The storm intensified as it continued northwards towards the island of Taiwan, becoming a category 4-equivalent Typhoon on the 24th, with maximum (10-minute) sustained winds of 185 km/h. It made a prolonged landfall in northeast Taiwan on the 24th, bringing both heavy rain and high winds that killed 10 people and injured more than 900, while the agricultural sector reported damages of roughly US$50 million (FocusTaiwan, 2024a, FocusTaiwan, 2024b). It subsequently made landfall as a weaker, but still destructive tropical storm on mainland China on July 25. Gaemi brought heavy rainfall to coastal and inland regions, particularly the Hunan province, as it weakened to a tropical depression. Cyclone-based rainfall is uncommon so far inland in China and the heavy precipitation led to flooding and a mudslide that killed 15 people, and another 15 people in neighbouring provinces.35 remained missing a week after the disaster, and 290,000 people were evacuated (CNN, 2024).

The influence of climate change on tropical cyclones is complex compared to other types of extreme weather events. However, attribution studies are increasingly focusing on these destructive events. Rapid attribution studies to date have focused primarily on severe rainfall from such storms. Here, we use several different approaches to investigate the influence of climate change on multiple aspects of Typhoon Gaemi. The study focuses on the three geographic regions that experienced severe impacts – northern Philippines, the island of Taiwan and Hunan province, and analyse whether and to what extent human-induced climate change affected wind speeds and rainfall. To study the conditions that formed and fuelled Gaemi, we also analyse the role of climate change in high sea surface temperatures and potential intensity, a metric combining sea surface temperature, air temperature and air humidity data to predict maximum typhoon wind speeds. The study combines the established World Weather Attribution protocol with a new approach using the Imperial College Storm Model (IRIS) to analyse the role of human-induced climate change in tropical cyclones. 

Main findings

• Typhoon Gaemi brought destructive winds and rainfall to large regions of southeast Asia, including the northern Philippines, Taiwan, and Hunan . At least 90 people were killed, thousands were injured and hundreds of thousands had to leave their homes. The extreme rainfall and high winds triggered landslides, widespread power outages and severe damage to infrastructure and agriculture. 
• In today’s climate, that has already been warmed by 1.2C due to the burning of fossil fuels, weather observations indicate that rainfall events as severe as those brought by Typhoon Gaemi now occur about once every 20 (5 – 30) years in the northern Philippines, about once every 5 (1.5 – 20) years in Taiwan, and about once every 100 (90 – 160) years in Hunan province.
• To determine the role of climate change we combine observations with climate models. In Taiwan and Hunan, the rainfall was about 14% and 9% heavier respectively due to climate change, and in both regions, the rainfall total was made about 60% more likely by climate change. If the world continues to burn fossil fuels, causing global warming to reach 2°C above pre industrial levels, devastating Typhoon rainfall events in both regions will become 30-50% more likely.
• In the northern Philippines, the analysis did not identify a significant trend up to today. Observations indicate that 3-day rainfall events have increased by about 12%, however, there is large uncertainty in these data sets. Climate models suggest both increases and decreases in rainfall in the current climate, but an increase in a future climate with 2°C of warming. 
• The IRIS model was used to investigate Gaemi’s strong winds by analysing category 4-equivalent storms in the Western North Pacific basin, a region that includes the South China and Philippine seas.
• By statistically modelling storms in a 1.2°C cooler climate, this model showed that climate change was responsible for an increase of about 30% in the number of such storms (now 6-7 times per year, up from 5 times), and equivalently that the maximum wind speeds of similar storms are now 3.9 m/s (around 7%) more intense.
• The conditions that formed and fueled Typhoon Gaemi were studied for links to climate change, using potential intensity and sea surface temperatures surrounding the storm track in July 2024. These conditions occur about every second year for potential intensity and about once every 15 years for sea surface temperatures.
• The influence of climate change on potential intensity is highly uncertain, as observations show a very large increase with warming (about a factor of 100 and a potential intensity increase of 6 m/s) that climate models do not capture. Sea surface temperatures as hot as those observed in July 2024 were almost impossible without climate change and have become about 1 degree warmer. If global warming reaches 2°C, sea surface temperatures are projected to be another 0.6°C warmer, and the conditions associated with Typhoon Gaemi will continue to increase in likelihood by a further factor of about 10. 
• Together, these findings indicate that climate change is enhancing conditions conducive to Typhoons, and when they occur the resulting rainfall totals and wind speeds are more intense. This is in line with other scientific findings that tropical cyclones are becoming more intense and wetter under climate change.
• Rural communities with climate sensitive livelihoods (e.g. agriculture), the urban poor residing in the lowest lying land, and those living on exposed hillsides susceptible to landslides were the most affected by the multitude of hazards stemming from the typhoon. 
• The regions affected by Typhoon Gaemi have early warning systems and comprehensive emergency response systems in place for tropical cyclones that help manage impacts. Flood risk associated with extreme rainfall is well-assessed in the affected regions, but existing urban plans and flood control infrastructure are not able to withstand the more extreme floods that are driven by climate change. Unplanned urban development, including in Metro Manila where the population has rapidly increased, is increasing the number of people at risk, especially in lower lying informal areas.

