Colorado Glaciers Were Rapidly Retreating During NOAA’s 4th Coldest Year On Record

In 1924, it was reported that all of glaciers in the Rockies had been retreating since 1902, with very rapid retreat since 1919.

2015-11-01-07-15-09

12 Nov 1924, Page 19 – at Newspapers.com

According to massively tampered data from NOAA, 1924 was the fourth coldest year on record in Colorado, and the entire period of retreat was very cold. CO2 was less than 310 PPM.

2015-11-01-07-18-47Climate at a Glance | National Centers for Environmental Information (NCEI)

This raises three important points.

  1. The NOAA temperature record is implausible
  2. Glacial melt has nothing to do with CO2.
  3. Nothing anyone does will stop glaciers from melting.

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66 Responses to Colorado Glaciers Were Rapidly Retreating During NOAA’s 4th Coldest Year On Record

  1. rah says:

    Not a good weekend to be above the tree line on Mt. Rainier in WA either.

    http://iceagenow.info/2015/10/more-than-13-feet-of-snow-mount-rainier-wa-by-monday-evening/

    13 feet+ of snow accumulation in 4 days! No doubt that mountain is rumbling with avalanches both big and small right now I suspect.

  2. rah says:

    Glaciers advance and retreat. Sometimes they disappear altogether. It’s what they do. The time for the average person to really start paying attention is when most all of them are advancing, not when some or even all are receding.

  3. Steve Case says:

    4. Why should anyone care if the glaciers retreat?

  4. Martin Smith says:

    Steven, if you have any evidence that NOAA tampered with the data, why not post it? NOAA has explained the adjustments to the data, and no one has argued that the explanation is wrong, but you are accusing NOAA of fraud. You have to have evidence for that, which you have not posted, as far as I can tell. Glaciers receding in Colorado during a cold year is not evidence of anything. The global average temperature for the years the news articles refer to was way above freezing, so the fact that some glaciers were receding during those years doesn’t demonstrate anything. It certainly does not argue for raising your “three important points.” You are making claims without evidence.

    • Can you explain how “global average temperature” affects the receding of Colorado glaciers? Or the Antarctica ice sheet, for that matter?

      • Martin Smith says:

        Not sure what you’re asking for, Colorado. The point is that the global average temperature for the cold years when Steven’s example glaciers were receding was about 13.5C, which is well above freezing. It means there were some places in the world where the temperature was much higher than 13.5C. So Steven can’t use receding glaciers in Colorado during those years as evidence that the NOAA data is wrong. In fact, the NOAA adjustment increased the global average temperature for the years Steven is talking about. Apparently he still doesn’t know that.

        • “Not sure what you’re asking for, Colorado.”

          Martin Smith,

          It was simple question about Colorado glacial melt. I threw in Antarctica as a clue. I wanted to give you a chance to reconsider your argument. You didn’t. In fact, you got deeper into your muddle:

          “The global average temperature for the cold years when Steven’s example glaciers were receding was about 13.5C, which is well above freezing.”

          Huh? Goddard posted NOAA average temperatures for Colorado. Global average temperatures above or below freezing point have little to do with local glaciation. You seem to understand averaging when you try to construct an argument, so I assume that you also understand that “global average temperatures” include the tropics.

          So let’s walk a little through your miscellany:

          “Glaciers receding in Colorado during a cold year is not evidence of anything.”

          Huh? By definition, glaciers receding in Colorado during that period provide clear evidence that the balance of precipitation and accumulation, glacier ice flow and melting caused by seasonal changes in local temperature, irradiation and wind through the seasons caused the glacier terminus to retreat.

          “The global average temperature for the years the news articles refer to was way above freezing, so the fact that some glaciers were receding during those years doesn’t demonstrate anything.”

          Again. Not “global average temperatures” and not “some glaciers”. Colorado average temperatures and Colorado glaciers.

          “NOAA adjustment increased the global average temperature …”

          Same as above. Global temperatures are largely irrelevant. Colorado temperatures matter to Colorado glaciers. Refer to the picture below.

          It certainly does not argue for raising your “three important points.”

          Yes it does. 3,2,1:

          3. Nothing anyone does will stop glaciers from melting.

          The glaciers were receding during NOAA’s claimed 4th coldest year in Colorado. They were advancing at other times of claimed warmer Colorado temperatures. The discussion is about CO2. Colorado glaciers receded during a claimed 1920s cold period with CO2 below 310 ppmv. Only to a partisan believer it “does not argue” anything. What in the world do you want to have done about CO2 that would have stopped the Colorado glaciers from melting at the beginning of the 20th century?

          2.Glacial melt has nothing to do with CO2.

          This is getting tedious. Same as above. CO2 was below 310 ppvm in 1920s and was not a factor in Colorado glacial melt. Why do you need to deny this? I know intelligent lukewarmers who would acknowledge it because they wouldn’t want to lose credibility.

          1. The NOAA temperature record is implausible

          Yes, it is suspect and implausible. A reasonable person interested in finding the truth would be curious and want to revisit the claims in light of the above contradictions. Most scientific discoveries are not accompanied by cries of “Eureka”. They start with a bewildered researcher muttering “That’s strange …”.

          You seem more interested in denying and misrepresenting the inconvenient facts. Your contortions and protestations are spread through this whole post.

          ”Steven, if you have any evidence that NOAA tampered with the data, why not post it?”

          He did. For starters, type NOAA into the search box.

