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Abstract Global gridded data sets of observed extremes indices underpin assessments of changes in climate extremes. However, similar efforts to enable the assessment of indices relevant to different sectors of society have been missing. Here we present a data set of sector‐specific indices, based on daily station data, that extends the HadEX3 data set of climate extremes indices. These additional indices, which can be used singly or in combinations, have been recommended by the World Meteorological Organization and are intended to empower decision makers in different sectors with accurate historical information about how sector‐relevant measures of the climate are changing, especially in regions where in situ daily temperature and rainfall data are hard to come by. The annual and/or monthly indices have been interpolated on to a 1.875° × 1.25° longitude‐latitude grid for 1901–2018. We show changes in globally‐averaged time series of these indices in comparison with reanalysis products. Changes in temperature‐based indices are consistent with global scale warming, with days with Tmax > 30°C (TXge30) increasing virtually everywhere with potential impacts on crop fertility. At the other end of the scale, the number of days with Tmin

This study was intended to evaluate the variability and trends of climate extremes by incorporating daily data from Chattogram station and from the high-resolution Coordinated Regional Climate Downscaling Experiment (CORDEX) for two different time series. Here, we also focused on evaluating the performance of the selected RCMs (CanESM2, CSIRO, and GFDL from CORDEX) using Taylor diagrams and heat map analysis. Twenty-two extreme climate indices from ETCCDI were computed for the 1950–1989 and 1990–2020 periods. Mann–Kendall and Sen's slope test were performed to estimate the trends from the indices from both station and RCMs data. Highly significant increasing trend for the warm days and warm nights’ frequencies were found, whereas the frequency of cold days and cold nights indicated a significantly decreasing trend. On the other hand, a mild increasing trend in 1-day and 5-day maximum rainfall was detected. Also, the average annual precipitation has increased by 6% from the 1950–1989 to 1990–2020 period. During the last three decades, the region has experienced heavier rainfall in the monsoon but increased water stress in the dry season. The two-fold effects of climate change on the local hydrology revealed by this study need to be addressed properly for the sustainable development of this region. HIGHLIGHTS Performance of the selected RCMs was evaluated using Taylor diagrams and Heatmaps analysis for the Chittagong region.; Variability of climate extremes from 1950–1989 to 1990–2020 was assessed.; A total of 22 extreme climate indices were computed and their changes over time were investigated.; Trend analysis was performed for the extreme rainfall and temperature indices from both station and RCMs data.;

In recent decades, the frequency and intensity of extreme weather events induced by global warming have increased significantly, exerting serious impacts on the development of society and ecosystems. Based on low (RCP2.6) and high (RCP8.5) greenhouse gas emissions scenarios from the Intergovernmental Panel on Climate Change, we use the general circulation model HadGEM2‐ES that is part of the Coupled Model Intercomparison Project Phase 5 (CMIP5) to drive the regional climate model RegCM4.7. This study evaluated the ability of both models to simulate (1986–2005) and projection (2080–2099) spatio‐temporal features of extreme indices over tropical South America (TSA). Indices based on precipitation and daily maximum and minimum temperature follow the definitions of the Expert Team on Climate Change Detection and Indices (ETCCDI). In general, the RegCM4.7 reproduces accordingly the spatial distribution of the ETCCDI indices derived from precipitation and temperature on the TSA, in addition to added value to HadGEM2‐ES, especially over regions of complex topography. HadGEM2‐ES performs poorly along the west coast, due to the topography and altitude of the Andes. On the other hand, it demonstrates better performance in the Amazon Basin compared to RegCM4.7. The projection results showed that climate extreme indices based on precipitation and temperature indicate that drought events may advance to the end of the century, showing a spatial pattern that precipitation will be gradually reduced in the Amazon Basin and Northeast region of Brazil. Despite some discrepancies between the models, studies like this one help us to understand how climate change can affect regional planning and development. [ABSTRACT FROM AUTHOR]

Historical simulations and projections of climate extremes indices of precipitation and temperature were analysed over South America until the end of the 21st century through 31 general circulation models (GCMs) under four Representative Concentration Pathways. Simulations were compared with reanalysis data, and a Bayesian inference method was used to assess the uncertainties involved in the multi‐model climate projections. Regarding the precipitation extremes indices, the GCMs' simulations reasonably approached the reanalysis data, but with heterogeneous biases, both in sign and in the location of the highest values. The temperature extremes indices presented the smallest biases when compared to precipitation. Projections show a gradual growth of precipitation extremes events as the analysed radiative forcing scenario increases, both in magnitude and extent, over a large part of South America. Projections also indicate a decrease in cold days and nights and an increase in warm days and nights, more pronounced in the equatorial region. Bayesian inference method smoothed changes in precipitation extremes events, both in magnitude and extent, compared to the simple GCMs' ensemble mean. There was no considerable variation in the temperature indices when applying the Bayesian inference. Finally, the probability density functions resulted in a predominance of multimodal and wide curves for the precipitation indices, showing great uncertainties in the GCMs' results, differently from those for the temperature indices, where the GCMs presented good agreement represented through unimodal and narrow curves. [ABSTRACT FROM AUTHOR]

