Editing Talk:1885: Ensemble Model

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Where's the guy who knows how to make tables? A table would be good for this article, so we could explain each joke scenario. [[Special:Contributions/172.68.26.5|172.68.26.5]] 15:41, 4 September 2017 (UTC)
:I don't like tables when the text in the data cells is more than only a few words. That's bad layout. I have entered all the text from the list into separate headers for the appropriate floating text layout.--[[User:Dgbrt|Dgbrt]] ([[User talk:Dgbrt|talk]]) 18:39, 4 September 2017 (UTC)
Might be worth mentioning the context for this comic; viz. the approach of hurricane Irma, with a wide range of predictions as to where it might end up (and which areas it would hit), making weather modeling (and hurricane modeling in particular) &ndash; and the uncertainties involved &ndash; topical. It's clear to us now, but won't be clear to readers a few years from now. [[User:Pelosujamo|Pelosujamo]] ([[User talk:Pelosujamo|talk]]) 01:37, 5 September 2017 (UTC)
:Wait - you mean it's not related to Harvey? (In other words, I'm not part of the "us" you speak about.) -- [[User:Hkmaly|Hkmaly]] ([[User talk:Hkmaly|talk]]) 02:17, 5 September 2017 (UTC)global warming https://www.explainxkcd.com/wiki/index.php/1885:_Ensemble_Model
::I'm pretty sure this was inspired by Irma, not Harvey, because it's about uncertainty in weather modeling; which has received more attention with Irma than it did with Harvey. By the time America started paying real attention to Harvey the National Hurricane Center already had a very good (and accurate) idea about its future path. By contrast, the uncertainties in the Irma models [http://edition.cnn.com/2017/08/31/us/hurricane-irma-forecast-weather/index.html made CNN's front page] long before Irma was anywhere near populated areas. Also, it would be a bit late for Randall to do a Harvey comic; Harvey was last week's news. (Of course, Harvey did make hurricanes cool again.) [[User:Pelosujamo|Pelosujamo]] ([[User talk:Pelosujamo|talk]]) 13:24, 5 September 2017 (UTC)

I would say that one  the idea of randall is related to point the change climate denier invalid reasoning that despite all scenario of global warning show increase of temperature, the fact that none of each is very likely to be wrong then all are wrong. (The fallacy is  in the last then:  the reunion of little probability can lead to high confidence or a the reunion of sum of various probable things can lead to absolutely certain ) [[User:Xavier Combelle|Xavier Combelle]] ([[User talk:Xavier Combelle|talk]]) 02:35, 5 September 2017 (UTC)

I have to disagree with the original explanation (now fixed) that ''"there is no reason to have the locomotion speed of dogs as a parameter"''. Dogs are known to chase cats, cats kill a large number of birds, birds eat insects including butterflies. If dogs would run slightly faster there could be a significant variation in the amplitude of the [https://en.wikipedia.org/wiki/Butterfly_effect Butterfly effect]. --[[Special:Contributions/141.101.69.147|141.101.69.147]] 12:13, 5 September 2017 (UTC)
:Besides, the running speed of dogs would presumably impact how often, and where, one would experience raining cats and dogs.[[Special:Contributions/162.158.155.32|162.158.155.32]] 15:30, 6 September 2017 (UTC)
"[one extra cloud in the Bahamas] is most likely too specific and subtle a difference to be useful to the model." - Doesn't that depend on the size and disposition of said cloud?  I'd say the problem here is vagueness, rather than insignificance.[[Special:Contributions/162.158.155.32|162.158.155.32]] 15:35, 6 September 2017 (UTC)


The upper graph looks like one plotting global temperatures with time using different scenarios, like this one: https://www.ipcc.ch/publications_and_data/ar4/wg1/en/figure-spm-5.html".  I do not think this is an appropriate example of an ensemble model.  The several trajectories for global temperature are for different policy decisions.  In an ensemble model various trajectories reflect uncertainty about are a result of uncertainty about initial conditions or the physical rules that control the evolution of the system.  TLDR: A map is not an ensemble model.
The uncertainty (shaded area) for each track may or may not be the result of an ensemble, but if it is an ensemble for one of the scenarios would be a better example.
Also ensembles are typically used for non-linear, chaotic systems and this should probably be somewhere in the explanation.  
[[Special:Contributions/162.158.62.159|162.158.62.159]] 17:06, 6 September 2017 (UTC)
:The global temperature doesn't decrease in any model. So I have changed this in the explanation and added the possibility of a depicted tornado, makes more sense for the big point at the beginning. Nevertheless I'm not sure what Randall means in this particular graph.--[[User:Dgbrt|Dgbrt]] ([[User talk:Dgbrt|talk]]) 14:35, 7 September 2017 (UTC)

Ensemble models are a form of a Monte Carlo Analysis.  They are used in many engineering analyses, usually to determine an upper limit for some particular limiting quantity.  The idea is that you do not necessarily believe any of the individual analyses, but that the ensemble forms an envelope of outcomes, so that if you design for the most extreme case, you can be confident that your design will not fail.  They are used to make sure that the design is robust and has margin to failure.  Of course, you cannot consider all of the uncertainties, which is why it is important to carefully identify sources of uncertainty before you do the analyses.  If you do generate an ensemble envelope, and the data for the particular event falls outside the envelope, it is time to seriously reconsider the models, or the sources of uncertainty.13:20, 7 September 2017 (UTC)~~

;…rain is 0.5% more likely in some areas
I have removed this because it's not accurate. This comic refers to the {{w|Universe (mathematics)}} and this outcome is high realistic.
:''Historical rain data are used to estimate the probability of rainstorms of a certain size and duration occurring, e.g. the {{w|Flood Studies Report|Flood Studies Report}} in the UK. Randall here is suggesting that an alternate universe exists where these estimates are higher (and presumably lower) in some areas, and that the estimates of rainfall in this alternate universe is accounted for within ensemble modelling in our own universe. This sort of change in prediction is frequently used when accounting for 'worst case scenarios' in the design processes of structures such as dams. However, the figures to the left appear to indicate time-dependent models, which are typically physics based, e.g. {{w|Large eddy simulation|Large Eddy Simulation}} models or other atmospheric process based models. In those sorts of models, likelihood of rain is usually a prediction rather than a parameter, but might be used as a parameter in a second iteration.''
Check my more realistic explanations on the first three outcomes, they are no jokes.--[[User:Dgbrt|Dgbrt]] ([[User talk:Dgbrt|talk]]) 15:01, 7 September 2017 (UTC)