          And I hope you’ll come back soon to build us another one of these:

          https://coloradowellington.files.wordpress.com/2015/09/strawman.jpg

        • Martin Smith says:

          Colorado, I still don’t see your point. You haven’t refuted what I said. Steven claims that melting glaciers in Colorado in 1924 prove that the NOAA adjustment is incorrect, even fraudulent. Melting glaciers in Colorado in 1924 don’t prove anything. They aren’t even evidence that the NOAA adjustment is wrong. In fact, NOAA’s adjustment for 1924 was to increase the temperature. To show the NOAA adjustment is wrong, you have to show where and why it is wrong. Glaciers melting in Colorado in 1924 can’t do that. The effect of the NOAA adjustment in the year in question, and most of the years before 1950, is to reduce global warming. So if Steven’s claim is correct now, then it was more correct before the adjustment. But his claim is not correct. Here is the graph showing the effect of the adjustment being to reduce global warming. See point 4: http://climatecrocks.com/2015/10/30/explaining-noaas-no-more-hiatus-paper/

        • Colorado, I still don’t see your point.

          I could be convinced you don’t see it. Maybe you are a vegetarian. I’ve seen cases like that before.

          It is also possible that you are an eager but underpaid intern with the Climate Response Team. You have a script to repeat. The minimal training they gave you stressed that you will just repeat the script without any deviation.

          It could be the Climate Response Team has outsourced the service to a low budget call center. You can speak English, it pays better than the alternatives, you have a standard procedural script to follow, you work the shift and go home.

          You could also be a small piece of code programmed to pretend a response and repeat a limited batch of statements until aborted by the proprietor.

          You could be the Strauß Collective—you are using their methods—but the Strauß didn’t do global warming last time I checked.

          There are a few other possibilities, increasingly more bizarre. I’ll go with vegetarian.

        • Martin Smith says:

          I’m not any of those things, Colorado, and I’m a bit mystified that you reverted to ad hominem so quickly. I have made my point repeatedly, and no one has refuted it. The point is Steven can’t use receding glaciers in Colorado in 1924 to claim the NOAA data adjustment is incorrect, let alone fraudulent.

        • It seems you know the words but don’t understand their definitions. Vegetarian is a state of mind but certainly no ad hominem.

          I responded to your post specifically. You ignored it and just repeated the same thing. I’m not judging you but your argumentation.

          As to why you are doing it, all my suggestions are admittedly just conjectures. You may not understand it but I am actually giving you the benefit of doubt. There is nothing wrong with being, for example, a young Indian lady just trying to make a living. There is nothing wrong with her personally, it’s just that she’s not in position to contribute anything useful and her responses are off topic. It’s not about who you are, it’s what you are doing.

          There is another, less benign, possibility that you actually know exactly what you are doing. If you carry on like this, I’m likely to abandon my charitable assumption you are a vegetarian.

        • Martin Smith:

          I have been too charitable in my assumptions. You did not reply to my specific rebuttal above. You didn’t rebut anything I wrote about your claims. It’s recorded above for everyone to see. You have simply moved on. You keep using the same methods in comments to others in this thread and elsewhere on this blog.

          Your methods, tactics and the content of your comments bare your intent:

          You don’t want to engage in a scientific argument or a struggle of ideas. You are not here to come closer to the truth. You are here to create the impression that Steven Goddard’s claims can be easily dismissed. Unless you are completely stupid, deluded or both, you can’t possibly believe this would work on anyone familiar with the basic facts about anthropogenic global warming. You have nothing to offer and you know it.

          You are targeting fence sitters, new or infrequent visitors, readers who don’t have the time or patience to read through entire threads and follow through consecutive posts. You are only trying to prevent people who started developing some doubts about the veracity of the alarmist claims from going down the skeptical path. You are implicitly acknowledging the damage Steven Goddard is inflicting on the public perception of the anthropogenic global warming scam. His success is why you are here.

          There is nothing unusual or extraordinary about your dishonest tactics. There are scores of people like you and some come to this blog from time to time. You are all alike.

          For my own purposes, I’m downgrading you from a potentially benign vegetarian to a garden variety troll.

        • gator69 says:

          Hey CW! Without Winston Smith’s nephews, the alarmist camp is getting thin, and the recruiting continues to fail. Another poll shows the real death spiral, the waning concern over the Gaian apocalypse.

          http://surveys.ap.org/data/NORC/October_Omnibus_Topline_FINAL_EARLYRELEASE.pdf

          Death of a salesman.

        • Martin Smith,

          You have not responded to any of the points I made here:

          https://stevengoddard.wordpress.com/2015/11/01/colorado-glaciers-were-rapidly-retreating-during-noaas-4th-coldest-year-on-record/#comment-548959

          I have quoted your words and showed that your statements do not make sense. I have specifically refuted things you said.

          All you have done was regurgitating the same talking points, as is your habit, and insisted I have not refuted anything.

          You should go home and put some serious work into the alarmist talking points database you said is needed to combat skeptical arguments. Your current effort doesn’t cut it.

      • Martin Smith says:

        Now that I understand your question, I don’t see what it has to do with the subject. Look at the graph Steven posted for Colorado. These are average temperatures, and they are all above freezing, as you would expect them to be. Why were glaciers receding faster than normal in Colorado during that time? I don’t know. If it is true, how does it invalidate the NOAA adjustment?

        Concerning Antarctic glaciers, then end in the sea. They are receding because the sea has warmed.

    • gator69 says:

      NOAA quietly revises website after getting caught in global warming lie, admitting 1936 was hotter than 2012

      ‘You can’t get any clearer proof’ of fraud

      “The previous warmest July for the nation was July 1936, when the average U.S. temperature was 77.4°F,” NOAA said in 2012.

      When checked by The Daily Caller, that claim by the NOAA was still available on the agency’s website. However:

      [W]hen meteorologist and climate blogger Anthony Watts went to check the NOAA data [June 29] he found that the science agency had quietly reinstated July 1936 as the hottest month on record in the U.S.