Global gridded data sets of observed extremes indices underpin assessments of changes in climate extremes. However, similar efforts to enable the assessment of indices relevant to different sectors of society have been missing. Here we present a data set of sector‐specific indices, based on daily station data, that extends the HadEX3 data set of climate extremes indices. These additional indices, which can be used singly or in combinations, have been recommended by the World Meteorological Organization and are intended to empower decision makers in different sectors with accurate historical information about how sector‐relevant measures of the climate are changing, especially in regions where in situ daily temperature and rainfall data are hard to come by. The annual and/or monthly indices have been interpolated on to a 1.875° × 1.25° longitude‐latitude grid for 1901–2018. We show changes in globally‐averaged time series of these indices in comparison with reanalysis products. Changes in temperature‐based indices are consistent with global scale warming, with days with Tmax > 30°C (TXge30) increasing virtually everywhere with potential impacts on crop fertility. At the other end of the scale, the number of days with Tmin < −2°C (TNltm2) are reducing, decreasing potential damage from frosts. Changes in heat wave characteristics show increases in the number, duration and intensity of these extreme events in most places. The gridded netCDF files and, where possible, the underlying station indices are available from https://www.metoffice.gov.uk/hadobs/hadex3 and https://www.climdex.org. Plain Language Summary: To be able to assess changes in extreme temperature and rainfall events across the globe, data sets which capture characteristics of these extreme events are required. The use of indices for these characteristics further enables both data sharing and the comparison of events across the world. Extreme events have impacts across human health, our infrastructure and the natural environment. So far there has not been a global product which presents indices which are relevant for different sectors of our society, including health, agriculture and water resources. In this work we present an extension to an existing data set of extremes indices, HadEX3, by including indices defined by the World Meteorological Organization which were developed with sector specific applications in mind. We have used the same approach and methodology, and where possible the same underlying daily temperature and rainfall observations. The temperature indices show changes consistent with global scale warming, with heat wave characteristics showing increases in the number, duration and intensity of these extreme events in most places. The data files are available for use by interested researchers in their work. Key Points: We present a sector specific extension to a data set of gridded temperature and precipitation extremesThis first quasi‐global product of these indices will support decision makers in a wide range of sectorsLong‐term changes show increases in intensity, frequency, and duration of warm extremes, and corresponding decreases in cool extremes [ABSTRACT FROM AUTHOR]

This paper presents a detailed spatio‐temporal analysis of the rainfall in the state of Pernambuco, Northeast Brazil. It is based on climate indices for extreme precipitation recommended by the Expert Team on Climate Change Detection, Monitoring and Indices. To accomplish this, daily rainfall 1data (1961–2019) were extracted from 809 high‐resolution grid points (0.1° × 0.1°) using the Brazilian Daily Weather Gridded Data (BR‐DWGD). The significance and magnitude of index trends were assessed using the modified Mann–Kendall and Sen's slope tests. This study also examined whether there existed a significant difference in climate indices among the three regions (Sertão, Agreste and Zona da Mata) within the state. The findings revealed notable significant negative trends in the PRCPTOT, R10mm, R20mm, Rx1day, Rx5day and CWD indices across all regions of Pernambuco, exhibiting a gradient from the coast to the state's interior. Reduction values of up to 15 mm year−1 for PRCPTOT, 0.7 day year−1 for R10mm, 0.2 day year−1 for R20mm, 0.01 mm year−1 for Rx1day, 0.03 mm year−1 for Rx5day, 0.4 day year−1 for CWD were observed. Furthermore, an alarming pattern was also noted for CDD, displaying a higher concentration of significant positive trends in all regions of the state, with estimated increases of up to 1.4 day year−1. Conversely, a balance of trends—both positive and negative—was observed across the entire state for R95p and R99p, with a majority of trends proving non‐significant. SDII exhibited a higher frequency of grid points showing a significant positive trend, particularly notable in the Sertão and Zona da Mata regions, where significant differences in the index values were absent. However, the remaining indices showcased notable regional differences, with values decreasing from the east to the west of the state, except for CDD. This study will assist decision makers, providing detailed long‐term information essential for preventing natural disasters and supporting socioeconomic and environmental policies in the state. [ABSTRACT FROM AUTHOR]

Study region: The study area comprising Pakistan is distributed in five homogeneous climatic zones. Study focus: An integrated five step approach has been used for zonal climate extreme analysis. Seven out of thirteen most appropriate Global Climate Models (GCMs) were selected using Posterior Inclusion Probability in the Bayesian model averaging approach. The output of selected GCMs is then downscaled using statistical downscaling. Climate extremes are projected for the baseline and future time periods. Spatio-temporal trend and statistical significance analysis were performed for climate extremes. New hydrological insights for the region: Most of the climate extremes have heterogeneous trends for the precipitation under RCP4.5 and RCP8.5. The increasing trends in climate extreme are noted in the northern region, monsoon region, and south-west parts of Pakistan. Significantly increasing trend is observed in TMAXmean and TMINmean across the country. TN10P (Cool nights) and TX10P (Cool days) have decreasing trends in the future for most of the GCMs across the country for RCP4.5 and RCP8.5. In contrast, TN90P (warm nights) and TX90P (warm days) have increasing trends for all GCMs in future under both scenarios. For RCP8.5, temperature extremes have significantly increased except TN10P and TX10P indicating significantly decreasing trends. There is notable increase in the number of summer days in future under both scenarios.

