Climate-related disasters, such as floods and heat waves, have grown fivefold in the last 50 years, killing more than 2 million people and costing $3.64 trillion in total losses, according to a United Nations body.
The World Meteorological Organization (WMO) claims that its “Atlas” is the most thorough examination of death and economic losses caused by weather, water, and climate extremes ever published.
Mami Mizutori, head of the U.N. office for disaster risk reduction, urged the world’s major economies to help hard-hit developing countries to invest in warning systems and risk modelling.
This summer’s extreme rainfall and flooding have wreaked havoc on towns all over the world. On September 1–2, 2021, remnants of Hurricane Ida inundated streets and subway lines in New York City, with more than 3.15 inches of rain falling in an hour and more than 7 inches in total. A record-breaking 17 inches of rain occurred in 24 hours in Tennessee a week earlier, turning creeks into rivers that inundated hundreds of houses and killed 20 people.
Even while the general climate change trends were obvious a decade ago, scientists couldn’t definitively link any single weather occurrence to climate change. Attribution studies can now determine if extreme occurrences were influenced by climate change or if they can be explained only by natural variability. Extreme event attribution is a blossoming new sector of climate science, thanks to rapid breakthroughs in research and increased processing capability.
Four phases are commonly involved in attribution studies.
The first stage is to use observational data to determine the magnitude and frequency of the occurrence. For example, rainfall in Germany and Belgium in July set new records by a wide margin. According to the scientists, a storm like that might occur every 400 years in the larger region in today’s climate.
The second phase is to run climate models on computers and compare the results to observational data. To have faith in a climate model’s conclusions, it must be able to effectively reproduce extreme events in the past and accurately depict the physical processes that contribute to their occurrence.
The final step is to create a virtual world of Earth as it might be if human activity had not warmed the globe. Then run the climate models once more.
The influence of human-caused climate change is represented by the disparities between the second and third stages. The final stage is to use statistical tools to measure these disparities in the magnitude and frequency of the exceptional event.