In honour of the scientific work of Alimonti et al. (2022) which was too honest for the climate censors and prompted them to force a retraction on the grounds of, well, think of the implications if people are allowed to see the data, aka Thoughtcrime, we’re re-running our summary series on it from last year. This week we look at tornadoes. According to the authors, “A tornado is a vortex extending upward from very near the surface at least as far as cloud base (with cloud base associated with deep moist convection, typically a cumulonimbus cloud), that is intense enough at the surface to do damage.” The USA gets a lot of them and has the best long term data. The data show an apparent upward trend – but there’s a catch.
Prior to the installation of Doppler radar and the advent of smartphones with everyone wanting selfies with a funnel cloud in the background most small tornadoes were never counted or recorded. Adjust for that change and the picture looks very different.
The raw data look like this:
The chart shows all tornadoes sorted by their severity on the Enhanced Fujita (EF) scale from 0 (smallest) to 5 (largest). The apparent growth is entirely due to the EF0-EF2 events, which are the hardest to detect. With increased population, radar and cell phones many small tornadoes now get recorded that would have been missed prior to 1980. The large tornadoes (EF3-EF5) tended to be counted accurately even back in the 1950s, because an occurrence couldn’t be missed at the time and was easier to confirm afterwards due to the characteristic damage even in uninhabited regions. That portion of the data set looks like this:
Not only is the count not going up, if anything it is going down. So what’s the connection with climate? The authors point out that climate models don’t predict or resolve tornadoes since they occur on too small and brief a scale. So no one knows. They might increase or decrease or not change at all. As far as the trends go, there is no reliable evidence of an upward trend in occurrence. More small tornadoes are recorded now than in past decades, because monitoring systems are better. So you are about as likely to experience a tornado now as you would have been back in the 1950s.
You and your little dog too.
The premise of all climate change analysis is fundamentally wrong. Climate always changes, so a fixed past baseline should not be used for reference. Instead, an envelope of possible natural variation should be used as the reference, and “changes” noted only if they are outside the envelope.
This is the same problem the global climate warming change goofs had with surface temps. Prior to World War 2 there were very few temperature recording stations around the world, WW2 incited a mass construction of airfields with weather instruments, so there really was no temperature record prior to the 1940s. After that came the disappointing news that the thermometers were installed without regard for potential heat islands and other effects like direct sunlight, low pressure zones caused by hills and mountains and an endless list of other considerations.
Same effect, detection bias, with hurricanes, the satellites pick up every swirl which gets named so “hurricane numbers are increasing” even as the ACE decreases
The other bigger issue is the only other long term readings outside of Western Europe and North America is mostly colonial cities in Asia Africa and South America, those dastardly sciency Europeans collecting data.
But what that really means is that all the long term data in the rest of the world is 100% UHI corrupted.
It’s why the second graph on Hansen’s 1998 paper, the world, shows much more linear increase in temperatures. It’s a graph showing the growth in cities not temperature.