A number of studies have noted that the use of distinct reference periods when comparing indices measuring the frequency of days exceeding a particular temperature percentile threshold leads to apparently different behaviour. We show that these differences arise because of the interplay between the increasing temperatures and the choice of reference period. The time series of the indicators calculated using the different reference periods are offset, as expected, but also diverge. Linear trends calculated over the same period from the same underlying data but where different reference periods have been used are substantially different if a change in climatological conditions has occurred between the two reference periods. We show this not only occurs in our simple empirical approach, but also for the averages of gridded observational and reanalysis datasets and also at a station level. This has implications for data set comparisons using trends in temperature percentile indices that are based on different reference periods. It also has implications for updates to standard reference periods used to monitor the climate.

The Climate Data Operators [1] tool kit (CDO) is a worldwide popular infrastructure software developed and maintained at the Max Planck Institute for Meteorology (MPI-M). It comprises a large number of command line operators for gridded data, including statistics, interpolation, or arithmetics. Users benefit from the extensive support facilities provided by the MPI-M and the DKRZ.As a part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), the German Federal Ministry of Education and Research (BMBF) is funding activities promoting the use of the CDOs for CMIP6 data preparation and analysis. Firstly, a new operator 'cmor' has been developed which enables the users to rewrite their data according to the CMIP6 standard. It may be piped with other CDO operators allowing users to finish CDO applications with a standardizing 'cmor' call. The web-based post processing workflow composition for CMIP6 developed at DKRZ [2] takes advantage of the cmor operator. Secondly, both the metadata model and the data model of the CDOs had to be adapted to the CMIP6 standard.In addition, activities are underway to revise some operators for climate indices in order to adopt the procedures defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) for 27 climate extremes indices. As with CMIP5, the ETCCDI climate extremes indices will be part of CMIP6 model analyses due to their robustness and straightforward interpretation.[1] Schulzweida, U. (2019): CDO user guide. code.mpimet.mpg.de/projects/cdo, last access: 01.09.2019.[2] Schupfner, M. (2019): The CMIP6 Data Request WebGUI. c6dreq.dkrz.de, last access: 01.09.2019. [ABSTRACT FROM AUTHOR]

In this study, the daily maximum and minimum temperatures measured over the period 1961–2020 by 18 stations located near the Mediterranean coast are analysed to evaluate temperature trends and to compute 10 climate indices, selected among those proposed by the Expert Team on Climate Change Detection and Indices to monitor the occurrence of climate extremes of temperature. The trend analysis is performed using the Seasonal‐Kendall test. The results show statistically significant positive trends in both above‐mentioned variables throughout the Mediterranean, although the rate of warming is more marked in the minimum than in the maximum temperature and is more evident in the western portion of the Mediterranean Basin from 1990 onward. The climate extremes indices are evaluated assuming two different base periods (1961–1990 and 1991–2020). The shift forward of the base period involves a general rise in the percentile‐based thresholds used for identifying temperature extremes, as a natural consequence of the current atmospheric warming, resulting in fewer warm events and more cold events since the 1990s using a warmer/later base period. The application of the Seasonal‐Kendall test to the occurrence of extreme warm and cold events reveals that the western portion of the Mediterranean and the Adriatic Sea are the subregions most influenced by the base period update. This study demonstrates that the selection of the base period for the identification of extreme temperature events significantly impacts the results, and that the choice of a recent base period partially masks the ongoing atmospheric warming. The results suggest that the base period 1961–1990 might be more appropriate for climatological studies, as it provides a solid and stable baseline, and that attention must be paid when scientific results are shared with stakeholders, so as not to alter the communication of warnings and specific risks for the population. [ABSTRACT FROM AUTHOR]

Interpreting changes in climate extremes indices and related large-scale teleconnection factors is critical to addressing intensified climate change. The spatiotemporal trend in SU25 (summer days) and ID0 (icing days), as well as the contribution rates of large-scale circulation factors, were investigated using daily maximum temperature data from 93 stations in the Shandong Peninsula and 8 metrics of large-scale teleconnections from 1961 to 2017. The results showed that SU25 increased significantly while ID0 decreased significantly in the Shandong Peninsula during the study period. SU25 ranged from 66.3 to 155.1 days and gradually declined from inland to coast. ID0 ranged from 4.7 to 24.8 days and decreased roughly from north to south. SU25 had a significant negative correlation with longitude, while the trend of SU25 had a significant positive correlation with longitude. ID0 had a significant positive correlation with both latitude and longitude, while the trend of ID0 had a significant negative correlation with both latitude and longitude. The abrupt years of SU25 were concentrated in 1965, 1976, 1977, 1994, 2007, and 2012, respectively. The change point of ID0 at each station was most concentrated in 1970, 1972, 1986, and 1988, respectively. In the future, SU25 in most stations will continue to increase, while ID0 in almost all the stations will decrease. The Atlantic Multidecadal Oscillation (AMO) was the most important factor influencing SU25 change. Both the Arctic Oscillation (AO) and AMO made significant contributions to the ID0 change. The combined results of the two factors were usually greater than the results of the single circulation factor, and the contributions to SU25 and ID0 were mostly nonlinear enhancement. [ABSTRACT FROM AUTHOR]

