The New RSS TLT Data is Unbelievable! (Or Would That Be Better Said, Not Believable?) A quick Introduction

In advance of my September 2018 global surface and lower troposphere temperature anomaly update, this is a very quick introduction to the new (over a year old) lower troposphere temperature anomaly data from RSS (Remote Sensing Systems)…just three graphs.

As you likely know, I haven’t published a monthly global temperature update in almost 2 years. Since then, in July 2017, RSS released their version 4.0 lower troposphere temperature (TLT) anomaly data. See the RSS webpage FAQ about the V4.0 TLT Update for more insights.

While preparing this month’s global temperature update, I downloaded the new global RSS TLT version 4.0 data for the first time and compared it to the UAH TLT data and to the three surface temperature datasets from NASA GISS, NOAA NCEI and the UKMO Hadley Centre—with all datasets starting in January 1979 and all referenced to the base years of 1981-2010. The new RSS TLT data shocked me, to say the least. (Expletives deleted.) See Figure 1.

Figure 1

Note that, from January 1979 to October 2018, the new RSS TLT warming rate is even higher than all three surface temperature datasets. Un-flip-flopping-believable!

That prompted me to compare the global (70S-85N) RSS TLT data version 3.3 data (still available here) to the new version 4.0 data (available here). See Figure 2. As illustrated, the new data has a noticeably higher warming rate. I actually said, “Wow!” aloud when EXCEL produced the graph.

Figure 2

And for anyone interested, Figure 3 presents the difference between the two RSS TLT datasets with the version 3.3 data subtracted from the version 4.0 data.

Figure 3


Dr. Roy Spencer, co-author of the lower troposphere temperature anomaly dataset from UAH, published a couple of posts about the new RSS TLT data.


I have a funny feeling this post will generate a couple of comments…hmmmm probably lots of comments at WUWT. Have fun!!!

That’s it for now. I’ll publish the full monthly update very soon. It’s almost ready. I just have to rewrite the text for the RSS data. Oy! I’ll try to remain civil.


Please purchase my recently published ebooks. As many of you know, this year I published 2 ebooks that are available through Amazon in Kindle format:


Be back soon.



139 thoughts on “The New RSS TLT Data is Unbelievable! (Or Would That Be Better Said, Not Believable?) A quick Introduction

  1. They are moving the goalposts once again. The results must fit. Credibility below zero? Who cares. It’s data, man!

    • It is worse than we thought. But will we be able to have bad enough thoughts, to keep pace with the ever-increasing litany of gloombal (gloomy-global) predictions?

    • History anyone ???
      I bet a million $ that we have been through the present climate dozens of times in the last ?,000 years, or perhaps NY under ????meters of ice, or GREENLAND ?

    • Why are we being asked to spend trillions of taxpayer dollars on controlling the weather when we need only ask the keepers of our temperature records to adjust them to whatever temperatures they feel are optimal. That shouldn’t cost more than a few beers and pizza and will have far less impact on the environment as it won’t require shredding natural habitats to erect ridiculous windmills and solar arrays that produce electricity on occasion at great expense but not necessarily when needed.

      • You are quite right Andy. When the time comes that the warmists are in complete control of our lives, they will simply adjust the temperatures back down again and give the new political system complete credit for the turn-around.

    • “When the Facts Change, I Change My Mind. What Do You Do, Sir?”
      – attributed to John Maynard Keynes

      “When UAH changes, I pay attention. When RSS changes, I ignore it.”
      – Allan MacRae

      Because UAH is assembled by Roy Spencer and John Christy and I know and respect them.
      RSS? Not so much…



        Because climate models are known to not represent the diurnal cycle to the accuracy needed for satellite adjustments, we decided long ago to measure the drift empirically, by comparing drifting satellites with concurrently operating non-drifting (or nearly non-drifting) satellites. Our Version 6 paper discusses the details.

        RSS instead decided to use climate model estimates of the diurnal cycle, and in RSS Version 4 are now making empirical corrections to those model-based diurnal cycles. (Generally speaking, we think it is useful for different groups to use different methods.)

        [end of excerpt]

        WTF? RSS-holes!

  2. Figure 3 says it all, really. When your data is so wildly different from one version to the next, the only question to ask is, “Were they publishing unreliable, inaccurate data in the past? Or are they doing that now?”

    The question, “Can we rely on their data, given the size of the revisions?”, simply answers itself.

    The differences are far past the levels of mere “refinements”.

    • Dr. Spencer’s comments are illuminating.

      So 0.134 becomes 0.197 thus 32% of the (new, improved) effect is due to the latest correction.

      The only thing that can be said with certainty is that if an effect is of the order of the corrections (no matter legitimacy), then we really don’t have a very trust-worthy effect.

      We certainly should not be “fundamentally changing the global economy” because of it.

    • Exactly. The sceptics’ case is that the data is unreliable. how this sort of adjustment disproves that case is beyond me. The only “argument” the Alarmists can make is that further adjustments would also make it “worse”, but that is obviously a fallacy.

      If it can be revised this much, it can be revised this much. So it’s really not very reliable.

  3. They have mangled the data as much as they can, and they have bought the critical line closer, going from 2 C to 1.5 C .

    The lines were too far apart, CO2 just wasnt playing ball, they were never going to meet. They had to do something.

    Yet what they have done is make fools of themselves.

  4. He he – the range of values introduced by the RSS “revisions” is comparable to the magnitude of the claimed warming rate. Unless you choose to believe the latest revision is perfect and all the previous revisions should be discarded, you have to consider the possibility there will be future revisions of similar magnitude to the latest revision, which means the rate of warming produced by the latest revision is completely unreliable.

  5. ” Un-flip-flopping-believable!”
    A classic argument from incredulity. Or confirmation bias. It’s wrong because we just know it is wrong.

