By the standard of that blog, it's possible for temperature to continuously really be rising 100 degrees over a century but for the last year to not be the hottest year on record, if the margin of error is a degree.
Hottest year on record isn't a great metric, though. It's all about the trendline. And the trend is for continuous, significant, and dangerous increases in global surface temperatures to be observed over timescales of ~5 years.
> The NOAA raw data shows no warming over the past century
> When presented with my claims of fraud, NOAA typically tries to arm wave it away with these two complaints.
> They use gridded data and I am using un-gridded data.
> They “have to” adjust the data because of Time Of Observation Bias and station moves.
> Time of Observation Bias (TOBS) is a real problem, but is very small. TOBS is based on the idea that if you reset a min/max thermometer too close to the afternoon maximum, you will double count warm temperatures (and vice-versa if thermometer is reset in the morning.) Their claim is that during the hot 1930’s most stations reset their thermometers in the afternoon.
> This is easy to test by using only the stations which did not reset their thermometers in the afternoon during the 1930’s. The pattern is almost identical to that of all stations. No warming over the past century. Note that the graph below tends to show too much warming due to morning TOBS.
This soundbite does not carry much useful information. Sure, it is an amusing factoid that the spreads of the data points overlap, but that does not mean anything, especially if you do not explain what that spread represents (is this a confidence interval for the true average, or is it just meant to represent the spread (due to geography) of the data over which it was averaged). It is completely nonsensical to use this margin in order to say things like "Year X was as hot as N other years".
Moreover, even if the margin of error is big, we can still easily calculate (with high precision and certainty) the presence of a slope when analyzing the whole data set.
P.S. A minor side note is that this is temperature averaged over the entire globe, so to a big extent this spread is not an "error", rather it is representative of the variance of Earth's temperature at different geographical locations and at different times throughout the year.
We don't have a fully accurate measure of what the earth's temperature is, so scientists estimate what is it based on available data. Any temperature recording device also has an error margin. Thus the annual temperature is an estimate with a 95% confidence interval.
Look at the year 1998. See how it clearly stands above many preceding and following years?
In fact, 1998 was so abnormally hot that for a long time AGW skeptics used it as baseline to harp on the meme "global warming has stopped for N years." (It's easy to pretend the world is cooling, when you pick one of the hottest years on record as baseline.)
And now see how 1998 is unambiguously cooler than 2016.
Rest assured, I expect a decade (two if we're lucky) of listening to "Global warming has stopped since 2016" from now on.
I've always considered that type of AGW argument as analogous to watching a rubber ball bounce down a hill and saying, "See? It bounces so high! There is no trend."
(I implore anyone who looks at this to take a look at their other visualizations, all of them push a narrative, and at least three misrepresent information from their sources or explicitly state false information)
Your (I assume your, since your username matches the site) visualization shows a tree, and reads as there being 31800 wiped emails, of which 12200 were later found, and of those 2800 were work related. I'll quote FactCheck.org, one of the sources you list on your site:
>There is no evidence to date that work-related emails were intentionally deleted. ... In his July 5 press conference, Comey said “like many e-mail users, Secretary Clinton periodically deleted e-mails or e-mails were purged from the system when devices were changed.”
Your visualization states that the FBI found emails that Clinton wiped. This isn't the case (or at least, the FBI doesn't believe this is the case).
The racial killing one is misleading, although I'll grant you not explicitly false, just heavily misleading. Specifically, your use of percentages is badly phrased and could be seen to push a misleading narrative.
If I hover over raw, I see "6546 blacks killed by blacks". This is a true statement. If I hover over percentages, I see "92.9% of blacks killed by blacks". This is obviously not true, since it would imply that every black person was killed this past year, and 93% of them by other, now dead, black people, a ridiculous assertion. Instead, what you should state is "Of the ~7000 black people killed last year, 92.9% were killed by other black people". That's the true statement.
I don't claim this is false though, because it was obviously just a formatting mistake, which I hope you'll amend now that I've informed you of it.
It seems to me however, that you are trying to include something percentage based to imply that you're normalizing by population. That is, according to the census bureau, there are about 39 million black Americans, and about 224 million white Americans (I rounded both to the nearest million, which was up in both cases).
That means that a black American had a 258/39,000,000 chance of being killed by police, while a white american had a 666/224,000,000 chance.
Or in other words, 6.6 in every million black Americans was killed by police, and 2.97 in every million white Americans was killed by the police.
To put it another way, you're normalizing within groups instead of across groups, and this leads to a practically useless set of numbers that you can throw at people, but don't have any practical value. So even if you do change your formatting issue, it would be better if you showed the across group normalization, instead of what you currently have, which isn't a valuable piece of data.
Edit:
For someone who is quick to claim others are making mistakes "its all about the trendline" and "I'm tired of people making the current year being the hottest into something its not", I would expect better work honestly.
Thanks for taking the time to help improve things. I agree with some issues you raise but not others.
For the Clinton server, I never stated that work email being wiped was intentional. The fact is though that almost half of her emails were securely wiped with bleachbit, and the FBI recovered 5600 work related emails, of which at most half are duplicates of those turned over. I give the benefit of the doubt and list that half of them are new. See the WSJ source for the FBI stating that they found emails that Clinton wiped.
Homicides by race - you're right about the tooltip not being as clear as can be. I need to be terse so that the tooltip can fit on mobile, but I do mean the percentage to be detailing the size of the histogram slice.
I defend using the percentages instead of whole populations though. Looking at the total population is asking what kills people the most. Looking at a breakdown of homicides is asking who kills the most. It's a case of Simpson's paradox where the subpopulation does not conform to the aggregated whole.
I'm happy you expect good work out of the site - that's what I strive to accomplish.
>For the Clinton server, I never stated that work email being wiped was intentional.
No, but your graph shows that of the 30K emails that were deleted after the start of the investigation (with bleachbit, as you say), 2800 were work related. The FBI does not claim this, nor do your sources. It is as far as we know, a false claim.
>It's a case of Simpson's paradox where the subpopulation does not conform to the aggregated whole.
Its not, you are never combining groups. Its just a bad application of percentages (and perhaps a worse visualization).
The trendline matters. Focusing on a specific year is meaningless, which is what this visualization is trying to show. It's not trying to argue against mercury but against the annual headlines that there is a hottest year.
Hottest year on record isn't a great metric, though. It's all about the trendline. And the trend is for continuous, significant, and dangerous increases in global surface temperatures to be observed over timescales of ~5 years.