February 2016 Global Surface Temperature Anomalies May or May Not Have Been Highest on Record, According to the UKMO

Guest Post by Bob Tisdale

UPDATE:  I used the phrase “may or may not” with respect to February 2016 being the warmest on record in the title and text of this post.  Nick Stokes on the thread of the cross post at WUWT advises that based on his analysis “98.7% of the time, Feb 2016 is higher” than January 2007.  Or to put that in the terms NOAA uses for their SOTC, it is “very likely” February 2016 is warmest.

Once again, when presented with evidence that I’ve presented something incorrectly in a post, I am more than happy to acknowledge and correct it.  Unfortunately, that cannot be said for many alarmists.

Additionally, that does not change the remainder of the post which notes that the uptick in global surface temperatures in response to the 2015/16 El Niño is comparable to that of the 1997/98 El Niño.  That has been evident in all of the surface temperature datasets examined so far.

[End update.]

With the publications of the NASA/GISS and NOAA/NCEI global surface temperature anomaly data over the past few weeks, alarmists have been touting “record high” February 2016 global surface temperature anomalies.  See the posts Alarmism Cranked Up to Absurd Level and More Alarmist Nonsense with the Release of the Redundant* NOAA Global Temperature Data for February 2016.

Yesterday, the UK Met Office published their global data for last month and so far the alarmists have been quiet.

Why?

See UPDATE above.

One possible reason:  Of the three primary suppliers of global land+ocean surface temperature data, the UK Met Office is the only one to include uncertainties on their data webpage. (See the HadCRUT4 data page here and the format page here.)  Figure 1 includes the monthly UKMO HadCRUT4 global (near land & ocean) surface temperature anomalies from January 1979 to February 2016 (black curve).  Also included are upper and lower bounds of the total uncertainties of their data (maroon and light blue curves).  The upper and lower bounds of the 95% confidence intervals include the combined effects of the measurement and sampling uncertainties and the bias and coverage uncertainties.

Figure 1

Figure 1 (Click illustration to enlarge.)

See UPDATE above.

As shown, the lower February 2016 value for the global temperature anomaly is +0.92 deg C referenced to the years of 1961-1990.  This was exceeded by the upper January 2007 value of +0.98 deg C. Just in case you’re having trouble seeing that in Figure 1, see the graph here, which starts the data in January 1997.  So the best the alarmists could claim, according to the HadCRUT4 data, is that the February 2016 global surface temperature anomalies may or may not have been the highest on record when considering the uncertainties of the data.

NOTHING UNUSUAL ABOUT THE RECENT UPTICKS

In the prior two posts, to combat the nonsense about the recent upticks being unusual, I’ve included comparisons of the evolutions in global surface temperature responses to the 1997/98 and 2015/16 El Niños.   The data have been normalized to the first 3 months of their respective first years.  The normalization was done so that we can easily compare, visually, the responses of global surface temperatures to the two comparably sized, strong El Niño events. Figure 2 provides a side-by-side comparison with the HadCRUT4 data.

Figure 2

Figure 2

Considering the uncertainties of the data, the best we can say is that there were comparable responses in global surface temperatures to the strong 1997/98 and 2015/16 El Niños.

Note:  Contrary to the nonsensical rants of alarmists who have trouble grasping reality and who apparently have difficulty reading time series graphs (sample posts archived here and here) the normalization of the data in the graphs (similar to Figure 2 above) in my two earlier posts (here and here) was not an attempt on my part to hide the fact that global warming has occurred between 1997/98 and 2015/16.  As you’ll recall, those earlier posts were about the GISS and NCEI data, which include the curiosity-filled Karl-ized ERSST.v4 “pause-buster” sea surface temperature data from NOAA. (For more on those ERSST.v4 abnormalities see the posts here and here).  Those increases between 1997/98 and 2015/16 were clearly shown in the time series graphs included in those earlier posts. The data were normalized in the graphs similar to Figure 2 to make the visual comparisons easier.

For example, Figure 3 is similar to Figure 2, but in Figure 3, the HadCRUT4 data have not been normalized.  That is, the anomalies are referenced to the UKMO-preferred period of 1961-1990.

