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Text of the page (random words):
ave two principal requirements accurate representation of changes in the relevant environmental factors e g sea surface temperatures that can affect tc activity and accurate representation of actual tc activity in given environmental conditions suppose in the future we had a model that was amazing at reproducing tropical cyclones when a variety of climate metrics were accurately reproduced however if the climate model didn t reproduce these metrics reliably we still wouldn t get a reliable answer about future trends in tropical cyclones as a result tropical cyclones are a major modeling challenge to see the whole article visit the new science of doom on substack page and please consider suscribing for notifications on new articles posted in climate models leave a comment natural variability attribution and climate models 12 october 16 2023 by scienceofdoom overview of chapter 3 of the ipcc 6th assessment report the periodic ipcc assessment reports are generally good value for covering the state of climate science i m taking about working group 1 the physical science basis which in the case of the 6th assessment report ar6 is 12 chapters they are quite boring compared with news headlines boring and dull is good if you want to find out about real climate if you prefer reading about the end of days then you ll need to stick to press releases here s a quick summary of chapter 3 human influence on the climate system chapter 3 naturally follows on from chapter 2 changing state of the climate system to see the whole article visit the new science of doom on substack page and please consider suscribing for notifications on new articles posted in climate models leave a comment natural variability attribution and climate models 11 october 10 2023 by scienceofdoom in 9 we looked at an interesting paper van oldenborgh and co authors from 2013 assessing climate models they concluded that climate models were over confident in projecting the future at least from one perspective which wouldn t be obvious to a newcomer to climate their perspective was to assess spatial variability of climate models simulations and compare them to reality if they got the spatial variation reasonably close then maybe we can rely on their assessment of how the climate might change over time why is that one idea behind this thinking is to consider a coin toss if you flip 100 coins at the same time you expect around 50 heads and 50 tails spatial if you flip one coin 100 times you expect 50 heads and 50 tails time there s no strong reason to make this parallel with climate models on spatial and time dimensions but climate is full of challenging problems where we have limited visibility we could give up but we just have the one planet so all ideas are welcome in the paper they touched on ideas that often come up in modeling studies assessing natural variability by doing lots of runs of the same climate model and seeing how they vary comparing the results of different climate models to see the whole article visit the new science of doom on substack page and please consider suscribing for notifications on new articles posted in climate models 19 comments natural variability attribution and climate models 10 more on droughts october 9 2023 by scienceofdoom in 1 we saw an example of natural variability in floods in europe over 500 years clearly the large ups and downs prior to the 1900s can t be explained by climate change i e from burning fossil fuels if you learnt about climate change via the media then you ve probably heard very little about natural variability but it s at the top of climate scientists minds when they look at the past even if it doesn t get mentioned much in press releases here s another example this time of droughts in the western usa this is a reconstruction of the pre instrument period to see the whole article visit the new science of doom on substack page and please consider suscribing for notifications on new articles posted in climate history leave a comment natural variability attribution and climate models 9 august 13 2023 by scienceofdoom originally i thought we would have a brief look at the subject of attribution before we went back to the ipcc 6th assessment report ar6 however it s a big subject in 8 and the few articles preceding we saw various attempts to characterize natural variability from the few records we have it s a challenge i recommend reading the conclusion of 8 in this article we ll look at a paper by g j van oldenborgh and colleagues from 2013 they introduce the concept of assessing natural variability using climate models but that s not the principle idea of the paper however it s interesting to see what they say their basic idea we can compare weather models against reality because we make repeated weather forecasts and then can see whether we were overconfident or underconfident for example one time we said there was a 10 chance of a severe storm the storm didn t happen that doesn t mean we were wrong it was a probability but if we have 100 examples of this 10 chance we can see did we get approximately 10 instances of severe storms if we got 0 3 maybe we were wildly overconfident if we got 30 maybe we were very underconfident now we can t compare climate models outputs of the future vs observations because the future hasn t happened yet there s only one planet and climate forecasts are over decades to a century not one week we can however compare the spatial variation of