One of the world's most challenging problems is climate change, which threatens many aspects of the social-ecological landscape of nature and human systems, particularly in the Horn of Africa. The study focuses on the spatiotemporal distribution of climate extremes indices under projected future climatic conditions over the Lake Tana sub-basin. Daily-time series in three socioeconomic pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5) for the near, mid, and far future periods and CMIP6 models were chosen as the best-fit models. Additionally, the climate variability of the basin is represented by eleven climate extreme indicators. The result indicates that model MPI-ESM1-2-HR gives reasonable performance for precipitation which is 0.76 coefficient of determination (R2) and 0.75 for Nash and Sutcliffe efficiency (NSE) and for maximum temperature 0.76 for R2, 0.75 for (NSE) and minimum temperature 0.65 for R2, 0.64 for NSE. Scenario SSP5-8.5 in the far future period will experience the highest warm period TXx and TXn around 33–32 °C and 21–20 °C, respectively, at stations Zegie, Addis Zemen, and Maksegnt. The coldest extremes TNn discovered at station Dangla throughout the near timeframe under the SSP2-4.5 scenario were between 5.9 and 6.7 °C. Heavy rainfall (R10) occurred in the top section of the subbasin for 26–27 days in Scenario SPP1-2.6, but exceptionally heavy rainfall (R20) was discovered in a far future period on average for 0.83–0.94 days in Scenario SSP5-8.5. The highest Rsum found was 1100–1000 mm rainfall at SSP1-2.6 at station Maksegnt in the same period. In a scenario of SSP5-8.5, dry CDD occurred at station Debretabor during a mid-future period for an average of 130–120 days. CWD was discovered during the mid-period of SSP2-4.5 in the upper portion of the basin at Maksegnt and Addis Zemen stations for an average of 120–130 days. In general, it is crucial for the stakeholders to be aware of the facts to develop and plan future activities on the basin that are related to the climate, health, and other extremes for alerting future adaptation and mitigation planning techniques to battle the effects of excessive heating in the sub-basin. [ABSTRACT FROM AUTHOR]

Understanding the spatiotemporal variations in climate extremes indices, as well as the influencing factors, is critical to the scientific response to climate change. The temporal and spatial variations of SU25 (annual count of days when daily maximum temperature > 25 °C) were discussed in this study, based on daily maximum temperature data from 2398 meteorological stations in China from 1961 to 2017. The contributions of associated large-scale circulation factors to SU25 were quantitatively assessed by using the geographical detector method (GMD). The overall spatial distribution of SU25 was marked by a considerable increase from north to south. The SU25 increased significantly over time, with the national SU25 increasing at a rate of 2.5 days/decade. The Tibet Plateau (TP) had the slowest growth rate, with an average increase rate of 1.4 days/decade. The Hurst values of SU25 in all the subregions were generally high, indicating that most stations of SU25 would continue to increase in the future. Except for TP, the tipping years of other subregions were concentrated in the 1990s, and SU25 increased after the years. Among the large-scale circulation factors affecting SU25 in each subregion, Atlantic Multidecadal Oscillation (AMO) played a major role in SU25 variability. As a whole, the result of the pairwise interaction of each circulation factor was mainly nonlinear enhancement. The joint contributions of multiple factors to SU25 were larger than the contribution of each individual factor. [ABSTRACT FROM AUTHOR]

In this work, the climatology, observed trends, and future projections of temperature and precipitation extremes are analysed in the drainage area of the Belo Monte Hydropower Plant in the Xingu River basin. Observed data come from gridded information for the period 1980–2013. The climate projections until the end of the 21st century are provided by the regional climate model Eta‐20 km nested to the global climate model MIROC5. Seventeen climate indicators were selected for this assessment, and statistical tests were used to evaluate the significance and magnitude of trends. A tropical climate predominates in the whole basin but with differences in the climatology of extreme temperature. The average annual rainfall (PRCPTOT) presents values between 1,500 and 2,200 mm. Remarkable contrasts of consecutive dry days (CDD) can also be seen. We found a warming signal during the examined period in much of the Xingu River basin, with an increase in the frequency of extremely warm days and nights. In the northern (south‐central) area of the basin, there is an increase (reduction) in precipitation. There is a contrasted and local distribution of detected trends in all climate extremes indices related to rainfall. CDD has displayed a considerable elevation in the south‐central area over the last decades. The study area exhibits statistically significant warming projections to the future climate. As for the precipitation projections, future changes are toward a dryer climate. We also found that dry periods may last longer in the following decades. Thus, heatwaves can be excited by subsequent days without precipitation in the basin in the future climate. The impacts of climate change on the balance of different environmental and socioeconomic sectors in this area must be wholly investigated. [ABSTRACT FROM AUTHOR]

Despite intense research on climate change (CC), regional studies for Central America, which is considered a CC hot spot, remain scarce. The information provided by general circulation models (GCMs) is too coarse to accurately reproduce local‐scale climatic features, which are needed for impact assessment. Thus, downscaling techniques are employed to address this scale mismatch. Costa Rica is the present case study, for which suitable predictors were tailored for downscaling related to regional climatic characteristics, such as the Inter‐Tropical Convergence Zone, El Niño Southern Oscillation, the Caribbean Low‐Level Jet, and the Mid‐Summer Drought. Statistical downscaling models were calibrated for precipitation, maximum and minimum temperature, using the perfect prognosis methodology by means of station data, ERA‐INTERIM reanalysis and artificial neural networks, yielding satisfactory results. As found in several studies, the temperature models replicated more accurately the statistics of the observed datasets. However, here, through the implemented approach and the tailored predictors, the precipitation models conveyed an improvement compared to standard methods. Projected daily climate was obtained employing CORDEX data under the RCP8.5 scenario for the central region of the country. Overall, the changes in climate estimated by the end of the 21st century agree with coarser‐scale projections. Finally, projected climate extremes indices were calculated and rendered further details on the intensity of future CC by the end of the century. [ABSTRACT FROM AUTHOR]