      Watts wrote: “Two years ago during the scorching summer of 2012, July 1936 lost its place on the leaderboard and July 2012 became the hottest month on record in the United States. Now, as if by magic, and according to NOAA’s own data, July 1936 is now the hottest month on record again. The past, present, and future all seems to be ‘adjustable’ in NOAA’s world.” [See his blog post here: http://wattsupwiththat.com]

      Watts had used data from NOAA’s “Climate at a Glance” plots from 2012, a graphic showing that July 2012 was the hottest month on record at 77.6°F. July 1936 — which was during the infamous Dust Bowl years — is listed at only 77.4°F.

      He ran the same data plot again on June 29 and discovered that NOAA inserted a new number in for July 1936; the average temperature for July 1936 was made slightly higher than July 2012, meaning, again, that July 1936 is the hottest year on record.

      “You can’t get any clearer proof of NOAA adjusting past temperatures,” Watts wrote. “This isn’t just some issue with gridding, or anomalies, or method, it is about NOAA not being able to present historical climate information of the United States accurately.”

      He went on to note that in “one report they give one number, and in another they give a different one with no explanation to the public as to why.

      “This is not acceptable. It is not being honest with the public. It is not scientific. It violates the Data Quality Act.”

      http://www.naturalnews.com/045808_global_warming_fraud_data_manipulation_NOAA.html#ixzz3qKL6Eft4

      Once again, Martin proves he is ignorant of the facts.

      • Martin Smith says:

        I’m not sure what your point i, gator, but I am sure it has nothing to do with Steven’s blog post. Steven claims the NOAA adjustment is wrong because glaciers were melting in Colorado in1924. His conclusion does not follow from that fact. In fact, the NOAA adjustment increases the global average temperature for 1924. See the evidence here in item 4: http://climatecrocks.com/2015/10/30/explaining-noaas-no-more-hiatus-paper/

        • gator69 says:

          Martin, are you as stupid as you pretend to be?

          NOAA has explained the adjustments to the data, and no one has argued that the explanation is wrong, but you are accusing NOAA of fraud.

          Yes, NOAA is always trying to explain away their fraud. And as I pointed out above (and over your head), they have been caught red handed in the past. You act like a Hillary supporter, a faithful democrat who knows their candidate is a liar, and yet still supports her. Enable much?

          Are you a battered husband? There is help.

          http://www.helpguide.org/articles/abuse/help-for-abused-men.htm

        • Martin Smith says:

          Gator, you haven’t shown fraud, but your reply has nothing to do with the subject of this thread. Steven claims the NOAA adjustment is wrong because glaciers were melting in Colorado in1924. His conclusion does not follow from that fact. In fact, the NOAA adjustment increases the global average temperature for 1924. See the evidence here in item 4: http://climatecrocks.com/2015/10/30/explaining-noaas-no-more-hiatus-paper/

        • gator69 says:

          I have shown erroneous adjustments by NOAA, and you dismiss it. That and the fact that you could not even comprehend the first sentence of a press release, speaks volumes. 😆

        • Martin Smith says:

          No, gator, you have not. Here is the explanation again. Read it this time. See item 4. The year you are talking about, 1936, is one of the years where the data was adjusted upward:
          http://climatecrocks.com/2015/10/30/explaining-noaas-no-more-hiatus-paper/

          You have attacked my character repeatedly. You gain nothing by that. Your attacks say nothing about me. They say a lot about you.

        • gator69 says:

          I have repeatedly attacked your ignorance, and that is part of your character.

          The adjustments were erroneous, period, that is why NOAA backtracked from their false claim.

        • Martin Smith says:

          Your excerpt from WUWT didn’t prove anything, gator. But it wasn’t even relevant to this discussion, which is about Steven Goddard’s claim that melting glaciers in Colorado in 1924 invalidate the NOAA data adjustment. The global average temperature for the cold years when Steven’s example glaciers were receding was about 13.5C, which is well above freezing. That means there were some places in the world where the temperature was much warmer than 13.5C. So Steven can’t use receding glaciers in Colorado during those years as evidence that the NOAA data is wrong. In fact, the NOAA adjustment increased the global average temperature for the years Steven is talking about. Apparently neither he nor you understand that. Here is the proof. See item 4: http://climatecrocks.com/2015/10/30/explaining-noaas-no-more-hiatus-paper/

        • gator69 says:

          Once again Martin, I have shown that NOAA adjustments have been found to be in error. What part of that do you not get?

        • Martin Smith says:

          No, gator, you didn’t show that any adjustment was incorrect. You didn’t show anything. You posted a blurb from somebody’s blog that made the same claim you are making. But that’s irrelevant anyway because it has nothing to do with the subject of this thread, which, once again, is what Steven wrote about Colorado glaciers in 1924. Steven claims the NOAA adjustment is wrong because glaciers were melting in Colorado in1924. His conclusion does not follow from that fact. In fact, the NOAA adjustment increases the global average temperature for 1924. See the evidence here in item 4: http://climatecrocks.com/2015/10/30/explaining-noaas-no-more-hiatus-paper/

        • gator69 says:

          No Martin, you are irrelevant, and stupid. NOAA made a false claim based upon erroneous adjustments, got caught, and was forced to reverse their claim.

        • gator69 says:

          And I forgot to add that your link is also “just a blog post”. At least my “blog post” is based upon facts, and not opinion. NOAA falsely claimed hottest year ever based upon their adjustments, when it wasn’t. They lied.

        • Martin Smith says:

          gator, you haven’t shown NOAA made any false claim, but it isn’t relevant to this discussion. Steven claims the NOAA adjustment is wrong because glaciers were melting in Colorado in1924. His conclusion does not follow from that fact. In fact, the NOAA adjustment increases the global average temperature for 1924. See the evidence here in item 4: http://climatecrocks.com/2015/10/30/explaining-noaas-no-more-hiatus-paper/

        • gator69 says:

          Martin, your failure to understand that what I have provided shows that NOAA’s adjustments cannot be trusted is prof of your mental limitations.

