Reddit reviews Paleoclimate (Princeton Primers in Climate Book 10)

You are talking about paleoclimatology, which is an entire scientific discipline that studies exactly what you were talking about. There is extensive literature out there that looks at past climate changes on earth. It is a challenging field, because the rock record has gaps in it and these studies use proxy evidence out of necessity. If you are genuinely curious about past changes in earth's climate (and not just a stubborn climate change denier), Princeton has printed a good, affordable book that introduces most of the major climate events. link

edit: Oh, and the rate of change in atmospheric composition and temperature we are currently experiencing are absolutely unprecedented in earth's 4.6 billion year history.

> so it's not that I don't trust the scientific method! I'm just looking for an explanation put into terms that I can understand.

I get where you're coming from, I just think that eventually you would have to decide whether to trust scientists' previous work and the scientific community as a whole or not. I mean, unless you have multiple years to study the field. Which could be fun, but you might have other plans ;)

When I search on the internet, I do usually see a lot of introductory/"general public" level information. My strategy is if there's a reference to a paper, jump to it. Usually every paper includes an introduction with an overview of previous research, which means I'm basically guaranteed to find the answer, if I am willing to take the time and read the papers (which can be very hard).

But, if you want the easy route, you can pick up a textbook, like this one and get a much more systematic overview. Although admittedly, a reviewer says he "speaks very casually about isotope fractionation, as if everyone should already be familiar with this speciality". Oops! Still, there are other textbooks.

> the last paragraph says that it can be an average of hundreds to thousands of years, measured in Vostok... averaged data... false peaks, false valleys

I don't see the paragraph you're referring to? Also, averaging out data only smooths out peaks and valleys, it can't create ones where none existed.

> chaos makes climate hard

I don't think so. This explains why. It depends what you're trying to do of course. If I had to predict the exact nature of the climate with a doubling of CO2 compared to today, I would be like, "uh, dunno, that's such a huge change, all sorts of chaotic things could happen". But if I were predicting the climate if we kept today's CO2, I think the climate system would stay more similar to today (although it would keep warming for a few decades, it's certainly better compared to the other scenario). That's just basic energy balance really.

> it's arguably a lot better techniques from the 1960ies and forward, that's when we started recording temperature with satellites.

Satellites don't record the temperature, they record radiation - which is actually rather different. To go from that to the temperature requires some assumptions. That's why the satellite temperature record has had to have many corrections that overall, flipped it from showing cooling to warming. Also, a satellite scientist says the thermometer record is probably more accurate. Here's an interesting article on the statistics behind the thermometer data and some issues with the satellite data.

You're right that our temperature data in the 50s isn't as good as today, that's why datasets like HadCRUT4 have 100 versions which basically show the range of possible ways the data can be fitted together. It's like putting error bars on each data point but more advanced.

> The main problem with most of the graphs that's circulating (as well as the ones in the links we've scratched here) is that different methods of obtaining the data has been used within the same graph.

If they are trying to measure the same thing, it should not be a problem. More important is where the data has come from - if somebody is deliberately picking and choosing their data to get a certain result, then that's bad. If all the data has been considered fairly, then the result can be good.