Ben Matthews

I’d like to have no phone at all, I don’t like small screens, nor being interrupted. Problem is that phone apps are now almost obligatory for IDs, transport tickets, passes, banking, etc. So I’d just like a phone-receiver (modem) with a sim card on a USB stick that can enable phone-app-stuff via my laptop or tablet. (Yes some tablets have data sim cards, but we still need sms and occasional phone functions for ‘verification’ etc.). Any suggestions?

No. first line in the article - “emissions in the world’s second-largest economy rose slightly as coal remained dominant”. It’s bad news. Also, article is about 2024 and your plots stop in 2019/20.
However your question is reasonable - when they made such “intensity” (emit-per-gdp) based targets, it seemed like a way to avoid constraining the economy and disguise emissions growth - but they didn’t anticipate the covid slump and such rapid demographic peaking, so maybe they’ll change the methodology for next ndc target.

This sounds positive, albeit unlikely it’s enough.
As I don’t follow the biodiversity COPs like the climate COPs, I’ll ask - was this like a COP16bis, and deal with or without US ?
I still recall UNFCCC-COP6bis which was a success despite Bush govt pulling out, inspired the rest of the world to unite.
And are people optimistic about COP17 in Armenia? Hope inspired to do better than Azerbaijan with climate. I suppose all Caucasus has much unique mountain biodiversity, maybe this can help overcome political divisions.

I’m more interested in distribution of users and local-focus of communities than country-based instances, nevertheless the map does illustrate that Lemmy has huge gaps - no country instance in all of Africa, hardly any in Asia… What can we do to make it a more global conversation ?

Too true, and good analogy with building a house extension…

I recall Putin himself expressed that, at a big climate conference they hosted in Moscow in 2003. But of course, there were also plenty of intelligent russian scientists who understand that melting permafrost, burning forests, flooded cities, and grey rain replacing white snow, is not such a great idea.

They say the other side (favour US over Ukraine) is only 20% - so 48:20 is a big difference ( in such surveys, there are always plenty who don’t know or hedge bets - and many people just don’t think beyond their local world) .

It seems the problem is the regional governments , which are prioritising regional coal mining, to prioritise regional jobs. In China there is plenty of renewable energy capacity but the sun and wind are mainly in the W and S, while the old coal mines are in the E and N. China has plenty of climate scientists and diplomats pushing central government policy, but these have less influence on ‘local government’. As many ‘local governments’ in China govern populations larger than European countries, this is something like Poland trying to keep it’s coal mines alive, in contradiction to European climate policy. Eventually there will be surplus energy, some coal contracts are going to break, question is who wins and loses then. Western observers tend to think of China as a big centrally controlled monolith - it isn’t, the ‘local’ chiefs have a lot of power. Similar central / ‘local’ governance problem with housing bubble and debt.

Potentially (ok - not currently), “24 gigatons of carbon accumulated in methane hydrates” is a serious amount. Note that as methane increases in the atmosphere, it’s lifetime increases as oxidising capacity is used up, a positive feedback. Methane may also help explain the rapid at the ends of ice ages (when sea-level rose ±100m). If there’s any really bad runaway warming scenario, it has to do with methane.

I vaguely recall Thatcher government in UK also tried to privatise the weather, added layers of complicated accounting (not sure how is now - how much of this got rolled back ? ).

So how about the Cahill Butterfly projection, …

Zed, for the last few months, and happy with it (previously vscode) - I code in Scala, so Metals provides the complex hints / actions.

Pour ajouter contexte - il semble que c’était une centre d’education pour adultes, y compris ceux venant d’autres pays qui y apprennent la langue suedoise.

Il me semble qu’il y existe d’offre ferroviaire entre quelque villes connectées avec des grosse lignes sur cette carte - par example Toulon-Nice, je me demande comment ils déterminent ‘suffisante’ ?
Autre problème - les voyages habituelles s’adaptent aux transports disponibles, donc par telle méthodologie on ne va jamais découvrir tous les voyages potentielles, si on remplirait les trous dans le reseau.

Many Ukrainian women are still in exile further west in europe, especially those with or expecting young children, for their safety. Their children are not included in this data (it says ‘on the territory’) but these are potentially the next generation of Ukrainians, if conditions become good for them to return.

The point is to encourage more to surrender, their outlook needs to be better than meat waves, and this info needs to spread behind russian lines. These guys come from a very-low-info world, if the mass-lies collapse, so would the war effort (this happened before).

Good, but I hope they also get the option not to be exchanged, poor chance of survival if they go back. Should stay, but work on communication to the other side.