Figure 3

Figure 3

If you’re an alarmist and have trouble reading time-series graphs, and you want to confirm that 2015/16 was warmer than 1997/98, you’d present Figure 3. In Figure 3, the evolutions appear to run somewhat in parallel, but the similarities in those evolutions are better shown when the data have been normalized, Figure 2.  Thus my use of the normalization.

[End note.]

CLOSING

With the publication of the February 2016 UKMO HadCRUT4 data, I suspect we’ll see a few more alarmist articles about “record high” global surface temperatures in February 2016.   As shown in Figure 2, the responses of global surface temperatures in 2015/16 are as we would expect from a strong El Niño. And as shown in Figure 1, the February 2016 global temperature anomaly may or may not have been the highest on record when we consider the uncertainties of the data.  See UPDATE above.

FOR THOSE NEW TO DISCUSSIONS OF EL NIÑO EVENTS AND THE REASONS FOR THE RECENT REPORTS OF RECORD HIGH SURFACE TEMPERATURES

I discussed in detail the naturally occurring and naturally fueled processes that cause El Niño events (and their long-term aftereffects) in Chapter 3.7 of my recently published free ebook On Global Warming and the Illusion of Control (25 MB).  For those wanting even more detail, see my earlier ebook Who Turned on the Heat? – The Unsuspected Global Warming Culprit: El Niño-Southern Oscillation. Who Turned on the Heat? only costs $5.00 (US).

We discussed and illustrated the natural causes of the 2014 “record high” surface temperatures in General Discussion 2 of my free ebook On Global Warming and the Illusion of Control (700+ page, 25 MB .pdf).  And we discussed the naturally caused reasons for the record highs in 2015 in General Discussion 3.

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taxed
March 30, 2016 11:08 am

Has anyone been able to check the how powerful the Polar jet stream in the NH has been this winter.
Because with the warming in the Arctic then it should have weakened this winter. But l have say that l have not seen any noticeable weakening of the Polar jet this winter. Which is odd given the warming in the Arctic. Just wondering if there is any data to back this up.

Toneb
Reply to  taxed
March 30, 2016 11:15 am

No it was just as, if not more powerful than normal – the EN saw to that. In wintertime there is a disconnect between surface and upper trop temps (no convection). It’s night in the Arctic and warmth comes from advected air from warm seas (Pacific/Atlantic) in stable surface layers.

March 30, 2016 11:52 am

Strong El Nino. Weather. Nothing to see here.
Temps will be back below 0.5 in less than a year.
The pause will live on.

taxed
Reply to  wallensworth
March 30, 2016 12:20 pm

wallensworth l think you maybe right. l take a interest in the weather and its giving me doubts about just how long term this current warming will be.

Sally
Reply to  wallensworth
March 30, 2016 12:29 pm

Agree. No different than any other strong El Nino years. Just watch and wait though for La Nina….let’s see how they respond to that one. 🙂
It is enough to give any marine biologist a migraine….better go stock up on ibuprofen now or maybe popcorn, then I can sit back and watch the train wreck from afar.

Donald
Reply to  wallensworth
March 30, 2016 7:33 pm

Hi wallensworth,
Even using the UAHV6beta5 product, and starting with the 1997/1998 el Nino, you would need some extremely low anomalies to produce a non-positive linear trend in the next year. In fact, assuming next month drops down to +0.45, or the next 2 months drop down to +0.22 each, then every month for the rest of the year could drop down to anomalies of 0.0 and the linear trend would still be positive. If the anomaly drops down to +0.33 for the next 3 months, then anomalies for the rest of the year could drop to -0.18 and still not remove the positive trend.
ENSO projections for the next few months show us returning to ENSO-neutral in the June/July timeframe, so it seems highly unlikely that we will see anything approaching such precipitous drops by August, never mind before then. La Nina conditions may begin in the August/September timeframes, but even if a resulting La Nina is deep, it is unlikely to be _that_ deep: for some context, there have only been 22 months with zero or negative anomalies in the past 10 years. There have only been 5 months with anomalies of -0.18 or less in the past 10 years. Having 7 of them line up in a row would be… improbable.

taxed
March 30, 2016 12:10 pm

Thanks for the reply. l have been stuck by just how powerful the jet has been at times. Which seemed a little at odds with a warming climate. lt will be interesting to see what happens during the summer.

bit chilly
Reply to  taxed
March 30, 2016 6:14 pm

the north sea temperatures during last summer were at one point 6 c below the same period as the year before. they peaked 3 c below the previous year. for me the north sea temperatures are the first indicator of atlantic cooling as the predominant flow of water into the north sea is from the north east atlantic. a la nina with the amo heading into the cool phase should provoke some interesting debate.

