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The analysis concludes that the 2016 drought in Somalia and Somaliland was primarily driven by natural variability and La Niña rather than climate change. While the autumn rains failed in both regions—representing a once-a-century event in Somaliland—climate change had a small effect on these dry extremes. La Niña increased the probability of a dry season and accounted for approximately one third of the precipitation deficit, though it was not well-predicted by seasonal forecast models.

The 2016 drought in Kenya was primarily driven by sea-surface temperature patterns, specifically La Niña, rather than human-induced climate change. While climate change did not significantly increase the likelihood of the rainfall deficit, it did lead to hotter temperatures that exacerbated the drought's impact. The event was less severe than the 2010-11 drought but still triggered a national emergency, affecting millions of people in arid and semi-arid lands.

The analysis finds that February 2017 was the second warmest February on record for the contiguous United States, with temperatures 3.1°C above the 1981–2010 normal. By combining historical observations with CMIP5, HadGEM3-A, and Weather@Home model ensembles, the study concludes that the probability of such a warm event has increased more than threefold due to human-induced greenhouse gas emissions. While the 2017 event had a return period of approximately 12 years in the current climate, it would have been a 1-in-160-year event around 1900. Projections suggest that by 2050, temperatures like those seen in February 2017 will be 'completely normal', occurring roughly every three years.

The report evaluates how to communicate the link between anthropogenic climate change and extreme weather events, testing various phrasings for probability, frequency, intensity, and uncertainty. Findings indicate that while high-level decision makers often prefer technical percentages and 'probability' terms, the general public finds these confusing, preferring simpler terms like 'worse' or 'more often'. The study highlights significant translation challenges in Swahili and Hindi and recommends that attribution information be downscaled to high spatial resolutions and co-developed with local communication experts and trusted sources, such as national meteorological agencies.

The document provides guidance on communicating extreme weather event attribution to different stakeholder groups in Kenya and India, focusing on phrasing for probability, frequency, intensity, and uncertainty, as well as the use of visual aids.

A scientific study assessed the record-breaking rainfall in Chennai on 1 December 2015, which saw up to 494 mm of rain and caused US$3 bn in economic losses. The analysis concluded that no measurable effect of human-caused emissions was detected for this specific one-day event, attributing this lack of detection to the masking effects of aerosol pollution over India.

The analysis finds that climate change significantly increased the likelihood of the record-breaking summer heat in New South Wales and the three-day heatwave in Canberra, while the influence on Sydney's heatwave was less clear due to high variability.

The document examines how climate science, specifically attribution science, can be used to link extreme weather events to climate change and inform disaster risk management. It highlights a case study of the 2016/2017 drought in Kenya, noting that while human-induced climate change signals were not strong for rainfall, hotter temperatures influenced by climate change and La Nina patterns contributed to the event. The brief recommends increased investment in national and subnational capacities for climate services, better inter-agency coordination, and the alignment of early warning systems with forecast-based early action.

The December 2015 extreme rainfall event in Chennai, India, which saw a record 494 mm of rain in 24 hours, was determined by climate attribution studies to be a 1 in 600–2,500 year event not caused by anthropogenic global warming. While the event's rarity would have overwhelmed most cities, its impact was exacerbated by poor land-use planning, including the encroachment of wetlands and riverbeds, and a clogged drainage system. The document recommends that Indian cities integrate wetland protection, river basin approaches, and vulnerability-focused disaster action plans into their urban development to build resilience against increasing extreme weather trends.

The document analyzes the devastating floods in Chennai on 1 December 2015, which killed over 470 people. While no measurable effect of human-caused emissions was detected for this specific event, the report highlights that unplanned urban growth, encroachment on water bodies, and poor infrastructure management significantly increased the city's vulnerability. Key impacts included the destruction of 4.92 lakh houses and the closure of Chennai Airport for five days. The flooding was exacerbated by the necessary release of water from the Chembarambakkam reservoir to prevent a breach, though the timing of this release was questioned by residents.

