Guest Post by Bob Tisdale
UPDATE: The author of the post has now been listed at the end of the Initial Notes.
# # #
This is a repost of a blog post written by a well-known and well-respected climate scientist. To date, it is one of the best answers I have come across to the often-asked question, “Was 2014 the warmest year?” What sets it apart from most articles is its down-to-Earth discussion of probabilities.
INITIAL NOTES:
- This is not a discussion of why 2014 might be warmest. For that, you’ll need to refer to the blog post here.
- The data discussed in the following post is the old version of the NCDC data, not the newly revised NCEI data introduced with Karl et al. (2015).
- The topic of discussion is surface temperature data, not lower troposphere data.
- This is not a discussion of adjustments to surface temperature data. It is also not a discussion of the slowdown in global surface warming.
- The basis of the discussion is: given the surface temperature data we had in hand at the end of January 2015, could we say that 2014 was the warmest year?
I would like the content of the post to be the topic of discussion on the thread, not the author. If you know who the author is, or have taken the time to search for the blog in which the following post appears, please do not identify the author by name. Later in the day, I will provide an update with a link to the original post and let you know who the author is.
UPDATE
The author of the blog post in John Kennedy of the UK Met Office. He blogs occasionally at DiagramMonkey. The original of the post was published on January 31st.
[End preface. The repost follows.]
The question of whether 2014 was or wasn’t the warmest year has recently exercised the minds of many. The answer, of course, is…
No.
At some point in the past, the Earth was a glob of molten rock pummelled by other rocks travelling at the kind of speeds that made Einstein famous, dinosaurs late and a very, very, very loud bang. There have also been periods, more hospitable to life (of various kinds), where global temperatures were in excess of what they are today.
However, if we narrow the scope of our question to the more conventional and cosmically brief period covered by our instrumental temperature record – roughly 1850 to now – the short answer is…
Maybe.
This has been an answer to a Frequently Asked Questions on the Met Office website (http://www.metoffice.gov.uk/hadobs/hadcrut4/faq.html) and has been the source of occasional ridicule.
That’s fine.
Obviously, one year was the warmest1. In other words, according to some particular definition, the global average of the temperature of the air near the surface of the Earth in 2014 or some other calendar year was higher than in any other. Unfortunately, we don’t know what that number is for any particular year. We have to estimate it1.5 from, sparse and, occasionally unreliable measurements. Some of them made with the help of a bucket.
That gap, the gap between the estimated value and the unmeasurable, might-as-well-be-mythical, actual global temperature is the reason for the “Maybe”. This is a common problem familiar to anyone who has attempted to measure anything2. If you are unfamiliar with it, ask a room full of people what time it is. You’ll get a range of answers3. These answers will be clustered close to the actual time, but not exactly on it. Most people are used to living in this chronological fog of doubt. They allow for the fact that watches and reality never line up precisely.
For global temperature (or any other measurement for that matter) we don’t know exactly how large that gap is, but we can by diverse methods get a reasonable handle on what kind of range it might fall within. Most people’s watches are within five minutes either side of the “right time”. Or, to put it another way, the right time is usually within five minutes either side of what most people’s watches say. That range is the uncertainty.
The good news is that, armed with this uncertainty information for global average temperatures, there are some years, for which the answer to the question “Well, what about this year, could this year be the warmest?” is, resoundingly, undoubtedly, 100%: No.
Non. Nein. Niet. Nopety, nopety, noooooo.
The number of years in the global temperature record which definitely aren’t the warmest is quite large. I would go so far as to say, it’s most of them. Here, for your enjoyment, is a list of definitely-not-the-warmest years.
1850, 1851, 1852, 1853, 1854, 1855, 1856, 1857, 1858, 1859, 1860, 1861, 1862, 1863, 1864, 1865, 1866, 1867, 1868, 1869, 1870, 1871, 1872, 1873, 1874, 1875, 1876, 1877, 1878, 1879, 1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1999 and 2000.
Out of a record, which currently runs to 165 years, 149 years definitely aren’t the warmest. To this we can add a few additional years that are distinctly unlikely to be the warmest.
1997, 2001, 2004, 2008, 2011 and 2012.
