Recent changes in climate extremes in the Caribbean region

This paper presents a synthesis of the main characteristics of precipitation in the State of Rio de Janeiro (Brazil) based on extreme rainfall indicators. Daily precipitation data are derived from 56 rainfall stations during the second half of the twentieth century and the 2000s. Eight indices related to extreme precipitation were analyzed. The Mann–Kendall nonparametric test and the Sen's Curvature were employed to evaluate the significance and magnitude of trends. The primary climatological aspects and identified trends throughout the last decades are discussed, besides the hydrometeorological impacts associated with them. Lower values of annual total precipitation are recorded in northern Rio de Janeiro (around 800 mm) and higher in the southern State (up to 2,200 mm). The Serra do Mar affects the frequency of heavy precipitation, and the areas near the sea and high relief present the highest values of consecutive days with expressive rainfall (more than 150 mm in 5 days). These areas also showed a high concentration of flood and landslides events. Most of Rio de Janeiro exhibits precipitation intensity of about 13 mm/day. The maximum number of consecutive dry days shows a gradient from the coast (about 30 days) to the State's interior (around 50 days). Regarding trends, there is a growth of accumulated extreme precipitation in various stations near the ocean. The extreme rainfall in 24 h displays an increase in most Rio de Janeiro (+ 1 to + 5 mm/decade). The consecutive dry and rainy days present similar signs of decreasing trends, suggesting irregularly distributed precipitation in the State. This study is especially relevant for decision-makers who need detailed information in the short and long term to prevent natural hazards like floods and landslides and the related impacts in the environmental and socioeconomic sectors of the Rio de Janeiro.

The increases in extreme climatic events over the northeastern Tibetan Plateau and their association with atmospheric circulation changes

Despite the obvious and significant impacts of climate change and variability on crop yields in the Sahel during the past three decades, few quantitative works on potential climate change impacts on Sahelian agriculture has been conducted. Hence, this chapter presents results of predictive statistical models of peanut yields in Diourbel (Senegal) for the period 2011–2040. Rainfall indices were used as input data for a Classification and Regression Tree (CART) model aimed at forecasting the level of yield which was broken into three classes (normal, above normal, below normal). Cumulative seasonal rainfall, the percentage of days with rain, the maximum cumulative precipitation on three consecutive days, the maximum number of consecutive dry days, the maximum consecutive days of precipitation, the average precipitation intensity by wet days and the 95th percentile of daily precipitation were used to describe rainy season characteristics. The model was successfully calibrated and validated over a control period (1997–2007), then driven by the downscaled projected precipitations of six Regional Circulation Models (RCMs). These RCMs were driven by two Global Circulation Models (GCMs) under the SRES A1B scenario (AMMA-SETS). Two types of downscaling techniques were taken into consideration for the outputs of RCMs (multiple regression and Quantile-Quantile transformation). Eventually, the corrected DMI-HIRHAM5 model was selected, and corrected outputs were used to generate predictors for the CART model for the period 2011–2040. These predictors were then used to estimate future results in Diourbel. The results show yields were split between high and low normal levels for the next 30 years.

Despite the importance of the Yellow River to China, climate change for the middle reaches of the Yellow River Basin (YRB) has been investigated far less than for other regions. This work focuses on future changes in mean and extreme climate of the YRB for the near-term (2021–2040), mid-term (2041–2060), and far-term (2081–2100) future, and assesses these with respect to the reference period (1986–2005) using the latest REgional MOdel (REMO) simulations, driven by three global climate models (GCMs) and assuming historical and future [Representative Concentration Pathway (RCP) 2.6 and 8.5] forcing scenarios, over the CORDEX East Asia domain at 0.22° horizontal resolution. The results show that REMO reproduces the historical mean climate state and selected extreme climate indices reasonably well, although some cold and wet biases exist. Increases in mean temperature are strongest for the far-term in winter, with an average increase of 5.6 °C under RCP 8.5. As expected, the future temperatures of the warmest day (TXx) and coldest night (TNn) increase and the number of frost days (FD) declines considerably. Changes to mean temperature and FD depend on elevation, which could be explained by the snow-albedo feedback. A substantial increase in precipitation (34%) occurs in winter under RCP 8.5 for the far-term. Interannual variability in precipitation is projected to increase, indicating a future climate with more extreme events compared to that of today. Future daily precipitation intensity and maximum 5-day precipitation would increase and the number of consecutive dry days would decline under RCP 8.5. The results highlight that pronounced warming at high altitudes and more intense rainfall could cause increased future flood risk in the YRB, if a high GHG emission pathway is realized.

