Arguably, the most unpredictable forces in the world are people and weather.
Data seems to back that up.
Overall losses from 980 world-wide natural catastrophes in 2020 totaled $210 billion dollars, significantly higher than $166 billion in 2019, according to Munich Re.
There were 980 events that caused those losses, but remarkably the loss of human life was down, despite the uptick in incidents: Natural catastrophes caused 8,200 deaths, compared with 9,435 in 2019.
“While it is wonderful that there was a decline in the loss of life, the impacts on communities who are underinsured have widespread and lasting implications,” said Toronto executive and risk management entrepreneur Neil Mitchell.
It might seem that the world would have caught a break with man-made disasters during Covid-19, with so much of society shutdown. That would be a misconception, however.
While the actual number of man-made disasters declined from 2019 to 2020, thanks to COVID-19 lockdowns, the $8 billion dollar price tag in insured losses remained unchanged between 2019 and 2020. This occurred “due to the massive explosion at the port of Beirut and civil unrest in the United States that led to property damage in 24 states.”
Still, the bulk of losses are caused by nature. Since 1990, flooding has earned the notoriety of being the most common form of natural disaster.
As alluring as the restorative power of water can be and time by rivers, lakes and oceans is often viewed as leisure, there are times when nature bucks that viewpoint with venom.
A deluge of rainfall lingers above an area and entire communities are swept away. Mountain communities have to worry about flooding from ice jams. After the winter freeze breaks and the massive ice chunks float like icebergs down rivers and block – and sometimes destroy – bridges and infrastructure.
“Flooding is the most common natural disaster in Canada,” Mitchell pointed out. “Yet people don’t often think of flood insurance until it is too late. Regular home insurance policies do not include flooding, flood policies are separate.”
While some areas of the world are notably used to monsoon rains, it does not mean they are ever properly prepared, particularly in developing countries.
When extreme flooding hit China during the summer monsoon season of 2020 there was a reported $17 billion in losses – and only two percent of those losses had insurance.
The United States saw the costliest year in disasters with the social unrest, hurricanes, wildfires and the dangerous derecho or straight line winds that hit Idaho and Illinois.
“Weather patterns are becoming more extreme, everything seems to be becoming more unpredictable. The Arctic Circle saw a heatwave and as a result Siberia had wildfires, who would have thought that possible even a decade ago?,” Neil Mitchell asked. “And 2021 has produced historic and deadly flooding all over the world, record breaking heat waves, wildfires and of course hurricanes. It does not appear that Mother Nature is easing up, at all.”
Fortunately, while technological innovation is not the cure-all, there are advancements that are paving the way to better climate predictions.
Enter: Climate informatics, a discipline that was fully minted in 2011 that appears at the intersection of climate science and data science.
“Climate informatics covers a range of topics: from improving prediction of extreme events such as hurricanes, paleoclimatology, like reconstructing past climate conditions using data collected from things like ice cores, climate downscaling, or using large-scale models to predict weather on a hyper-local level, and the socio-economic impacts of weather and climate,” according to National Geographic.
The technology that will be facilitating safety for the populace from dangerous weather is actually artificial intelligence (AI). All the data generated from climate simulations through climate modeling can be sorted by AI to discover new insights.
A recently published paper titled “Tackling Climate Change with Machine Learning,” was discussed at a major AI conference. The paper is being regarded as a call to action in order to bring researchers together behind the issue of climate change.
“It’s surprising how many problems machine learning can meaningfully contribute to,” said David Rolnick, a University of Pennsylvania postdoctoral fellow who co-authored the paper and helped organize the workshop about AI and climate change.
There were 13 areas identified where AI can help confront pressing issues including “energy production, CO2 removal, education, solar geoengineering, and finance.”
The possibilities created by machine learning include more energy-efficient building, new low-carbon materials, more accurate monitoring of deforestation, and greener transportation.
“While the world is weighted down with big problems, we can only hope that rapid scientific innovation will be able to keep up and curb some of the problems we have been creating for the planet,” said Mitchell. “While what is happening to the climate is disconcerting, I am emboldened that the best and brightest scientific minds are working toward solutions.”