    In fact, yes, RSS rose by about 0.063 °C/decade. In going from V 5.6 to v 6.0, the trend of UAH global TLT went from 0.16°C/dec to 0.13°C/decade. No incredulity there.

    RSS has a FAQ on the changes here. As they point out, RSS V4.0 is much more in line with radiosonde measures.

    Both satellite measures are extremely unstable in updates compared with land temperatures. I showed here that changes to UAH and RSS where close to mirroring each other, but, on the same 1981-2010 baseline, far greater than any changes that had been made to GISS since 2995. The plot is here.

    • “It’s wrong because we just know it is wrong”. Yes, Mr. Stokes – we’ve heard that from you a few times…….

    • Nick, let me explain the “Un-flip-flopping-believable!”.

      For decades, it was accepted that the lower troposphere was warming at a rate that was lower than the near surface. With the new RSS TLT 4.0 data, that relationship has changed…flip-flopped.


      • Bob,
        You’ve explained the flipflopping. But you haven’t explained why it is unbelievable. “It was accepted…” sounds like an argument from concensus. But it’s not clear who shared that concensus.

        • So you are happy to believe that decades of climate science is wrong now Nick?

          Or are you just being a sophist as usual?

        • Nick,,, the adjustments are done constantly over time….RSS is used to program the models….the models will never be right
          The numbers they feed into the models today, will change tomorrow

          The news was alive with “warming faster than we thought” when these up adjustments came out

          • This sounds like the infinitely positive feedback cycle they are looking for, a self fulfilling calculation!

          • It’s an infinity circle of clusterf..ks

            The models can only reproduce the slope….so they adjust the past down to try and match that projected slope…but by doing that, they get an even faster slope…and have to adjust the present up to match that……wash rinse repeat

          • So when they compare the models….they use all the temp reconstructions but RSS??
            …and at the same time say there were no thermometers at sea

        • What’s “flipflopping” … unbelievable to me is that we are talking thousanDTHS of a degree, as if this number of decimal places is even valid here.

          HOW is this number of decimal places valid? I am open to a reasonable explanation.

          0.197 C – 0.134 C = 0.063 C

          Can we REALLY justify any concern for any difference at all ?

          Creeping up the warming by a meaningless amount is still meaningless.

        • “Unbelievable” is a nearly 50% increase in trend with the revised data. Really? That’s reasonable to you? You’re going to pretend that’s comparable to a change from 0.16 to 0.13?

          • It used to be that the future was a surprise but now the past is a surprise and the future certain!

      • Bob: Respectfully, for decades it has been accepted that rising temperature in convective regions would be accompanied by rising absolute humidity, a lower lapse rate and therefore more warming in the upper troposphere than at the surface. Those expectations were challenged first by observations from radiosondes (at least until that data was “homogenized”) and then by data from satellites. Now, two different publishable sets of corrections for previously poorly-understood satellite drift indicate that it is POSSIBLE that there has been at least as much warming in the upper troposphere as near the surface.

        Until recently, the failure to observe more warming in the upper troposphere than near the surface has cast doubt on AOGCMs in general and the cause of at least some warming, but the failure to observe negative lapse rate feedback also suggested that climate sensitivity might be higher than models predict. FWIW, I’ve always be skeptical that we could measure warming in the upper troposphere via radiosondes more accurately than near the surface. The size of the possible corrections now associated with satellite drift has reduced my confidence in this record of warming. I don’t feel it is appropriate to characterize this as flip-floppying. We have always been dealing with very small differences in warming rate (say 0.05-0.10 K/decade measured over decades with changing equipment and satellites.

    • And you believe it because it fits your views. Oh, but of course not, you are entirely unbiased and entirely open to being persuaded everything you have said over the last decade is wrong. Because you are not actually human?

      All this shows is all that sceptics claim – that we should be extremely sceptical about the data.

      You try and spin it that we are claiming it’s not happening, but that’s not what we are saying. A hefty revision now means there can be one in the opposite direction next week, or next year.

          • “Dubious”, “extremely dubious”, … of satellite/global temperatures ?

            Well, I’ve gone even further downhill than that during the past year — I flat-out reject the very concept of “global temperature”.

            Hence, (and I mean no disrespect to the statistical masters here), I think a lot of good talent is being wasted on these sorts of data-handling exercises.

            Does anybody here ever lower themselves to watch the TV competition show, World of Dance ? I see a similar phenomenon there — a lot of good talent is wasted on sucky choreography.

          • I still have to agree with a statement I heard many years ago.

            An average global temperature is about as useful as an average global phone number

          • Robert Kernodle – Now that was a post I can appreciate. I like, and agree, with what you say – though I don’t know the TV show you refer to since TV is something I gave up years ago as truly being “the vast wasteland.” The parallel, however, is not lost on me.

        • We’ve already proven that ground based measurements are unusable.
          And now you want to toss out satellite measurements as well.

          Might as well shut down the whole IPCC establishment because we agree that we don’t have a clue what the temperature of the earth is, not now, and even less so in the past.

          • “…What exactly is wrong with RSS?…”

            Oh nothing. Temperature trends are corrected about 50% all of the time. A change of 0.063 deg C/decade is 0.63 deg C per century. I’d say being that far off is quite “wrong.”

