@mdalleau said in Your animations:
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Hey @StephenBeste, welcome to the world of Windy! Ivo and the team have really created something special here. So, as others have mentioned, the "historical" data you need doesn't go back especially far... And it sounds like you want to understand model performance for your specific location. There's a technique called Model Output Statistics (MOS) that deals with this. Although model verification is a whole science in itself, I've also been interested lately in the idea of creating something like that on a more basic level. Maybe I'll look into it again...
@Franzus-0, of course your post counts! Do bear in mind though, this is merely a discussion; I must reiterate that I don't work for Windy, and I'm not collecting "requests" as such! Congrats on the new vessel, and glad you found your way in the end :) As I understand it, that was one of Ivo's main motivations for Windy; that everyone could have access to the best data possible for free. I was blown away when I saw that they had the full 9km ECMWF fields on discovering Windy; I found myself asking around about Windy at the next ECMWF workshop I was at :) As to the historical data, you seem to be looking for something similar to @rfleming – essentially a type of analysis chart.
Some kind of MOS-based analysis charts that go back a few months, perhaps with some satellite and MADIS data mixed in.... this might have to be my next project :) Thank you so much all for your input. Please keep the discussion going if you have any other perspectives on historical data!
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@TomSlavkovsky please check and reply :)
I've constructed two new Copernicus pollution forecasting replacement overlays:
Air quality NO2 [no2] - The standard version of the air quality overlay has some typical problems (which seem to affect most standard windy pollution overlays) namely that it's strongly non-linear and the representation is highly distorted in that it dramatically over emphasizes the very low-levels of pollution, whilst limiting or cutting-off the visual detail with respect to the highest levels of pollution. It's a strange way to construct an overlay as it will implicitly strongly bias the forecast information, which will lead to incorrect perception of the forecast hazard level. To rectify this I've made completely linear the display below 10µg/m³. The rest of the replacement overlay is not equally linear to this, but this is done to cut down on the complexity of the resulting overlay setting (and due to some other implicit range limitations within this overlay). It now shows things in their correct proportions with a minimum of visual distortion. So although this new overlay appears to show less emphasis it is in fact showing the forecast pollution levels in the linearly correct relative proportions, both at the low-end level whilst also making clear where serious pollution problem-areas are actually located. The standard Windy overlay looks positively 'bloated' in comparison simply because it's showing the forecast information strongly out of the correct relative proportions and thus will distort a casual user's perception of where the real air-quality hazards exist.
This new Air Quality setting is available here:
Example of Air Quality overlay:
The very unhealthy air-quality in the heart of China is simply disgusting.
The other new overlay is ...
Aerosol [aod550] - This overlay was much more straight forward as the standard version had fewer problems with it. I've ensured a low visual distortion exists within a linear overlay depiction below 1AOD (it's still linear above 1AOD, but with a different linear increment to reduce the complexity of the shading). Plus I've changed the colors and increments to better display were the real problem areas are located and their relative proportions and detail.
The new Aerosol setting is here:
Examples of Aerosol
In summary, both of these new overlays are easier to read or assimilate at a glance to develop a correct sense of the pollution proportions and their relative hazard level.
I'm still developing a PM2.5 replacement overlay which will be much more complicated due to the range scale of the information within it.