And, while we’re at it…
1998, 2002, 2003, 2005, 2006, 2007, 2009, 2010, 2013 and 2014.
Pick any one of those years and, more likely than not, it won’t be the warmest year either. Careful readers will have noticed that there is not a single year in all of those 165 years that is unaccounted for; the vast majority of years definitely aren’t the warmest, but even in the small remainder there is no year that is more likely to be the warmest year than not.
We really should have stuck with “maybe” because this is going to take a while to unpick.
Seriously, folks, consider maybe.
No? OK. This is on you.
According to a very good global temperature data set, 2014 was estimated to be 0.56° above the long term average. The uncertainty on that estimate is about 0.10°. In other words, according to that data set there’s about a 95% chance that the true global temperature will be between 0.46° and 0.66°. Likewise, we can consider 2010, with an estimated global temperature of 0.53°C and an uncertainty, again, of about 0.10°C. If these were the only two years and this was all we knew, we could calculate the probability that 2014 was warmer than 2010. It’s about 69%. We can also compare 2014 to 2005 (0.56 vs 0.52). In this case 2014 is about 75% likely to be warmer than 2005.
However, to work out the probability that 2014 is the warmest year on record, we have to compare it to all the other years at the same time. This is a slightly more involved calculation, so we’ll build up to it. First by asking what’s the probability that 2014 is warmer than both 2010 and 2005.
We’re going to do this using a Monte Carlo method. We’ll take the best estimates for 2014, 2010 and 2005 and use the uncertainties to generate possible “guesses” of what the real world might have done4. We’re going to do that thousands of times and count how often 2014 comes out on top.
The probability that 2014 is warmer than both 2010 and 2005 is about 60%, less than the probability that 2014 is warmer than either one or the other separately. If we add 1998 into the mix, then the probability drops even further, to 56%. The more years we add the lower that probability goes. Why does that happen? Simply, each year gets a crack at being warmer than 2014. The more years there are, the higher the chance that just one of them will be warmer. And one year is all it takes.
However, this process doesn’t go on indefinitely. As we move further down the list of warm years, the probability that a year is warmer than 2014 drops rapidly. Soon we get to the point that it’s so unlikely that a year was warmer than 2014 that we can drop it from our calculation and it makes no difference. The probability that 2014 is warmer than 2010, 2005, 1998 and 2013 is 50%. If we compare 2014 to the other nine of the ten warmest years the probability that it comes out on top is about 47%. If we go further down the list than that the probability doesn’t change. 47% is therefore the probability that 2014 is the warmest year on record.
If we do the same analysis for a different, but equally excellent data set, we’ll get a slightly different set of probabilities, but the basic pattern will be the same. In this case 2014 has about 39% probability of being the warmest year on record.
We can repeat these analyses focusing on other years (is 2010 the warmest? 2005? 1998?) and in each case the probability will be lower than for 2014. That was all a bit tedious, but based on this simple analysis it turns out that no year is more likely than not (greater than 50% probability) to be the warmest year on record. On the other hand, we know that one year has to be the warmest, which is, if you are so inclined, pleasingly paradoxical as questions of probability often are.
We can rephrase the question and ask which year has the highest probability of being the warmest year? The answer based on these two data sets is 2014. As one blogger (I can’t remember who) put it, no year has a better claim.
All of the above needs the rather large caveat: “based on these two data sets” and “based on this particular method”. The probabilities I calculated depend on the data set and on the method. Change either one, change the probabilities. We could look at other data sets, such as those produced by Berkeley Earth (who declared 2014 a tie with 2010 and 2005), or the ECMWF reanalysis (which had 2014 in the top 10% of years in their reanalysis, nominally third warmest). Cowtan and Way look poised to put 2014 in second place. There’s no way to rigorously combine all this information to get a single best answer to any of the questions we might want to ask, but it does underline the fact that there is uncertainty and that it is limited.
For example, there’s no data set of global surface temperature that places 2014 outside the top four years based solely on best estimates. Based on those data sets that have uncertainty estimates, it is very unlikely that 2014 is outside the top 10. It’s quite unlikely that it’s outside the top 5.
So, 2014 was a very warm year. Was it a top 10 year? Yes. A top 5 year? More likely than not. The warmest?
Maybe.