I’m not convinced this plot bears much relation to the Hansen et al paper. The plot combines SSPs - socioeconomic scenarios, RCPs - levels of ‘radiative forcing’ (all gases together - the numbers 1.9 to 8.5 are RF in W/m2) and temperature.
Hansen et al (OP) are suggesting that the climate sensitivity may be higher than the IPCC range, which would imply a higher temperature for any given RCP level. This suggestion is derived from the recent history of aerosols and temperature, as I discuss in another comment (above/below?).
However this doesn’t change which curve we are on (in reality none of them), as the big difference between curves is from projections of future emissions depending on technology, population, policies etc. Also the near-term projections have little relation to the long term, due to inertia but also the range of different models and assumptions used to make them (some years ago). So you can’t look at very recent data to derive which curve we are on.

I was (years ago) part of the process that designed the IPCC scenario structure of splitting the SSPs from RCPs, to allow the two modelling groups to work in parallel rather than one waiting for the other, so they could get on with connecting feedbacks (not sure this happened…).
But IPCC ends up re-blending too many varying factors in one plot, because they have page limits, which can be somewhat confusing. Work of 10,000 scientists over six years condensed into one summary report… - is that the most effective method of communication ? That’s why I prefer to make an interactive model.

Fundamentally, the useful question is not ‘where are we going’ but ‘where do we want to go’ - taking into account all the feedbacks and inertia in the systems, but making choices about our common future. To get to the lowest (1.9) curve we’d need a global green revolution tomorrow, but it’s not physically impossible. As for the 8.5 curve it’s very unlikely it’s part of the set as similar to earlier high-end scenarios run by IPCC since 1990s, which might have happened if we’d stayed in the coal age (still useful for comparing the high end of the physical models). The others are still in play. Extrapolating current trends and policies (especially tech and popn in China) I’d say the most likely is somewhere between 2.6 and 4.5 curves, but we could do better. While if you are building sea-walls you should anticipate worse. But don’t be fatalistic, we still have many options.

[ Side remark in response to comment - as for Jan 2025, it’s really not ‘climate’ to conclude anything from one month. Even the El-Niño cycle depends on heat transfer between surface and deep ocean, which is a slow process, you need to integrate over much longer time. There may be a warm anomaly recently in tropical oceans, and also the high-arctic, but it’s actually quite cold where most northern people live (due to Rossby waves whose amplitude is increasing, as we expected in an hand-waving kind of way). ]

My model, no not yet clathrates or specific permafrost feedback, although I’m concerned about these and would like to put such feedbacks in (with wide adjustable parameter ranges to reflect high uncertainty). My model is interactive, you can play with it in a browser, so it’s hardly typical.
However, in relation to the OP and the Hansen paper, it’s important to understand that the usual definition of climate sensitivity does not include such “slow” feedbacks - it’s assumed to assume fast atmospheric feedbacks e.g. physics of clouds, but not slower biogeochemistry. CS has been used for decades for comparing models, so it’s useful that the definition remains the same, simply the equilibrium (multi-century) response to CO2 doubling, it’s not any kind of prediction. That’s why it’s surprising that he would draw strong conclusions from a number (4.5) that’s well beyond the normal range.
Complex 3d physics models derive CS, while integrated assessment models use CS as a calibration parameter for one component of a complex system, including socioeconomic drivers, emissions policies, land use change, etc. Most models (including mine) do have some climate - biogeochemistry feedbacks (for example, there is faster soil respiration at higher temperature), which are included in such ‘real’ scenario projections, but wouldn’t change the CS.

I think the Guardian article may be somewhat exaggerating what the Hansen et al paper says. I’ve been studying this kind of problem for 30 years. It’s indeed true, that there are many ways to explain the historical temperature rise, by adjusting the balance of positive (mainly greenhouse gases) and negative (sulphate and white-carbon aerosols, volcanos etc.) forcings. So if you think the aerosol effect was greater, you also have to assume the greenhouse warming was greater to balance - hence deriving a higher climate sensitivity (CS). In this case, they are arguing that we underestimated the (former) cooling effect of shipping sulphate - I’d agree this is not a trivial factor (and similarly for the warming effect of aviation induced cirrus, which we could also change quickly with global transport policy). However, I really doubt this change is sufficient to justify such a big shift from the long-developed consensus range of CS.
In general, the recent historical data series has never been a sufficient constraint on CS (I know from having tried a similar approach for probabilistic analysis with earlier versions of my own model). So we have to use other methods too, and the IPCC consensus for the likely range of 2.5-4ºC for CS is derived from a wide range of methods and sources, particularly but not only big physics-based models (GCMs). I’d be very cautious about overturning this based on any one study, despite my respect for Hansen and colleagues. Of course, this contributes an interesting new view on this important topic, but it does not justify the headline of the article.