A broad spectrum of model-derived weather datasets are available in the US. Because each product integrates atmospheric conditions with different model processes, each produces different statistical biases. This study validated air temperature from NLDAS-2 and a novel statistically downscaled NLDAS-2 against observational weather station data for the state of Florida. We statistically downscaled NLDAS-2 to a 1-km grid product using MODIS land surface temperature. We investigated mean biases and Pearson correlation coefficients between daily observational data and the two model-derived datasets. We then calculated multiple Climate Extremes Indices to further scrutinize differences in capturing extreme temperatures. Finally, we quantified potential causes of systematic NLDAS-2 biases related to distance from the coast, urban heat island, land cover, and type of observational stations. Two model-derived datasets showed similar mean biases and correspondence with observational data, underestimating maximum temperature by 1°C and overestimating minimum temperature by 2°C. Extreme temperatures were well simulated in both datasets. However, we still found overestimated extreme minimum temperatures and underestimated extreme maximum temperatures. Systematic biases tended to be higher for coastal stations and grids having a high fraction of water. Our study suggests that including physical processes covering land surface and ocean interactions may improve the model accuracy. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper documents the changes in climate extremes over Indonesia during the past three decades (1983-2012) based on a subset of extreme indices recommended by the Expert Team on Climate Change Detection and Indices ( ETCCDI). The extreme indices were calculated based on the quality controlled daily observational data (minimum and maximum temperature and precipitation) from 88 weather stations. Overall, we found significant and spatially coherent trends of warming in the temperature indices over Indonesia, consistent with other studies conducted at different countries within the Southeast Asia. The frequency of cool days ( TX10p) and cools nights ( TN10p) had decreased whereas warm days ( TX90p) and warm nights ( TN90p) were observed more frequently. Averaged over the country, the annual mean of daily maximum ( TXmean) and minimum temperature ( TNmean) had increased significantly by 0.18 and 0.30 °C decade−1, respectively. Other temperature indices also showed significant warming trends. In contrast, trends in the precipitation extremes indices were generally not significant and less spatially coherent. However, a tendency towards wetter conditions was observed, in agreement with the results at the global scale. The daily precipitation intensity ( SDII) had increased significantly over the country by 0.21 mm day−1 decade−1 during the period studied. At the regional scale, we observed a significant wetting trend in the annual highest daily amount ( RX1day) and the rainfall amount contributed by the extremely very wet days (R99p) in the northern part of the country. The wetting trends of a number of extreme precipitation indices were depicted prominently in December-January-February ( DJF) and/or March-April-May ( MAM) seasons, both at country and regional levels. However, for the southern region of Indonesia, a drying tendency was observed for June-July-August ( JJA), September-October-November ( SON) and MAM. [ABSTRACT FROM AUTHOR]

Central America and the Caribbean are regularly battered by megadroughts, heavy rainfall, heat waves, and tropical cyclones. Although 21st-century climate change is expected to increase the frequency, intensity, and duration of these extreme weather events (EWEs), their incidence in regional protected areas (PAs) remains poorly explored. We examined historical and projected EWEs across the region based on 32 metrics that describe distinct dimensions (i.e., intensity, duration, and frequency) of heat waves, cyclones, droughts, and rainfall and compared trends in PAs with trends in unprotected lands. From the early 21st century onward, exposure to EWEs increased across the region, and PAs were predicted to be more exposed to climate extremes than unprotected areas (as shown by autoregressive model coefficients at p < 0.05 significance level). This was particularly true for heat waves, which were projected to have a significantly higher average (tested by Wilcoxon tests at p < 0.01) intensity and duration, and tropical cyclones, which affected PAs more severely in carbon-intensive scenarios. PAs were also predicted to be significantly less exposed to droughts and heavy rainfall than unprotected areas (tested by Wilcoxon tests at p < 0.01). However, droughts that could threaten connectivity between PAs are increasingly common in this region. We estimated that approximately 65% of the study area will experience at least one drought episode that is more intense and longer lasting than previous droughts. Collectively, our results highlight that new conservation strategies adapted to threats associated with EWEs need to be tailored and implemented promptly. Unless urgent action is taken, significant damage may be inflicted on the unique biodiversity of the region., (© 2024 The Authors. Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology.)

