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> Since the movie “Inconvenient Truth” the amount of ice of the world has increased significantly toward the mean.
Let's go to that link (or read the top reply) and verify ourselves![0] Should be easy, right? Let's click "hide all years" on the side and also uncheck the median and ranges (so we have nothing). Then one by one, let's click the decade averages in the top right. Where does the graph move? We could also click every 5 years, or even 1 year and watch each line be drawn. Is there a trend? The one I see completely disagrees with that tweet.
But why is the tweet misleading? That's a better question. Well, click 2022 and you'll see something interesting. In Jan-April there's actually a bit more ice than in 2006, with about 0.5 million km2 as a max differential. But July through December it goes far below, with a differential of about a million km2. But let's check other years, to see if there's a bias. Just select 2022, we'll add 2023 and down to 2017. Okay, we see 2022, 2017, and 2020 are a bit different, so let's keep those in mind. Now let's do the same thing around 2006. We see here that 2006 is a bit abnormal for the years surrounding it. Now let's select the bounding years and then compare the two. Does this make sense and agree with the averages? It should.
Your alarm bells should have gone off in the first place because 2023 doesn't even have a full year to plot. Not even half of one.
> Additionally nearly every climate sensor is located on the tarmac of an airport.
Yeah! That's actually exactly right! We need a lot of thermometers and placed in a lot of locations. (I should also mention that there are a lot of thermometer systems that aren't based on airports though but we could also get deep into wet bulb vs dry bulb and all kinds of things. We'll just stay here for now) So we look for existing ones to work with and then use that data. What I find interesting about this tweet is that usually we're criticized for "manipulating" data rather than this. There's a surprisingly good and approachable article on all this here[1]. You'll find how we adjust surface temperature data to account for being near a black body, how ocean temperatures are adjusted based on the measurement techniques that are used (because each one introduces a different bias), and so on.
Actually one thing you'll frequently find me complaining about is how difficult analysis actually is (though usually in the context of ML). This is quite similar. You can't ever really work with "raw" data, because your measurements have biases in them and if you don't account for them you'll get biased results which do not align with observations. But the best first check that you can actually do is look at prediction model and then look at the results and see how good the predictions were. Luckily with something like climate science we've had decades of this going on and so we can verify this pretty well. We just need to look at models created in the 80's, 90's, and 00's and see how good they predicted the subsequent decades of temperature rise[2,3,4].
So I can get the misunderstandings here and the reason to be skeptical. But I think we've thoroughly shown that the two tweets you linked to are either by people that are misunderstanding a highly complex thing (pretty understandable) or are not acting in good faith (which if they're claiming expertise with lacking knowledge, this too is not in good faith). Climate is a pretty complicated topic with a lot of moving parts that can appear to contradict one another if you aren't careful. I highly suggest drawing charts to keep track of how things connect. Most people aren't trained in these things and so it is understandable. But you also should focus on asking questions when you don't understand rather than asserting "facts". There's no reason to feel embarrassed for not knowing things. We all are pretty fucking stupid, myself included. But let's also try to not trick ourselves. The best way to do that seems to be to challenge our own beliefs. You set up a challenge of "how would I disprove myself" and then see if you can do so. If you can't, then congrats, your opinion should get stronger. If you do, dang, let's update our beliefs. Usually it is somewhere in between though and you don't have to tear everything down. But I have to admit, when the whole perception changes, it is kinda exhilarating. Finding out new things is quite a lot of fun.
[0] https://nsidc.org/arcticseaicenews/charctic-interactive-sea-...
[1] https://arstechnica.com/science/2016/01/thorough-not-thoroug...
[2] https://climate.nasa.gov/news/2943/study-confirms-climate-mo...
[3] https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/201...
[4] https://www.columbia.edu/~jeh1/mailings/2020/20200203_Models...
You can see the archived link here:
https://web.archive.org/web/20170115133353/https://www.epw.s...
The other two links are alive but you need a twitter account to view them.
None of the claims zackees is making are new or obscure. They're well known problems proven many years ago. For example so many thermometers are located next to runways because climatologists collect data from weather stations that were never intended for them. Airports need this data but then it gets mixed into datasets that are claiming to measure general change in climate.
