme precipitation indices from 1990 to 2021 was lower than that from 1960 to 1989. Furthermore, areas with high precipitation values and regions with high trend values of climate tendency are predominantly concentrated in the northern and western parts of Xinjiang, with over 71.00% of the entire region experiencing an upward trend. The research results provide theoretical foundations for formulating climate risk strategies in the northwest region of China.

Profile of Rainfall Patterns and Extreme Air Temperatures 1981-2020 in the Mosunal Region of Indonesia (Case Study: South Sumatra)

Increasing concentrations of greenhouse gases have led to changes in extreme climate events. This study aims to describe the picture of climate change in the South Sumatra Region during the last 40 years, namely from 1981-2020. Rainfall and extreme temperature data were obtained from BMKG data for South Sumatra Province at the Palembang City Climatology Station (SK Palembang City) and the Sultan Mahmud Badaruddin II Meteorological Station (SM SMB II). Maximum temperature data, minimum temperature and rainfall were obtained based on parameter profiles obtained from BMKG data for South Sumatra Province based on the ETCCDMI provisions. Maximum temperature data, minimum temperature and rainfall are processed with RClimDex software so that temperature and extreme rain index data are obtained. These indices are extreme climate indices consisting of TN90p, TX90p, TNn, TNx,TXx, TXx, TMAXmean, TMINmean, RX1day, RX5day, SDII, CDD and CWD. The results of this study indicate that the trend of air temperature will increase significantly in South Sumatra Province, especially the minimum air temperature, then the precipitation pattern will also increase, especially the accumulation of rainfall for 5 consecutive days. There is an increase in the number of dry days and a decrease in the number of wet days, as well as the higher accumulation of daily rainfall but the wet days are decreasing day by day. This is also increasingly having an impact on climate change in South Sumatra Province which is getting hotter day by day and the smoke disaster due to land and peat fires in South Sumatra Province is increasingly worrying.

Urbanization Effect on Changes in Extreme Climate Events in Urumqi, China, from 1976 to 2018

This study investigates, for the first time, the urbanization effect (UE) on local extreme climate events in Urumqi, China, based on 22 indices of climate extremes, which are calculated with daily observation data from 1976 to 2018. These analyses reveal a pronounced nocturnal urban heat island (UHI) effect and a daytime urban cold island (UCI) effect. Due to Urumqi’s arid climate background, the UCI effect is considered a unique feature of the UE, which significantly differs from those in eastern and northern China. The UE on the TR20 index (number of days with minimum daily temperature exceeding 20 °C) reached 5.22 d/10a, indicating that urbanization has led to a fast increase in the number of hot nights in Urumqi. The absolute averaged UE on the indices measuring the frequency of warm events is about twice as large as that on the indices measuring the frequency of cold events, while that on the indices measuring the intensity of warm events is about one third of that on the indices measuring the intensity of cold events. The highest averaged urbanization contributions (UCs) to the extreme warm and cold events are represented by the frequency indices and the intensity indices, respectively, while those contributing to the extreme precipitation events are represented by the duration indices. Moreover, urbanization probably exacerbates the degree of wetting in the overall “warming and wetting” climate trend of the region. These findings can be seen as new evidence to provide scientific basis for further investigation of the UE on climate changes in arid regions.

A novel approach for evaluation of CMIP6 GCMs in simulating temperature and precipitation extremes of Pakistan

