News & Blog
Its increasing deployment trend compares well with that of PAL’s correlation of extreme weather-related disasters and global warming – another evidence-based validation of PAL’s algorithm-based predictability.
Boiled frog syndrome is when you think nothing much is wrong until suddenly you realise it’s too late and you have run out of time to prevent catastrophe. The boiled frog fable imagines that a frog dropped into boiling water will jump out immediately. However, if the frog is immersed in tepid water that is then slowly heated, the frog gets used to the gradually increasing heat before realizing – too late – that it cannot escape being boiled alive. How did this metaphor for our present day attitude to climate change come about?
The twin threats to London of fluvial flooding and storm surges are no longer exceptional.
PAL’s methodology is a classic research narrative that reveals the tip of a $1.8 trillion iceberg of potential claims from cities across the globe. In brief, PAL’s step-by-step research narrative goes like this: historically GDP has driven emissions, emissions drive temperature increases, increased temperatures drive more extreme weather, which in turn increases insured and uninsured loss and damage.
New York City’s claim is paving the way to an enormous black hole in the share value of 5 Big Oil (and other oil companies too). The staggering sums scoping the size of their potential liability from climate-related claims is a warning to asset managers and pension fund administrators. The 5 Big Oil companies should identify this potential liability as Value at Risk (VaR) in their annual reports: failure to do so could be seen by shareholders as a lack of transparency.
In 2015 a report “Small City, Regional and Global Predictions for 2015, 2016 and 2017” was sealed and lodged by Predict Ability (PAL) in the safe of a legal firm. The report was generated programmatically, using PAL’s proprietary prediction technology: this machine-generated report was designed to identify qualifying ‘disaster events’ predicted to occur within specified time and distance windows. Once the reporting period had passed, a verification of PAL’s predictions, compared to the GLIDE online database confirmed an accuracy approaching 90% of those vulnerable cities pinpointed by PAL’s program.
An estimated $19billion will be needed to fund the infrastructure to protect New York City from storm surges such as 2012’s Super Storm Sandy, that are bound to come again and come more frequently. Mayor de Blasio’s primary claim against 5 Big Oil (BP, ExxonMobil, Chevron, ConocoPhillips and Royal Dutch Shell) implies – correctly – that 11% of extreme weather-related losses to the City are attributable to the climate changing emissions of their oil and gas products. If successful, such a claim might result in between $1.4billion and $6.2billion in damages – crucially dependent on the date upon which the…
This new case study shows how PAL’s Carbon Value at Risk (VaR) metric is used to determine the extent of carbon liability risk – the potential cost of damage attributable to carbon emission related anthropogenic (manmade) climate change. For users of biomass as a fuel source such as Drax power station, it highlights a potential $23bn ‘black hole’ between the expected loss and damage caused by carbon dioxide emissions over the next 25 years ($33bn) and equivalent loss and damage where biomass emissions are excluded ($10bn).
Global warming, caused by CO2 emissions released into the atmosphere by burning fossil fuels, currently costs global GDP a staggering $1 trillion in damages p.a. Small wonder the UN, IMF and World Bank have all called for a carbon price: policy makers in government and corporations urgently need this price so they can account for the true cost to humanity of their decisions, activities and investments. Way ahead of the curve, PAL is the ONLY company in the world to have scientifically determined the true carbon price, based on the loss and damage caused by extreme weather events attributable…
An algorithm-based calculation of the economic damage from climate change compares well with a study led by Prof. Solomon Hsiang of the University of California at Berkeley.