The document describes a process for improving disaster response and recovery by integrating climate science and social analysis. It emphasizes that determining the influence of climate change on extreme events, combined with an analysis of exposure and vulnerability, allows policy makers and community members to make informed decisions to 'build back better' and ensure systems are resilient to future climate risks.

A scientific analysis of the December 2015 Chennai floods found no detectable effect of human-induced climate change on the extreme one-day rainfall event, likely due to the masking effect of aerosol pollution in the region.

The document discusses the increasing frequency and magnitude of extreme heat events in India, highlighting the role of climate attribution science in identifying the human-induced causes of these events. It emphasizes that such science helps decision-makers create targeted heat action plans that account for vulnerability, exposure, and local factors like the urban heat island effect, air pollution, and humidity. The brief notes that while aerosols can temporarily lower peak temperatures, their reduction through clean energy policies may increase heat wave intensity. It advocates for coordinated government responses, early warning systems, and capacity building to protect marginalized populations, such as slum dwellers and outdoor workers, who are most at risk.

The report investigates the 51°C record temperature in Phalodi, Rajasthan, on 19 May 2016. While annual mean temperatures in India are increasing, the analysis found that human-induced climate change did not play a statistically significant role in this specific event or a similar 2015 event in Andhra Pradesh. The authors suggest that the warming effect of greenhouse gases may be masked by the cooling effects of aerosols and increased irrigation. However, the report warns that as energy policies shift away from fossil fuels, the diminishing cooling effect of aerosols could increase the intensity of future heat waves.

The 2016–2017 drought in Kenya, declared a national emergency in February 2017, was primarily driven by sea surface temperature patterns, specifically La Niña. While attribution analysis found no strong climate change signal in rainfall trends, it concluded that temperatures during the drought were hotter than they would have been without human-induced climate change. The drought severely impacted 23 counties, leaving up to 4 million people in need of food aid by April 2017, though it was less extreme than the 2010–2011 event.

The analysis concludes that human-caused climate change increased the frequency of extreme three-day precipitation events like the August 2016 Louisiana downpours by at least 40% and increased their intensity by approximately 10%. Using observational data and high-resolution climate models (FLOR-FA and HiFLOR), the study found that such events are now more likely and intense than they were in 1900. While the specific local event was characterized as a 1-in-550 year occurrence, similar events now occur somewhere along the Central U.S. Gulf Coast region approximately once every 30 years.

The report analyzes severe May 2016 rainstorms in Europe, finding that climate change significantly increased the probability of extreme 3-day rainfall in France's Seine and Loire basins, while results for southern Germany remained inconclusive.

The analysis found that while human-induced climate change slightly increased the probability of the 2016 record-breaking heat in Rajasthan, the effect was not statistically significant. The study suggests that the warming effect of greenhouse gases in India is being partially offset by the cooling effects of aerosols and increased irrigation. Despite the lack of a strong temperature trend, the combination of high heat, pollution, and humidity is increasing the health risks and mortality associated with heat waves.

The document analyzes the tension between the risk-management approach of the UNFCCC and the justice-based demands for compensation regarding climate-induced loss and damage. It evaluates four scientific traits—attributability, irreversibility, unavoidability, and intolerability—concluding that while science can inform risk management, the determination of liability and compensation remains a political and value-based challenge.

The study investigated the December 1, 2015, rainfall event in Chennai, where some stations recorded up to 494 mm of rain in 24 hours, causing an estimated US $3 billion in economic costs. Using observational data and regional climate models, researchers found no detectable effect of human-induced climate change on the probability of this extreme one-day rainfall. The analysis suggests that the cooling effect of aerosols in the western Bay of Bengal likely counteracted greenhouse gas warming, while non-anthropogenic factors, such as El Niño and sea surface temperature anomalies, played a more significant role.