AbstractThe study used a hybrid approach to evaluate the performance of 20 global climate models (GCMs) from CMIP6 in reproducing 20 extreme temperature and precipitation indices over Pakistan. This study first analysed the future simulations of extremes and discarded the GCMs whose projections fell outside the 95% confidence interval. The remaining GCMs' performance was evaluated using the Kling Gupta Efficiency‐based criteria. The changes in extreme climatic events in Pakistan were projected using the multi‐model ensemble (MME) median of the selected GCMs for four shared socioeconomic pathways (SSPs) in two future periods, 2020–2059 and 2060–2099. Four GCMs' showed inconsistency in projecting future climatic extremes and were discarded initially. The past performance of the remaining GCMs revealed EC‐Earth3‐Veg‐LR, GFDL‐ESM4, MRI‐ESM2‐0 and NOR‐ESM2‐MM to be effective in reproducing extreme indices for the historical period. The MME median of the selected GCMs showed a gradual increase in most of the temperature and precipitation extreme indices in the future periods for all SSPs across the country. Specifically, it showed a higher increase in daily maximum temperature (TXx) by 4.5–5°C, daily minimum temperature (TNn) by more than 4.5°C, consecutive days with a temperature higher than the 95th percentile (WSDI) by >160 days, one‐day maximum rainfall by 9–15 mm and days with precipitation above the 95th percentile by >50 mm in northern high‐elevated areas during 2060–2099 for SSP585. Similarly, a higher increase in TXx by 4.5–5°C, TNn by >4.5°C, WSDI by 140 days and tropical nights by 40–60 days was also found in the western arid region during 2060–2099 for SSP585. The study highlights that northern high‐elevated and western arid regions are at a higher risk of extreme temperatures and precipitation due to climate change.

On the potential use of weather types to describe the interannual variability of annual maximum discharge across the conterminous United States

AbstractWeather types or weather regimes represent the dominant modes of large‐scale atmospheric circulation patterns and have been used to understand and explain the physical mechanisms of different weather events. While there have been many studies that analyse the changes in extreme climate events through the lenses of weather typing, there is a lack of studies that attribute changes in flood extremes to changes in weather regimes. Here we examine the potential applicability of weather types as predictors of flood extremes. For 4535 streamgages across the conterminous United States, we employ a statistical attribution approach to model the seasonal and annual maximum discharge, utilizing five weather types with distinct synoptic features. Although there are regional patterns in the relationship between weather types and the major climate drivers of flooding, our results show that the frequency of weather types does not provide enough information to model the interannual variability in the magnitude of flood peaks across the conterminous United States.

Projected changes in extreme climate events over Africa under 1.5[formula omitted], 2.0[formula omitted] and 3.0[formula omitted] global warming levels based on CMIP6 projections

The ongoing global warming is projected to persist throughout the entire century if effective mitigation measures are not put in place. The warming is associated with occurrence of extreme climate events that are prone over Africa. This study uses model data from 24 CMIP6 modeling centers to investigate future changes in extreme climate events over Africa under 1.5 °C, 2.0 °C and 3.0 °C global warming levels (GWLs). The amplified impact in extreme climate events by additional is computed relative to GWL1.5 °C. The models generally simulate observed climate extremes well, with the ensemble mean minimizing data uncertainties. The entire continent is projected to get warmer with the Sahara, Kalahari and parts of the Mediterranean depicting relatively higher temperatures. Both Rx1day and Rx5day are projected to increase over the continent except for the northern and southern regions of the continent. Rx5day is projected to increase by 4–10% for GWL1.5 and GWL3.0 °C. In comparison, an additional 0.5 °C warming between GWL2.0 °C and GWL1.5 °C will lead to an increase of about 43% impact for the climate extremes. An additional GWL1.5 °C (GWL3.0 °C) could result in about 68% increment in climate extremes. The amplified impact of global warming will result in devastating socioeconomic impacts over Africa. This stresses the need of formulating and implementing more ambitious climate change mitigation measures in effort to limit global warming to 1.5 °C.

Precipitation-type discrimination and changes in related climate indices in the upper Heihe River Basin during 1960–2021