This study uses the results of 28 CMIP5 global climate projections to link regional climate extremes in the Mediterranean region to the global mean annual surface temperature change. It shows that global warming will further increase the existing difference in intensity of precipitation and hydrological extremes between north and south Mediterranean areas (SMed and NMed, respectively), while the increase/decrease of warm/cold temperature extremes will be only marginally larger in the SMed. The Simple daily precipitation intensity index (SDII) and the total precipitation during very wet days (R95pTOT) are already larger in the NMed than in the SMed; they will increase with global warming at a rate of approximately 0.1 mm/K and 5 mm/K, respectively, in the NMed, with no significant change in the SMed. The maximum number of consecutive dry days (CDD) is already larger in the SMed than in the NMed and will increase more in the former than in the latter (rates are about 8 days/K and 5 days/K, respectively). Global warming will not affect the difference of maximum number of consecutive wet days (CWD), which is presently larger in the NMed than in the SMed and will decrease at a similar rate (about 0.5 days/K) in both areas. Changes of temperature extremes (warm nights, TN90p, and cold days, TX10p) will be similar in the north and south Mediterranean, though marginally larger in several areas of the SMed than in the NMed. Their increase will be dramatic and with a 4 K global warming almost all nights will be warm and there will be no cold days.

Recent changes in daily extremes of temperature and precipitation over the western Tibetan Plateau, 1973–2011

Over the recent decades, Brazzaville in the Republic of Congo has experienced significant shifts in temperature and precipitation, including notable changes in both mean values and extremes. Understanding the evolving characteristics of hydroclimatic extremes, such as their frequency, seasonal timing, spatial extent, and severity, is essential for mitigating risks to the economy, society, and environment. This study analyzes projected changes in extreme temperature and precipitation events using high-resolution CMIP6 climate simulations across three time periods: historical (1981–2010), mid-century (2031–2060), and late-century (2071–2100). Climate data were processed in MATLAB using quantile mapping, statistical downscaling, and trend and correlation analyses. Findings reveal a robust warming trend, with mean annual temperatures projected to rise by up to 3.5 ∘ C ([Formula: see text]C) by the end of the century, accompanied by a rise in extreme heat events exceeding the 95th percentile. Seasonal rainfall projections suggest a 6.8% increase during the peak wet months and a 10.3% decline in the dry season, leading to heightened seasonal imbalances. The likelihood of extreme precipitation events is expected to increase by 14.7%, while the number of consecutive dry days (CDDs) may rise by about 8 days per year, indicating greater drought risk. These results underscore the urgent need for localized adaptation strategies, particularly in light of the increasing probability of compound events such as concurrent hot–dry or wet–hot extremes under future climate scenarios.

There is a high‐risk attendant on the changes in precipitation in developing countries, for example, Gaza Strip (GS). These changes have far‐reaching social and economic ramifications by causing devastating flash floods and droughts. Based on the daily precipitation observations of eight meteorological stations over GS, from 1974 to 2016, the trends of 11 extreme precipitation indices (EPIs) were estimated using linear least squares method and then assessed statistically by Mann‐Kendall test. The results show that, on average, most of the indices exhibited increasing trends during 1974–2016. It includes total wet‐day precipitation (PRCPTOT), simple daily intensity index (SDII), and max 1‐day precipitation (RX1day). Others were the max 5‐day precipitation (RX5day), very wet day precipitation (R95p), extremely wet day precipitation (R99p), number of heavy precipitation days (R10mm), number of very heavy precipitation days (R20mm), and the number of consecutive dry days (CDD). Three of these indices passed the significance test (with p < .05): RX1day, RX5day, and R95p. Other EPIs, including number of wet days (R1mm) and consecutive wet days (CWD), exhibited non‐significant decreasing trends. Spatially, many stations over GS exhibited opposite trends, especially in R1mm and CDD; however, they are separated by a few kilometres. Moreover, all EPIs have significant positive correlations with PRCPTOT at the 99% confidence level, except CDD (trend was non‐significant). The contribution of extreme precipitation to annual PRCPTOT exhibited an increasing trend, which was significant at 62% of GS stations. The study indicates a potential increase in summer (drought) season.

Several seasonal and annual climate extreme indices have been calculated and their trends (over 1958 to 2000) analysed to identify possible changes in temperature- and precipitation-related climate extremes over the eastern Mediterranean region. The most significant temperature trends were revealed for summer, where both minimum and maximum temperature extremes show statistically significant warming trends. Increasing trends were also identified for an index of heatwave duration. Negative trends were found for the frequency of cold nights in winter and especially in summer. Precipitation indices highlighted more regional contrasts. The western part of the study region, which comprises the central Mediterranean and is represented by Italian stations, shows significant positive trends towards intense rainfall events and greater amounts of precipitation. In contrast, the eastern half showed negative trends in all precipitation indices indicating drier conditions in recent times. Significant positive trends were revealed for the index of maximum number of consecutive dry days, especially for stations in southern regions, particularly on the islands.