Michael Carter
March 30, 2016 12:23 pm

It is clear that the likes of the UKMO HAVE to calculate an optimistic margin of error. Otherwise, their reporting becomes useless
If you really want to put pressure on these institutions keep asking the question, “How do your calculate margin of error?” Here is something you statisticians can really get your teeth into
I would not bet one cent that their published range is accurate – or their mean, within 0.5 C

Reply to  Michael Carter
March 30, 2016 1:40 pm

Michael,
“How do your calculate margin of error?” Here is something you statisticians can really get your teeth into”
See my post above and Nick Stokes replies. That pretty well defines how they do it – the median of 100 runs with varying assumptions about measurement accuracy, is the final number, and the range of deviations in those runs defines the confidence interval – learn something new every day. However, that also implies that the answer to “what is the actual quoted anomaly?” is the result of a simulation – also an interesting fact.
Nick, have I got that right?
Taylor

Reply to  Taylor Pohlman
March 30, 2016 2:14 pm

Taylor,
“However, that also implies that the answer to “what is the actual quoted anomaly?” is the result of a simulation – also an interesting fact.”
Well, I think that may overstate the distinction. The normal calculation of global temperature combines a whole lot of best estimates, as most scientific calculations do. The Hadley approach is to do 100 calcs using estimates that aren’t the best, but in the reasonable range, probably chosen from a normal distribution. Each individual calc is done in much the same way with those varied numbers.

Reply to  Taylor Pohlman
March 30, 2016 3:24 pm

Nick: have the original data been checked for normality? If not, any further statistical manipulation is useless for using parametric statistics unless the data is transformed by log/log10 or something.

Nick Stokes
Reply to  Taylor Pohlman
March 30, 2016 4:32 pm

“Nick: have the original data been checked for normality?”
It’s not an issue of whether the data are normal. We’re talking about multiple runs in which HADCRUT let the parameters vary subject to distributions. I would expect those were normal, but even if not, the combined effect of several factors (listed by Bob) would tend to normal by the law of large numbers.
I see Tamino has done the relevant calculation . I did it too, and got a similar answer, which is about 1.3%. That is, if you did many ensemble calcs in HADCRUT style, you would expect Jan 2007 to exceed Feb 2016 in just 1.3% of cases. 98.7% of the time, Feb 2016 is higher.
So I guess you could say “may or may not”. You could say on that basis that Feb 2016 may or may not have been the coldest in the record. You could say anything.