          • Alan Tomaltey – “What exactly is wrong with the UAH dataset Nick?”
            Nick Stokes – “What exactly is wrong with RSS?”
            This is the whole point. We are talking about hundredths of a degree. There are two datasets mostly coming from the same instruments (from what I remember, there is a disagreement between RSS and UAH on the use of a sensor the could possibly be malfunctioning (or not)).
            No one can say for sure which is correct. In fact, we can say that they are probably both correct +-1 to 2 degrees C.
            So, given that we have a +-1 to 2 deg. error temperature reading, we are supposed to take a gradual change in the average temperature over time, and create some computer simulations that model this history. In the simulations, we greatly simplify them to a linear-based model (vs. sinusoidal or other type) and pick one parameter as the major driver to changes in temperature. We know that the simulations in no way have been correct in their modeling of the general temperature changes and have also been incorrect in almost every other facet of the climate that they are purported to model.
            Then, based on these incorrect models based on tiny temperature trends with large errors, we are supposed to bring civilization to its knees, send much of the world back into poverty, and possibly cause the deaths of millions from lack of heat and food and the resulting turmoil.

            It doesn’t sound like a good bet to me.

          • “So, given that we have a +-1 to 2 deg. error temperature reading, we are supposed to take a gradual change… “
            I don’t agree with your calculations. But as to the whole point, I don’t recommend relying on the AMSU temperatures. I don’t even think surface temperatures are the whole basis for recommending action about CO2 emission. The physics, going back to Arrhenius, says that emission will cause warming. You can decide whether or not you think that is bad, but it is the starting point. Imperfect observation may delay confirmation, but doesn’t challenge the physics.

          • What a pathetic comment. LOL

            Given the chaotic nature of our atmosphere and climate, it is impossible to assign all change to one minor trace gas. Thanks for jumping the shark on this thread Nick, we now know what is definitely not the answer, and can conclude this discussion.

            Simple physics! Right Nick? LOL

          • @Nick Stokes

            “The physics, going back to Arrhenius, says that emission will cause warming. You can decide whether or not you think that is bad, but it is the starting point. Imperfect observation may delay confirmation, but doesn’t challenge the physics.”

            You seem to have conveniently forgotten the most important part of what “the physics” say. Allow me to remind you. ALL OTHER THINGS HELD EQUAL, doubling the atmospheric concentration of CO2 would increase the temperature by about 1 degree Celsius, on average.

            Back here in the REAL world, “all other things” are most certainly NOT “held equal,” and the “feedbacks” are NEGATIVE, not positive as they are in your fantasy world. This is why the paleoclimate record shows that CO2 has absolutely NO effect on temperature.

            The “physics” you’re talking about are purely hypothetical. The real world doesn’t accumulate heat because of elevated CO2, you’re guilty of the same thing the so-called “main stream” climate science is. Taking a kernel of hypothetical physics and extrapolating it into an alleged “catastrophe.”

        • Nick Stokes October 16, 2018 at 4:31 am
          “And you believe it because it fits your views.”
          No, I’m dubious about all satellite temperatures.”
          As explained with crystal clear logic by one NS
          “”Nick Stokes October 16, 2018 at 2:56 am
          A classic argument from incredulity. Or confirmation bias. It’s wrong because we just know it is wrong.”

          Nick Stokes October 16, 2018 at 4:31 am
          “And you believe it because it fits your views.”
          No, I’m dubious about all satellite temperatures.

        • Nick Stokes October 16, 2018 at 4:31 am
          “And you believe it because it fits your views.”
          No, I’m dubious about all satellite temperatures.
          A classic argument from incredulity. Or confirmation bias. It’s wrong because we just know it is wrong.

        • Oh good grief, Nick. You are dubious about all satellite temperatures? What about the surface temperatures? Dubious about those as well, or only the ones you don’t like?

          Or is it that you change your opinion on the credibility of something at the drop of a hat when you need to argue in a certain direction.

          • “Dubious about those as well, or only the ones you don’t like?”
            Well, one difference is that surface measures are more stable and in agreement with each other. But another reassuring thing is that I can and do calculate the surface average for myself, from the raw data (TempLS). And that is in agreement too.

          • roflmao.. Come off it Nick .. that is so funny 🙂

            Only because they use the same corrupted procedures and get the same mish-mash of once-was-data from NCDC

            Surface data compilations/fabrications are not fit for embossing toilet paper. !!

    • Who knows what the temperatures are. It’s all guess work.
      IF… as in IF AGW was right about the warming, they’d never need to revise anything. In fact, they wouldn’t consider revising the data set if it was meeting the goals. That’s confirmation bias. AGW isn’t doing that in the interest of science, they are doing that in the interest of a political agenda.
      It is difficult to separate the 2 issues: 1) is warming 2) the cause. Since the 1970’s chill is something I remember quite well, the slight warming we’ve enjoyed is much better. So I don’t disagree with it being somewhat warmer.
      I do disagree with the cause and that is where AGW is doing an enormous amount of damage. The real cause of climate change is still lurking out there. And since the time and money is being focused on this pseudo cause, it is even a greater waste. CO2 is not causing the climate to be warmer. The co2 ppm/v per year data and temperature anomaly per year supports that conclusion. It has been ignored but not refuted. And that’s using the numbers of ‘who knows what they are’. It’s not a contradiction, it’s what I have to work with. AGW is not a convincing argument. If you can’t prove the math and science to me, you can’t prove it to anyone. That is unless they are sold on the unstated or stated political agenda.

      A sudden drop in temperature back to 1970’s level or lower will result in untold hardships. It’ll take vast areas of food producing areas off line. It will increase the amount of fuel necessary to stay warm. It will cause delays and shortages of everything.

    • RSS wrote a report in 2011 that showed their data was equal to or warmer than radiosonde measurements. So, how do they warm their data and become more accurate? Does not pass the smell test.

      I suspect they are now comparing to the infilled radiosonde fantasies instead of individual measurements. IOW, more made up nonsense.

    • Nick, in your link to the RSS FAQ, the RSS V3.3 Trend is 1.34K/decade, in line with Tisdale’s graph. However, on that same FAQ page the RSS V4.0 Trend is 1.74K/decade, while Tisdale’s RSS V4.0 Trend says 1.94K/decade.