          And let’s see if you can answer my earlier question. What is NOAA’s adjustment for UHI?

        • Martin Smith says:

          Yes, gator, my post is a blog post, but it contains links to the actual science that shows the graph is correct and that my statements are correct. Your blog post doesn’t. But your comments aren’t relevant to this discussion. Steven claims the NOAA adjustment is wrong because glaciers were melting in Colorado in1924. His conclusion does not follow from that fact. In fact, the NOAA adjustment increases the global average temperature for 1924. See the evidence here in item 4: http://climatecrocks.com/2015/10/30/explaining-noaas-no-more-hiatus-paper/

        • gator69 says:

          No Martin, your blog post is based upon opinions that are based upon bogus adjustments, adjustments by NOAA, who as I have shown cannot be trusted.

    • AndyG55 says:

      “you are accusing NOAA of fraud”

      Yes.. and NOAA knows this, yet DOES ABSOLUTELY NOTHING ABOUT IT.

      They know that CANNOT CHALLENGE THE ACCUSATION.

      Because it is THE TRUTH.

      Legal “Discovery” is their worst nightmare, as Mickey Mann has proven.

      Do you really think that SG could get away with the accusations otherwise ?

      • Martin Smith says:

        Not sure what you are referring to, Andy, but Steven hasn’t shown anything, let alone fraud.

        • wizzum says:

          Martin, please explain why any temperatures should be altered from the actual reading and not just tossed out if it cannot be proved to be accurate?
          Once you have done that please explain how to arrive at the correct amount of adjustment?

        • Martin Smith says:

          Wizzum, your questions are answered at the NOAA and/or NASA website. The explanations for data adjustments are discussed quite often, and peer-reviewed papers are published about them, so I am surprised you aren’t already familiar with the subject. The websites and papers explain how they determine the size of each bias/error.

        • darwin says:

          Martin,

          Nothing the climate fanatics predicted for the last forty years has come true.

          Nothing.

          Yet you keep believing that people paid billions to promote a singular theory are honest and their data is correct.

        • Martin Smith says:

          Darwin, that is simply false.

      • Martin Smith says:

        Darwin, that is simply false.

        • darwin says:

          No, it’s not.

          Billions and billions of dollars are being pumped to corrupt government scientists to produce fake data because their predictions have an accuracy rate of ZERO.

          How long will you continue to believe blatant propaganda?

        • wizzum says:

          We are feeding HAL

        • Martin Smith says:

          No, darwin, your claim is false.

        • darwin says:

          Oh? Which dire predictions have come true? All the models failed, even the prediction around which this entire scam is based … that temperatures will rise as CO2 increases … didn’t pan out.

          Every year we get hysterical claims that we only have a few years left to save the world … this has been going on for decades.

    • DD More says:

      Martin, tried to put this down a few days ago.
      Adjustments also include wrong way values

      From the Climategate emails # – 2328
      date: Wed, 3 Jun 2009 15:07:25 +010 ???
      from: “Parker, David”
      subject: RE: Tom’s thoughts on urban errors …
      Everybody wants to add an estimate of what UHI bias might be into their error bars, but it seems to me that rather than trust folk lore that there is a uhi bias, they first need to find one systematically in the network. Until they do that, the former is just hand waving to appease the know-littles. Jim Hansen adjusts his urban stations (based on night-lights) to nearby rural stations, but if I recall correctly (I’ll send that paper shortly), he warms the trend in 42 percent of the urban stations indicating that nearly half have an urban cold bias. Yet error analyzers want to add a one sided extra error bar for uhi…..
      Regards,
      Tom

      http://www.ecowho.com/foia.php?file=1057.txt&search=Hansen+adjust
      Bold in the original.

      What they say.

      Climate Etc. – Understanding adjustments to temperature data

      by Zeke Hausfather All of these changes introduce (non-random) systemic biases into the network. For example, MMTS sensors tend to read maximum daily temperatures about 0.5 C colder than LiG thermometers at the same location.
      http://judithcurry.com/2014/07/07/understanding-adjustments-to-temperature-data/

      What He measured

      Interviewed was meteorologist Klaus Hager. He was active in meteorology for 44 years and now has been a lecturer at the University of Augsburg almost 10 years. He is considered an expert in weather instrumentation and measurement. One reason for the perceived warming, Hager says, is traced back to a change in measurement instrumentation. He says glass thermometers were was replaced by much more sensitive electronic instruments in 1995. Hager tells the SZ ” For eight years I conducted parallel measurements at Lechfeld. The result was that compared to the glass thermometers, the electronic thermometers showed on average a temperature that was 0.9°C warmer. Thus we are comparing – even though we are measuring the temperature here – apples and oranges. No one is told that.” Hager confirms to the AZ that the higher temperatures are indeed an artifact of the new instruments.
      http://notrickszone.com/2015/01/12/university-of-augsburg-44-year-veteran-meteorologist-calls-climate-protection-ridiculous-a-deception/

      Also from Zeke, a serial adjuster.

      Zeke ‘says’ At first glance, it would seem that the time of observation wouldn’t matter at all. After all, the instrument is recording the minimum and maximum temperatures for a 24-hour period no matter what time of day you reset it. The reason that it matters, however, is that depending on the time of observation you will end up occasionally double counting either high or low days more than you should. For example, say that today is unusually warm, and that the temperature drops, say, 10 degrees F tomorrow. If you observe the temperature at 5 PM and reset the instrument, the temperature at 5:01 PM might be higher than any readings during the next day, but would still end up being counted as the high of the next day. Similarly, if you observe the temperature in the early morning, you end up occasionally double counting low temperatures. If you keep the time of observation constant over time, this won’t make any different to the long-term station trends. If you change the observations times from afternoons to mornings, as occurred in the U.S., you change from occasionally double counting highs to occasionally double counting lows, resulting in a measurable bias.