1. Unless the thought-provokingly-fine tuning of various fundamental parameters stretches as far as global-mean temperature. On earth. In the 21st century. This has not, to the best of my knowledge been previously suggested. You saw it here first, folks.
1.5. There are lots of different estimates of global temperature and, obviously, in each of those there will be a year that is warmer than any other.
2. The textbook example is the carpenter’s maxim: measure twice, cut once.
3. Usually. The exception would be if a large fraction of them recently had cause to synchronize their watches, something that Hollywood would have me believe occurs a short, and presumably well-measured, period before it all kicks off
4. To do this we assume that the distribution of errors is Gaussian – the famous bell curve – with mean equal to the best estimate and standard deviation equal to the estimated 1-sigma uncertainty. Errors are considered to be independent from year to year. This is a lot simpler than the real world is, but it will give us an intuition for what’s going on and how uncertainty interacts with rankings. This analysis is a lot simpler than NOAA used too. Consequently, the probabilities I get will be somewhat different.
[Update: 4/2/2014 corrected 2005 global temperature anomaly for NCDC’s data set. Was quoted as 0.54 now, more correctly, 0.52]
[Update: 6/2/2015 First, the date immediately above this one is wildly wrong. Second, Lucia pointed out that the mystery blogger who said no year has a better claim was, in fact, Nick Stokes. Third, Significance has reposted this here.
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Better question is why the adjusters/homogenizers did not attempt to change the CET temperatures. Too many people watching? Knew they would get caught out? knew that any attempt would cause a storm of scientific protest. If those are the answers, then those craven cowards who quietly and behind the scenes wrecked historical temperature data have a lot to answer for, but over an above that even worse is those that not only knew what was going on but permitted it to happen.
I live for the day that these, I can’t call them “scientists”, are called to account, each and every one of them.
Miserable miscreants or worse? I leave that to those with the power to bring them forward for the explanation of their motivation.
Winters can arrive early, winters can arrive late. Summers can arrive early, summers can arrive late. Each calendar year begins and end during winter (northern hemisphere) and summer (southern hemisphere) so the accumulated temperatures for a given calendar year are affected (at beginning and end) by the timing of winters and summers. Surely this adds even greater uncertainty to the calculation of a year’s “hotness” in comparison to another’s?
A difference in annual temperatures may simply be an artefact of the timing of the seasons.
e.g. allow me to invent a very hot year – in my hot year, the NH winter arrived early (in Nov/Dec of the previous year) such that Jan-Mar was quite mild. At the end of the year, the NH winter arrived late (in Jan/Feb of the next year) such that my Nov-Dec was quite mild. Meanwhile, in the SH, summer at the beginning of that year arrived late (Jan-Mar) and at the end of that year, it arrived early so that Oct-Dec was statistically warmer. Averaged out, the 3 years (with my hottest year in the middle) could have been very average, but the middle year – what a statistical stinker it was! Stinking hot that is.
I’m a novice at this – yet my scientific “gut” says that the moment you segment a time series into months or years, the timing of the seasons will muddy the waters.
Heck, every accountant knows that you can fiddle a year’s financial results by bringing forward or deferring revenue or expenses, depending on the desired result for the financial year. Nature does the same via the timing of the arrival of the seasons.
If you find my post in this thread, that’s exactly what I calculate, as well as summarize 1940 to 2014, and there’s not much of a change in temp.
Was 2014 the warmest year on record?
Not where I live. The relatively good 76 year record suggests 2014 was cooler than the 30 year average and the 76 year average.
Of course non of these temperatures have been homogenized or corrected yet.
So NCEP, measuring the earths temp every 6 hours based on the based available data and their gridding system, is out to lunch with these measurements. Why is the actual result of the data on a 6 hourly basis ignored?
http://models.weatherbell.com/climate/cfsr_t2m_2005.png
2014 not even the warmest year in the last 10
hi Joe, your pic shows up “access forbidden”. got a public link?
The average surface temperature of the earth going up or down does not prove that carbon dioxide caused it, It is only consistent with the theory believed by many climate scientists. If the maximum temperatures measured at any location shows a clear increase when carbon dioxide increases in the atmosphere then this would be evidence that the mechanism proposed for carbon dioxide is correct but if we don’t see that rise in maximum temperatures then it would be evidence that there is no forcing from carbon dioxide. We suspect that temperature records are being altered to show this relationship ,I give the case of the Australian temperature record as a recent example .