Wide variability in the rainfall regime and drought is characteristic of semi-arid regions. A better understanding of this variability can aid decision-making in the short, medium and long term. The aim of this study was to identify long-term patterns and trends in rainfall and temperature through the use of temporal patterns, in addition to assessing the duration of wet and dry periods. Daily historical series of rainfall and temperature for the district of Iguatu, Ceará were used. For rainfall, the annual and monthly climate normal (1974-2018) was calculated, in addition to the number of consecutive dry days (CDD) during the rainy season. The annual mean value for the maximum, mean, and minimum temperatures (1996-2017) was also calculated. Wide interannual variability in the rainfall was found, with very wet years (1985; 2009 and 2011) and very dry years (1979; 1983 and 1993) interspersed with periods of around average rainfall. When analysing the total occurrence of dry spells by class, it was found that events of from 5 to 10 days were the most frequent, and tended to reduce in number over the period under investigation. There was also an increase in the number of longer events, those over 16 days. Maximum annual temperatures show an increasing trend over the years, with minimum temperatures showing the smallest increases. It was concluded that extreme rainfall events are common, and alternate between rainy years and years of drought. The increase in maximum temperature and the reduction in rainfall express the extreme climate variability that may be a consequence of climate change.

Under the background of global warming, precipitation extremes are the main reasons for the cause of drought-flood disasters at local scales. Regional evaluations on the spatial and temporal variations of precipitation extremes are needed for comprehensively understanding the precipitation-related natural disasters. In this study, ten extreme precipitation indices from 17 meteorological stations in the Hanjiang River Basin, China, were computed and their spatial and temporal variations were analyzed using linear tendency method, based on daily precipitation data for the period of 1960–2015. Results indicated that consecutive dry days, number of heaviest precipitation days, maximum 1-day precipitation, very wet day precipitation, extremely wet day precipitation, and simple precipitation intensity index exhibited non-significant increasing trends. Consecutive wet days, number of heavy precipitation days, maximum 5-day precipitation, and total wet day precipitation exhibited non-significant decreasing trends. Using Mann-Kendall test, cumulative anomaly method, and moving t test for cross-validation, an abrupt increase was detected in 1978 for both very wet day precipitation and extremely wet day precipitation and for both these two indices, there were two significant periodic variation cycles, i.e., 1–2 years and 4 years, and in addition, extremely wet day precipitation had a change cycle of 8 years. The cross-wavelet transform method suggested that Pacific Decadal Oscillations and Sea Surface Temperature might be the two driving factors of extreme precipitation variation. The changing trends of precipitation extremes showed regional differences, but the stations with significant trends were not clustered. All the indices were highly correlated with each other, except for the number of consecutive dry days and consecutive wet days. The contribution of extreme precipitation to total precipitation revealed a non-significant increase in the study area. There were negative correlations between most of the indices and elevation with high level of significance. Changes of large-scale atmospheric circulation showed an increasing geopotential height and a weakened summer monsoon and had an impact on the variations of extreme precipitation.

Precipitation extremes and their underlying causes are important processes to understand to plan appropriate adaptation measures. This paper presents an analysis of the spatiotemporal variability and trend of precipitation extremes in the important source region of the Yellow River and explores the connection to global teleconnection patterns and the 850-mb vector wind. Six indices for precipitation extremes were computed and analyzed for assessment of a changing regional climate. Results showed that these indices have a strong gradient from the northwest to the southeast part for the period 1961–2015, due to the great influence from the south-easterly summer monsoon flow. However, no statistically significant trends were found for the defined indices at the majority of stations, and their spatial distribution are noticed by irregularly mixed positive and negative changes except for the maximum number of consecutive wet days (CWD). Singular value decomposition analysis revealed that the precipitation extreme indices—including annual total precipitation when daily precipitation >95th percentile (R95p), annual count of days with daily precipitation ≥10 mm (R10mm), annual maximum consecutive 5-day precipitation (R5d), total precipitation divided by the number of wet days (SDII), and CWD—are negatively related to the El Nino-Southern Oscillation (NINO 3.4) in the first mode, and the maximum number of consecutive dry days (CDD) is positively related to the Scandinavian pattern in the second mode at 0.05 significance level. The 850-mb vector wind analysis showed that the southwestern monsoon originating from the Indian Ocean brings sufficient moisture to this region. Furthermore, the anti-cyclone in the western part of the North Pacific plays a significant role in the transport of moisture to the source region of the Yellow River. The links between precipitation extremes and teleconnection patterns explored in this study are important for better prediction and preparedness of climatic extremes.