Researchers from India, Sweden, the United States, and the United Kingdom collaborated to assess to what extent human-induced climate change altered the likelihood and intensity of extreme rainfall that led to devastating  landslides and floods.

The soils in Wayanad were highly saturated, which is common in the region during the rainy monsoon season, meaning the meteorological cause of the landslide was the heavy rainfall on the preceding day of the event. Wayanad has been determined to be the most susceptible district to landslides in Kerala  (Sharma, Saharia & Ramana, 2024). 

To characterise the event, we analyse the 1-day maximum rainfall (RX1day) during the monsoon season from June to September, focusing on a region of northern Kerala (red outline, figure1). 

Main findings

• The Wayanad landslides resulted in devastating loss of life and occurred in a mountainous region with loose, erodible soils after 140mm of precipitation fell on saturated soils. 
• In today’s climate, which is 1.3°C warmer than it would have been at the beginning of the industrial period, an event of this magnitude is expected to occur about once every 50 years. The event is the third heaviest 1-day rainfall event on record, with heavier spells in 2019 and in 1924, and surpasses the very heavy rainfall in 2018 that affected large regions of Kerala.
• To assess if human-induced climate change influenced the heavy rainfall, we first determine if there is a trend in the observations. Heavy one-day rainfall events have become about 17% more intense in the last 45 years, over a period when the climate has warmed by 0.85°C. Longer-term trends in the pre-satellite era are not clear, which may relate to lower quality weather data. 
• To quantify the role of human-induced climate change we analyse climate models with high enough resolution to capture precipitation over the relatively small study region. Overall, the available climate models indicate a 10% increase in intensity. Under a future warming scenario where the global temperature is 2°C higher than pre-industrial levels, climate models predict even heavier 1-day rainfall events, with a further expected increase of about 4% in rainfall intensity. 
• Given the small mountainous region with complex rainfall-climate dynamics, there is a high level of uncertainty in the model results. However, the increase in heavy one-day rainfall events is in line with a large and growing body of scientific evidence on extreme rainfall in a warming world, including in India, and the physical understanding that a warmer atmosphere can hold more moisture, leading to heavier downpours. 
• While the extreme rainfall was well forecast by the Indian Meteorological Department (IMD) and warnings were issued, the information was at the state-level, making it difficult to discern which localities would be impacted by landslides (one of the potential impacts of heavy rainfall listed in the warning) and would therefore require evacuation. Slope-specific landslide early warning systems can be extremely costly and difficult to implement, but those would provide the best opportunity for effective early action. Given this, reducing exposure of people and assets to landslide-prone places may be a more effective strategy. 
• While the linkage between land cover and land use changes and landslide risk in Wayanad is mixed in the limited existing studies, factors such as quarrying for building materials, and a 62% reduction in forest cover, may have contributed to the increased susceptibility of the slopes to landslides when the heavy rain fell. 
• The increase in climate change-driven rainfall found in this study is likely to increase the potential number of landslides that could be triggered in the future, raising the need for adaptation actions that may include the reinforcement of susceptible slopes, landslide early warning systems, and construction of retaining structures to protect vulnerable localities. 

These episodes occurred just outside of the region’s main winter rainfall season, which runs from November to early April. The unusually high rains and subsequent floods in April and May followed a three-month dry period from December to March

Researchers from Pakistan, the Netherlands, Sweden, the United States, Canada, France, Germany, and the United Kingdom collaborated to assess to what extent human-induced climate change altered the likelihood and intensity of the weather conditions at the time of the most impactful floods. 

To analyse the event, we focus on a region centred on Afghanistan, bounded on the west by the Iranian provinces of Razavi Khorasan, Sistan and Baluchestan, Hormozgan, Kerman, and South Khorasan, and on the east by Balochistan and Khyber Pakhtunkhwa provinces of Pakistan. This area covers the flood-impacted regions through April and May 2024. Due to the atypicality of this season, occurring outside of the usual rainfall period and featuring an unusual number of storms that made it wetter than normal, we choose the seasonal accumulated precipitation during April and May for the temporal definition. Fig. 1 shows the total rainfall during April-May 2024 and the anomaly with respect to 1991-2020 average, over the region.

Main findings 

• Afghanistan and Pakistan are highly vulnerable to flooding due to factors such as limited transboundary water management, unplanned urban expansion, and deforestation which are contributing to increased flood risks, in combination with socio-economic conditions and compounding natural hazards, e.g. earthquakes, landslides, and drought. While Iran is less vulnerable than the other countries studied, urban infrastructure-related vulnerabilities in some cities in the northeast contributed to the impacts.
  
• The floods also occurred on top of existing vulnerabilities linked to complex crises. Displaced populations were particularly impacted, especially as limited essential infrastructure was destroyed and already vulnerable populations were exposed to more waterborne diseases.
  
