The occurrence of extreme heat events offset CO2 fertilization and deteriorate grain quality in double cropping rice systems under projected climate change

Modelling the occurrence of heat waves in maximum and minimum temperatures over Spain and projections for the period 2031-60

Concurrent extreme events, i.e. multi-variate extremes, can be associated with strong impacts. Hence, an understanding of how such events are changing in a warming climate is helpful to avoid some associated climate change impacts and better prepare for them. In this article, we analyse the projected occurrence of hot, dry, and wet extreme events’ clusters in the multi-model ensemble of the 6th phase of the Coupled Model Intercomparison Project (CMIP6). Changes in ‘extreme extremes’, i.e. events with only 1% probability of occurrence in the current climate are analysed, first as univariate extremes, and then when co-occurring with other types of extremes (i.e. events clusters) within the same week, month or year. The projections are analysed for present-day climate (+1 °C) and different levels of additional global warming (+1.5 °C, +2 °C, +3 °C). The results reveal substantial risk of occurrence of extreme events’ clusters of different types across the globe at higher global warming levels. Hotspot regions for hot and dry clusters are mainly found in Brazil, i.e. in the Northeast and the Amazon rain forest, the Mediterranean region, and Southern Africa. Hotspot regions for wet and hot clusters are found in tropical Africa but also in the Sahel region, Indonesia, and in mountainous regions such as the Andes and the Himalaya.

Reviewing recent literature, we report that changes in extreme heat event characteristics such as magnitude, frequency, and duration are highly sensitive to changes in mean global-scale warming. Numerous studies have detected significant changes in the observed occurrence of extreme heat events, irrespective of how such events are defined. Further, a number of these studies have attributed present-day changes in the risk of individual heat events and the documented global-scale increase in such events to anthropogenic-driven warming. Advances in process-based studies of heat events have focused on the proximate land-atmosphere interactions through soil moisture anomalies, and changes in occurrence of the underlying atmospheric circulation associated with heat events in the midlatitudes. While evidence for a number of hypotheses remains limited, climate change nevertheless points to tail risks of possible changes in heat extremes that could exceed estimates generated from model outputs of mean temperature. We also explore risks associated with compound extreme events and nonlinear impacts associated with extreme heat.

Surface turbulent heat flux is the most direct variable denoting air‐sea interactions. In wintertime North Pacific, in addition to the Kuroshio‐Oyashio extension (KOE) region, high‐resolution observations show that the North Pacific subtropical region (NPSR) is also characterized with high surface heat flux, whose characteristics need systematic investigation. In this study, the extreme surface turbulent heat flux events in the NPSR are investigated using daily observational data. Our results show that the extreme events exhibit dipolar changes of surface flux over NPSR and KOE regions, lasting for several days. Though with a spatially correlated pattern, the occurrence of extreme events in NPSR and KOE is found greatly independent. In the extreme events, both surface sensible and latent heat fluxes display evident changes in north NPSR, while in south NPSR the change in surface latent heat flux dominates. The formation of extreme events in the NPSR is mainly determined by anomalous atmospheric circulation. Changes in the intensity of subtropical high influence the surface air wind speed, humidity, and temperature, contributing to the formation of extreme events in the NPSR. Our results further suggest that the processes through which the extreme events affect the atmospheric precipitation may be different in south and north NPSR. In south NPSR, the change of precipitation in extreme events is very likely attributed to the change of surface latent heat flux. In north NPSR, the change of water vapor transport by atmospheric circulations is found to play a major role.