      To show the effect of time of observation on the resulting temperature, I analyzed all the hourly temperatures between 2004 and 2014 in the newly created and pristinely sited U.S. Climate Reference Network (CRN). I looked at all possible different 24 hour periods (midnight to midnight, 1 AM to 1 AM, etc.), and calculated the maximum, minimum, and mean temperatures for all of the 24 hours periods in the CRN data. The results are shown in Figure 4, and are nearly identical to Figure 3 published in Vose et al 2003 (which was used a similar approach on a different hourly dataset).If you keep the time of observation constant over time, this won’t make any different to the long-term station trends. If you change the observations times from afternoons to mornings, as occurred in the U.S., you change from occasionally double counting highs to occasionally double counting lows, resulting in a measurable bias..

      If the TOA does not trend in the monthly average, then a single change in time of observation would not change more than the month in which the time change was made in. His study only looked at the daily temperature changes based on TOA. He never shows how much it would change the monthly average, most likely because it doesn’t.

      https://stevengoddard.wordpress.com/2015/10/29/new-ways-to-visualize-nasa-temperature-fraud/#comment-548377

      Or just put in any number you like.

      Monthly temperatures which are marked with an “E” are “estimated” rather than measured. More than half of the current data for 2015 is fake.

      https://stevengoddard.files.wordpress.com/2015/02/screenhunter_7444-feb-26-07-59.gif?w=640

      Forget the past.

      August 2015 – The combined average temperature over global land and ocean surfaces for August 2015 was 0.88°C (1.58°F) above the 20th century average of 15.6°C (60.1°F) => 0.88°C (1.58°F) + 15.6°C (60.1°F) = 16.48°C (61.68°F)
      http://www.ncdc.noaa.gov/sotc/global/201508

      July 2015 – The combined average temperature over global land and ocean surfaces for July 2015 was the highest for July in the 136-year period of record, at 0.81°C (1.46°F) above the 20th century average of 15.8°C (60.4°F), surpassing the previous record set in 1998 by 0.08°C (0.14°F).
      => 0.81°C + 15.8°C = 16.61°C or 1.46°F + 60.4°F = 61.86°F
      http://www.ncdc.noaa.gov/sotc/global/201507

      May 2015 – The combined average temperature over global land and ocean surfaces for May 2015 was the highest for May in the 136-year period of record, at 0.87°C (1.57°F) above the 20th century average of 14.8°C (58.6°F),
      => 0.87°C + 14.8°C = 15.67°C or 1.57°F + 58.6°F = 60.17°F

      (1) The Climate of 1997 – Annual Global Temperature Index “The global average temperature of 62.45 degrees Fahrenheit for 1997” = 16.92°C.
      http://www.ncdc.noaa.gov/sotc/global/1997/13

      (2) 2014 annual global land and ocean surfaces temperature “The annually-averaged temperature was 0.69°C (1.24°F) above the 20th century average of 13.9°C (57.0°F)= 0.69°C above 13.9°C => 0.69°C + 13.9°C = 14.59°C
      http://www.ncdc.noaa.gov/sotc/global/2014/13

      16.48°C >> 16.61 >> 15.67 >> 16.92 << 14.59

      They cannot even keep the same 20th century average of 15.6°C or 15.8°C or 14.8°C or 13.9°C the same 15 years after it was over?

      Since 1997 was not even the peak year, which number do you think NCDC/NOAA thinks is the record high. Failure at 3rd grade math or failure to scrub all the past. (See the ‘Ministry of Truth’ 1984).

      What would it have been if they were still using the semi-adjusted HADCRUT3 version instead of the full-adjusted HADCRUT4.

      12 month average anomaly
      HADCRUT3 HADCRUT4
      Dec 1998 0.55 0.52
      Dec 2011 0.34 0.40
      Increase/ -0.21 -0.12

      The new version increases warming (or rather decreases cooling) since 1998 by 0.09C, a significant amount for a 13 year time span. Whilst the changes should not affect the trend in future years, they will affect the debate as to whether temperatures have increased in the last decade or so.

      https://notalotofpeopleknowthat.wordpress.com/2012/10/10/hadcrut4-v-hadcrut3/Decrease

      There is your evidence.

    • DD More says:

      Martin, here is your fraud and fake adjustments. Part 1

      Adjustments also include wrong way values

      From the Climategate emails # – 2328
      date: Wed, 3 Jun 2009 15:07:25 +010 ???
      from: “Parker, David”
      subject: RE: Tom’s thoughts on urban errors …
      Everybody wants to add an estimate of what UHI bias might be into their error bars, but it seems to me that rather than trust folk lore that there is a uhi bias, they first need to find one systematically in the network. Until they do that, the former is just hand waving to appease the know-littles. Jim Hansen adjusts his urban stations (based on night-lights) to nearby rural stations, but if I recall correctly (I’ll send that paper shortly), he warms the trend in 42 percent of the urban stations indicating that nearly half have an urban cold bias. Yet error analyzers want to add a one sided extra error bar for uhi…..
      Regards,
      Tom

      http://www.ecowho.com/foia.php?file=1057.txt&search=Hansen+adjust
      Bold in the original.

      UHI urban cold?

      What they say.