Introduction: Precipitation in the upstream region of the Heihe River basin (UHRB) in the northeastern of the Tibetan Plateau, which is the main water source of the basin, has undergone drastic changes in extreme climate events in recent decades. In addition to the amount of precipitation, the type of precipitation has a substantial impact on hydrological processes.Methods: In this study, we compared the results from three methods aimed at improving precipitation type estimation based on daily precipitation type records for 24 discontinuous years. Based on the precipitation type distinction, we examined the spatial and temporal changes in the total precipitation, rainfall, snowfall and air temperature at the six stations as well as the spatial average of the UHRB during the past 62 years. We also analyzed changes in the quantity, duration magnitude, and frequency of extreme precipitation using the RClimDex model and statistical analysis.Results: The probability of detection value of the T3.6_4.5 method was 1.9%, indicating the estimation was closest to actual records. The analyses based on precipitation type diving showed that rainfall accounts for an average of 81.9% of the total precipitation received in a year. In the context of large scale climate warming, temperatures at all six stations increased significantly, but precipitation changes were only apparent at about half of the stations which were located in regions of higher elevation and influenced by both ENSO and the East Asian monsoon. Analysis of the spatial averages in the UHRB revealed that the annual drought events (CDD) were significantly alleviated, and that the growing season length (GSL) was significantly extended. The annual total precipitation, rainfall, and extreme precipitation indices (P99P, P95P, R95P, and SDII) increased in magnitude, and the frequency of extreme precipitation events (P10mm) also significantly increased.Discussion: The findings of this study indicate that under the background of climate warming, the changes of precipitation patterns in the UHRB which may have resulted in bringing better vegetation growth, but also the increasingly frequent extreme rainfall events may pose challenges to growing extreme rainfall events to agriculture and other human activities in local and downstream areas.

Based AHP Loss Function Model for Equilibrium Dam Water Use

The purpose of this paper is to establish a model to balance water for power generation and domestic use. Dams and reservoirs have been an important part of human production and life since ancient times. In order to make full use of water resources, we have modelled the distribution of water resources in Lake Powell and Lake Mead to help achieve optimal allocation of water resources. Several models are established, Model I: Multiobjective Optimization. Model II: Loss function model based on Analytic Hierarchy Process. The discussion of the above models covers a wealth of industry factors and emergencies, so our model has strong adaptability and flexibility. It can be used not only in the factor we are learning, but also in other factors. Finally, we conduct a sensitivity analysis for extreme climate events. The results show that the model is insensitive to changes in extreme climate events, which means it can deal with water allocation problems in extreme situations. The model can be considered stable.

Historical and Future Changes in Extreme Climate Events and Their Effects on Vegetation on the Mongolian Plateau

Climate change has increased the frequency of extreme climate events, with different regions showing different sensitivities to these events. In this study, the full subset regression analysis, correlation analysis, and multiple linear regression analysis were used to analyze trends of extreme climate changes and their effects on vegetation on the Mongolian Plateau from both historical and future perspectives. The results showed significant increasing and decreasing trends in extreme warming and extreme cooling indices, respectively, over the past three decades. The extreme temperature indices and precipitation trends under three scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios) were consistent with historical trends, and the rates at which temperature and precipitation increased were positively correlated with increasing radiation intensity. In comparison with historical changes, there were gradual increases in areas of regions with increasing temperature and precipitation and decreases in areas with decreasing precipitation. There was an overall increasing trend in the normalized difference vegetation index (NDVI) of the Mongolian Plateau, and the indices that had the greatest influence on the NDVI during the analysis of climate extremes were: (1) the number of days of heavy rainfall (R20); (2) the number of summer days (SU25) and; (3) high extreme daily minimum temperature (TNx). There was an increasing trend in the NDVI from 2021 to 2080, and the rate of the NDVI increase decreased with increasing radiation intensity. The rates of change in the NDVI under all three scenarios were lower than that of the historical period.

Evaluating and projecting of climate extremes using a variable-resolution global climate model (VR-CESM)