As one of the most important extreme weather event types, extreme precipitation events have significant impacts on human and natural environment. This study assesses the projected long term trends in frequency of occurrence of extreme precipitation events represented by heavy precipitation days, very heavy precipitation days, very wet days and extreme wet days over Ontario, based on results of 21 CMIP3 GCM runs. To achieve this goal, first, all model data are linearly interpolated onto 682 grid points (0.45° × 0.45°) in Ontario; Next, biases in model daily precipitation amount are corrected with a local intensity scaling method to make the total wet days and total wet day precipitation from each of the GCMs are consistent with that from the climate forecast system reanalysis data, and then the four indices are estimated for each of the 21 GCM runs for 1968–2000, 2046–2065 and 2081–2100. After that, with the assumption that the rate parameter of the Poisson process for the occurrence of extreme precipitation events may vary with time as climate changes, the Poisson regression model which expresses the log rate as a linear function of time is used to detect the trend in frequency of extreme events in the GCMs simulations; Finally, the trends and their uncertainty are estimated. The result shows that in the twenty-first century annual heavy precipitation days, very heavy precipitation days and very wet days and extreme wet days are likely to significantly increase over major parts of Ontario and particularly heavy precipitation days, very wet days are very likely to significantly increase in some sub-regions in eastern Ontario. However, trends of seasonal indices are not significant.

ABSTRACTThe concurrent occurrences of drought and extreme heat events, such as heatwaves, present substantial threats to human health and ecosystems. This study delves into a thorough examination of the collective impacts of drought and extreme heat events in Southeast Asia (SEA) over the past 83 years (1941–2023). Two primary definitions guided the investigation: Compound Drought and Heatwave Events (CDHW) and Compound Hot Droughts (CHD). The Wet‐Bulb Globe Temperature (WBGT) was employed to define heatwaves and extreme hot events, while the Standardised Precipitation Evapotranspiration Index (SPEI) was used for drought definition. In addition, the study explored the impact of linear detrending on copula fitting, assessing its effects. The findings of the study consistently revealed a strong positive correlation between drought and heatwaves in CDHW. On the other hand, CHD exhibited varied correlation patterns across regions. Furthermore, the study highlighted that linear detrending had a lower sensitivity in CDHW compared to CHD. The analysis uncovered significant regional disparities in the joint return period ranking of compound events, stemming from diverse copula analysis approaches. Particularly in non‐continental SEA, notably in some regions like Sumatra Island, a noteworthy distinction between CDHW and CHD emerged, indicating the limited applicability of CHD in scenarios with stringent concurrence of compound events. These insights provide valuable assistance to the research community, aiding in the discernment of the distinctions between CDHW and CHD in drought and heat‐event assessment.

Focal Area: This white paper proposes advanced data-driven and computing techniques to improve the predictability of extreme climate events (precipitation) and focuses on comprehending their impact dynamics to enhance resilience of urban systems. Science Challenge: In urban systems, climate change has presented significant challenges related to accurate spatiotemporal prediction of extreme climate events (heavy precipitation) and their impacts, i.e. flooding. The occurrence of extreme climate events and their compounding repercussions on the built environment make urban systems increasingly more vulnerable. The interactions between extreme climate events, urban systems, and the corresponding impacts are irregular, non-linear, and dynamic, making it difficult to standardize resilience. As it stands, the management of complex urban systems is affected by uncertainties related to the nature of short- and long-term consequences caused by extreme events.

In our changing climate we expect an increase in the frequency of heatwaves, which are extreme events that can have severe consequences for human health, ecosystems, and economies. In this study, we examine how the weakening of the atlantic meridional overturning circulation (AMOC) may influence the occurrence of extreme warm events in Europe. Our analysis is based on a series of numerical experiments conducted using the EC-Earth3 climate model, which includes three ensembles of 20 Atmospheric Model Intercomparison Project-like members. The large ensemble size makes these simulations well-suited to studying rare extreme events. Our findings reveal that during boreal summer, the Northern hemisphere (NH) experiences overall mean cooling, most pronounced in the North Atlantic region. Therefore, the extreme warm events in Europe identified by using a fixed threshold tend to be less frequent. However, the cooling pattern reduces the meridional gradient of near-surface air temperature at high latitudes of the NH. As a result, the speed of the summer jet stream decreases, while the frequency of Ural atmospheric blocking events increases. Atmospheric blocking in summer is closely linked to heatwaves, primarily through subsidence warming and enhanced downward shortwave radiation under clear sky conditions. Consequently, the weakening of the AMOC leads to an increased frequency of heatwaves in Eastern Europe, the only region that presents this opposite trend. This study highlights the significant role that three-dimensional ocean circulation plays in shaping weather patterns, including extreme events such as heatwaves in Europe. These findings have important implications for future climate projections, as the AMOC is expected to weaken by the end of this century. Thus, as the Earth continues to warm, we may face an increased risk of heatwaves due to the combined effects of global warming and a weakening AMOC.