This can lead to absurd outcomes. The UK had a very hot day last year, with the Met Office reported a "record breaking" temperature. The problem is that this temperature was recorded by a thermometer right next to a military airbase runway at the exact moment three fighter aircraft were landing. The temperature spiked up to the record level for 60 seconds and then dropped again, with the spike+drop being quite massive. Finding this out took a year of FOIA requests, done by independent bloggers of course, not journalists.
Jet exhaust shouldn't be reported as climate change, but it is, because climatologists don't seem to care much about data quality. The underlying networks they use have a lot of corruption in them from various sources and the error bars are wide, but the uncertainty is never reported or shown to the public.
A couple of decades ago this problem flared up in the US and Congress spent the money to build out a new state of the art weather station network just for climatologists, with very carefully sited stations. It's called the Climate Reference Network and climatologists refuse to actually use its data. If you review the thermometer readings it generates you can see why:
https://www.ncei.noaa.gov/access/monitoring/national-tempera...
For nearly 20 years it's shown no warming in the USA whatsoever.
I'm going to need a source on this. This doesn't even really make sense to me, because a single 1s spike (in either direction) should be filtered out. It also doesn't make sense how this would significantly affect a model which is performing a multi-decade analysis unless that single 1s spike was used to represent at least a month's worth of temperature. Which as far as I know the data is being pulled at at least a daily rate if not more, so the spike would disappear.
For the "no warming" part, let's adjust things a little bit to be more clear. First, let's clear that noise. It is all jiggly and difficult to read and trend going on. Let's select the month of June (middle of the year) and then select a 12-month time scale. Interesting, the beginning and end have the same point. Let's now find out if this is a coincidence or not (current window should be 2006-2022). If we move our window to 2010-2022 we see a clear trend line up over the last decade, but it is noisy (-1.07 -> +0.96). So let's go in the other direction. 2000-2022 seems down, slightly. Let's keep going. 1990-2022, okay, very clear upwards. 1980-2022, very upwards. 1970-2022, we're now at -1.65 -> +0.96. 60's, seems we've stabilized. 50's, oh, difference is decreasing again. And we keep going and see a clear trend of increasing.
I think when we're talking about a multi-decade effect we need to look at... multiple decades and be a bit more careful to not only look at one single window. Especially with numbers jumping around a lot.
I was in London all last summer, as I am now. You are correct. The idea that the record breaking temperature of 19 July 2022 (1) was some kind of fake or artifact of measurement, is horseshit, plain and simple. There's no other way to put it. This is a glib but nonsensical assertion. It's just deliberately wrong.
That 1 day was the worst of it but the whole several weeks were bad. I myself measured 41C in my back yard on the 19th. Others had similar.
1) https://www.independent.co.uk/climate-change/met-office-uk-w...
https://www.theguardian.com/world/live/2022/jul/19/uk-weathe...
It begins here, with the BBC lying about where the record temperature was observed. Not a great start:
https://dailysceptic.org/2022/07/20/climate-alarmists-turn-u...
"The BBC noted on Radio 4 last night that the record temperature arose in the “village” but co-ordinates on the Met Office site place the device halfway down the runway at RAF Coningsby, home of two squadrons of frontline, combat ready squadrons and a training base for Typhoon pilots."
Here's where they discover the record was set during a brief spike:
https://dailysceptic.org/2022/11/27/fresh-doubts-emerge-abou...
"Over six minutes, the temperature jumped suddenly by 1.3°C to 40.3°C at 15.12 (3.12pm), and was 0.6°C lower just a minute later. In just two minutes from 15.10 the rise was 0.6°C."
Here the Met Office claims that they have a rigorous verification process, and maybe a break in clouds was the reason for the spike, but Morrison got a satellite photo that showed it was a cloudless day:
https://dailysceptic.org/2022/12/04/doubts-remain-about-40-3...
Here's where they FOIA the logs and find the 3 planes landing at the time the record was set:
https://dailysceptic.org/2023/06/28/exclusive-three-typhoon-...
Re: no warming. Someone else was confused by this, maybe my language wasn't clear enough. The US CRN only has data back to 2005 because that's when it was opened. The point is that the older network is garbage, with lots of heat-causing corruption in the record and very low data quality. Climatologists in the 1990s were drawing totally different temperature graphs to today's, yet they are both supposed to be based on the same observations. This is clearly a terrible situation to be in for any field, and a big driven of distrust in climatology. Good scientists care about instrument accuracy, they don't collect low quality data and then constantly rewrite the collected data in a never ending attempt to retroactively fix it! So if we restrict our view to the data collected by the trustworthy weather station network, what do we see? No warming at all, even though CO2 rose constantly over the time period in question. That's a serious problem and the attempts at debunking it aren't convincing.