      I’m just pointing that out, not accusing anyone of anything.


      • Don,
        “However, on that same FAQ page the RSS V4.0 Trend is 1.74K/decade”
        That is actually one of their Q’s in the RSS FAQ, about a page down, headed:
        “When I go to the time series browser, I see different trends than are in the paper and in Fig. 1 above. Why are they different?”
        A part of the reason is that V4.0 takes the area covered to 82.5°N, while they went to 80° for consistent comparison. So for the same area, the trend difference is about 0.04°C/decade, not 0.063°C.

    • Hi Nick,

      I want to thank you for being a pain in the butt and bringing in ideas and comments that challenge the WUWT audience. Still I am part of the WUWT audience and here is my take.

      Why are all changes to homogenization processes resulting in new versions that support the consensus?

      When you work with data your homogenization process should be updated as you learn new information, but when your results always conform to the theory you have to wonder if bias is part of the decision making process.

      • Reasonable Skeptic said:

        “When you work with data your homogenization process should be updated as you learn new information, but when your results always conform to the theory you have to wonder if bias is part of the decision making process.”

        What I can tell you is that answer won’t be found in speculation about peoples motives and biases.

        It will be found by examining and testing the methods used to see if they are sound.

    • Nick, you know very well why the datasets diverge. The question informed readers and contributers should be asking is if drift has been identified and dealt with correctly. Spencer and Christy have both commented on Mears continued use and equal weighting of a wildly divergent variable. Why are we defending RSS? Your statistical gripes with the uninformed have no bearing on the topic at large.

    • Well Nick, then you, they at RSS, will have to explain why version 3 temperatures were higher than version 4 during the 80’s, in the 90’s version the Version 3 and 4 are roughly in line but then after the year 2000, the more the time goes the higher is version 4 compare to version 3.

      Nothing better to increase the rate of variation of the version 4 of course…

  6. More cooling the past and warming the future! These scientists must be working real had to constantly adjust.

  7. I remember Nick once saying that the adjustments made to the temperature data lowered as many points as it raised. What he didn’t say can be seen in the graphs, such as the ones above. The data points that were lowered are mostly in the early part of the record. The ones that were increased are mostly in the more recent time period. So even if all the adjustments averaged out to zero, it still has a huge affect on the slope of the trend line by lowering past temperatures and raising recent ones. Either the current temperature data is wrong, or the future data will be wrong when they adjust the past again. Of what use is the current data when you know it is all going to change in the future?

  8. Isn’t RSS using ‘model’ input as part of their ‘adjustments’? I seem to remember them starting to do that. If so, this is a natural consequence of that decision.

    • I don’t use, can’t use such alleged “data” because of the holes, the gaps, the incomplete explanations of what they are doing to get the incredible, fantastic “data” they report from the actual measurements made. Even the best of them leave out a crucial “magic begins here”… “magic ends” portion of their process. Just bits and pieces.

      Now, it may be understandable. When one is immersed in a specialization, it is very easy, when trying to explain something to an outsider or noob, to leap over “what everyone knows”. It is easy to fall into the trap of saying “do this” when there is implicit in “this” a sequence of actions that “just go without saying” that the outsider has never heard of, never seen, has no reason to realize is required.

      It is common to find such holes in journal articles of some fields (math & computer science seem to be the worst; medical journals seem pretty good), and, sometimes, it is because an editor cut out crucial steps or other details to “save space”.

      There may even be explanations of most of these steps, and the reasons for them…scattered over 6 books, 8 manuals, 40 articles, 100 e-mail messages, 2,000 discussion list/web-log postings… somewhere the vast majority of people will never be able to find the scraps and be able to piece them together.

      You may say it is “amazing”, but to me it is all “Fantasy & Science Fiction”.

  9. “The New RSS TLT Data is Unbelievable! (Or Would That Be Better Said, Not Believable?)”

    Unprecedented, anyone?

  10. From my little flock of Wundergrounds, pretty well covering the area of the CET and going back 15 years from present(30 Sept 2018) – in degrees centigrade and x is monthly

    Cumbria……..y=-0.0009x+9.2717 (west)
    Manchester.. y=-0.0073x+11.311 (west)
    Lancashire…. y=-0.0097x+11.339 (west)
    Bedford…….. y=+0.0004x+10.641 (east)
    Somerset…… y=-0.0033x+12.077 (west)
    Suffolk……… y=+0.0006x+10.559 (east)
    Derby……….. y=-0.0027x+10.45 (central east)

    What I take away from them is that the west-facing ones are going negative, giving a lie to the notion of heat being stored in the ocean. It may get stored in some other ocean but surely the North Atlantic Gulf Stream would dredge it up and dump it on Western UK.
    The ones rising are where epic land drainage operations have been carried out (Fens) and hence/also where the industrial scale farming is going on.

    Related and from Beer Goggles: “3 tonnes per hectare for barley yield”
    You Really *Have* Got To Be Joking
    (optionally out-of-your-mind, drunk or desperate beyond belief)

    I quit growing spring-barley in Cumbria at less than 5 tonnes per hectare – the weather-related stress and low yield meant it wasn’t worthwhile – *even* accounting for the straw which, in the livestock area I was in, had a value not dissimilar to that of gold-dust.
    And this was in a place where 50 years ago, spring planted wheat was viable?

    Take heed of what Stefan Boltzmann said – “Higher temperature differences mean greater energy flow”
    And what I add to that- “Gobsmackingly so when the flow goes as the 4th power of the temperature”
    When warmists suggest we are going to A Hot Place, implying =Hell, in a way they are correct except that: Hell is a Cold Place.