      Climate Etc. – Understanding adjustments to temperature data

      by Zeke Hausfather All of these changes introduce (non-random) systemic biases into the network. For example, MMTS sensors tend to read maximum daily temperatures about 0.5 C colder than LiG thermometers at the same location.
      http://judithcurry.com/2014/07/07/understanding-adjustments-to-temperature-data/

      What He measured

      Interviewed was meteorologist Klaus Hager. He was active in meteorology for 44 years and now has been a lecturer at the University of Augsburg almost 10 years. He is considered an expert in weather instrumentation and measurement. One reason for the perceived warming, Hager says, is traced back to a change in measurement instrumentation. He says glass thermometers were was replaced by much more sensitive electronic instruments in 1995. Hager tells the SZ ” For eight years I conducted parallel measurements at Lechfeld. The result was that compared to the glass thermometers, the electronic thermometers showed on average a temperature that was 0.9°C warmer. Thus we are comparing – even though we are measuring the temperature here – apples and oranges. No one is told that.” Hager confirms to the AZ that the higher temperatures are indeed an artifact of the new instruments.
      http://notrickszone.com/2015/01/12/university-of-augsburg-44-year-veteran-meteorologist-calls-climate-protection-ridiculous-a-deception/

      +0.5C – = 1.4C theory – measured difference

      • DD More says:

        Martin, here is your fraud and fake adjustments. Part 2
        Also from Zeke, a serial adjuster.

        Zeke ‘says’ At first glance, it would seem that the time of observation wouldn’t matter at all. After all, the instrument is recording the minimum and maximum temperatures for a 24-hour period no matter what time of day you reset it. The reason that it matters, however, is that depending on the time of observation you will end up occasionally double counting either high or low days more than you should. For example, say that today is unusually warm, and that the temperature drops, say, 10 degrees F tomorrow. If you observe the temperature at 5 PM and reset the instrument, the temperature at 5:01 PM might be higher than any readings during the next day, but would still end up being counted as the high of the next day. Similarly, if you observe the temperature in the early morning, you end up occasionally double counting low temperatures. If you keep the time of observation constant over time, this won’t make any different to the long-term station trends. If you change the observations times from afternoons to mornings, as occurred in the U.S., you change from occasionally double counting highs to occasionally double counting lows, resulting in a measurable bias.

        To show the effect of time of observation on the resulting temperature, I analyzed all the hourly temperatures between 2004 and 2014 in the newly created and pristinely sited U.S. Climate Reference Network (CRN). I looked at all possible different 24 hour periods (midnight to midnight, 1 AM to 1 AM, etc.), and calculated the maximum, minimum, and mean temperatures for all of the 24 hours periods in the CRN data. The results are shown in Figure 4, and are nearly identical to Figure 3 published in Vose et al 2003 (which was used a similar approach on a different hourly dataset).If you keep the time of observation constant over time, this won’t make any different to the long-term station trends. If you change the observations times from afternoons to mornings, as occurred in the U.S., you change from occasionally double counting highs to occasionally double counting lows, resulting in a measurable bias..

        If the TOA does not trend in the monthly average, then a single change in time of observation would not change more than the month in which the time change was made in. His study only looked at the daily temperature changes based on TOA. He never shows how much it would change the monthly average, most likely because it doesn’t.

        Or just put in any number you like.

        Monthly temperatures which are marked with an “E” are “estimated” rather than measured. More than half of the current data for 2015 is fake.

        https://stevengoddard.files.wordpress.com/2015/02/screenhunter_7444-feb-26-07-59.gif?w=640

        • Martin Smith says:

          DD, the techniques used to “fabricate” this data, as you call it are based on good science. It has been shown to be correct, so listing this here as evidence of fraud is really dishonest of you.

        • rah says:

          Martin you’ve made it clear you wouldn’t know “good science” if it hit you in the nose.

      • DD More says:

        Martin, here is your fraud and fake adjustments. Part 3
        Forget what was reported in the past.

        August 2015 – The combined average temperature over global land and ocean surfaces for August 2015 was 0.88°C (1.58°F) above the 20th century average of 15.6°C (60.1°F) => 0.88°C (1.58°F) + 15.6°C (60.1°F) = 16.48°C (61.68°F)
        http://www.ncdc.noaa.gov/sotc/global/201508

        July 2015 – The combined average temperature over global land and ocean surfaces for July 2015 was the highest for July in the 136-year period of record, at 0.81°C (1.46°F) above the 20th century average of 15.8°C (60.4°F), surpassing the previous record set in 1998 by 0.08°C (0.14°F).
        => 0.81°C + 15.8°C = 16.61°C or 1.46°F + 60.4°F = 61.86°F
        http://www.ncdc.noaa.gov/sotc/global/201507

        May 2015 – The combined average temperature over global land and ocean surfaces for May 2015 was the highest for May in the 136-year period of record, at 0.87°C (1.57°F) above the 20th century average of 14.8°C (58.6°F),
        => 0.87°C + 14.8°C = 15.67°C or 1.57°F + 58.6°F = 60.17°F

        (1) The Climate of 1997 – Annual Global Temperature Index “The global average temperature of 62.45 degrees Fahrenheit for 1997” = 16.92°C.
        http://www.ncdc.noaa.gov/sotc/global/1997/13

        (2) 2014 annual global land and ocean surfaces temperature “The annually-averaged temperature was 0.69°C (1.24°F) above the 20th century average of 13.9°C (57.0°F)= 0.69°C above 13.9°C => 0.69°C + 13.9°C = 14.59°C
        http://www.ncdc.noaa.gov/sotc/global/2014/13

        16.48°C >> 16.61 >> 15.67 >> 16.92 << 14.59

        They cannot even keep the same 20th century average of 15.6°C or 15.8°C or 14.8°C or 13.9°C the same 15 years after it was over?

        Since 1997 was not even the peak year, which number do you think NCDC/NOAA thinks is the record high. Failure at 3rd grade math or failure to scrub all the past. (See the ‘Ministry of Truth’ 1984).

        What would it have been if they were still using the semi-adjusted HADCRUT3 version instead of the full-adjusted HADCRUT4.