Increasing risk of many natural hazards including floods, wildfires, and reduction of agricultural production are often due to extreme climate events such as heavy precipitation, heat waves and drought. In this study, the variable-resolution Community Earth system model (VR-CESM) was used to investigate potential changes in extreme climate events at refined-resolution (14 km) in the western U.S. and eastern China. The model performance for simulating climate extremes is evaluated by various extreme metrics and assessed against the PRISM reference dataset in the U.S. VR-CESM is also compared with other models at different resolutions, including the uniform coarser resolution model CESM with the same physical parameterization, and HadGEM2-WRF, one RCM in the CORDEX-NA ensembles with the same SST forcing as the GCMs. Among those precipitation extreme metrics, VR-CESM simulates the short-term daily metrics (e.g., 95th percentile precipitation) in the western U.S. well (with greater uncertainties in the Sierra Nevada and Cascade Mountains), but underestimates the long-term metrics (e.g., number of dry years) during the historical period. For temperature extremes, VR-CESM also overestimates the number of hot temperature extremes in California’s Central Valley and southwestern desert regions; this is consistent with the warm seasonal average JJA biases. In model intercomparisons, VR-CESM has smaller biases than CESM and HadGEM2-WRF for both extreme precipitation and temperature events. Additionally, the Palmer Drought Severity Index (PDSI) for all models is simulated at four watersheds and compared to the PRISM reference dataset with statistical testings for their similarities. Under RCP8.5 through 2050, VR-CESM projects stronger and more frequent extreme precipitation in the mountains and hot events in the deserts of the western U.S., with more wet periods in California as indicated by PDSI. In another VR-CESM refined-resolution region in China, VR-CESM projection indicates an increase in strength and magnitude of extreme precipitation in southern China and hot temperature extremes in eastern China. Geographic heterogeneity in PDSI projections is also evident as the North China Plain is projected to have more dry periods while the Three Gorges Basin is projected to not change much. This study demonstrates that the analysis of multiple extreme metrics is essential to provide an adequate understanding of how extremes may change in the future in a particular place.

Research and Analysis of Global Weather Extremes Affecting Civil Engineering Construction Schedules Based on LSTM Algorithm

The occurrence of extreme weather events will cause serious harm to natural ecosystems, human social economy and construction sites. Large-scale construction projects have a long cycle and complex construction environment, and the schedule control is obviously disturbed by meteorological and other factors. Risk control of schedule delays is an important part of project risk management. The study of extreme weather events has become a key focus and hotspot in meteorological and climate science research in the context of global change. This paper proposes a more objective approach to defining extreme climate events from the study of extreme climate event uncertainty. On this basis, the spatial and temporal characteristics of extreme temperature and precipitation in recent decades are analysed. Considering the variability of precipitation and temperature, an idea is proposed to study extreme continuous precipitation events, and the mechanism of extreme precipitation occurrence in the region is explored. Finally, the LSTM model data are used to carry out studies and projections of changes in extreme climate events under different future scenarios.

Extreme temperature and rainfall events in Bangladesh: A comparison between coastal and inland areas

AbstractAlthough coastal and inland areas of Bangladesh exhibit distinct physiographic and climatic characteristics, spatiotemporal variation of extreme climatic events is poorly understood in these two areas. This study was an attempt to understand the trends in extreme climatic events in coastal and inland areas over the period 1968–2018. The missing data in daily maximum and minimum temperature, and daily rainfall datasets were imputed using the multiple imputation by chained equations technique and implementing a predictive mean matching algorithm. The imputed datasets were then tested for inhomogeneity using the penalized maximal t and modified penalized maximal F tests. A quantile matching algorithm was then applied to homogenize the datasets, which were then used for generating 13 extreme temperature and 9 extreme rainfall indices. The trends were assessed using the Trend Free Pre‐whitened Mann–Kendall test and the magnitudes of the changes were determined using the Thiel–Sen slope estimator. Additionally, standardized anomalies were calculated to understand the seasonal variability of temperature and rainfall over the past five decades. Results suggested that both coastal and inland areas were warming significantly but coastal areas exhibited a higher rate of warming. Although most of the extreme rainfall indices showed statistically non‐significant changes for coastal and inland stations, there is evidence of localized dryness and increased rainfall at individual stations. In particular, the drought‐prone northwestern region of the country experienced decreased rainfall, which is discordant to the results of previous studies. Findings from this study highlighted important local and regional‐scale changes in extreme climate events that were previously overlooked. The findings of this study can help undertake targeted climate change adaptation strategies to save population and resources.