• The event, despite occurring outside the usual rainy season, is not a particularly rare event in today’s climate that has been warmed by 1.2°C with a return time of about ten years under the current El Niño Southern Oscillation (ENSO) conditions. 
• The declining El Niño Southern Oscillation, a naturally occurring climate phenomenon, is  important to explain the variability in the observed rainfall, consistent with previous research. In observations, as compared to a neutral ENSO year, the declining El Niño resulted in a consistent increase across all datasets by a factor of about two  in likelihood and about 8% in intensity.
• To assess the role of human-induced climate change we combine observation-based products and climate models that include the observed ENSO relationship and assess changes in the likelihood and intensity for the heavy rainfall in the study region. While the last 40 years of  observational data show an increase, climate models have a very different signal, depending on the model, with some showing an increase and some a decrease. Consequently, without further analysis into why the models show such different behaviour we can not attribute the observed increase, which is also not consistent across observation-based products, to human-induced climate change. 
• The disagreement between model results and observations prevents us from concluding with certainty that human-induced climate change is the main driver making this event more likely. However, given the observed trend over the last 40 years, the absence of evidence does not mean that human-induced climate change is not a driver of increasingly heavier rainfall in this region and season in a warmer climate.
  
• There are ample opportunities to improve climate adaptation and resilience through, for example, investing in building resilient infrastructure and reinforcing existing structures to withstand extreme events, implementing more comprehensive nature-based solutions, increasing the coverage of early warning systems, and improving flood risk management policy and planning. 

Heatwaves are arguably the deadliest type of extreme weather event and while the death toll is often underreported, hundreds of deaths have been reported already in most of the affected countries, including Palestine, Bangladesh, India, Thailand, Myanmar, Cambodia and the Philippines. The heat also had a large impact on agriculture, causing crop damage and reduced yields, as well as on education, with holidays having to be extended and schools closed in several countries, affecting millions of students. 

Extreme heat in South Asia during the pre-monsoon season is becoming more frequent. Two previous World Weather Attribution studies focused on extreme heat events in the region: the 2022 India and Pakistan heatwave and the 2023 humid heatwave that hit India, Bangladesh, Lao PDR and Thailand. Despite differences in the nature and impact of the events (drier heat in 2022 leading to widespread loss of harvest, and humid heat in 2023 with greater impacts on  people), both studies found that human-induced climate change influenced the events, making them around 30 times more likely and much hotter.

Scientists from Lebanon, Sweden, Malaysia, the Netherlands, the United States  and the United Kingdom collaborated to assess to what extent human-induced climate change altered the likelihood and intensity of the extreme heat in three Asian regions: 1) West Asia, including Syria, Lebanon, Israel, Palestine and Jordan; 2) the Philippines in East Asia; and 3) South and Southeast Asia, including India, Bangladesh, Myanmar, Lao PDR, Vietnam, Thailand and Cambodia. 

Using published peer-reviewed methods, the scientists analysed how human-induced climate change altered the likelihood and intensity of the 3-day April heatwave in West Asia and a 15-day April heatwave in the Philippines. Figure 1 shows these two regions, outlined in blue, while figure 2 shows the South Asia region. For this region, the analysis focused on observed weather data, but not climate models, as the affected region largely overlaps with the study areas of the previous studies. The observational data for the whole month of April confirmed that the role of climate change is likely of similar magnitude to the heatwaves studied in 2022 and 2023, and the results of a full attribution analysis would not be significantly different. 

Main Findings

• • The heatwave exacerbated already precarious conditions faced by internally displaced people, migrants and those in refugee camps and conflict zones across West Asia. In Gaza, extreme heat worsened the living conditions of 1.7 million displaced people. The heatwave added pressure to the many challenges already faced by people in refugee camps and conflict zones, such as water shortages, difficulties to access medicines and poor living conditions for the large population that lives in makeshift tents that trap heat. With limited institutional support and options to adapt, the heat increases health risks and hardship. 
  • The extreme heat has forced thousands of schools to close down in South and Southeast Asia. These regions have previously also incurred school lockdowns during COVID-19, increasing the education gap faced by children from low-income families, enhancing the risk of dropouts, and negatively impacts the development of human capital.
  • Heat impacts certain groups like construction workers, transport drivers, farmers, fishermen etc. disproportionately. It both impacts their livelihoods and causes a reduction in income, and results in personal health risks.
  • In the current climate, warmed by 1.2°C since pre-industrial times due to human activities, this kind of extreme heat event is not very rare. In West Asia, the chance of it occurring in any given year is around 10% – or once every 10 years. In the Philippines, the chance of such an event happening in any given year is also around 10% – or once every 10 years under the current El Niño Southern Oscillation (ENSO) conditions, and a 1-in-20 year event, overall, without the influence of El Niño. In the larger South Asia region, an extremely warm April such as this one is a somewhat rarer event, with a 3% probability of happening in a given year – or once every 30 years.
  • To estimate the influence that human-caused climate change has had on extreme heat in West Asia and the Philippines, we combine climate models with observations. Observations and models both show a strong increase in likelihood and intensity. In the Philippines, the change in likelihood is so large that the event would have been impossible without human-caused climate change. In West Asia, climate change increased the probability of the event by about a factor of 5.
  • In terms of intensity, we estimate that a heatwave such as this one in West Asia is today about 1.7°C warmer than it would have been without the burning of fossil fuels. In the Philippines the intensity increase due to human-induced climate change is about 1.2°C.
  • We also look at the role of the ENSO. In the Philippines, we find that the current El Niño made the heatwave about 0.2°C hotter. In West Asia, on the other hand, we do not find any influence of ENSO in the event, which is consistent with previous research.  
  • If the world warms to 2°C above pre-industrial global mean temperatures, in both regions the likelihood of the extreme heat would increase further, by a factor of 2 in West Asia and 5 over the Philippines, while the temperatures will become another 1°C hotter in West Asia and 0.7°C hotter in the Philippines.
  • In South Asia, a region that we have studied twice in the last two years, our analysis was simpler and based only on observations. Similarly to what we found in previous studies, we observe a strong climate change signal in the 2024 April mean temperature. We find  that these extreme temperatures are now about 45 times more likely and 0.85ºC hotter. These results align with our previous studies, where we found that climate change made the extreme heat about 30 times more likely and 1ºC hotter. 
  • Existing heatwave action plans and strategies are challenged by rapidly growing cities, increase in informal settlements and exposed populations, reduction in green spaces and rise in energy demands. While many cities have been implementing solutions like cool roofs, nature based infrastructure design, and adherence to climate risk informed building codes, there is limited focus on retrofitting and upgrading of existing buildings and settlements, with infrastructure deficits (e.g. asbestos roofs), to make them more liveable.
  • Some countries such as India have comprehensive heat action plans in place, yet to protect some of the most vulnerable people, these must be expanded with mandatory regulations, such as workplace interventions for all workers to address heat stress, such as scheduled rest breaks, fixed work hours, and rest-shade-rehydrate programs (RSH) are necessary, but yet to become part of worker protection guidelines in the affected regions.
  • The recurrent heat events and associated impacts every year in these regions in the past few years have enabled heatwaves to be recognised as a serious hazard of concern in most countries, with proper guidelines and action plans in place. At the same time, cross-sectoral collaborative strategies that focus on providing immediate relief during the hot days are needed. 