TA
March 30, 2016 2:05 pm

Taylor Pohlman
March 30, 2016 at 11:20 am wrote:
“Better to grasp at a straw, Magma, than to suck KoolAid through your straw 🙂
However, I don’t know why you (or Bob) for that matter would be surprised that the potentially higher temperature would be nine years ago, given the reasonably steady warming since the end of the Little Ice Age some 160 years ago. Given that the 1930’s have been [falsely] cooled (where there is a lot of anecdotal evidence of warmer conditions, but little data that hasn’t been adjusted),”
Here’s some anecdotal newspaper headline evidence about the climate during the 1930’s:
Below, you can read a little bit about what it was like weatherwise
during the middle part of the 1930’s. See if you think it sounds like
the weather we are having today.
1933: West Australian Heat Wave – “Severest In History”
1933: Heat Waves, Floods, Droughts, Famines Plague China
1933: Spain’s Heat Wave: 130 Degrees In Shade
1933: Heat Wave Causes New Jersey Road To “Explode”
1933: Hottest June In U.S. History – Heat Wave & Drought
1933: 21 Perish During Texas, Louisiana Tornado & Hail Storms
1933: Drought In South Africa – “Worst Outlook For 50 Years”
1933: Flooding In China Kills 50,000
1933: India’s Ganges River Bursts Its Banks – Widespread Flood Damage
& Fatalities
1934: 80% of U.S. Suffers From Drought Conditions
1934: “Heat Wave In China Kills One In Every Thousand”
1934: Antarctic Has Incredible Heat Wave – 25 Degrees Over Zero
1934: February Tornado Strikes Several U.S. States
1934: World Wide Drought & Heat Causes Vast Majority of Alps’ Glaciers
To Melt
1934: Iowa Heat Wave In May – Pushes Temps Over 110 Degrees
1934: All 48 U.S. States Over 100 Degrees During June
1934: 14 Days of Above 100°F Temps Kill Over 600 Americans
1934: South African Drought Severely Hits Farmers
1934: Nebraska Temperatures Soar To 117 Degrees
1934: Drought, Heat, Floods, Cyclones, & Forest Fires Hit Europe
1934: British Drought Stunts Hay Growth
1934: Worst Drought In England For 100 Years
1934: 7 Days of Incessant, Torrential Rains Cause Massive Flooding In
Eastern Bengal
1934: Global Warming Causes 81% Of Swiss Glaciers To Retreat
1934: Canadian Crops Blasted By Intense Heat Wave
1934: “South African Floods Are Unprecedented”
1934: Typhoon Hits Japan Followed By A Massive Tsunami
1934: Record Heat And Drought Across The Midwest
1934: China’s Fall Crops Burning Up During Drought & Heat
1934: Five Million Americans Face Starvation From Drought
1934: Adelaide, Australia Has Record Dry Spell
1934: Gigantic Hailstorm Blankets South African Drought Region
1934: Drought And Sweltering Heat In England
1934: Record Heat Bakes Wisconsin – 104°F
1934: 20 Nebraskans Succumb To Unprecedented 117 Degree Heat
1934: Poland Swamped By Floods – Hundreds Perish
1934: 115 Degrees In Iowa Breaks Record
1934: 115 Degrees Reached In China In The Shade – Heat Wave Ruining
Crops
1934: Majority of Continental U.S. Suffers From Drought Conditions
1934: Severe Northern Hemisphere Drought Causes Wheat Prices To
“Skyrocket”
1934: Extreme U.S. Winter Weather Leaves 60 Dead In Its Path
1935: Severe Wind Storm Lashes Western States With 60 MPH Gusts
1935: Florida Burns Its Dead After The Most Powerful Hurricane In US
History
1935: “The Worst Dust Storm In History” – Kansas City
1935: Worst Drought Since 1902 Has Queensland, Australia In Its Grip
1935: “50 Dust Storms In 104 Days
1935: France Cooked By Heat Wave
1935: Tropical Windstorm Strikes Texas With 85 MPH Gusts
1935: ‘Black Dusters’ Strike Again In The Texas Dust Bowl
1935: India Hit With Extreme Heat Wave – 124 Degrees
1935: Heat Wave, Drought & Torrential Rains Cause Misery In Europe
1936: “Niagara Falls Freezes Into One Giant Icicle”
1936: February Was Coldest In U.S. History
1936: Italian Alps Glacier Shrinks: WWI Army Bodies Uncovered By
Melting
1936: Ice Bridge In Iceland Collapses From Heat Wave & Glacier Melt
1936: Violent Tornadoes Pummel The South – 300 Dead
1936: Dust, Snow & Wind Storm Hit Kansas Region In Same Day
1936: Unprecedented Heat Wave In Moscow
1936: Ukraine Wheat Harvest Threatened By Heat Wave
1936: 780 Canadians Die From Heat Wave
1936: Iowa Heat Wave Has 12 Days of Temperatures Over 100 Degrees
1936: Heat Wave Deaths In Just One Small U.S. City: 50 Die In
Springfield, IL
1936: Missouri Heat Wave: 118 Degrees & 311 Deaths
1936: Ontario, Canada Suffers 106 Degree Temps During Heat Wave
1936: Alaska’s 10-Day Heat Wave Tops Out At 108 Degrees
1936 : Record Heat Wave Bakes Midwest; “Condition of Crops Critical”
1936: Midwest Climate So Bad That Climate Scientist Recommends
Evacuation of Central U.S.
1936: 12,000 Perish In U.S. Heat Wave – Murderous Week
1936: Single Day Death Toll From Heat Wave – 1,000 Die
1936: Iceland Hurricane Sinks Polar Research Ship Filled With
Scientists
1936: Severe Drought & Disastrous Floods In Southern Texas
1936: 20,000 Homeless In Flame Ravaged Forests of Oregon
1936: Northern California Seared By Forest Fires Over 400-Mile Front
1936: Tremendous Gale & Mountainous Waves Pound S. California – 7
Persons Missing
1936: Glacier Park Hotel Guests Flee As Forest Fire Advances – Worst
Fire In Years
1936: Iowa Christmas Season Heat Wave Sets Temperature Records – 58
Degrees
end
Now, I don’t recall reading many such weather headlines during the last ten or 15 years. You? I think if you compared newspaper clippings, the 1930’s would win the “hottest evah! award, hands down.
Can you imagine what the Alarmists would be doing if we were currently having weather headlines like the ones in the 1930’s!
And of course, I have to mention that Hansen said 1934, was hotter than 1998, before he changed his mind and the chart.
So this “hottest year evah! bs just depends on how far back you go in time.