Homo Sapiens Sapiens Progressive Defaunation During The Great Acceleration: The Cli-Fi Apocalypse Hypothesis

Homo Sapiens Sapiens Progressive Defaunation During The Great Acceleration: The Cli-Fi Apocalypse Hypothesis

Characterisation of Vegetation Response to Climate Change: A Review

Climate change extreme events have consequential impacts that influence the responses of vegetation dynamics as well as ecosystem functioning and sustainable human well-being. Therefore, vegetation response to climate change (VRCC) needs to be explored to foster specific-organised management programmes towards ecological conservation and targeted restoration policy to various climate extreme threats. This review aimed to explore the existing literature to characterise VRCC and to identify solutions and techniques fundamental in designing strategies for targeted effective adaptation and mitigation to achieve sustainable planning outcomes. Accordingly, this review emphasised recent theoretical and practical research on the vegetation-climate responses and their related impacts in the wake of climate change and its debilitating impacts on vegetation. Consequently, this study proposes the Information-based model (IBM), needed to examine Factors–forms of Impacts–Solutions (Techniques)–Risks assessment to identify and provide insights about VRCC in a given region. In conclusion, two enablers of adaptive indicators and the novel systems-based serve as a key policy formulation for sustainability in strengthening the goals of global involvement of local and sub-national governments and institutions in the effective management of vegetation and ecosystem protection.

Assessing the Impacts of Extreme Precipitation Change on Vegetation Activity

Extreme climate events frequently have more severe effects on terrestrial vegetation activity than long-term changes in climate averages. However, changes in extreme climate events as well as their potential risk on vegetation activity are still poorly understood. By using the Middle and Lower Reaches of the Yangtze River (MLR-YR) in China as an example, this paper aims to understand the vegetation response to changes in extreme precipitation events from 1982 to 2012 using the maximum normalized difference vegetation index (NDVI) as an indicator. By applying extreme value theory (EVT), the potential risks of extreme precipitation events on vegetation activity were analyzed by conducting return period analysis. Results indicated that vegetation activity could be affected by extreme precipitation events, especially the combined effects of the frequency and intensity of precipitation extremes. For instance, vegetation activity could be enhanced in the regions with weakened intensity but increased occurrence of extreme precipitation events. In addition, we found potential risk of extreme precipitation events on vegetation activity from the results of precipitation extreme trend and return period analysis. These phenomena can be associated with the local occurrence of extreme precipitation events, different land cover types, and soil moisture cumulative effect on vegetation growth. This study stresses the importance of considering both current changes in and the potential risk of extreme precipitation events to understand their effects on vegetation activity.

Changes in Extreme Climate Events in Rice-Growing Regions Under Different Warming Scenarios in China

Scientific prediction of critical time points of the global temperature increases and assessment of the associated changes in extreme climate events can provide essential guidance for agricultural production, regional governance, and disaster mitigation. Using daily temperature and precipitation model outputs from the Coupled Model Intercomparison Project Phase 6 (CMIP6), the time points of the temperature that will increase by 1.5 and 2.0°C were assessed under three different scenarios (SSP126, SSP245, and SSP585). To characterize the change of extreme climate events in the rice-growing regions in China, six indices were designed, and a time slice method was used. An analysis from an ensemble of CMIP6 models showed that under SSP245, the global mean temperature will rise by 1.5°C/2.0°C by approximately 2030/2049. A global warming of 2.0°C does not occur under SSP126. The time for a 1.5°C/2.0°C warming all becomes earlier under SSP585. Under 1.5°C of global warming, the number of warm days (TX90p), rice heat damage index (Ha), consecutive dry days (CDD), 5-day maximum precipitation (Rx5day), and number of annual total extreme precipitation events (R99pTOT) will clearly increase, while the number of cold damage (Cd) events will decrease. All the indices show a strong variability regionally. For example, the CDD increased significantly in the Central China and South China rice-growing regions. The monthly maximum consecutive 5-day precipitation increased by as much as 6.8 mm in the Southwest China rice-growing region.