In Dubai, most of the rain fell on Monday 15th of April and exceeded all previous records of daily rainfall in the last 75 years, when records began (UAE government, 2024). 

Researchers from Saudi Arabia, Pakistan, Switzerland, the Netherlands, Sweden, the United States, Canada, France and the United Kingdom collaborated to assess to what extent human-induced climate change altered the likelihood and intensity of the weather conditions at the time of the most impactful floods. 

To characterise the event we focus on daily maximum precipitation (RX1day). As this event was the highest on record we also looked at the annual maximum, which usually falls within this season. Using this RX1day variable has the additional advantage that it is one of the routinely calculated indices in most climate projections, thus making it easy to compare our analysis with published literature.

For the spatial definition of the event we analysed the region that saw the biggest impacts during the 1-day heavy rainfall event, indicated by the red box in Figure 1. The region includes the UAE, the northern part of Oman, Bahrain and a small part of Saudi Arabia. 

Main Findings

• The UAE, Oman and the wider analysed region are located in a so-called hyper-arid region, with on average very little rainfall but with very high variability from year to year. Thus heavy rainfall events such as the one analysed here occur very rarely, leading to short records of similar events which results in high uncertainty in the assessment. 
• The El Niño Southern Oscillation, a naturally occurring climate phenomenon, was found to be important to explain the variability in the observed rainfall. Most previous heavy rainfall events in the area occurred during El Niño years. 
• To assess the role of human-induced climate change we first estimate if there is a trend in the observations associated with the warming up until today of 1.2°C and find that there is a trend, making heavy rainfall such as observed more likely. Based on the observations, the event was 10-40% more intense than it would have been had it occurred in an El Nino year in a 1.2°C cooler climate. 
• To further characterise and quantify the role of human-induced climate change we then also look at climate models with high enough resolution to capture precipitation over the comparably small study region. The available climate models do not consistently exhibit a trend even for the models that were evaluated to simulate rainfall in the region reasonably well. However there is high uncertainty in this finding, again, due to high year to year rainfall variability.  
• Based on the IPCC AR6 assessment, which includes scientific literature available up to January 2021, there is “medium confidence” that heavy precipitation would be detectably larger in the Arabian Peninsula at about 1.5°C of global warming compared to pre-industrial climate conditions, which is close to the current level of global warming.
• The disagreement between model results and observations prevents us from concluding with certainty that human-induced climate change is the main driver making this event more likely. However, while multiple reasons could explain the absence of a trend in our model results, we have no alternative explanation for a trend in observations other than the expectation of heavy rainfall increasing in a warmer climate.
• While the heavy rainfall was well forecasted by national meteorological agencies, floodwaters led to a high number of deaths and extensive damages to homes, shops, offices and cars in the UAE and Oman. The majority of flood related deaths occurred when people were travelling, and many people in Dubai were forced to abandon their cars in floodwaters. The researchers say this suggests warnings may not have reached some people or were not specific enough to the impacts expected in particular regions.
• The high flood risk varies across demographics. In Oman and the UAE,  80 and 85% of the total populations, respectively, live in flood-prone and low-lying areas that are highly exposed. Because of various challenges to their abilities to respond to flood risk, particularly vulnerable groups tend to include older adults, individuals with disabilities, women with caregiving responsibilities, racial/ethnic minorities, migrant workers, and lower-income groups.
• Across both countries, a high degree of surfaces with limited permeability and absorptive capacity from urban developments, inadequate drainage and the hyper-arid soils exacerbate the risk and severity of flash floods. 
• UAE and Oman adopt proactive disaster risk management strategies, with functional systems for early warning, early action, and emergency response to floods, along with long-term adaptation planning. However, reducing the high exposure to flood risk, more proactive urban planning and integration of impact-based forecasting in EWS are necessary to reduce impacts associated with similar events in the future.  
• Finally, cloud seeding was reported to not have been implemented in the context of this event, and additionally even in case of implementation has no influence on the amount of atmospheric moisture available, which was the main anomalous variable preceding the precipitation event. Hence, we can conclude that cloud seeding had no significant influence in the event