luagha
Reply to  TA
March 30, 2016 4:02 pm

This is especially funny considering that global temperatures were depressed due to volcanic ash from a series of 4 intense eruptions from 1931-1934. If you look at the multitudinous graphs we see here, you can usually see a mini-pause around that time, before the temperatures continue to rise into 1940-1945.
Makes you think about the conditions WWII was fought under.

Bindidon
Reply to  TA
March 30, 2016 5:36 pm

Before speaking so superficially about alarmists, you should try to understand your basic mistake: a sum of locally hot events doesn’t result in a globally hot year.
Below you see a worldwide representation of surface temperature anomalies in a grid of 72×36 cells, produced by Japan’s Meteorology Agency. It starts with February 2016.
http://ds.data.jma.go.jp/tcc/tcc/products/gwp/temp/map/temp_map.html
Select the year 1934, switch to “annual”, and maybe you get it…
Only small parts of the globe were as warm as you suppose: nearly all sea surfaces are far below the 1981-2010 average temperature.
By switching back to “monthly”, move from january till december, and you will see what happened here and there.
Sorry: what we’re talking about all the time is the global average temperature. The huge difference between global and local you best detect when accessing the data at
http://vortex.nsstc.uah.edu/data/msu/v6.0beta/tlt/uahncdc_lt_6.0beta5.txt
and comparing e.g. the columns “Global” and “USA48”.

TA
Reply to  Bindidon
March 31, 2016 7:57 am

Bindidon
March 30, 2016 at 5:36 pm wrote:
“Before speaking so superficially about alarmists,”
You deny that alarmists wouldn’t be shouting from the rooftops, if we had weather headlines today, like we had in the 1930’s? Tell me you wouldn’t be ringing the alarm bells over a headline like this, if it were to occur today instead of in 1934: “1934: 14 Days of Above 100°F Temps Kill Over 600 Americans”. Alarmists would be claiming this was confirmation that humans have adversely affected the climate. I would bet money on it. I would win, too.
“you should try to understand your basic mistake: a sum of locally hot events doesn’t result in a globally hot year.”
Well, those headlines show the heatwave was a global phenonenon, IMHO.
“Below you see a worldwide representation of surface temperature anomalies in a grid of 72×36 cells, produced by Japan’s Meteorology Agency. It starts with February 2016.”
You know what, I’m a little skeptical of these official surface temperature figures. Where did the Japanese meteorological Agency get their figures? From NASA and NOAA?
“http://ds.data.jma.go.jp/tcc/tcc/products/gwp/temp/map/temp_map.html
Select the year 1934, switch to “annual”, and maybe you get it…”
No, I don’t get it. I would trust newpaper headlines more. They didn’t have a climate change agenda way back when.
“Only small parts of the globe were as warm as you suppose:”
The newspaper headlines included the entire globe, NH and SH. The same type of extremely hot weather was happening over the entire globe, over a very short period of time.
“nearly all sea surfaces are far below the 1981-2010 average temperature.”
According to who?
“By switching back to “monthly”, move from january till december, and you will see what happened here and there.”
I have no confidence in the data you are offering.
“Sorry: what we’re talking about all the time is the global average temperature.”
I think the newspaper headlines were describing a global temperature. A *high* global temperature.
“The huge difference between global and local you best detect when accessing the data at
http://vortex.nsstc.uah.edu/data/msu/v6.0beta/tlt/uahncdc_lt_6.0beta5.txt
and comparing e.g. the columns “Global” and “USA48”.”
Sorry, but I don’t trust the data you are offering. That’s why I offer newspaper headlines as a counter-argument to the bogus data being put out by the climate science charlatans at NASA and NOAA and their followers and fans.
If the data doesn’t show the 1930’s being hotter than 1998, then the data is a BIG LIE.