Processing data is pretty common. I mean we aren't fucking idiots. If you can figure out an issue in 2 seconds, you bet it has been addressed. Other sources are just other blog posts so forgive me for not taking them as good value given that I can read articles from scientists and understand all their methods and models (which are open sourced[2]). I mean even the blog you linked me has a graph of arctic sea ice[1] (also addressed in other comment) where they didn't even bother to remove the 1981-2010 mean line. Which both years are below... But if you look at my comment[0] you'll also see why their selection (especially of the time range in months) is deceptive. I walk you through how to verify yourself. It is fine if you don't believe the NOAA data, but if you don't then you also can't believe dailysceptic since they are using that same data to dispute NOAA's claims. Both are dependent on the data being accurate. Which a big irony given our above discussion.
To be more direct with satellite data (because I'm guessing you aren't going to read the arstechnica article), satellites don't measure temperature, they measure brightness. That is then turned into temperature. But they also don't measure ground temperature. So you're biased to that. But this can of course be adjusted and corrected for. But again, if we can do that for satellites why can't we do it for airport thermometers? The reasoning just doesn't line up in a consistent fashion.
I can tell you're really passionate about the subject. I congratulate you on that. We need passionate people and in no way do I want to get rid of your passion. You're trying to seek truth, and that is honorable. But an important part in science and truth seeking is to become your own adversary. Once you feel that an idea is good you have to attack it pretty fucking hard. You can't be sad when things get knocked down, it is just part of the process. You take what's left and rebuild from there and repeat. You need to challenge your own viewpoints. If there is nothing to convince you that would cause you to change viewpoints (even in the hypothetical!) then you aren't actually seeking truth, you're seeking validation.
So if you're seeking truth and you are acting in good faith, tell me just one precise thing that would get you to change your mind if the data suggested. I'll go first: I would doubt the weather models if I saw a constant or increasing trend of arctic sea ice that was outside variance levels.
[0] https://news.ycombinator.com/item?id=36564370
[1] https://dailysceptic.org/wp-content/uploads/2022/07/image-69...
[2] https://berkeleyearth.org/archive/about-data-set/ (btw, their skeptics guide also addresses all these issues. I hate to break it to you, but these are the same talking points from skeptics over the last decade. So it tends to be fairly easy to refute because noting additional has to be done. Just reapply the previous method to the newer data)
We can discuss other unrelated stuff, that's fine. But please accede first to these three requests:
1. Let's resolve the RAF Coningsby discussion before moving on. You appear to have mis-read the initial claim and then decided it didn't make sense and asked for sources. You now have the evidence. As you don't mention RAF Coningsby or the record breaking temperature in your reply, is it OK to assume you accept that evidence and thus that this reporting problem is real and did in fact occur as stated?
2. Please make it clear what the heck you're actually replying to! Quotes would avoid a lot of confusion here. Remember that some of these articles came out a year ago and I dug them up to satisfy your request for sources, I don't remember every single sentence in them by heart.
3. Finally, please cut out the attempts at philosophical lessons. You seem to be a climatologist, from your posts saying "we" when talking about that group? If so then that's a small community and one with a poor track record of accepting when its theories and evidence have been successfully knocked down by others. Before lecturing others about epistemic humility and truth seeking you may wish to take on Mann and other famous grifters that clutter up the scientific landscape, before random internet commenters of no note or impact.
Moving on.
> If you know the direction it is biased, you can unbias it. Processing data is pretty common. I mean we aren't fucking idiots. If you can figure out an issue in 2 seconds, you bet it has been addressed.
If you know the direction and magnitude of the bias, which the Met Office clearly do not, and if the bias is constant and well characterized, etc. That's important! As you seem to have accepted by choosing to debate something different, climatological agencies are happy to report momentary blasts of jet exhaust as evidence of climate change. That's an issue that literally anyone can figure out in two seconds the moment they discover the thermometer isn't in the village as claimed, but rather right next to a place jet fighters take off, and yet, unambiguously, the Met Office had not figured this out. They even claimed they'd used a rigorous verification process!
So please forgive us if we assume that you guys are in fact not addressing issues that any "fucking idiot" can spot in two seconds, because this would seem to be one of them.