The occurrence of extreme climate events (ECEs) in the Amazon basin (AMZ) and northeast Brazil (NEB), such as torrential rains and severe droughts, varies in both spatial and temporal scales. Spatial analysis of trends allows observing changes in behaviour and determining in which regions a particular variable has been experiencing changes over time. Thus, the objective of this study is to analyse trends of 21 climate extremes indices, relative to maximum and minimum precipitation and temperature, as defined by the World Meteorological Organization, for the AMZ and NEB. The 21 indices were selected according to meteorological and climate characteristics of the regions. Through annual analysis it was possible to observe an increase in most of the climate extremes indices for air temperature in all AMZ and NEB subregions. As for extreme precipitation, only a few of the selected indices presented significant increase and/or decrease in their values. Overall, the eastern Amazon subregion in the AMZ presented the highest significant indices for temperature and precipitation. In NEB, both Northern Coast and Southern Coast subregions presented substantial increase or decrease in precipitation and temperature indices. Location of the reference points selected for each of the 11 homogeneous precipitation subregions in the AMZ and the NEB. [ABSTRACT FROM AUTHOR]

The most disastrous heatwaves are very extreme events with return periods of hundreds of years, but traditionally, climate research has focussed on moderate extreme events occurring every couple of years or even several times within a year. Here, we use three Earth System Model large ensembles to assess whether very extreme heat events respond differently to global warming than moderate extreme events. We find that the warming signal of very extreme heat can be amplified or dampened substantially compared to moderate extremes. This modulation is detectable already in mid-century projections. In the mid-latitudes, it can be explained by changes in event soil moisture-temperature coupling during the hottest day of the year. The changes depend on the interplay of present soil moisture and coupling during heat events as well as projected precipitation changes. This mechanism is robust across models, albeit with large spatial uncertainties. Our findings are highly relevant for climate risk assessments and adaptation planning. Climatic changes in extreme events are well studied, but research has so far focused on moderate extremes. The authors show that changes in very extreme heat events can be, depending on the region, much stronger or weaker than changes in moderate extremes. [ABSTRACT FROM AUTHOR]

While historical observations reveal increases in meteorological drought frequency across China during 1960–2021, future drought characteristics at the regional scale are uncertain. We evaluate historic and twenty-first-century-projected dryness changes using the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) 0.25° resolution dataset for representative concentration pathways (RCPs) 4.5 and 8.5. The 20-model NEX-GDDP ensemble mean precipitation and derived potential evapotranspiration, which is calculated by utilizing the Thornthwaite approach, are consistent with gridded station data over China from 1961 to 2005. Results show that the projections of occurrence frequency of moderate drought based on the standardized precipitation evapotranspiration index (SPEI) increase remarkably under the RCP4.5 scenario, and a significant increasing frequency is seen for severe drought under the RCP8.5 scenario, while few droughts of extreme dryness occur during the twenty-first century under both emission scenarios. More moderate drought projections are found over northwestern, northern, and southeastern regions under the RCP4.5 scenario, but all of China will face severe droughts for RCP8.5. The areas affected by moderate droughts begin to extend rapidly around 2030s at both national and regional scales for the RCP4.5 scenario, and the substantial increases in drying area extension for RCP8.5 appear around the 2050s. Particularly, the severe drought areas are found to grow much more sharply after the 2070s under the RCP8.5 scenario, implying that the occurrences of severe droughts over China are more sensitive to greenhouse gas emissions. Significance Statement: Both temperature and rainfall are closely associated with drought variability; therefore, this study examines the changes in frequency and intensity of projected droughts across China based on the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI). Severe droughts are projected to increase over most of the regions according to SPEI. The substantial increases in moderate and severe droughts are seen over all of China under the RCP4.5 and RCP8.5 scenarios, respectively. At the temporal scale, most of the areas are projected to experience more severe droughts by the end of twenty-first century, while the areas of moderate droughts are projected to exhibit fluctuating variations during the twenty-first century. These results indicate more future droughts, which may increase the vulnerability of more areas of China from exposure to the consequences of global warming. [ABSTRACT FROM AUTHOR]

This paper analyzes the heavy rainfall on 16–20 May 2021 across southeastern Texas and southern Louisiana. In Louisiana, five fatalities were attributed to the event and > $1 billion in losses. The rainfall was caused by two slow-moving, mesoscale convective vortices that concentrated precipitation south of Port Arthur, TX, Lake Charles, LA, and Baton Rouge, LA, in 6 to 12-hour periods. Using calibrated radar data, the Storm Precipitation Analysis System estimated 6-h rainfall totals of 254–362 mm south of Lake Charles, surpassing 200–500-year average recurrence intervals (ARI) for those locations, with an isolated area receiving 367.5 mm, equating to a > 800-year ARI. In East Baton Rouge Parish, LA, 203–268 mm was estimated in 6-h (200–500-year ARI), with an isolated area receiving 274 mm, equivalent to a 750-year ARI. A comparison of the May 2021 and August 2016 events, which both affected southern Louisiana, is made using a depth-area-duration analysis. While the forcing mechanisms differed, 1–6 h rainfall depths were similar at 1 –25,900 km2. The May 2021 event exceeded rainfall depths produced by the August 2016 event for 2–6 h durations for area sizes of 1–388 km2, highlighting the precipitation intensity produced by the May 2021 event. [ABSTRACT FROM AUTHOR]