Researchers from the Philippines, the Netherlands, Germany, Sweden and the United Kingdom collaborated to assess to what extent human-induced climate change altered the likelihood and intensity of the weather conditions at the time of the most impactful floods. 

The impacts over Mindanao were primarily driven by the accumulated rainfall that persisted over Mindanao from 28 Jan to 1 Feb. To capture this event, we chose the maximum 5 days of accumulated rainfall during the December-February (DJF) period as the temporal extent. In terms of spatial extent, the Caraga and Davao regions that make up the east of the island of Mindanao were the most severely impacted, received the greatest rainfall totals, and are bounded to the west by mountains. Figure 1 shows the event region outlined in red. 

Main findings

• The terrain is mountainous, rendering rainfall highly variable within the region, and thus uncertainties in relatively short records from a sparse observation network are high. Regardless, there is a strong upward trend in extreme rainfall in this region.
• To capture the heavy rainfall connected to the recent flooding that led to widespread devastation,  we assess the 5-day maximum rainfall during December to February, the peak of the Northeast monsoon (Amihan) season.  We find that in today’s climate, a heavy rainfall spell  like this is expected with a 10% chance in any given year. 
• We then assess to what extent El Niño had an influence on the heavy rainfall and found that El Niño typically leads to on average to less rainfall in this region during the Northeast monsoon. In other words, had it not been an El Nino year we would have expected the rainfall to be more extreme. 
• To assess the role of climate change we first estimate if there is a trend in the observations associated with the warming up until today of 1.2C and find that there is indeed a strong trend, having made heavy rainfall such as observed more likely. 
• To identify whether this trend is due to human-induced climate change we then also look at climate models with high enough resolution to capture precipitation over the study region. The available climate models do not exhibit a trend even for the models that were evaluated as “good”.  This is surprising, as a comparably large body of scientific literature has identified an increase in heavy rainfall in most regions and seasons of the Philippines, including the region we studied.  
• Given that the trend in the observations is large, there is probably an aspect of the atmospheric circulation that is systematically misrepresented by the models. This prevents us, without further detailed assessment of underlying processes and their representation in the climate models, to draw an overarching attribution conclusion that quantifies the influence of climate change on this event. 
• Despite significant economic improvement, there is a higher-than-average rate of poverty across eastern Mindanao. Poverty negatively impacts communities’ ability to cope with extreme weather events, as their livelihood channels tend to be more limited and climate- sensitive, including farming and mining which the majority of residents are engaged in. 
• Recent protracted conflict has contributed to limited access to and quality of basic services including healthcare as well as considerable displacement. Across displaced populations, a range of development indicators remain lower than the national average, which, coupled with limited health services, increase people’s vulnerability and reduce their coping capacity to natural hazards.
• In rural areas, intensified deforestation increases the risk of landslides and floods, whereas in cities, the loss of urban wetlands and tree cover coupled with clogged waterways enhance the risk of flooding. Across the region of study, construction in areas declared ‘no-build zones’ raises these dangers considerably.
• Policies, laws, and funding of disaster risk management have largely stalled over the past decades and are primarily geared towards ex-post strategies, notably response. Crucially, despite the presence of automated sensors for rainfall and stream level in the region, these have not been recording data since at least 2022. Further, while forecasts and warnings were issued every 12h, warnings have limited granularity on local risk and lack instructions on where and when to evacuate. However, Early Action Protocols are in place for floods and typhoons, and PASAGA is currently developing a pilot project on impact-based forecasting which can further improve anticipatory action. 

Scientists from Iran, the Netherlands, the UK and the US used published peer-reviewed methods to assess whether and to what extent climate change influenced the 3-year drought in two regions: (1) the fertile crescent around the Euphrates and Tigris rivers, encompassing large parts of Iraq and Syria and (2) Iran. There are several ways to characterise a drought: meteorological drought considers only low rainfall, while agricultural drought combines rainfall estimates with evaporation. As increased evapotranspiration due to regional warming can play a major role in exacerbating drought impacts, we assess agricultural drought in this study. The main variable used to characterise the drought is the Standardised Precipitation Evapotranspiration Index (SPEI) which calculates the difference between rainfall and potential evapotranspiration to estimate the available water. The more negative the values are, the more severe the drought is classified. Figure 1 depicts the SPEI classification for the 36 months from July 2020 up to June 2023 over the two study regions. 