My objection is rather different.
I knew someone who kept temperature records near the Lyneham one and consistently got lower reading by about a degree. When the air base closed the differential dropped to half a degree.
I do not believe that any reading taken in the greater London area can be considered valid any longer as a comparison with earlier ones but any within five miles of Heathrow is a definite non starter.
On top of this one of my friends did a study of the effectiveness of the Stevenson screen as an enclosure given various standards of air cleanliness and found that the cleaner air resulted in a near half degree increase in measured temperature with clean act quality air relative to the air quality measured in the same spot in 1950. Surprisingly even the air near Heathrow which seems disgustingly oily smelling to me is better than the average for the area in the fifties.
It is an unfortunate fact that the research value of data collection is low for a scientist so little or no effort is put into making sure this is of even low commercial grade let alone the top quality that should be required for science justifying multi billion pound subsidy policies.
Even with the margin of error (0,1°C), 2014 would still be a top 10 year. The strong El Nino 1998 added more than 0,2°C of global warming.
So yes, with the margin of error and El Nino warming you can compare 1998 and 2014.
But you could also look the other side. The margin of error could be +0,1°C for 2014, climbing at +0,78°C. Without El Nino, 1998 could have been -0,2°C, falling at +0,42°C.
So +0,78°C in 2014 ; +0,42°C in 1998. And by the way, the year to date anomaly is +0,76°C in 2015 and El Nino has not peaked yet.
I’m sorry but on a statistical point of view you can say 2014 was warmer than 1998.
honestly, what is the point of having an error margin smaller than the adjustments made to the raw data?
first, you accept there is an error of x.xx with the raw data that must be ‘adjusted’ out, then you turn around and say that your result has more accuracy. in other words, you believe in yourself.. nothing to do with the actual data, just your ‘adjustment’. so, you just dream up accuracy? what world do you people live in?!
The point is to have small error margin. First, I accept there’s a SYSTEMATIC error that must be adjusted out. Obvious.
WPeszko:
You say
In a science lab. the point is to understand the data and what it indicates.
Therefore, in a science lab. when a SYSTEMATIC error is detected then the cause of the error is corrected and the measurement is repeated; failing ability to do that then, in a science lab., the total inherent error range is reported.
So, in a science lab., an error is corrected or reported and is never – not ever – “adjusted out”.
In a political assertion any error is excused as having been “adjusted out”. Obvious.
Richard
@richardscourtney
When a SYSTEMATIC error is detected and if it’s possible to correct – it’s corrected. If not, it’s adjusted out. How do you correct Earth rotation?
WPeszko:
You ask me
I don’t “correct Earth rotation”. Any scientist would define, measure and report “Earth rotation” together with an error estimate for the measurements.
How do you correct “correct Earth rotation”; with a hand-brake?
I repeat what I said and you are commenting but failing to dispute.
Richard
“Any scientist would define, measure and report “Earth rotation” together with an error estimate for the measurements.”
Then the final value would be adjusted for that. It’s just your imagination that a systematic error is not adjusted out, nothing to dispute.
WPeszko:
You make an unacceptable assertion in response to me
NO! ABSOLUTELY NOT! HOW DARE YOU!?
I said and I repeated
The fundamental principles of metrology are NOT my “imagination”. It seems that you don’t know what is meant by defining a parameter and defining a measurement method. When a method provides a result then that result is a datum which is reported together with its method of determination and an estimate of its error range.
When measurements have been conducted then no scientist would “adjust” the obtained data: only a charlatan would do that.
Richard
“When measurements have been conducted then no scientist would “adjust” the obtained data: only a charlatan would do that.’
Somehow you imposed that adjusting data for errors means original data is lost/not reported. Therefore you’re arguing now with yourself, not me.
WPeszko:
I am “arguing” with nobody. I am telling you that you are wrong.
You are refusing to accept or discuss what I have written.
You now say
That ignores the fact that in climate science the original data IS “lost”.