Global warming in the 21st century will alter the frequency of extreme climatic events, such as high-temperature anomalies and “heat waves”. Observations of extreme high temperatures during recent decades have detected upward trends in their frequency of occurrence, and recent state-of-the-art Global Climate Models (GCMs), e.g., Climate Model Intercomparison Projects (CMIPs), notably CMIP5 and CMIP6, have predicted acceleration of temperature trends and high-temperature events by 2100 under projected greenhouse-gas emission scenarios. Hence, the 21st century is expected to experience substantial shifts in the occurrence of extreme events, where present-day, extreme-but-rare high-temperature events will become common during the summer months. The increasing frequency of extreme heat may affect the health and resiliency of social, biological, and infrastructure systems in many regions worldwide, underscoring the need for accurate and reliable long-term assessments of climatic change across global and regional scales. So far, many investigations of high-temperature extremes have been carried out under end-point scenarios, e.g., by comparing GCM-projected changes in the frequency of high-temperature extremes expected in the late 21st century to the late 20th century. In this study, we use extreme value theory and decades of observations of high-temperature extremes at thousands of meteorological stations across North America to investigate continuous shifts in the frequency of extreme high-temperature events due to projected local warming trends. We find that the odds of exceedance of 50-year extreme high-temperature events increases exponentially with increases in mean local temperature. At a majority of the stations studied here, a local mean temperature increase of 0.5–1 ^{circ }C can double the odds of exceedance of 50-year extreme high-temperature events. Based on time-dependent temperature projections, the odds of exceedance of 50-year extreme high-temperature events doubles approximately every 20 years (or sooner) for sim 96% of the stations. Moreover, we find that, for sim 80% of the stations in North America, investigated here, the 50-year extreme high-temperature events will be exceeded annually before 2100.

Due to a continuous increase in global temperature, the climate has been changing without sign of alleviation. An increase in the air temperature has caused changes in the hydrologic cycle, which have been followed by several emergencies of natural extreme events around the world. Thailand is one of the countries that has incurred a huge loss in assets and lives from the extreme flood and drought events, especially in the northern part. Therefore, the purpose of this study was to assess the hydrological regime in the Yom and Nan River basins, affected by climate change as well as the possibility of extreme floods and droughts. The hydrological processes of the study areas were generated via the physically-based hydrological model, namely the Soil and Water Assessment Tool (SWAT) model. The projected climate conditions were dependent on the outputs of the Global Climate Models (GCMs) as the Representative Concentration Pathways (RCPs) 2.6 and 8.5 between 2021 and 2095. Results show that the average air temperature, annual rainfall, and annual runoff will be significantly increased in the intermediate future (2046–2070) onwards, especially under RCP 8.5. According to the Flow Duration Curve and return period of peak discharge, there are fluctuating trends in the occurrence of extreme floods and drought events under RCP 2.6 from the future (2021–2045) to the far future (2071–2095). However, under RCP 8.5, the extreme flood and drought events seem to be more severe. The probability of extreme flood remains constant from the reference period to the near future, then rises dramatically in the intermediate and the far future. The intensity of extreme droughts will be increased in the near future and decreased in the intermediate future due to high annual rainfall, then tending to have an upward trend in the far future.