Contribution of urbanization to the changes in extreme climate events in urban agglomerations across China

Unprecedented urbanization in China facilitates the rapid development of urban agglomerations (UAs) and may exert prominent effects on regional climate and environment change. By analyzing a set of 27 extreme temperature and precipitation indices, this study examines the changes in extreme climate events in 20 UAs in China and evaluates the urbanization effects using a dynamic classification of urban and rural stations by time-varying land use/cover maps. The regional differences of the urbanization effects on extreme climate events are also investigated by a k-means clustering. It is found that, for both temperature and precipitation extremes, the urban and rural areas exhibit remarkably distinct changes and demonstrate significant urbanization effect, which also varies across different climate backgrounds. Urbanization profoundly contributes to increasing hot extremes and reducing cold extremes in most UAs, while it seems to pose the opposite effects in several UAs of arid and high-latitude regions. On average, the urbanization effect accounts for around 30% of the total change in extreme temperature events over the urban core areas of 20 UAs. On the other hand, the urbanization effects on extreme precipitation indices display stronger regional discrepancies than temperature extremes. Urbanization tends to have weakening effects on extreme precipitation events in UAs over coastal regions and intensifying influences on those in central/west China. It causes more (less) frequent and more (less) intense precipitation in UAs of inland central/west (coastal) areas. Our findings provide a systematic understanding of the urbanization effects on extreme climate and may have important implications for the mitigation of urban disasters.

Multi‐model ensemble of CMIP6 projections for future extreme climate stress on wheat in the North China plain

AbstractFuture extreme climate events will become more intense and frequent with global warming, which is a great threat to wheat productivity in the North China Plain (NCP). Projecting future changes in extreme climate events is an important prerequisite for exploring crop adaptation measures to climate variation. In this study, we calculated 11 extreme climate indices at different wheat growth stages that are sensitive to wheat yield across NCP. The future climate projections were sourced from thirteen Global Climate Models (GCMs) from the Coupled Model Inter‐comparison Project phase 6 (CMIP6) under two emission scenarios of future societal development pathway (SSP) 245 and SSP585. Daily climate data of thirteen GCMs were generated by using a statistically downscaled method. Two multi‐model ensemble methods, that is, arithmetic mean and independence weighted mean (IWM), were used to assess the performance of thirteen GCMs in reproducing historical changes of extreme climate indices. The IWM ensemble results could better reproduce historical changes of extreme climate indices than multi‐model arithmetic mean and any individual GCM. We found that the frequency and intensity of heat extremes were projected to increase over the 21st century for both scenarios, but those of cold extremes will decrease. Heat stress intensity (HSI) increases around 1.0°C for SSP245 scenario and 1.6°C for SSP585 scenario by the end of the 21st century. There was no significant change in extreme precipitation indices across the NCP, but the changes of extreme precipitation had strong spatial heterogeneity. Overall, wheat production in the NCP might have a higher frequency of exposure to extreme climate, especially under heat stress. Therefore, adopting effective adaptation measures to mitigate heat stress for wheat is the first priority in the NCP.

Changes in Extreme Climate Events in China Under 1.5 °C–4 °C Global Warming Targets: Projections Using an Ensemble of Regional Climate Model Simulations

AbstractExtreme climate events in China, including its 10 main river basins, were projected under global warming of 1.5 °C–4 °C using the latest version of a regional climate model (RegCM4) for dynamical downscaling, driven by the outputs of four global climate models. Firstly, evaluation indicated that the simulations satisfactorily reproduced the spatial distribution of temperature extremes and, although with lower performance, the spatial distributions of precipitation extremes were generally captured. Additionally, a better description was achieved over areas with complex terrains by using RegCM4. Next, the model was used to make projections under global warming of 1.5 °C–4 °C. Warm extremes were projected to increase, while cold events were projected to decrease, particularly in northern and western China. In addition, the number of wet days was projected to increase in the northern part of China, and to decrease in the southern part. The maximum consecutive five‐day precipitation and the precipitation intensity were projected to increase significantly throughout China, while the consecutive number of dry days was projected to significantly decrease in northern and western China. The changes of atmospheric moisture content and atmospheric circulation lead to the increase of extreme precipitation. Specifically, the increases in the indices of wetness were closely correlated with the summer precipitation, wind, moisture flux convergence, and surface specific humidity, while the consecutive number of dry days was related to the change in summer moisture flux convergence and precipitation in dry seasons. Notably, the magnitude of the changes in extremes events was projected to increase as the warming target increases.