Bindidon
Reply to  Bindidon
April 2, 2016 5:14 pm

TA, I’m afraid that if you think the University of Alabama be a follower of NASA/NOAA, than some kind of persecution mania has reached you and won’t leave you anymore.
I wish you all the best!

Tom in Texas
Reply to  TA
March 31, 2016 5:19 am

This is truly interesting. The dust bowl in the US was starting about this time. As I have seen in the past, the jet stream circulation continued for 7 years in most areas and 11 years for some isolated areas. Looking through the drier patterns that started in 2006 here in Texas, you will see that this jet stream pattern occurred again. It is difficult to gather this information because most is written in different description from those who actually lived through this time. Approximately 58-66 year interval. Is there then a 60 year trend?

barry
Reply to  TA
April 1, 2016 1:49 am

TA, Iow, I don’t recall reading many such weather headlines during the last ten or 15 years. You? I think if you compared newspaper clippings, the 1930’s would win the “hottest evah! award, hands down.
If you google ‘heatwave,’ ‘drought’, forest fire,’ or any of the other widely used weather descriptor in your list, and filter by ‘News,’ you’ll get a few million hits for each. The vast majority will be post-2000, if not all of them.
That’s not to say there are vastly more headlines of the ilk in the last 15 years than through the 1930s, just to indicate that the above claim may be way off-base.
Bit I’m curious, TA. How did you form your list of headlines of the 1930s, and can you perform the same search for the most recent decade?

J Calvert N(UK)
March 30, 2016 3:15 pm

If the ‘hottest year evah’ world wide is anything like our ‘hottest year evah’ here in UK, then it would be a misnomer. Our so-called hottest year could be better described as our mildest year ever – because although the summer of was not especially hot, the winter was exceptionally mild (and rainy).
It would have been quite pleasant really – if it hadn’t been for all the rain!

bit chilly
Reply to  J Calvert N(UK)
March 30, 2016 6:22 pm

yep, it is only forecast to get down to -1 in the early hours in inverness at sea level, real scorcher for the time of year 😉

March 30, 2016 6:50 pm

I wanted to see how small-town USA fared in the “hottest February evah!” I picked four stations from the GHCN inventory based on long-term continuous operation: Fairhope, Alabama (pop. 15,326), Jerome, Arizona (pop. 448), Aberdeen, Idaho (pop. 1,994), and Ridgway, Pennsylvania (pop. 4,078). I plotted extreme highs, extreme lows, and monthly averages for February (°F). Here’s the result:comment imagecomment imagecomment imagecomment image

Dave
March 30, 2016 11:50 pm

If you are going to pick any one month in history to compare with the most recent, Jan 2007 seems an odd choice, given that it is itself a relatively recent year in the HadCRUT4 data set and smack in the middle of the pause in warming claimed by some. Indeed, there is a greater degree of overlap in the error range of the Feb 2016 value with the two months immediately preceding it. Of course you can always drill down into noisy time series to ever shorter intervals if you seek sufficient statistical uncertainty to allow you to make what statisticians refer to as a “Type II” error. But I wonder what might happen if you were to be a little more objective and instead do the opposite by comparing the 3 months centred on Jan 2016 with those centred on Jan 2007?

March 31, 2016 9:18 am

Based on your comments and a comparison of your fig 2 & 3 it appears you agree with this earlier comment by NOAA:
Was El Niño solely responsible for the record warm winter for the contiguous United States? No, but for some areas, like the northern U.S., the El Niño likely played a role. We know that other factors including climate patterns in the north Atlantic, Pacific, and tropics also influenced our weather during winter. Longer-term climate change was also a player, similar to Alice, the Brady family’s housekeeper—an ever-present force influencing outcomes to varying degrees.
Fig 2 implies an El Nino contribution of ~0.4ºC and fig 3 shows a longterm contribution of ~0.4ºC with possibly a fallback of ~0.2ºC over the next 12 months.