Future changes in the 50-yr return level for temperature and precipitation extremes over mainland China are investigated based on a CMIP5 multi-model ensemble for RCP2.6, RCP4.5 and RCP8.5 scenarios. The following indices are analyzed: TXx and TNn (the annual maximum and minimum of daily maximum and minimum surface temperature), RX5day (the annual maximum consecutive 5-day precipitation) and CDD (maximum annual number of consecutive dry days). After first validating the model performance, future changes in the 50-yr return values and return periods for these indices are investigated along with the inter-model spread. Multi-model median changes show an increase in the 50-yr return values of TXx and a decrease for TNn, more specifically, by the end of the 21st century under RCP8.5, the present day 50-yr return period of warm events is reduced to 1.2 yr, while extreme cold events over the country are projected to essentially disappear. A general increase in RX5day 50-yr return values is found in the future. By the end of the 21st century under RCP8.5, events of the present RX5day 50-yr return period are projected to reduce to < 10 yr over most of China. Changes in CDD-50 show a dipole pattern over China, with a decrease in the values and longer return periods in the north, and vice versa in the south. Our study also highlights the need for further improvements in the representation of extreme events in climate models to assess the future risks and engineering design related to large-scale infrastructure in China.

Climate extremes, such as heat waves, droughts, extreme rainfall can lead to harvest failures, flooding and consequently threaten the food security worldwide. Improving our understanding about climate extremes can mitigate the worst impacts of climate change and extremes. The objective here is to investigate the changes in climate and climate extremes by considering two time slices (i.e., 1962–1990 and 1991–2019) in all climate zones of Pakistan by utilizing observed data from 54 meteorological stations. Different statistical methods and techniques were applied on observed station data to assess changes in temperature, precipitation and spatio-temporal trends of climatic extremes over Pakistan from 1962 to 2019. The Mann-Kendal test demonstrated increasing precipitation (DJF) and decreasing maximum and minimum temperatures (JJA) at the meteorological stations located in the Karakoram region during 1962–1990. The decadal analysis, on the other hand, showed a decrease in precipitation during 1991–2019 and an increase in temperature (maximum and minimum) during 2010–2019, which is consistent with the recently observed slight mass loss of glaciers related to the Karakoram Anomaly. These changes are highly significant at 5% level of significance at most of the stations. In case of temperature extremes, summer days (SU25) increased except in zone 4, TX10p (cold days) decreased across the country during 1962–1990, except for zones 1 and 2. TX90p (warm days) increased between 1991–2019, with the exception of zone 5, and decreased during 1962–1990, with the exception of zones 2 and 5. The spatio-temporal trend of consecutive dry days (CDD) indicated a rising tendency from 1991 to 2019, with the exception of zone 4, which showed a decreasing trend. PRCPTOT (annual total wet-day precipitation), R10 (number of heavy precipitation days), R20 (number of very heavy precipitation days), and R25mm (very heavy precipitation days) increased (decreased) considerably in the North Pakistan during 1962–1990 (1991–2019). The findings of this study can help to address some of the sustainable development goals related climate action, hunger and environment. In addition, the findings can help in developing sustainable adaptation and mitigation strategies against climate change and extremes. As the climate and extremes conditions are not the uniform in all climate zone, therefore, it is suggested to the formers and agriculture department to harvest crops resilient to the climatic condition of each zone. Temperature has increasing trend in the northern Pakistan, therefore, the concerned stakeholders need to make rational plans for higher river flow/flood situation due to snow and glacier melt.

Abstract. Extreme precipitation events are major causes of severe floods and droughts worldwide. Therefore, scientific understanding of changing properties of extreme precipitation events is of great scientific and practical merit in the development of human mitigation of natural hazards, such as floods and droughts. Wetness and dryness variations during 1961–2008 in Xinjiang, a region of northwest China characterised by an arid climate, are thoroughly investigated using two extreme precipitation indices. These are annual maximum consecutive dry days (CDD) and annual maximum consecutive wet days (CWD), based on a daily precipitation dataset extracted from 51 meteorological stations across Xinjiang. As a result, we present spatial distributions of mean annual CDD and mean annual CWD and their trends within the study period. The results indicate that: (1) CDD maximize in the Taklimakan and Turban basins of southeast Xinjiang, while minima are found in the Tianshan Mountains and the Ili river valley of northwest Xinjiang. On the contrary, the longest CWD are observed in northwest Xinjiang and the shortest in the southeast part of the region. (2) On an annual basis, CWD temporal variability shows statistically positive trends and a rate of increase of 0.1d/10a. CDD temporal variability shows statistically negative trends and a rate of decrease of 1.7d/10a. (3) Goodness-of-fit analysis for three candidate probability distribution functions, generalised Pareto distribution (GPD), generalised extreme value (GEV) and Gumbel, in terms of probability behaviours of CDD and CWD, indicates that the GEV can well depict changes of CDD and CWD. (4) The CDD and CWD better describe wet and dry conditions than precipitation in the Xinjiang. The results pave the way for scientific evaluation of dryness/wetness variability under the influence of changing climate over the Xinjiang region.