South America has experienced significant changes in climate patterns over recent decades, particularly in terms of precipitation and temperature extremes. This study analyzes trends in climate extremes from 1979 to 2020 across South America, focusing on their relationships with sea surface temperature (SST) anomalies in the Pacific and Atlantic Oceans. The analysis uses precipitation and temperature indices, such as the number of heavy rainfall days (R10mm, R20mm, R30mm), total annual precipitation (PRCPTOT), hottest day (TXx), and heatwave duration (WSDI), to assess changes over time. The results show a widespread decline in total annual precipitation across the continent, although some regions, particularly in the northeast and southeast, experienced an increase in the intensity and frequency of extreme precipitation events. Extreme temperatures have also risen consistently across South America, with an increase in both the frequency and duration of heat extremes, indicating an ongoing warming trend. The study also highlights the significant role of SST anomalies in both the Pacific and Atlantic Oceans in driving these climate extremes. Strong correlations were found between Pacific SST anomalies (Niño 3.4 region) and extreme precipitation events in the northern and southern regions of South America. Similarly, Atlantic SST anomalies, especially in the Northern Atlantic (TNA), exhibited notable impacts on temperature extremes, particularly heatwaves. These findings underscore the complex interactions between SST anomalies and climate variability in South America, providing crucial insights into the dynamics of climate extremes in the region. Understanding these relationships is essential for developing effective adaptation and mitigation strategies in response to the increasing frequency and intensity of climate extremes. [ABSTRACT FROM AUTHOR]

With an estimated 357.7 million internal displacements caused since 2008, weather-related disasters are a major driver of human mobility worldwide. As climate change is projected to increase the frequency and intensity of extreme weather events in many parts of the world, it is important to better understand how trends in weather patterns related to global warming have affected the intensity of disasters that have caused displacements. Here we combined observational and counterfactual climate data with global internal displacement records to estimate how climate change has affected precipitation and wind speeds at the time and location of floods and storms that led to internal displacements. We estimate that, on average, climate change increased precipitation and decreased wind speeds during such events by +3.7% and − 1.4%, respectively. However, the variability across events is considerable (±28.6 and ± 6.6%, respectively), highlighting the large signal of natural variability of the weather system as compared to the global warming signal. Our results caution against overstating the role of climate change in displacement-inducing disasters in the past, especially compared to socio-economic and development factors of vulnerability and adaptive capacity that determine whether weather-related hazards turn into disasters.' [ABSTRACT FROM AUTHOR]

Understanding precipitation properties at regional scales and generating reliable future projections is crucial in providing actionable information for decision-makers, especially in regions with high vulnerability to climate change, where future changes impact ecosystem resilience, biodiversity, agriculture, water resources and human health. The South America Convection-Permitting Regional Climate Model experiment (SA-CPRCM) examines climate change effects in convection-permitting simulations at 4.5 km resolution, on climate time scales (10 year present-day and 10-year future RCP8.5 around 2100), over a domain covering most of South America, using the Met Office Unified Model (UM) convection-permitting RCM. Under the RCP8.5 scenario, precipitation in the CPRCM decreases, becomes less frequent and more seasonal over the Eastern Amazon region. Dry spells lengthen, increasing the risk of drought. In the Western Amazon, precipitation increases in the wetter austral autumn (Apr. – Jun.) and decreases in the drier austral winter and spring (July – Oct.), leading to a more distinct dry season and imposing a greater risk of contraction of the tropical forest. Over South-eastern Brazil, future precipitation increases and becomes more frequent and more intense, increasing the risk of floods and landslides. A future increase in the intensity of precipitation and extremes is evident over all these regions, regardless of whether the mean precipitation is increasing or decreasing. The CPRCM and its driving GCM respond in a similar way to the future forcing. The models produce broadly similar large-scale spatial patterns of mean precipitation and comparable changes to frequency, intensity, and extremes, although the magnitude of change varies by region and season. [ABSTRACT FROM AUTHOR]

This study aims to detect changes in rainfall variability caused by climate change for various scenarios in the CMIP6 (Coupled Model Intercomparison Project Phase 6) multi-model ensemble. Projected changes in rainfall unevenness in terms of different timescale indices using three categories, namely WD50 (number of wettest days for half annual rainfall), SI (seasonality index), and DWR (ratio of dry-season to wet-season rainfall) are analyzed in Zengwen Reservoir watershed, southern Taiwan over near future (2021–2040) and midterm future (2041–2060) relative to the baseline period (1995–2014) under SSP2-4.5 and SSP5-8.5 scenarios. The projected rainfall for both baseline and future periods is derived from 25 GCMs (global climate models). The results indicate that noticeably deteriorated rainfall unevenness is projected in the Zengwen Reservoir watershed over future periods, which include decreased WD50, increased SI, and decreased DWR. Though there were noticeable differences in the rainfall projections by the different GCMs, the overall consensus reveals that uncertainties in future rainfall should not be ignored. In addition, WD50 has the greatest deviated relative change in mean, which implies that the short-timescale rainfall unevenness index is easily affected by climate change in the study area. Distributional changes in rainfall unevenness determined by simultaneously considering alterations in relative changes in mean and standard deviation indicated that there was no single dominant category. However, the top two categories, with summed frequencies exceeding 0.5, characterize different properties of rainfall unevenness indices. The top two categories of WD50 and SI commonly have decreased mean and increased mean, respectively, but nearly equal frequencies of the top two categories in DWR exhibit opposite variations. The proposed rainfall unevenness change detection approach provides a better understanding of the impacts of climate change on rainfall unevenness, which is useful for preparing adaptive mitigation measures for coping with disasters induced by climate change. [ABSTRACT FROM AUTHOR]

