Both visualizations look pretty much the same apart from some visualization effects. But this is how the line in the above time range (here until Dec 18 in 2016) looks as of today in the new LISIRD app:
For those who are interested in what keeps us busy – here is one thing: Local politics and in particular Berlin traffic planning.
If you are able to endure german subscripts you might watch our attempt to convince people that their ideas of traffic load removal may have the opposite effect of what they think.
If not -Tim had only very few hours to work on the music but you might just enjoy his lofty kind of ambient electronica.
Remark: The code as posted at the randform post ShutterSploshScatterPlots needs to include the new Content Security Policy.
That is you have to embed the following lines (at least thats how it worked here for the moment) into your html head:
In case you feel a bit overcharged by all that – as a courtesy for you I quickly filmed the program output with my mobile and turned it into a gifanimation, which you can watch after the ” Read the rest of this entry”.
This month no new randform post.
The previous post is hard enough to digest.
On a personal note:
The previous post is actually a main result of a phase between mid/end 2012 – spring 2015. In this phase I was investigating in which way I could apply my math/physics and visualization skills to climate science. In 2015 I more or less ended the investigation, since I found that -amongst others- my programming skills were not good enough for a continuation on a more professional level and started to work in a company in which I have been working since then.
Most of randform readers might have heard that the socalled greenhouse effect is one of the main causes of global warming.
The effect is not easy to understand. There are two posts which give a nice intro to the greenhouse effect on Azimuth. One is by Tim van Beek and one is by John Baez.
The greenhouse effect can also be understood in a slightly more quantitative way by looking at an idealized greenhouse model.
In the above diagram I now enhanced this idealized greenhouse model (as of Jan 2017) in order to get an idea about the hypothetical size of the effect of an absorption of non-infrared sunlight and it’s reradiation as infrared light, i.e. the possibly effect size of a certain type of fluorescence.
I sort of felt forced to do this, because at the time of writing (February 2017) the current climate models did not take the absorption of UV and near infrared light in methane (here a possible candidate for that above mentioned hypothetical greenhouse gas) into account and I wanted to get an insight into how important such an omission might be. The simple model here is far from any realistic scenario – in particular no specific absorption lines but just the feature of absorption and reradiation is looked at.
The above diagramm shows the earth temperature in Kelvin as a function of two parameters, as given by this enhanced model. The two parameters can be seen as being (somewhat) proportional to densities of a hypothetical greenhouse gas, which would display this type of fluorescence. That is the parameter x is seen as (somewhat) proportional to the density of that hypothetical greenhouse gas within the atmossphere, while y is (somewhat) proportional to the density near the surface of the earth. Why I wrote “somewhat” in brackets is explained below.
The middle of the “plate” is at x=0, y=0 (please hover over the diagram) which is the “realistic” case of the idealized greenhouse model, i.e. the case where infrared absoptivity is 0.78 and the reflectivity of the earth is 0.3. The main point of this visualization is that linearily increasing x and y in the same way leads to an increase of the temperature. Or in other words, although raising x by a certain amount leads to cooling this effect is easily trumped by raising y by the same amount.
As far as I learned from discussions with climate scientists the omission of non-infrared radiation in the climate models was mostly motivated by the fact that an abpsorption of non-infrared is mostly happening in the upper atmossphere (because methane is quickly rising (but there are also circulations)) and thus leading rather to a global cooling effect than a global warming effect and so it in particular doesn’t contribute to global warming. The enhanced simple model here thus confirms that if absorption is taking place in the upper athmossphere then this leads to cooling. The enhanced model however also displays that the contribution of methane that has not risen, i.e. methane that is close to the earth surface, is to warm upon absorption of non-infrared light and that the effect of warming is much stronger than the cooling effect in the upper athmosphere. Unfortunately I can’t say how much stronger for a given amount of methane, since for assessing this one would need to know more about the actual densities (see also discussion below and the comment about circulations). Nonetheless this is a quite disquieting observation.
I had actually exchanged a couple of emails with Gunnar Myrhe, the lead author of this corresponding chapter in the IPCC report, who confirmed that non-infrared light absorption in methane hasn’t sofar been taken into account, but that some people intended to work on the near-infrared absorption. He didn’t know about the UV absorption that I had found e.g. here (unfortunately my email to Keller-Rudek and Moortgat from 2015 whether there is more data for methane especially in the range 170nm-750nm stayed unanswered) and thanked for pointing it out to him. He appeared to be very busy and as drowning in (a lot of administrative) work, so that I fear that those absorption lines still might not have been looked at. That is also why I decided to publish this now. I sent a copy of this post to Gunnar Myrhe, Zong-Liang Yang and John Baez in June 2017, where I pointed out that:
I have strong concerns that the estimations of the global warming potential of methane need to be better assessed and that the new value might eventually be very different then the current one.
Last year (Jan 2017) there was a long essay in the german newspaper “Die Zeit” (“The time”) about how important a natural scientific evaluation could be for historical research. The essay: “Darum hatte Hitler keine Atombombe” (“That’s why Hitler had no nuclear bomb”) was written by physicist Manfred Popp. A very brief summary of his argumentation is that a lot of historical research about german nuclear research during Nazi times was more or less flawed due to missing knowledge or misinterpretations of physical facts.
The frequent randform reader knows that a lot of randform posts are concerned with questions about how to keep earth as a habitat for humans. One of the biggest problems seems to be: population growth. That is humans are the root cause of “pollution”, they are to a great extend causing climate change, they massively reduced the habitat for other beings including those in their own food chain and if their own strive for efficiency keeps on like that, then they (partially?) need to abolish themselves and eventually (?) start the AI machine population explosion-if they haven’t wiped themselves out beforehand in their wars for ressources.
But what really are the reasons for this human population growth?
This seems to be a very deep systemic question, but for me it is rather suggestive that this strive or “competition for efficiency” is playing a major role here. So today I would like to discuss this quest for efficiency again a bit at the example of agriculture.