        12 month average anomaly
        HADCRUT3 HADCRUT4
        Dec 1998 0.55 0.52
        Dec 2011 0.34 0.40
        Increase/ -0.21 -0.12

        The new version increases warming (or rather decreases cooling) since 1998 by 0.09C, a significant amount for a 13 year time span. Whilst the changes should not affect the trend in future years, they will affect the debate as to whether temperatures have increased in the last decade or so.

        https://notalotofpeopleknowthat.wordpress.com/2012/10/10/hadcrut4-v-hadcrut3/Decrease

        Published study.
        Psych-ops operations have maximum effect with people who:
        – have little education
        – accept information uncritically
        – benefit from the proposed change
        – want to believe the propaganda
        – do not wish to understand their own motivations
        http://www.systemiccoaching.com/psych-ops.htm

        Hey Martin, check them off and tell us how many check marks to you have?

        • Martin Smith says:

          DD, all you have done, again, is show that data have been adjusted. Nobody denies that data have been adjusted. All the datasets have been adjusted numerous times.

      • Gail Combs says:

        Here is another smoking gun. The data is not ‘adjusted’ it is made out of whole cloth! OVER FORTY F…KING PERCENT OF IT!!!

        (Also see the KRIGGING SCAM that makes the infilling even worse.)

        Infilling Is Massively Corrupting The US Temperature Record

        …The graph below shows the average of three different USHCN groups of data since 1990, which was the year they started exponentially losing data.

        The raw data is green. It shows a small warming since 1990, all of which occurred before 1998. The final adjusted data is blue, and shows much stronger warming. The fabricated data (temperatures marked with an “E”) shows a very strong warming, and is the component of the final data which creates almost all of the difference between final and raw.

        According to the USHCN V1 documentation, there is no additional adjusting needed after 1990, and according to the USHCN V2 documents they use the same TOBS algorithm as V1. So other than infilling, final should match raw after 1990.

        I don’t see how this could be any clearer. Infilling of fabricated temperatures is causing the vast majority of reported warming since 1990. The reason I see this and others don’t – is because I use the actual data reported by USHCN exactly as it is reported….

        https://stevengoddard.files.wordpress.com/2014/06/screenhunter_717-jun-30-07-51.gif

        “Note how the divergence coincides with the beginning of wide scale station data loss.”

        https://stevengoddard.files.wordpress.com/2014/06/unnamed.gif

        Steven is not the only one who found the data is just plain missing:
        http://wattsupwiththat.com/2010/03/08/on-the-march-of-the-thermometers/

        https://diggingintheclay.wordpress.com/2010/04/11/canada-top-of-the-hockey-league-part-1/ (Many many other posts around the same time)

        http://chiefio.wordpress.com/2009/08/05/agw-is-a-thermometer-count-artifact/

    • Gail Combs says:

      From Steven’s various posts:
      US temperatures have not warmed over the past century (blue line below) – but NCDC alters the data to create the appearance of warming (red line below)

      https://stevengoddard.files.wordpress.com/2014/10/screenhunter_3231-oct-01-22-56.gif

      They accomplish this through a spectacular hockey stick of data tampering, which cools the past and warms the present.

      https://stevengoddard.files.wordpress.com/2014/10/screenhunter_3232-oct-01-22-58.gif

      So I tried correlating the magnitude of the tampering with the amount of CO2 in the atmosphere, and found almost perfect correlation – shown below.

      https://stevengoddard.files.wordpress.com/2014/10/screenhunter_3233-oct-01-22-59.gif

      Before data tampering by NCDC, US temperatures show essentially zero correlation with atmospheric CO2. Climate sensitivity of zero.

      https://stevengoddard.files.wordpress.com/2014/12/screenhunter_5685-dec-30-18-55.gif

      That is just ONE smoking gun.

      • Martin Smith says:

        Gail, you, too, have tried to claim that data adjustments are wrong by showing there have been data adjustments. You have to show that an adjustment is wrong.

        • Gail Combs says:

          And YOU Martin have just shown you are more interested in scoring points than in actually READING what is shown.
          POINT ONE

          There is a R^2 = 0.0028 for the correlation between US temperatures and CO2 over time.

          POINT TWO
          There is a R^2 = 0.987 for the correlation between US temperatures ADJUSTMENTS and CO2 over time.
          So what does a R^2 mean?

          R-Square

          A mathematical term describing how much variation is being explained by the X.

          Rsq = 1 – SS(regression)/SS(total), Assuming “SS” = Sum Squared error, and that “SS(total)” means the variance in the data. This should be obvious, as R-squared approaches unity as a regression approaches a perfect fit.(i.e., Rsq = 1 – sum((data – regression)^2))/sum((data – datamean).^2))

          The R-squared value is the fraction of the variance (not ‘variation’) in the data that is explained by a regression.
          http://www.isixsigma.com/dictionary/r-square/

          AND THERE IS NO WAY IN HELL YOU ARE GOING TO HAVE THAT GOOD A FIT WITHOUT THE ADJUSTMENTS BEING SET-UP THAT WAY! In other words FRAUD not science is what is behind those adjustments.

          There is plenty of other independent information that shows the adjustments are not justified by that R^2 = 0.987 yells FRAUD loud and clear to anyone with any statistical training.

          Since you are not actually interested in the actual facts I will just put up a couple links for those who are.
          On Thermometer resolution, and ERROR
          http://pugshoes.blogspot.se/2010/10/metrology.html
          http://iceagenow.info/2015/02/london-telegraph-agw-biggest-science-scandal/#comment-284188
          https://stevengoddard.wordpress.com/2015/02/10/lubos-missing-the-forest-for-the-trees/#comment-489960

        • Martin Smith says:

          Gail, in your POINT ONE, you are using the raw data, which were found to be biased/incorrect. You have completely dismissed that fact. The biases and errors have been explained, but you are ignoring those explanations and simply accepting the raw data as correct. Why? What is your evidence that the adjustments are wrong? You have not shown any evidence that the adjustments are incorrect, let alone fraudulent. You simply begin by assuming the raw data are correct and therefore the adjustments are incorrect. That’s why the correlation in your POINT TWO is so much higher. That and the laws of physics.