Shifting precipitation regimes are a well-documented and pervasive consequence of climate change. Subsistence-oriented communities worldwide can identify changes in rainfall patterns that most affect their lives. Here we scrutinize the importance of human-based rainfall observations (collated through a literature review spanning from 1994 to 2013) as climate metrics and the relevance of instrument-based precipitation indices to subsistence activities. For comparable time periods (1955-2005), changes observed by humans match well with instrumental records at same locations for well-established indices of rainfall (72% match), drought (76%), and extreme rainfall (81%), demonstrating that we can bring together human and instrumental observations. Many communities (1114 out of 1827) further identify increased variability and unpredictability in the start, end, and continuity of rainy seasons, all of which disrupt the cropping calendar, particularly in the Tropics. These changes in rainfall patterns and predictability are not fully captured by existing indices, and their social-ecological impacts are still understudied.This paper provides an analysis or rainfall changes that integrates human-based and instrument-based observations, identifying regions of agreement and disagreement, and providing insights on how traditional ecological knowledge can complement instrumental indices. [ABSTRACT FROM AUTHOR]

In the context of increasingly frequent and severe climate extremes, an understanding of the impacts of these events on gross primary production (GPP) and thus on land carbon uptake is crucial. However, research utilizing new model outputs to assess the future trends, characteristics, and driving factors of GPP reduction associated with extreme events remains limited. Here, we use model outputs from Phase Six of the Coupled Model Intercomparison Project (CMIP6) to investigate the spatiotemporal patterns of negative GPP extreme events during the 21st century. We find a notable increase in negative GPP extremes globally under the SSP5‐8.5 scenario. They are characterized by longer durations and larger sizes, despite the smaller number of events. Under the SSP1‐2.6 scenario, while the total negative GPP extremes remain relatively stable, hotspots, including tropical forests, southern China, and boreal forest zones, still experience increases in negative extremes. By attributing these GPP extremes to climate conditions, we identified compound hot and dry conditions, which contributed to over 40% of the negative GPP extremes under both scenarios, as the dominant driver, followed by single‐driver dry conditions. Under SSP5‐8.5, the increasing contribution of compound hot and dry conditions leads to greater GPP reductions through prolonged and intensified negative extreme events. Compared with CMIP5 models, CMIP6 models project an asymmetry of negative and positive GPP extreme events that favors more negative extremes across most regions. Our findings highlight the escalating damage from climate extremes on future ecosystem productivity, emphasizing the urgent need for effective mitigation and adaptation actions. Plain Language Summary: In a world facing more frequent and severe climate extremes, an understanding of how these events affect plant growth and the uptake of CO2 by terrestrial ecosystems is crucial. Our study uses outputs from Earth system models in Coupled Model Intercomparison Project (CMIP6) to analyze the future trends and driving forces of negative extreme events in gross primary production (GPP). We found that under a high‐emission scenario (SSP5‐8.5), global GPP loss linked to negative extreme events of increasing severity and duration almost doubled by the end of the 21st century compared with current levels. Under a strong mitigation scenario (SSP1‐2.6), negative GPP extremes increase in regions such as tropical forests, southern China, and boreal forest zones despite a relatively stable global total GPP loss. Compound hot and dry conditions, the main driver of negative GPP extremes, contributed to more than 40% of the GPP extremes under both scenarios. Compared with those in CMIP5, the latest models in CMIP6 project more negative GPP extremes than positive extremes across most regions. These results emphasize the urgent need for action to mitigate and adapt to the escalating damage caused by climate extremes on future ecosystem productivity. Key Points: A notable increase in negative gross primary production (GPP) extremes is found under SSP5‐8.5, characterized by longer durations and greater magnitudes of eventsCompound hot and dry conditions are the dominant driver, contributing to >40% of the negative GPP extremes under both SSP5‐8.5 and SSP1‐2.6Compared with CMIP5, the Coupled Model Intercomparison Project (CMIP6) models project more negative GPP extremes than positive extremes across most regions [ABSTRACT FROM AUTHOR]

Global warming has led to an increasing frequency and intensity of extreme precipitation events worldwide. The extreme precipitation of Henan Province in central China usually occurs in summer, with the climate transition from the northern subtropical to the warm temperate climate. Compared with the study of extreme precipitation events in other regions, the study of Henan Province pays less attention. In order to systematically understand the spatial and temporal characteristics of extreme precipitation in Henan Province, this study applied RClimDex model to obtain nine extreme precipitation indices based on daily precipitation data from 90 meteorological stations from 1981 to 2020. Linear propensity estimation, M-K mutation test, Morlet wavelet analysis, and geostatistical analysis were used to investigate the spatial and temporal variation characteristics of the extreme precipitation indices in the region. The results indicated that continuous dry days (CDD), number of heavy rain days (R20mm), maximum daily precipitation (Rx1day), maximum precipitation for 5 consecutive days (Rx5day), and precipitation intensity (SDII) showed an overall increasing trend, but none passed the significance test (p > 0.01). Extremely strong precipitation (R99p) and Rx5day changed abruptly in 1994, and Rx1day and SDII changed abruptly in 2004. The seven extreme precipitation indices, except CDD and continuous wet days (CWD), had a 30-year cyclical pattern. The multi-year average of extreme precipitation indices showed that the CDD gradually decreased from north to south, CWD and R20mm gradually increased from north to south. Rx1day and Rx5day gradually increased from northwest to southeast, and SDII increased from west to east. The results can contribute valuable insights to extreme precipitation trends and future climate predictions in Henan Province and provide scientific support for coping with extreme precipitation changes and disaster prevention. [ABSTRACT FROM AUTHOR]