    • Having done military service stationed at approx. 70 degrees north in winter, I completely agree with Peta.

      • Also a reason they don’t stage the game show “Survivor” in Canada during the winter. Probably couldn’t get away with spring or autumn, either.

  11. Can we see a scatter plot of adjustment with respect to CO2 level? But regardless, this entire exercise is wrong anyway, since somehow “significant digits” has become fluid. If the anomaly is calculated with the correct significant digits, the anomaly can be only an integer value. We already know a liquid-in-glass thermometer can’t be read accurately any closer than the nearest digit. That makes the anomaly not calculable any closer than the nearest digit. It’s all a figment of their fevered imaginations.

  12. Historical climate data changes/is re-written over time. This is not anything new. It is also not news worthy at least in the so-called main stream news media. Here’s a comparison GISSTEMP’s Land Ocean Temperature (LOTI) from 1997 to 2018

    The linear trend for the LOTI time series for the period 1950-1997 increased from 0.75°C/century to 1.00°C per Century by 2018

    Here are the source URLs for that:

    • It may be that there was significant change in the data base from 1997 and 2018. I know that in the early years of the GISS data base there was much less land coverage, mainly Europe and the US, which had a very warm 1930s. As more data from the SH was gathered, which did not have a very hot 1930s, that changed the global profile.

      So what I want to know is: when people see a difference, do they start to investigate why? Or does cynicism prevent such diligence?

    • You beat me to it…I loved the continual corrections that the Boston Globe had to update because they couldn’t find anyone in the newsroom who had 8th Grade math.

    • The central value for Warren’s Amerindian markers was eight generations ago, ie 1/256, ie 0.39%. My Neanderthal share is about ten times that level. And I have the brow ridges to prove it!

      Where are my reparations from the evil anatomically modern humans who displaced my people with violence aforethought from Europe and western Asia? Where are the affirmative action programs giving preference to the persecuted minority of Neanderthals and Denisovans, so ruthlessly exploited by AMH imperialist, racist, heteronormative swine?

  13. the beauty in all of this is that every year their lie has to get bigger and more divorced from the reality people are experiencing. eventually they will have to target old people who can remember the hot summers of their youth.

  14. I certainly think I can reinforce what Bob has presented here.

    Prior to the last prominent El Nino readers of this site were treated to a monthly picture that looked like this.

    I have been analyzing the RSS data for some time now. Back in 2017 I downloaded the RSS data and associated with the date I downloaded the data.

    The data you see in my analysis below came from 06/03/2017. There are other interesting facets in the chart but let’s focus on the overall slope of the data and the pause line. Yes, I do analyze the data to determine what date results in the lowest slope pause line.

    Toward the end of the month I went back to see if additional data were added. Instead I found that the data had changed, altered if you will.

    Make note that the slope of the new pause line now approximates the overall slope in the previous chart. That is why the pause is dead. Note also the increases in slopes for this newer data.

    The data were altered by people with an agenda. They knew the answer they needed, and they got it from the back of the book.

    The next figure lays these two datasets on top of each other. You don’t see differences until you get past or near the 97 El Nino, the pivot point. Note also that the differences widen as time goes on. The data were rotated which is reflected in the near tripling of the slope of the pause line.

    I think the next chart makes it even clearer. At one time the RSS and UAH were approximately parallel. No longer.

  15. I’d give my right arm if one publishes the raw (not homogenized, corrected, adjusted, calibrated etc) satellite data as recorded by the instruments on board. Give us also the formula that you use to scale these into temperature. Let us double check what you are doing is correct.

    Do we need a FOI get these from them?

  16. Roy Spenser said

    “I suspect the next chapter in this saga is that the remaining radiosonde datasets that still do not show substantial warming will be the next to be “adjusted” upward.”

    The above statement just confirms what all of us skeptics believe. The UAH dataset is the only one that both sides trust. Imagine ; our society has got to the point where skeptic climate scientists are resigned to the fact that alarmist climate scientists fudge the data.

  17. The science is settled. If they didn’t keep changing the data there would be nothing else to do.

  18. The RSS team are decent scientists and have done a good work with version 4. The major change, an improved diurnal drift correction of AMSU-satellites, has been validated against the experimental reference series REF_SAT and MIN_DRIFT, which only use satellites with little or no drift.
    UAH v5.6 had a similar approach, using non-drifting AMSU satellites mainly, and it also corroborates RSSv4.
    As a comparison, UAH v6 is flawed in the AMSU-era, it has not been properly validated, and has a much lower trend than the old v5.6 non-drifting “reference” data .

    Here is a comparison of UAH and RSS with state of the art (third generation) reanalysis data (TLT-weighted)

    RSSv4 has almost the same trend as the reanalysis average, whereas UAHv6 lose around 0.06 C per decade.
    UAH is particularly poor in the AMSU-era (starting in late 1998).

    The graph also show the effect of UAH’s cherrypick of satellites.
    The last MSU satellite NOAA-14, and the first AMSU-satellite disagree largely in the overlap 1999-2005. The UAH-team believes (without supporting evidence) that NOAA-15 is right and NOAA-14 is wrong, so they discard NOAA-14 data between 2001 and 2005, and arbitrarily adjust down earlier NOAA-14 data.
    RSS on the other hand, acts in a scientifically correct way. They can’t find any error in either of the satellites, so the keep both and split the error. RSS wants their satellite product to be independent of other data, so they don’t use radiosonde, reanalyses, etc to choose the right satellite.
    The above chart shows whether the choice of UAH and the non-choice of RSS makes sense in weather models (reanalyses are weather models that ingest all kinds of weather data and reconstruct
    the likely state of the atmosphere)

    UAH drops like a rock between 1999 and 2005
    RSS drops a little less here
    Hence, NOAA-14 seems to be right and NOAA-15 wrong
    UAH made the wrong pick of satellite, resulting in a too low AMSU-era trend
    RSS is only half wrong since they didn’t choose and split the error.