Main findings

• The drought affects a region with a highly vulnerable population due to varying degrees of fragility and conflict including war and post-war transition, rapid urbanisation in the face of limited technical capacity, and regional instability. These dynamics increased vulnerability to the impacts of drought and created a humanitarian crisis.
• The whole Euphrates and Tigris basin (ET-basin) and large parts of Iran experienced extreme and exceptional agricultural drought over the 36 months up to June 2023, making it the second-worst drought on record in both regions based on SPEI. 
• The extreme nature of the drought is not rare in the present climate (which has been warmed by 1.2°C due to burning of fossil fuels). Events of comparable severity are expected to occur at least every decade. 
• Using three different observations-based data products we find a strong trend towards more severe droughts in both regions. We find that the combination of low rainfall and high evapotranspiration as unusual as the recent conditions – that is, an event that occurred around every 5-10 years – in a world that had not been warmed 1.2°C  would be so much less severe that nowadays it would not be classified as a drought at all.
• In order to identify whether and to what extent human-induced climate change was a driver of these trends we combine observations-based data products and climate models and look at the 36-month SPEI in both regions. We find that over the ET-basin the likelihood of such a drought occurring has increased by a factor of 25 compared to a 1.2°C cooler world. Over Iran the likelihood of such a drought occurring has increased by a factor of 16 compared to a 1.2°C cooler world. 
• For both regions human-induced climate change has increased the intensity of such a drought such that it would not have been classified as a drought in a 1.2°C cooler world. Thus confirming that the observed finding is indeed caused by human-induced climate change. 
• To understand the meteorological drivers behind this change in agricultural drought we also analysed rainfall and temperature separately and found there to be little change in the likelihood and intensity of rainfall but a very large increase in temperature. We thus conclude that this strong increase in drought severity is primarily driven by the very strong increase in extreme temperatures due to the burning of fossil fuels. 
• Unless the world rapidly stops burning fossil fuels, these events will become even more common in the future. In a world 2°C warmer than preindustrial an event like this would be an exceptional drought, the worst category possible. 
• The high levels of water stress in the region today are exacerbated by limitations in technical capacity, water management, and regional cooperation. Rapid population growth, industrialization and land-use changes, dam practices and river flow management between upstream and downstream countries, aged water treatment plants, and low efficiency of irrigation water systems have contributed to a complex water crisis. Water is moreover weaponised in conflict, with water systems increasingly targeted for sabotage.
• These results highlight that despite ‘low confidence’ in IPCC projections for drought in the region, increasing water stress driven by human-induced climate change as well as other systemic factors continues to be a major threat for the population and requires urgent efforts for more effective water management strategies, interdisciplinary humanitarian response, and regional cooperation that includes farmers and other stakeholders in the planning. 

Several heat deaths have been confirmed in the US, including migrants on the US Mexican border. In Mexico alone over 200 people died due to the heat. Spain, Italy, Greece, Cyprus, Algeria, and China also reported heat deaths, as well as a large increase in hospitalisation due to heat related illnesses. Large parts of the population in Italy and Spain and over 100 million people in Southern US are under heat alerts. In all three regions, demand for power spiked and negatively impacted a number of important crops, including olive oil in Spain and cotton in China. 

Scientists from the World Weather Attribution initiative collaborated to assess to what extent human-induced climate change altered the likelihood and intensity of the extreme July heat in these three regions.

Using published peer-reviewed methods, we analysed how human-induced climate change altered the likelihood and intensity of 1) 18-day average maximum temperatures over the most affected regions in western US, Texas and northern Mexico (fig 1, top). 2) 7-day average maximum temperatures over land in the rectangular box(5W-25E, 36-45N) covering the most affected region (fig1, middle). 3) 14-day average maximum temperatures over the lowlands of China, again covering the most affected region (fig 1, bottom). 

Main findings

• Heatwaves are amongst the deadliest natural hazards with thousands of people dying from heat-related causes each year. However, the full impact of a heatwave is rarely known until weeks or months afterwards, once death certificates are collected, or scientists can analyse excess deaths. Many places lack good record-keeping of heat-related deaths, therefore currently available global mortality figures are likely an underestimate.
• In line with what has been expected from past climate projections and IPCC reports these events are not rare anymore today. North America, Europe and China have experienced heatwaves increasingly frequently over the last years as a result of warming caused by human activities, hence the current heat waves are not rare in today’s climate with an event like the currently expected approximately once every 15 years in the US/Mexico region, once every 10 years in Southern Europe, and once in 5 years for China. 
• Without human induced climate change these heat events would however have been extremely rare. In China it would have been about a 1 in 250 year event while maximum heat like in July 2023 would have been virtually impossible to occur in the US/Mexico region and Southern Europe if humans had not warmed the planet by burning fossil fuels. 
• In all the regions a heatwave of the same likelihood as the one observed today would have been significantly cooler in a world without climate change. Similar to previous studies we found that the heatwaves defined above are 2.5°C warmer in Southern Europe, 2°C warmer in North America and about 1°C in China in today’s climate than they would have been if it was not for human-induced climate change. 
• Unless the world rapidly stops burning fossil fuels, these events will become even more common and the world will experience heatwaves that are even hotter and longer-lasting. A heatwave like the recent ones would occur every 2-5 years in a world that is 2°C warmer than the preindustrial climate.
• Heat action plans are increasingly being implemented across all three regions and there is evidence that they lead to reduced heat-related mortality. Furthermore, cities that have urban planning for extreme heat tend to be cooler and reduce the urban heat island effect. There is an urgent need for an accelerated roll-out of heat action plans in light of increasing vulnerability driven by the intersecting trends of climate change, population ageing, and urbanisation. 