          >AND THERE IS NO WAY IN HELL YOU ARE GOING TO HAVE THAT GOOD A FIT
          >WITHOUT THE ADJUSTMENTS BEING SET-UP THAT WAY!
          That’s wrong. See the explanation above.

          Your first link discusses the difficulty in measuring temperature accurately. It doesn’t support your claim of fraud. The second link is to another Steven Goddard post that makes the same claim you are making, again without evidence of fraud. Your third link is one of your own comments, which, again, does not prove fraud. Forget trying to prove fraud. None of you has shown any intent to commit fraud. Just concentrate on showing that some adjustment to some dataset is incorrect. None of you has proved that either. You certainly have not. Evidence of adjustment is not evidence of incorrectness. The adjustments are made to correct the data, so we expect the correlation you show to improve if the adjustment does indeed correct the data. You seem totally oblivious to this.

  5. rah says:

    All I know right now is that for the first time in the more than 22 hours since I’ve been up I chuckled thanks to Gator and Colorado. It was a tough run that never should have been put together the way it was for a single driver. That’s what happens sometimes where your the Guinea pig. I had only 6 minutes of legal drive time remaining out of the 11 hour limit when I pulled back into the terminal an hour ago and have been on the road working for 15 1/2 hours. Nighttime fog in the hills and turns of SE Indiana and some real A holes on the road along with some other problems made it worse. But you two guys and this Jack & Coke on the coaster beside me have gotten started me in the right direction to get my attitude readjusted and back on a even keel. Thanks guys!

    • You are welcome, rah. You did the heavy lifting. Glad you are back and in good spirits.

    • Martin Smith says:

      Good to see you back, rah. I hope my comments here weren’t what drove you to drink.

      • rah says:

        Commercial drivers must blow a .00. There is no .08 or even .05 slack for us as there is for regular motor vehicle operators. I had my Jack Danials & coke in hand before I sat down at the computer. Had just one before I went to bed after eating dinner and while drinking it spent my time here. My job limits my consumption of adult beverages. So normally I consume none between 06:00 Sunday morning and 06:00 Friday morning which is the period I’m on call. But when the opportunity and desire does coincide during my on call period I live by the 12 hours bottle to throttle is the rule which is the same policy commercial pilots use. Since there was no possibility of me being called to work in the next 14 hours or so I had a drink.

  6. Gail Combs says:

    “…DD, all you have done, again, is show that data have been adjusted. Nobody denies that data have been adjusted. All the datasets have been adjusted numerous times….”

    “…DD, the techniques used to “fabricate” this data, as you call it are based on good science….”
    >>>>>>>>

    Those two statement show that either Martin Smith has zero idea of how science actually works or he is a Propagandist trying to confuse people.

    First you DO NOT ‘ADJUST DATA’ It is a dam good reason for FIRING a scientist. Heck Gillette fired Sarah for writing in the number on the printout when the ink when dry instead of repeating the test! The FDA will ream a company who does not have their scientists carefully keep data in a bound notebook so there is no possibility of data tampering. A wrong number gets a single line through it, dated and initialed and a full explanation. (Computers caused a major headache for all involved)

    I mention this because it is the classic method for keeping data and would have been used for older temperature recording. (I have gone through the various aspects of the quality of the US data record earlier this year several times as has Steven, you can go look it up.)

    SECOND “…the techniques used to “fabricate” this data, as you call it are based on good science….”

    NO THEY ARE NOT! It is called Krigging and for the fence sitters I will give you a pointer. THINK! The temperature can not be estimated because the earth is not a featureless billiard ball with not weather or micro-climate. That is why Krigging does not work.

    THE KRIGGING GAME

    …In the real world, geostatistics cannot possibly provide unbiased estimates and 95% confidence limits for contents and grades because it violates fundamental requirements of classical statistics. Bre-X’s infamous fraud puts into perspective what the difference between classical statistics and the geostatistical practice of kriging is is all about.

    Classical statistics proved that the Busang gold resource was a salting scam several months before Bre-X’s kingpins were honored by their peers. In the meantime, kriging continued to convert bogus grades and barren rock into the largest phantom gold resource the world has never seen until Bre-X’s boss salter was nudged to jump into the Kalimantan jungle when the scam was exposed….

    To bad the Climate scammers who use the same bogus method can’t also be “nudged to jump into the Kalimantan jungle….”

    The problem is “…kriged estimates violate the requirement of functional independence in classical statistics…” You can go to the website to see all the nitty gritty about the statistics. Start with Test for spatial dependence

    Seems the Climate scammers are really having a heck of a lot of trouble with dependent variables!

    New Science 4: Error 1: Partial Derivatives. Index to rest of the series HERE

    • Martin Smith says:

      Gail, the Kriging (not Krigging) method is used because it has been shown to be skilful. You can’t invalidate it by posting quotes from blogs that agree with you. Infilling is explained here: http://www.skepticalscience.com/understanding-adjustments-to-temp-data.html

      Explanation of Kriging:
      https://en.wikipedia.org/wiki/Kriging

      • Gail Combs says:

        Again Martin you show your ignorance of statistics. Kriging doesn’t work (as Merck showed) because it violates the mathematical laws governing statistics. (Dependent vs independent variables among others) Merck goes into the the laws that are violated in a manner that can be under stood by most people so that is why I linked to him.

        On the other hand Kriging is very very useful in perpetrating scams on people like you. It certainly has been very very successful so far.

        So, You want to buy a gold mine?

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