More generally, your field's attitude to data quality is guaranteed to create train wrecks like this. If your data is poor quality you often won't know how to characterize the corruption, which is exactly why good scientists obsess over how to collect data with high quality instruments and setups in the first place. They don't just scrape whatever data they find on the internet and then assume with 100% confidence that 100% of the measurement error both can be well characterized and actually will be. That's an absurd methodology that is guaranteed to lead to continuous disasters like this, as well as the entirely reasonable lack of trust when people discover that you constantly rewrite the historical record. You guys can't even change the data once, you keep doing it, meaning that the vast majority of the climate literature is based on measurements you later decided were wrong! Most of the climate literature should have been retracted by now! This is inevitable when you can't reliably characterize measurement error. Thermometers aren't advanced tech and it's easy to build networks to a standard that satisfies even critics so why do you persist in "fixing" and then constantly "refixing" corrupted data sets?
Feel free to not respond to any of the points made, but the arguments so far are in good faith. If you think they aren't then the problem is on your side.
I want to also clarify that good faith doesn't just mean that you have good intentions. The bar is far higher than that. You have to have a willingness to change opinions given countering evidence. You have to do your best to interpret my words as to their intended meaning, not to the literal (because language is fuzzy and imprecise). It does require you to take time and process to the best of your ability, to ask for clarification where you are confused. But I assure you that everything I have wrote is not only connected to the responses, but strongly so. If you can take time to see this then you'll demonstrate good faith. But if you also do so then the conversation need not continue further anyways. So that's kinda where we'll stand because frankly I don't have the energy to continue. You can put that on me. But maybe you should attempt to understand why that is so.
https://heartland.org/wp-content/uploads/documents/2022_Surf...
Well, I haven't yet seen you change any of your opinions, but obviously that isn't proof you're unwilling, so I don't think trying to figure out other people's willingness is very productive. How would anyone ever know? If someone is putting in the effort to cite sources and defend their position, it makes sense IMO to assume a default of good faith argumentation. The alternative is a kind of nihilism. Indeed, I'm willing to continue. It's you who aren't! So, who is most willing to change their views?
Let's agree that our disagreement here stems originally from a disagreement over the nature of citing sources. I'd prefer to discuss the original claims (the leaves, as you put it), or at least finish discussing them, with the source excerpts being there to back up those claims only. You'd prefer to debate the entirety of the sources themselves as part of determining the validity of the original claims. Am I right in understanding this is because you don't (yet) believe the specific claims about the airport, the logbooks, etc? Or do you accept that this problem did occur and now wish to have a broader debate? Also how wide does this go? Will you bring up non-cited articles by the same author? Non-climate articles on the same site?
Getting more towards the roots. There seem to be three "branches" of this tree. (1) the RAF airport, I believe this has been proven conclusively unless you think Morrison is inventing FOIA requests and things out of whole cloth so let's put that to one side now, (2) data adjustment vs improved instrument quality and (3) the sea ice chart.
I've already laid out my views (and those of zacharees I guess and lots of other people) when it comes to (2). We don't accept the idea that scientists should just suck up data of arbitrarily low quality, do some processing and then demand the public blindly trusts that the data is fixed. Jet exhaust spikes being declared climate change are clear evidence that this fixing process doesn't work properly, but there's also a logical circularity issue. Anyway. No need to repeat all that as I wrote it out above.
That leaves (pun intended har har) (3) the sea ice chart. It helps to have context here about what Morrison believes. His line is that global warming was real, but "started to run out of steam 20 years ago" as he put it. He thinks that CO2 saturates i.e. climate response isn't linear but logarithmic and that whilst there was indeed some industrial warming in the 20th century, in the last 20 years most impact on temperatures has been a mix of natural factors like El Ninos and poor data handling by climatologists. The 1980-2010 trend line remains because, firstly, climate skeptics don't like tampering with charts! These charts are generated by government provided websites and the standard in that community is to use the generated images as-is. And secondly, because it doesn't contradict his views on what's happening. Indeed he calls it out specifically, "As can be seen in the graph above, the decline rate of the sea ice extent is not far off the 1981-2010 average and well above 2012" so I don't understand why you say he didn't even remove it. Why would he? He goes on to talk about natural cycles and the AMO/PDO, so it's a part of his argument. The chart supports that view because if sea ice were driven purely by human activity (the standard line we're fed) then sea ice should continue to decline year-on-year but there's been no effect from the last 10 years of emissions, apparently. So clearly natural variation is dominating here.