These extreme temperatures, combined with humidity, caused a sudden increase in heat stroke cases, roads melting and a strong surge in electricity demand in all four countries. 13 casualties and about 50-60 hospitalisations due to heat stroke were reported in Navi Mumbai, Maharashtra on 16th of April alone, while other sources mention 650 hospitalisations. Casualties have also been reported in Thailand. The true cost to human lives will only be known months after the event. In India, in the states of West Bengal, Tripura and Odisha, schools closed three weeks earlier than planned due to the heat. In addition, a large number of forest fires occurred during the same time in India, Thailand and Lao PDR.

Scientists from India, Thailand, France, Australia, Denmark, Germany, Kenya, the Netherlands, the US and the United Kingdom collaborated to assess to what extent human-induced climate change altered the likelihood and intensity of the extreme heat in these four countries where temperature records were broken at several locations and harm to lives, livelihoods, and well-being were reported, also due to the accompanying humid conditions. 

Using published peer-reviewed methods and available datasets, scientists analysed how human-induced climate change altered the likelihood and intensity of the 4-day April heatwave event measured as a heat index that integrates temperature and humidity. Humidity is an important factor in how high temperatures affect the human body, as sweating, the way for humans to cool themselves, becomes less effective at high humidity. Thus, heat is more dangerous in humid conditions. The heat index (reported in °C) takes both temperature and humidity into account. Due to the high humidity conditions during the heatwave, heat index values are higher than the actual temperatures (reported in the first paragraph), as shown in Figure 1. Due to the heterogeneity in climate and landforms over this large area, the team separated the analysis into two smaller homogeneous regions as follows: (1) South and central parts of India and the whole of Bangladesh, excluding the dry, semi-arid region that runs parallel to the Western Ghats where humidity is low in the pre-monsoon season. (2) Thailand and Lao PDR together.

Main findings

• Heatwaves are amongst the deadliest natural hazards with thousands of people dying from heat-related causes each year and many more suffering other severe health and livelihood consequences. However, the full impact of a heatwave is often not known until weeks or months later, once death certificates are collected, or scientists can analyse excess deaths. Many places lack good record keeping of heat-related deaths, therefore currently available global mortality figures are likely an underestimate.
• While people in the affected regions are used to hot and humid temperatures, those who are more physiologically susceptible to heat (e.g. due to pre-existing conditions, age, disability etc.) and/or are more exposed due to their occupation (e.g. outdoor workers, farmers) are at highest risk of heat-related health impacts. Such exposure and vulnerability are intensified by societal disadvantage based on factors such as socio-economic status, religion, caste, gender, migration, and living conditions. On top of this, factors such as air pollution, the urban heat island effect, and wildfires further compound health impacts, particularly among the most vulnerable populations. 
• In the current climate, which has warmed by 1.2°C since pre-industrial times due to human activities, the humid heat event (defined using the heat index) is not very unusual over India and Bangladesh, but is estimated to be rare in Thailand and Lao PDR. 
• The estimated heat index values exceeded the threshold considered as “dangerous” (41°C) over the large parts of the South Asian regions studied. In a few areas,  it neared the range of “extremely dangerous” values (above 54°C) under which the body temperature is difficult to be maintained.
• There is only one data set available for the entire region to calculate the heat index (ERA5). This dataset is known to underestimate extreme temperature trends over India, so the estimates for the rarity and severity of the event are more uncertain than when several datasets can be compared. 
• ​​To estimate the influence that human-caused climate change has had on extreme heat since the climate was 1.2°C cooler, we combine climate models with observations. Observations and models both show a strong increase in likelihood and intensity of April humid heat events similar to that of 2023. 
• The combined results give an increase in the likelihood of such an event to occur of at least a factor of 30 over India and Bangladesh due to human-induced climate change. At the same time, a heatwave with a chance of occurrence of 20% (1 in 5 years) in any given year over India and Bangladesh is now about 2°C hotter in heat index than it would be in a climate not warmed by human activities.
• Over Thailand and Lao PDR, a humid heatwave with a 0.5% chance of occuring in any given year (1 in 200 years) is now 2.3°C hotter in heat index. An event of the same magnitude as the observed heatwave would have been extremely rare in a 1.2°C cooler climate and hence it would have been virtually impossible to have occurred without climate change. 
• These trends will continue with further warming. They are stronger for the rarer event over Thailand and Lao PDR where a heatwave like the recent event would be about 10 times more likely in a 0.8°C warmer world (2°C global warming since pre-industrial times). In India and Bangladesh, the likelihood of this April’s event reoccuring would increase by about a factor of 3 between today and reaching 2°C global warming, meaning that this humid heat event could be expected every 1-2 years. 
• There are a range of solutions to heat-related harms from the individual to the regional level. They are currently implemented as a patchwork, to various degrees, across the countries studied, with India having the most advanced heatwave planning. Solutions, such as self-protective action, early warning systems for heat, passive and active cooling, urban planning, and Heat Action Plans can be effective at reducing fatalities and other negative impacts. In fact, heat-related fatalities have decreased in regions where heat action plans have been in place, e.g. in the city of Ahmedabad and the region of Odisha in India. However, these solutions are often out of reach for the most vulnerable people, highlighting the need to improve vulnerability assessments and design interventions that account for group-specific needs. 
• High social vulnerability among various segments of society, in combination with the strong increase in extreme heat in the region, is likely to exacerbate the impacts of extreme heat events on those already experiencing substantial disadvantages in their daily lives and hence requires comprehensive adaptation and development interventions.   