<p>Existing databases for extreme weather events such as floods, heavy rainfall events, or droughts are heavily reliant on authorities and weather services manually entering details about the occurrence of an event. This reliance has led to a massive geographical imbalance in the likelihood of extreme weather events being recorded, with a vast number of events especially in the developing world remaining unrecorded. With continuing climate change, a lack of systematic extreme weather accounting in developing countries can lead to a substantial misallocation of funds for adaptation measures. To address this imbalance, in this pilot study we combine socio-economic data with climate and geographic data and use several machine-learning algorithms as well as traditional (spatial) econometric tools to predict the occurrence of extreme weather events and their impacts in the absence of information from manual records. Our preliminary results indicate that machine-learning approaches for the detection of the impacts of extreme weather could be a crucial tool in establishing a coherent global disaster record system. Such systems could also play a role in discussions around future Loss and Damages.</p>

Urbanization has been shown to significantly increase the frequency and intensity of extreme weather events, i.e., extreme precipitation events, and heatwave events. Actually, the occurrence of compound extreme events, such as sequential flood-heatwave (SFH) events, can lead to more severe impacts than singular extreme events. However, the impact of urbanization on these compound extreme events is not well understood. In this study, we examine urbanization effects on the growth of SFH events in the Guangdong-Hong Kong-Macao Greater Bay Area from 1961 to 2017. We classify stations into urban and rural types based on dynamic land use data and define SFH events using the criteria from previous studies. We find that the frequency of SFH events in urban stations increased from 0.218 events per year before the 1990s to 1.401 events per year after the 1990s, while the frequency of SFH events in rural stations increased from 0.250 events per year to 0.920 events per year. The urban impact of 0.131 events per decade also shows that urbanization can promote the occurrence of SFH events. Our analysis also indicates that urbanization promotes the growth of SFH events mainly by increasing the frequency of heatwave (HW) events. These findings highlight the need for further research on the effects of urbanization on compound extreme events and the development of effective management strategies to reduce their risks.

Brazilian agricultural production stands out in world food security, accounting for a large part of the food produced worldwide. However, occurrence of extreme climate events is a challenge for the sector across the country. Thus, this study aims to assess extreme climate events impacts on Brazilian agricultural production. The loss index was calculated using crop data made available by the IBGE from 2005 to 2017, while data on the occurrence of extreme climate events (2002-2017) was obtained from literature. Data related to PROAGRO (2010-2018) and the Crop Assurance Program (2002-2016) were obtained from reports made available by the relevant agencies. Results showed high drought-induced production losses, mainly maize and beans produced in the Caatinga biome, and soybean and wheat in the Southeastern and Southern regions of the country. Hail and frost events also caused reductions in soybean and rice production in the Southeastern and Southern regions. Those impacts on the Brazilian agricultural production, in different regions, might have serious consequences on the availability and access of food to the population in the country.

Climate Change and Extreme Events

This work examines drought and flood events over Kenya from 1981 to 2016 using the Standardized Precipitation–Evapotranspiration Index (SPEI). The spatiotemporal analysis of dry and wet events was conducted for 3 and 12 months. Extreme drought incidences were observed in the years 1987, 2000, 2006, and 2009 for SPEI-3, whilst the SPEI-12 demonstrated the manifestation of drought during the years 2000 and 2006. The SPEI showed that the wettest periods, 1997 and 1998, coincided with the El Nino event for both time steps. SPEI-3 showed a reduction in moderate drought events, while severe and extreme cases were on the increase tendencies towards the end of the twentieth century. Conversely, SPEI-12 depicted an overall increase in severe drought occurrence over the study location with ab observed intensity of −1.54 and a cumulative frequency of 64 months during the study period. Wet events showed an upward trend in the western and central highlands, while the rest of the regions showed an increase in dry events during the study period. Moreover, moderate dry/wet events predominated, whilst extreme events occurred least frequently across all grid cells. It is apparent that the study area experienced mild extreme dry events in both categories, although moderately severe dry events dominated most parts of the study area. A high intensity and frequency of drought was noted in SPEI-3, while the least occurrences of extreme events were recorded in SPEI-12. Though drought event prevailed across the study area, there was evidence of extreme flood conditions over the recent decades. These findings form a good basis for next step of research that will look at the projection of droughts over the study area based on regional climate models.