    • I think you partially answered my question below. RSS acts unscientifically by averaging 2 satellites (the average of wrong data is wrong), and not using other sources to insure their data is correct. It is UAH that uses the radiosonde data to insure their numbers are correct. I incorrectly thought it was RSS.

      • Jeff:
        “RSS acts unscientifically by averaging 2 satellites (the average of wrong data is wrong), and not using other sources to insure their data is correct. It is UAH that uses the radiosonde data to insure their numbers are correct. I incorrectly thought it was RSS.”

        Except that UAH V6 does not agree with radiosonde data in the AMSU era aboard NOAA15 as well as does RSS v4 …..
        So how can that be?

        (h/t to Olof for graphs)

        UAH is the cold outlier – here is a comparison of trends for various tropospheric temp series.
        If UAH validate against radiosonde (as you say) then why is it so far away from RATPAC?
        Much further than anything else…..

        • Because RatPac converges from other radiosonde data.

          Its a “selected and adjusted” compilation.

          And like all fabrications that are agenda driven, it shows more warming.

          • “Its a “selected and adjusted” compilation.”

            The classic naysayers “and with one bound” response.

            If you say so fred.

          • AB, so tell everyone how the average of radiosondes shows very little warming just like UAH6 and agrees better to RSS3.3 while RATPAC (which is supposedly based on those very same measurements) shows much more warming.

            I’ve been waiting ever since RATPAC came out for someone to explain is little inconvenient truth.

      • Jeff in Calgary,
        UAH does NOT use “the radiosonde data to insure their numbers are correct”.
        Their v6 AMSU data and significant “choices” have not been validated (and can’t be validated by any kind of relevant independent data). If I’m wrong, please show me the evidence.
        What UAH did was a brief check of the overall trend (1979-2015) versus Ratpac B and Raobcore. Not surprisingly (from a cherry-picking perspective) these happens to be the two radiosonde datasets with the lowest trends, and not suitable for the purpose. Ratpac B is unadjusted after 1996 and has inhomogeneities. Raobcore is too circular since it is adjusted by reanalysis which are partly based on satellite data.

        Anyway, with a proper difference chart it would be quite easy to see that UAH’s AMSU data and choices are not supported by Ratpac B: (a comparison to Raobcore would be similar)

        The picture is even worse compared to Ratpac A:

        If anyone believes that something is wrong with just Ratpac, here’s a comparison with the average of four independent radiosonde datasets:

        These charts were made after 2016, and to be honest, UAH has improved slightly since then. They introduced a new non-drifting satellite, Metop-B with data beginning in 2013, and all of a sudden the trend increased. This was simply because their lousy diurnal drift correction became diluted with good data.
        UAH has also, for unclear reasons, avoided the non-drifting satellite Metop-A. This gold standard reference satellite (not needing drift adjustments) formed the backbone of UAH v5.6 AMSU data, and of course also the RSS datasets.

    • “…The RSS team are decent scientists and have done a good work with version 4…”

      So these “decent scientists” must have done a piss poor job with versions 3.3 and earlier to be so far off.

      • “So these “decent scientists” must have done a piss poor job with versions 3.3 and earlier to be so far off.”
        You could say exactly the same of UAH and V5.6. But in fact, they are both just dealing with a very difficult measurement problem. The proper response is to be sceptical of measures that can vary so much, even with best efforts.

        • I trust land based temps .

          Just wondering Nick if your bank used the same method with your bank account would you be happy ?

      • “So these “decent scientists” must have done a piss poor job with versions 3.3 and earlier to be so far off.”

        I seem to remember Roy Spencer saying much the same thing at the time.

        • Here’s the quote I had in mind. Dr Roy Spencer on the spurious cooling in RSS 3.3.

          Anyway, my UAH cohort and boss John Christy, who does the detailed matching between satellites, is pretty convinced that the RSS data is undergoing spurious cooling because RSS is still using the old NOAA-15 satellite which has a decaying orbit, to which they are then applying a diurnal cycle drift correction based upon a climate model, which does not quite match reality. We have not used NOAA-15 for trend information in years…we use the NASA Aqua AMSU, since that satellite carries extra fuel to maintain a precise orbit.

    • that’s the problem with climate science olof ,people don’t seem to understand if something isn’t quite right,it is wrong. it would appear you don’t agree with that.

  19. It is my understanding that RSS used balloon measurements to calibrate their sensors. So if this is the case, it is hard for me to believe that this big of a change would ever be needed. Is the new data better calibrated to the balloon measurements? I need answers.

    • Jeff:
      “At RSS, we do not use radiosonde data to guide our choices when constructing long-term satellite datasets. This is done in order to try and keep the two types of data independent of each other. That being said, these results do suggest that our changes to the AMSU data are supported by the radiosondes (RSS V3.3 also shows a large cooling signal relative to the radiosondes over the 1998-2007 period). Note that all satellite data warm relative to radiosondes before about 2000, and then cool after about 2000. We don’t know if this overall pattern is due to problems with the radiosonde data, with the satellite data or (most likely) both.”

      This Roy Spencer’s take and his response to Olof R….

      Olof R says:
      March 5, 2016 at 4:10 AM
      The difference between Ratpac A and B Global is that B is weighted by latitude only, whereas A is weighted by both latitude and longitude.
      Thus, in A the oceans get a more fair representation. A has a slightly higher trend than B during the alleged pause years, because the troposphere over oceans (maybe a little contraintuitive) has warmed faster than over land during this period..