The rains and resulting flooding affected over 33 million people, destroyed 1.7 million homes, and nearly 1500 people lost their lives (NDMA, 2022; VOA News, 2022). On August 25th, the government declared a national emergency. Damages likely exceed preliminary estimates of around US$30 billion with further economic disruption certain in the months to come (Business Standard, 2022), as around 6700 kilometres of road, 269 bridges and 1460 health facilities were destroyed (OCHA, 2022), 18590 schools damaged (Save the Children, 2022), approximately 750 thousand livestock were killed (NDMA, 2022) and around 18,000 square kilometres of cropland were ruined, including roughly 45% of the cotton crop – one of the nation’s key exports. The loss of food crops totalling around US$2.3 bn also compounds the ongoing food shortages due to the war in Ukraine and summer heatwaves in the region. There is also a severely heightened risk of the spread of disease, as stagnant flood waters provide a breeding ground for pathogens, and the vast number of people displaced results in poor hygiene and sanitation in temporary accommodation (Sarkar, 2022; Baqir et al., 2012). Notably, across Sindh and Balochistan, there has been an outbreak in waterborne disease such as diarrhoea and cholera, as well as skin and eye infections, and malaria (IRC, 2022).

To analyse whether and to what extent human-caused climate change altered the likelihood and intensity of this extreme rainfall, scientists from Pakistan, India, the Netherlands, France, Denmark, South Africa, New Zealand, the US and the UK used published, peer-reviewed methods to perform an event attribution study, focussing on two aspects of the event: (1) The annual maximum of the mean 60-day precipitation during June-September over the Indus river basin (Figure 1 (a)), and (2) the annual maximum of the mean 5-day precipitation in June-September over the worst hit provinces Sindh and Balochistan (Figure 1 (b)).

Main findings

• The flooding occurred as a direct consequence of the extreme monsoon rainfall throughout the summer 2022 season exacerbated by shorter spikes of very heavy rain particularly in August hitting the provinces Sindh and Balochistan. We therefore consider 60-day and 5-day maximum rainfall during the monsoon season for the Indus basin and the two provinces respectively.
• The devastating impacts were also driven by the proximity of human settlements, infrastructure (homes, buildings, bridges), and agricultural land to flood plains, inadequate infrastructure, limited ex-ante risk reduction capacity, an outdated river management system, underlying vulnerabilities driven by high poverty rates and socioeconomic factors (e.g. gender, age, income, and education), and ongoing political and economic instability.
• The return time for both events defined above is about 1 in 100 years in today’s climate. Rainfall in the Indus basin is however extremely variable from year to year, due to, amongst other drivers, the strong correlation with the ENSO cycle. Thus, exact quantification is difficult.
• First, looking just at the trends in the observations, we found that the 5-day maximum rainfall over the provinces Sindh and Balochistan is now about 75% more intense than it would have been had the climate not warmed by 1.2C, whereas the 60-day rain across the basin is now about 50% more intense, meaning rainfall this heavy is now more likely to happen. There are large uncertainties in these estimates due to the high variability in rainfall in the region, and observed changes can have a variety of drivers, including, but not limited to, climate change.
• Secondly, to determine the role of human-induced climate change in these observed changes we looked at the trends in climate models with and without the human-induced increases in greenhouse gases. The regions involved are at the western extreme end of the monsoon region, with large differences in rainfall characteristics between dry western and wet eastern areas.
• Many of the available state-of-the-art climate models struggle to simulate these rainfall characteristics. Those that pass our evaluation test generally show a much smaller change in likelihood and intensity of extreme rainfall than the trend we found in the observations. This discrepancy suggests that long-term variability, or processes that our evaluation may not capture, can play an important role, rendering it infeasible to quantify the overall role of human-induced climate change.
• However, for the 5-day rainfall extreme, the majority of models and observations we have analysed show that intense rainfall has become heavier as Pakistan has warmed. Some of these models suggest climate change could have increased the rainfall intensity up to 50% for the 5-day event definition.
• Looking at the future, for a climate 2 °C warmer than in preindustrial times, models suggest that rainfall intensity will significantly increase further, for the 5-day event, while the uncertainty remains very large for the 60-day monsoon rainfall.
• Our results are in alignment with recent IPCC reports.
• Both current conditions and the potential further increase in extreme peaks in rainfall over Pakistan in light of anthropogencilimate change, suggest that there is an urgent need to reduce vulnerability to extreme weather in Pakistan.