Hurrycane Milton: 10,000 Years Of Synthetic Data Based On 42 Years Of Observations Proves It Was Stronger On Landfall And Zero Observations Prove It Was Wetter!

I was going to do a write up on the Hurricane Helene attribution analysis by World Weather Attribution, but damn it if they haven’t gone and done another even more rapid quick-fire attribution analysis, this time of Milton. I just can’t keep up! The media can though. The news is splashed all over the MSM: ‘Hurricane Milton was 30% wetter and a Category stronger on landfall because of climate change.’ Anyone who says different is spreading misinformation and should be censored online.

Ryan has a very dry sense of humour, so his posts should definitely not be taken at face value!

I skipped through the 56 pages of the Hurricane Helene attribution analysis. It’s extremely convoluted and probably not worth the effort of trying to make sense of here. But what struck me was the use of the so-called ‘IRIS’ model:

The IRIS model was used to investigate Helene’s strong winds by analysing storms making landfall within 2 degrees of Helene. By statistically modelling storms in a 1.3°C cooler climate, this model showed that climate change was responsible for an increase of about 150% in the number of such storms (now once every 53 years on average, up from every 130 years), and equivalently that the maximum wind speeds of similar storms are now about 6.1 m/s (around 11%) more intense.

What is this IRIS model? This is what the authors say in their study:

Wind speed attribution using IRIS

The event definitions studied in this section are as follows:

Florida landfall: category 4 hurricanes making landfall in a region 2 degrees from Helene

Assessing tropical cyclone risk given the infrequency of landfalling tropical cyclones (TC) and the short period of reliable observations remains a challenge. Synthetic tropical cyclone datasets can help overcome these problems. We explore this method here using a new global tropical cyclone wind model (IRIS) with several key innovations.

They also say this:

This is a new approach, used in only one rapid study to date (World Weather Attribution, 2024), that sits alongside the usual WWA protocol. First, it is a single model, whereas WWA normally combines multiple models and approaches into a single statement. In general, additional models help to sample a wider range of possibilities to ensure that we are as close to reality as possible.

However, this approach is fundamentally different in nature. It is a stochastic model that is not based on climate models, only on observations and well understood physics. This means that it is not subject to the same biases and challenges around simulating phenomena at small scales that climate models struggle with. Furthermore, it is based on a very large number of data points (~10000 years of synthetic data) and the results are tested against observed storm tracks and intensities.

With its basis in fairly simple and robust thermodynamic and physical arguments, this method is complementary to the WWA protocol. In particular, for tropical cyclones, it allows us to make statements about wind speeds that we cannot do on a rapid basis using the traditional method. This is because climate models (and therefore our method) are fundamentally limited in their ability to resolve the phenomena leading to these intensities.

This approach just leverages other knowledge to bypass that challenge. However, overall, the results are still valid for the ‘class of event’ in the same way as our normal results, and thus the interpretation is essentially the same. Similarly, as shown by the study of storms close to the point of landfall, the analysis can be constrained in various ways so that they are as close to the impacts as we can manage.

They used IRIS as well in the Milton study:

The IRIS model was used to investigate Milton’s strong winds by analysing storms making landfall within 2 degrees of Milton. By statistically modelling storms in a 1.3°C cooler climate, this model showed that climate change was responsible for an increase of about 40% in the number of storms of this intensity, and equivalently that the maximum wind speeds of similar storms are now about 5 m/s (around 10%) stronger than in a world without climate change. In other words, without climate change Milton would have made landfall as a Category 2 instead of a Category 3 storm. 

So I thought I would look a little more closely at this IRIS model, and here is the paper which describes it, produced by Imperial College London.

Have you got that? WWA make a big deal about observations by saying:

It is a stochastic model that is not based on climate models, only on observations and well understood physics. This means that it is not subject to the same biases and challenges around simulating phenomena at small scales that climate models struggle with.

However, their ‘stochastic model’ generates 10,000 years of synthetic tropical cyclone data which is validated against . . . . . . just 42 years of limited observations re. landfalling hurricanes!

As if this isn’t dodgy enough with regard to the findings of the two rapid attribution analyses of Helene and Milton, in the case of Milton the authors were so keen to get out an analysis before residents had even got the chance to pick up a broom to clean up the mess made by the storm that they based their rainfall estimates on no data!

At the time of writing, the day after landfall, the observation-based datasets are not all updated to include the event. We can thus not reliably estimate how rare the heavy rainfall in the path of Milton was, a usual step in attribution analysis. Instead, we assessed trends in observations for an estimated 1 in 10 year and a 1 in 100 year event in the region indicated in figure 1. In both cases the results are comparable and thus not very sensitive to the exact event definition.

Can you believe that? Yes, I can unfortunately. It’s far more important to get the propaganda message ‘out there’ as quickly as possible after the event via an obliging main stream media than to bother with mundane stuff like getting the actual data in order to produce reliable results. Clowns, charlatans.

Update

Now we know why it was so important to rush out these two attribution studies: so the media could publish crap like this. The ‘climate crisis’ psyop is now winding up to something approaching the tempo of the Covid crisis psyop at its hysterical zenith.