models with reality to see the whole article visit the new science of doom on substack page and please consider suscribing for notifications on new articles posted in climate history climate models leave a comment natural variability attribution and climate models 8 july 31 2023 by scienceofdoom in 7 we looked at huybers curry 2006 and pelletier 1998 and saw power law relationships when we look at past climate variation over longer timescales pelletier also wrote a very similar paper in 1997 that i went through and in searching for who cited it i came across the structure of climate variability across scales a review paper from christian franzke and co authors from 2020 to summarize many climatological time series exhibit a power law behavior in their amplitudes or their autocorrelations or both this behavior is an imprint of scaling which is a fundamental property of many physical and biological systems and has also been discovered in financial and socioeconomic data as well as in information networks while the power law has no preferred scale the exponential function also ubiquitous in physical and biological systems does have a preferred scale namely the e folding scale that is the amount by which its magnitude has decayed by a factor of e for example the average height of humans is a good predictor for the height of the next person you meet as there are no humans that are 10 times larger or smaller than you however the average wealth of people is not a good predictor for the wealth of the next person you meet as there are people who can be more than a 1 000 times richer or poorer than you are hence the height of people is well described by a gaussian distribution while the wealth of people follows a power law to see the whole article visit the new science of doom on substack page and please consider suscribing for notifications on new articles posted in climate history leave a comment natural variability attribution and climate models 7 july 22 2023 by scienceofdoom in 6 we looked in a bit more detail at imbers and co authors from 2014 natural variability is a big topic in this article we ll look at papers that try to assess natural variability over long timescales peter huybers william curry from 2006 who also cited an interesting paper from jon pelletier from 1998 here s jon pelletier understanding more about the natural variability of climate is essential for an accurate assessment of the human influence on climate for example an accurate model of natural variability would enable climatologists to make quantitative estimates of the likelihood that the observed warming trend is anthropogenically induced he notes another paper with this comment explained in simpler terms below however their stochastic model for the natural variability of climate was an autoregressive model which had an exponential autocorrelation dependence on time lag we present evidence for a power law autocorrelation function implying larger low frequency fluctuations than those produced by an autoregressive stochastic model this evidence suggests that the statistical likelihood of the observed warming trend being larger than that expected from natural variations of the climate system must be reexamined in plain language the paper he refers to used the simplest model of random noise with persistence the ar 1 model we looked at in the last article he is saying that this simple model is too kind when trying to weigh up anthropogenic vs natural variations in temperature to see the whole article visit the new science of doom on substack page and please consider suscribing for notifications on new articles posted in climate history leave a comment natural variability attribution and climate models 6 july 17 2023 by scienceofdoom in 5 we examined a statement in the 6th assessment report ar6 and some comments from their main reference imbers and co authors from 2014 imbers experimented with a couple of simple models of natural variability and drew some conclusions about attribution studies we ll have a look at their models i ll try and explain them in simple terms as well as some technical details autoregressive or ar 1 model one model for natural variability they looked at goes by the name of first order autoregressive or ar 1 in principle it s pretty simple let s suppose the temperature tomorrow in london was random obviously it wouldn t be 1000 c it wouldn t be 100 c there s a range that you expect but if it were random there would be no correlation between yesterday s temperature and today s like two spins of a roulette wheel or two dice rolls the past doesn t influence the present or the future we know from personal experience and we can also see it in climate records that the temperature today is correlated with the temperature from yesterday the same applies for this year and last year if the temperature yesterday was 15 c you expect that today it will be closer to 15 c than to the entire range of temperatures in london for this month for the past 50 years essentially we know that there is some kind of persistence of temperatures and other climate variables yesterday influences today ar 1 is a simple model of random variation but includes persistence it s possibly the simplest model of random noise with persistence to see the whole article visit the new science of doom on substack page and please consider suscribing for notifications on new articles posted in climate models statistics leave a comment older posts pages about this blog 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