No, because I'm discussing the data. That's why it is the roots. My claim about the sources you mentioned are the stalk, which is rotten. Because they are misinterpreting or misunderstanding the data and making conjecture that isn't validated. I haven't really discussed (1) but I've extensively discussed (2) and (3).
a. Doesn't plot trend lines. What are they trying to link to, exactly?
b. Has no observable trend in it. You can see that with your own eyes.
Look at the graph!
BTW, in the text there's a claim there's a trend but, "the warming rate (trend) in USCRN annual temperatures is 0.86°F per decade, with uncertainties ranging from -0.58°F to 2.31°F per decade."
In other words the trend is so tiny the uncertainty bound includes zero, which means they can't actually say if there's a trend at all. It might even be going down. This is all another way to say there's no observable problem in this data. It's called global warming, but in the country with the best temperature network it doesn't happen.
> A couple of decades ago this problem flared up in the US and Congress spent the money to build out a new state of the art weather station network
> For nearly 20 years it's shown no warming in the USA whatsoever.
i.e. since the construction of a high quality network, warming doesn't happen anymore.
If you zoom out to the 1950s you're incorporating data from the old network. The US government built a new one because data from the old network was being extensively modified by climatologists post-collection, and they were even modifying data long in the past, using the low quality of the network as a justification for doing so. More than half of all observed warming comes from these administrative adjustments and aren't actually visible in the original data, so you can see why you'd want to fix that.
Example: https://www.ncei.noaa.gov/maps/lcd/
What you are looking for are “authoritative” analysis from the same in group perpetuating this scam, which is circular reasoning and a logical fallacy.
Many authoritative sources outside of this club are rightly pointing out with hard data that this warming is so overstated, fraught with integrity problems (to put it lightly) and conflicts of interests that the entire narrative needs an audit and inclusion of climate scientists that have been locked out of this debate.
https://web.archive.org/web/20090404150607/http://www.giss.n...
This is a very interesting historical article which NASA has long since deleted from their website. Look at the two graphs, in particular the graph of US temperatures on the left. The text says this:
How can the absence of clear climate change in the United States be reconciled with continued reports of record global temperature? Part of the "answer" is that U.S. climate has been following a different course than global climate, at least so far. Figure 1 compares the temperature history in the U.S. and the world for the past 120 years. The U.S. has warmed during the past century, but the warming hardly exceeds year-to-year variability. Indeed, in the U.S. the warmest decade was the 1930s and the warmest year was 1934.
OK, so in 1999 the historical record said there was no clear climate change in the USA and the hottest year was 1934. Temperature declined from +1.5F (anomaly) to about -0.2F in 1970. Now look at the modern NASA temperature graph:
https://data.giss.nasa.gov/tmp/gistemp/CUSTOM_GRAPHS/87aa1e2...
If you look at the 1900-2000 period in both graphs, the story is very different. Now 1999 is hotter than 1934. In the old graph, the period between 1980 and 2000 doesn't do much. In the modern graph you see rapid warming.
So what's going on? As you can see, by the year 2000 climatologists were getting seriously bothered by the US data. It can't really be called global warming if it isn't global. Also, the US temperature network had a lot of problems but it is by far the most comprehensive for 20th century data. Much of the world doesn't have any data at all for much of the 20th century! Theory and observed data didn't match, so they went looking for reasons to change the data. If you look hard and long enough you can find such reasons, and they had plenty of time. The weather stations were never intended for climate monitoring so their siting and procedures weren't good enough for that. More and more adjustments started being made until the picture you see today: they cooled the dustbowl years and warmed the most recent history. Fast forward 20 years and they're so comfortable with changing historical data that some temperature records rewrite the entire history of every thermometer reading, every month.
This isn't really kosher, obviously, hence the construction of the new Climate Reference Network. Unlike the historical network this one is built for climatologists, with very careful siting away from heat sources. It shows no warming. So to recap: in 1999, the weather stations show no warming in the 20th century. A few years later a new network opens, and it shows no warming either. The appearance of warming comes from big piles of FORTRAN that reprocess the old data. Although this is about the US data, the global thermometer network has even bigger problems with siting, rewritten histories etc.
Hopefully that's enough to go on, if you feel like researching the topic further!