      Roy W. Spencer, Ph. D. says:
      March 5, 2016 at 5:55 AM
      I’ve asked John Christy about the discrepancy…he’s the one who did the raob comparisons.

      Roy W. Spencer says:
      March 5, 2016 at 11:34 AM
      OK, according to John Christy, it’s because you are using the 850-300mb layer to estimate MT, which is a little apples and oranges. You need to do appropriate weighting of all pressure levels up into the lower stratosphere for MT. If you use only 850-300, you won’t sample the statospheric cooling that MT includes, the warming trend will increase, and so you will get better agreement with RSS because it has a warmer trend.

      Olof R says:
      March 4, 2016 at 11:21 AM
      Sorry, I posted this comment in the wrong place. I’ll better move i here were it was intended:

      Well, this discussion is about the trend during the alleged pause years or AMSU years, ie from 1997-2000 til now.
      The trends of UAH v6 TLT and RSS v3 TLT cant exactly be validated/verified by satellites or radiosondes:
      All other reanalysis and radiosonde datasets agree with those above. The new RSS TTT v4 have a trend roughly the same as UAH 5.6.

      Why should AMSU-5 on NOAA-15 be OK? Is it normal that the trend is 0.15 C/ decade lower than that of AMSU-4 (Mo 2009)?
      Is it normal that AMSU-5 on NOAA-15 drifts versus the other AMSU-5s and makes the joint Channel 5 trend much lower than that of a weighted average of nearby Channel 4 and 6?

      (free poster, there is a paywalled paper with the same title)

      Roy W. Spencer, Ph. D. says:
      March 4, 2016 at 11:46 AM
      we have examined the NOAA-15 trends (unadjusted) as a function of height…channels 3,4,5,6,7,8,9….and ch. 4 is an outlier. Ch. 5 does not significantly depart from the vertical profile of trends produced by the other channels. The AMSU channel 4 has a history of problems on most of the AMSUs for some reason, including channel failures.

      Olof R says:
      March 4, 2016 at 12:43 PM
      Yes, but in the AMSU-only dataset by NOAA STAR, state of the art intercalibrated and adjusted, AMSU 5 is the obvious outlier in trend vs the other channels.

      AMSU 4, a TLT in itself, has a slightly lower trend than UAH 5.6 TLT over the 1998-2011 period, which is in the lower end of those trends suggested by radiosondes and reanalyses.
      Even lower and true outliers are those datasets that make full use of AMSU-5 onboard NOAA-15. UAH 5.6 TLT is relatively immune against this spurious cooling contamination, since it relies relatively more on other satellites than NOAA-15, IMO…

      In the NOAA STAR poster, it is quite obvious that there is a drift in NOAA-15 AMSU 5 versus the other AMSU-satellites, also after intercalibration, etc..

  20. Data fiddling, sorry, data recalibration, to get at the desired result is the hallmark of a pseudo science. The data fiddlers are also known as quacks.

    • Yes, data fiddling is the right word. There is a lot of “divine interference” , unsupported by evidence, in the UAH v6 AMSU data. UAH v5.6 was much better, using nondrifing AMSU satellites only, that didn’ t need adjustment.

  21. Ah shucks…..going to get harder to make those numbers look better with the cold wave that’s coming

  22. Figure 3 patently displays an all-too-familiar pattern of trend exaggeration via a whole panoply of dubiously rationalized data adjustments. We’ve already seen similar increases of trend by GISS, HADCRUT and BEST in the successive versions of their respective GAST series. And then they have the temerity of pretending that such blatant trend manipulations produce scientifically improved data accuracy.

  23. Direct (or indirect) cause of natural variability of the global temperature may not be currently well understood, thus a high correlation to the other natural variables should not be dismissed as irrelevant.
    The old graph updated with the most recent data is here

  24. I’m continually amazed by the amount of analysis, reanalysis, weighting, re-weighting, etc. that temperature data is subjected to.

    “.. state of the art (third generation) reanalysis data (TLT-weighted)”

    The “art” part seems more obvious, where temperature data is concerned.

    I honestly don’t know the answer to the question that I am about to ask, and so someone fill in my ignorance:

    “In what other field of science is data so artfully improved?”

  25. Hi Bob T,

    Just a tip to enhance readability of your figure 1 especially.

    In Excel go to menu ‘Format’, click ‘Shape outline’ then ‘Weight’ then select most suitable line thickness.

    Cheers, Bob Fernley-Jones

  26. I did up this pair of graphs last night for a blog argument.

    The top graph is snow cover extent anomaly data from Rutgers Snow Lab. The bottom graph is UAH NH LT land temperature anomaly from the data Roy Spencer puts up on his blog each month. So they are an apples to apples comparison, albeit lower troposphere for the temperature. I inverted the UAH y axis so that it would be easier to match peaks in the two graphs. They do match well: as you might expect low temperature equates to more snow cover.

    I’ve included linear trends from mid 1994.

    What these graphs show is that even UAH v6.0 is running too hot. The snow cover extent anomaly is a measure of the geographical area at or below 0 C. If the trend is flat it means the area isn’t changing, and therefore real world temperature isn’t rising. Since UAH and RSS are both rising it suggests the corrections being made for orbital decay and whatnot are introducing a warming bias.

    But it’s pretty clear that snow is saying that not much is happening. You can’t fool snow, it’s easy to measure directly by satellite, it melts at 0 C and ignores adjustments.

  27. How about plot 4 with the difference between RSS and one of the reconstructions from thermometer readings. How can the differences between versions be so noisy while measurements of two different things, although closely related, by a completely different method not be much noisier? (There obviously months with huge differences such as during the 1998 El Nino).