Importantly, no scientist would “adjust” data because she thinks it has errors: only a charlatan would do that. A scientist would attempt to repeat the measurement in a manner that does not include the error or – failing ability to do that – would report the suspected source of error along with the data and estimated error range.
Richard
1. Data isn’t lost just because WUWT says that.
2. Every scientist would adjust data (final values), knowing a proven systematic error. I’m happy you finally agreed with me “would report the suspected source of error along with the data and estimated error range.” And then would report raw & adjusted data.
3. You says you’d correct Earth rotation. How?
Dear richardscourtney,
The guide to the expression of uncertainty in measurement says the following:
3.2.3 Systematic error, like random error, cannot be eliminated but it too can often be reduced. If a systematic error arises from a recognized effect of an influence quantity on a measurement result, hereafter termed a systematic effect, the effect can be quantified and, if it is significant in size relative to the required accuracy of the measurement, a correction (B.2.23) or correction factor (B.2.24) can be applied to compensate for the effect. It is assumed that, after correction, the expectation or expected value of the error arising from a systematic effect is zero.
http://www.bipm.org/en/publications/guides/gum.html
Best regards,
John
WPeszko: Just to clarify, It’s not WUWT that says the data is lost.
It’s Phil Jones – the guy who lost the data
Here is an interview with Nature where he acknowledges that he shouldn’t have done that.
John Kennedy (@micefearboggis):
Yes. Thankyou.
As your quotation says
I explain this together with an analogy to aid comprehension in Appendix B of this.
Of course, such a correction is nothing like “adjustments” to climate data that occur almost every month, that are also reported in the item I have linked, and that have this effect.
If adjustment of data to match a ‘known’ result were acceptable then there would be no reason to conduct measurements; the ‘known’ result could be stated instead.
Richard
Wojciech Peszko
You say to me
I said no such thing!
In fact I ridiculed your asking me how I would do it when I replied
Richard
If you look at the satellite data for the lower troposphere, 1998 was clearly the warmest year since we had actual global temperature data. This makes sense, since it was an el Nino year. If you ask what was the warmest consecutive 12 months, you get the 12 months ending in November 1998. December 2014 ranks 79 th. 2010 ranks much higher – October 2010 ranks 9th.
Satellites exagerate el nino effects and again you would not use satellite to have a precise local temp. So why would it be different for a global temp ? Satellites are usefull to infill uncovered regions though.
And uah long term trends show nearly the same warming as surface stations that’s because el nino and la nina have a net zero effect (if you omit ocean heat storage).
BTW – I understand this is off topic. I posted it just to give a reference point.
For decades 1934 was the hottest year on record. Then after repeated adjustments it is no longer even in the running. Not buying sorry.
If you are going to confine yourself to land based temperatures, you expect temperature readings to increase over time regardless of any naturally occurring increase in temperatures. If 1880 we did not have airports, parking lots, skyscrapers and all the other things that cause urban heat islands. However, land based temperatures only cover 1/3 of the globe (much less if you include Siberia and Antarctica). There is also the question of biasing the results to the northern hemisphere where the landmass is larger.
My focus has been day to day changes in temp, daily and annually, always comparing a station to itself. From this I set requirements for the number of readings as well as the number of years at those annual samples. Lastly I can select stations in an area, I’ve done approximately by continent, 1×1 degree blocks, 10 degree lat bands. But the big issue with everywhere but the northern hemisphere is they have poor coverage, even now. But you can still look at the stations and see how much they changed day by day. In particularly comparing how much the temp went up yesterday, and then dropped last night. That to me seems to be the key to this, did it cool as much last night as it warmed yesterday, and the answer is on average it did.

This is day to day change, daily Rising temp, and Solar forcing. Forcing and rising are scaled to allow you to see how day to day temps changed.
Here’s day to day averaged by station.
If these “very good global temperature data set”(s) would not retroactively adjust the past, I would be more inclined to read and take posts about “warmest year” more seriously.
Seriously…
http://notrickszone.com/2015/07/07/noaas-data-debacle-alterations-ruin-120-years-of-painstakingly-collected-weather-data/
https://stevengoddard.wordpress.com/2014/08/12/what-part-of-this-isnt-clear-3/
There’s a 38% chance that in 2015 I will meet Sofia Vergara and she will become my love slave.
I consider that a done deal.