Dave
March 31, 2016 12:14 pm

Bob, I’m neither an ‘alamist’ or a ‘denier’ although I see that the two sides of this debate seem to feel a need to label the others. But like many other educated folk, I’ve been looking to the internet for evidence for or against all the alternative hypotheses that explain what is (by every obective measure I’ve been able to ascertain) a recent period of record or near record temperatures by a substantial margin, despite this El Nino being ‘only’ (by your own account) similar to the one 18 years ago and despite the claims by some that the world hasn’t really warmed in that time. As such I’ve been reading info posted here as well as on sites that you would label ‘alarmist’, since at least folk like you are attempting to interpret primary data and help the rest of us digest it. I just want you to know that I’m heartened by your update to your own original post here. As a scientist (albeit not a climate scientist) I had felt that your original argument based on a slight overlap in 95% confidence intervals was skating on very thin ice (please excuse my ‘alarmist’ pun) in a statistical sense. But the fact that you are not only prepared to acknowledge that you may have overstated your original idea (it was a blog post after all, not a research paper) gives me some hope that at least the rational people on both sides of this debate might eventually come to some reasonable consensus. I hope I’m not proven wrong on this point at least……

barry
Reply to  Bob Tisdale
March 31, 2016 9:41 pm

I’m nominally on the “other side” and I endorse these remarks. Seeing someone say “I was wrong on that” makes me trust and respect that person more.
For the rationals on either side, it’s encumbent on us to speak up to our own irrationals. Dispatching nonsense is likelier and more efficient if led by familiars. Unless you want the noise to overcome the signal in these debates (and some do want that – the political animals), it’s well to correct your own while engaging your opponents. And you can see some do that on both sides.
(Frankly, the notion of ‘two sides’ always seems a little false to me – another political construct – but I defer to it for the sake of brevity)

March 31, 2016 12:17 pm

If you’re an alarmist and have trouble reading time-series graphs, and you want to confirm that 2015/16 was warmer than 1997/98, you’d present Figure 3.
I for one am glad that you presented both figures 2 and 3. When viewing figure 2 on first reading, I mentally adjusted the 2015/16 graph upward, but I was not sure how much upward adjustment was accurate..

Bindidion
April 5, 2016 8:03 am

No sarcasm at all here: sincere congratulations to Bob Tisdale for acknowledging Nick Stokes, a person so many deniers call an irreductible warmist.
NS’ comment seems somewhat surprising if I look at all the El Niño comparisons here
http://fs5.directupload.net/images/160405/c57z3kwm.jpg
(normalised Jan x- Feb x+1, somewhat like you did, and to which I added their big brother of 1877/78), here
http://fs5.directupload.net/images/160405/9c4jtmnw.jpg
and here
http://fs5.directupload.net/images/160405/j66jlbs6.jpg
because on all images, the 2015/16 edition really looks a bit weaker than the 1997/98 event, as show anomaly levels and OLS trends.
But NS has more knowledge, experience, tools and data than I could ever accumulate.
Trusting Nick Stokes can be dangerous for skeptics! Because if you were told that the two images below represent (1)
http://fs5.directupload.net/images/160405/t42p628a.jpg
the difference between two consecutive revisions of a surface temperature dataset, and (2)
http://fs5.directupload.net/images/160405/z55ew37x.jpg
the same data, but with in addition the differences in the North Pole (blue) and South Pole (green), you probably would unconditionally agree.
Look how the global differences scale down within the second plot, when compared with the much bigger differences in the polar regions!
But… it’s no surface data! The two plots I have made in Excel out of the differences between UAH6.0beta5 and UAH5.6. It was amazing to see that some differences between anomalies were, in absolute value, even bigger than the anomalies themselves.
Here is the original plot by NS, with in addition the differences between two GISS revisions:
http://www.moyhu.org.s3.amazonaws.com/2015/12/uahadj1.png
It’s a bit hard to accept, but I’m afraid he is right… and I must add that I wouldn’t trust that UAH6.0 dataset if UAH’s manager was not Roy Spencer.

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