  28. Please consult this paper published earlier this year. The information is in regard to the mid-troposphere, but is applicable to TLT since the same channels are used to generate TLT. In particular, note the reasoning behind all of our decisions, including the strong case for shutting off NOAA-14 early as it had drifted will past its time frame for diurnal corrections to be meaningful while NOAA-15 was the new AMSU with highly calibrated sensors which maintained a stable orbit for several years (and was in excellent agreement with NASA’s AQUA satellite). As noted in the paper, UAH and RSS (as compared with satellite datasets of NOAA and UW) had the lowest error rates relative to ALL of the radiosondes, with UAH a bit better. Note also the tropical plots and trend differences – demonstrating RSS tends to warm up more rapidly than the other various datasets (balloons and reanalyses). Both datasets are pretty good and I’ve advocated using the average of the two for a way to decrease the random error contained in both datasets and to reduce the effect of any unforeseen biases we each may have inflicted upon our datasets (I often do this in formal presentations, especially for comparison with models.)

    Thank you

    • Doesn’t reanalysis use MSU/AMSU data for their model based re-constructions?

      Also, as I recall UAH used to remove those scan positions which are impacted by precipitable ice (aka: hydrometeors). In your newest version 6 data analysis, do you still delete those and do you do so for both the MSU and AMSU data?

      • yes, reanalyses use satellites, but I don’t know the details of how they adjust for various drift effects.

        Out current v6 does not do any precipitation screening… previous tests showed it has not effect on global trends, but certainly can affect interannual variability in certain regions, such as the regional shifting of deep convection during El Nino and La Nina in the tropical Pacific. Out new LT is less sensitive to precipitation effects than the old LT (RSS still uses the old way of computing LT).

        • Dr Spencer,

          I would have thought otherwise, as there have been projections for increased storm intensity from AGW. Also, if one were to expand the definition of “tropical” to +/- 30 degrees, that might catch more of the intense tropical cyclones as they exit the +/-20 band and move into the mid-latitudes. Figure 1 from your 2018 paper shows the projected warming extending to that range. The cloud top temperatures from Michael were as low as -93 C (180 K). Panama City, FL is located at 30N.

          Have/will you document those tests you mention? I’m sure lots of folks would like to see the reasoning and analysis behind your decision to exclude screening.


    • Dr Christy,
      I understand that NOAA-14 has drifted outside the time frame for diurnal correction.
      But the time frame for diurnal correction has increased since 2015, because NOAA-18 and NOAA-19 continue to drift apart. The problem is that you use the difference between two drifters to calculate the drift. An obvious limitation with your empirical drift correction. RSS’ hybrid model/empirical diurnal drift correction can handle NOAA-14.

      I’m not astonished that NOAA-15 and Aqua agrees, because the drift (diurnal + other) in NOAA-15 is corrected with the difference to Aqua.
      However, I don’t consider it wise to trust NOAA-15 (the first satellite of its kind, never tested in the field before) enough to let it run alone in space, before it is accompanied by Aqua (June 2002?).
      The complete confidence in NOAA-15 and interference with NOAA-14 data needs a sanity check, ie it has to be supported by other/independent data.

      Like this:

      As far as I can see, there is not a single dataset supporting UAH v6 during the NOAA 14/15 overlap period. NOAA 15 is likely rogue, having other drifts than the diurnal. Half of your diurnal drift corrections rely on NOAA-15. What are the consequences of an unknown drift on the TMT/TLT datasets?

  29. Literally everyone I have talked to about temperature data adjustments by our record keepers looks at me with a confused look and says “Adjustments? Its just measurements right?”.

    They have the whole world fooled. Thats why I say eventually, after enough adjustments, by say 2030, the ten plus years of the “Pause” in the early 2000s will be changed into the largest temperature rise in a ten year period in our planet’s history. Thats what happened to the 90s. When the century ended even Hanson’s summary on the decade (and the whole 20th century) said there was no meaningful trend in temperature one way or another. Then after 10 or 15 years of slowly making the data before 1950 cooler and the 80’s and 90’s data warmer, we now have this massive temperature rise in the 80s and 90s that wasn’t there in the data when the century ended.

  30. I have a funny feeling this post will generate a couple of comments…hmmmm probably lots of comments at WUWT. Have fun!!!</blockquote

    Yes. Don't mind if I do. Just what the global adjusters ordered: Pivoting about the chronological mid-point of the data they produce the desired gentle warming in the first half, followed by a nice acceleration in warming. How delightfully convenient.

  31. I laughed – literally – at Figure 3. 0.25°C warming between 1980 and 2015, purely of adjustments between one version and another. Pathetically hilarious, were it not used as justification by the UN globalists for shutting down the developed world’s power generation and personal mobility.

    My daughter’s going to have the same reaction when she sees it 🙂

  32. Consider the many, many authors who did the research and wrote the papers – but used a temperature data set that has been discontinued because it was shown to be wrong.
    Where are all of the science papers saying “Please disregard the finding from our paper on (such-and-such) because we now have to go back and do it all again because the temperatures were wrong”.
    Don’t know about others here, but I have not been seeing the expected number of retractions and corrigenda, let alone the press releases announcing : “We were wrong … because temperature” – or “We were right more than we imagined … because temperature.”
    Maybe we need to launch a new Journal of Temperature Adjustment Consequences.
    Or just carry on as at present with the lackadasical “Don’t worry about it, we know it’s mainly guesswork so a bit more erroneous work won’t make any difference to our preconceptions. It is climate work, after all ….”

  33. This is actually expected because RSS has taken on the warming error that UAH had before it. This was removed by UAH, but RSS implemented it with that recent data adjustment. UAH showed a warming bias back in the 2000’s that neither surface or RSS showed. RSS was cooling a little more than HADCRUT and especially GISS, but UAH was warming more than any of them. this was corrected now RSS resembles the error that UAH had and has not been corrected since.

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