April 2017 Projected Temperature Anomalies from NCEP/NCAR Data

Guest Post By Walter Dnes

In continuation of my Temperature Anomaly projections, the following are my April projections, as well as last month’s projections for March, to see how well they fared.

Data Set Projected Actual Delta
HadCRUT4 2017/03 +0.817 (incomplete data)
HadCRUT4 2017/04 +0.606 (incomplete data)
GISS 2017/03 +1.03 +1.12 +0.09
GISS 2017/04 +0.77
UAHv6 2017/03 +0.351 +0.185 -0.166
UAHv6 2017/04 +0.044
RSS v3.3 2017/03 +0.437 +0.349 -0.088
RSS v3.3 2017/03 +0.115
RSS v4.0 2017/03 +0.479
RSS v4.0 2017/04 +0.329
NCEI 2017/03 +0.9831 +1.0477 +0.0646
NCEI 2017/04 +0.7709

The Data Sources

The latest data can be obtained from the following sources

Miscellaneous Notes
At the time of posting 5 of the 6 monthly data sets were available through March 2017. HadCRUT4 is available through February 2017. The NCEP/NCAR re-analysis data runs 2 days behind real-time. Therefore, real daily data from March 31st through April 28th is used, and the 29th is assumed to have the same anomaly as the 28th.

The projections for the surface data sets (HadCRUT4, GISS, and NCEI) are derived from the previous 12 months of NCEP/NCAR anomalies compared to the same months’ anomalies for each of the 3 surface data sets. For each of the 3 data sets, the slope() value (“m”) and the intercept() value (“b”) are calculated. Using the current month’s NCEP/NCAR anomaly as “x”, the numbers are plugged into the high-school linear equation “y = mx + b” and “y” is the answer for the specific data set. The entire globe’s NCEP/NCAR data is used for HadCRUT, GISS, and NCEI.

For RSS and UAH, subsets of global data are used, to match the latitude coverage provided by the satellites. This month, the RSS version 4.0 data set has been added, while retaining the version 3.3 data set that had been identified as simply “RSS” in previous posts. RSS version 4.0 has similar global coverage to UAH v6, so the same NCEP/NCAR data subset is used for the projections. RSS version 3.3 has its own subset.

For the satellite data sets the monthly anomaly difference (current month minus previous month) in the NCEP/NCAR subset anomalies is multiplied by the slope() of the previous 12 months, and added to the previous month’s anomaly.

The NCEP/NCAR anomalies (especially the satellite subsets) have dropped noticably for April. I’m a bit nervous about the low projections for the satellite data sets. But I continue to follow the algorithm projections. This is no place for “gut feeling”.

The graph immediately below is a plot of recent NCEP/NCAR daily anomalies, versus 1994-2013 base, similar to Nick Stokes’ web page. The second graph is a monthly version, going back to 1997. The trendlines are as follows…

  • Black – The longest line with a negative slope in the daily graph goes back to early July, 2015, as noted in the graph legend. On the monthly graph, it’s August 2015. This is near the start of the El Nino, and nothing to write home about. Reaching back to 2005 or earlier would be a good start.
  • Green – This is the trendline from a local minimum in the slope around late 2004, early 2005. To even BEGIN to work on a “pause back to 2005”, the anomaly has to drop below the green line.
  • Pink – This is the trendline from a local minimum in the slope from mid-2001. Again, the anomaly needs to drop below this line to start working back to a pause to that date.
  • Red – The trendline back to a local minimum in the slope from late 1997. Again, the anomaly needs to drop below this line to start working back to a pause to that date.

NCEP/NCAR Daily Anomalies:

NCEP/NCAR Monthly Anomalies:

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93 thoughts on “April 2017 Projected Temperature Anomalies from NCEP/NCAR Data

    • The same way you can measure two different veins of rock or metal and get two different average atomic masses for the same element.

      • Uses scientific principles to get unscientific and statistically irrelevant
        results. Side note: my front yard and my back yard sometimes have a 5 deg C difference in temperature on a summer day at noon.

    • Because the so-called “surface data” are made up out of thin air, as it were. They are whatever the corrupt book-cookers want them to be.

      • Tom Trevor, jaxad0127, Chimp and Donald Kasper:

        The dominant problem is that there is no agreed definition for global average surface temperature anomaly (GASTA).

        Each team that generates values of GASTA uses its own unique definition of GASTA and frequently alters its definition with resulting changes to its determined values of past GASTAs; see e.g. this.

        Also, if there were an agreed definition then there is no possibility of a calibration standard for it.

        Anyone wanting more understanding of these matters can obtain it b y reading this especially its Appendix B.

        Richard

      • Especially the further back in time you go. I actually wonder how accurate the temperature data really is from 50-100 years ago irrespective of obvious weather station sites in urban locations or that uncalibrated mercury thermometers were all we had from 1850 to 1950 or later. Hard to make a proper observation on a thermometer to even 1 degree, just because of the scaling.

        I remember my Mom and Dad used to take weather data observations on the farm in the 1950’s/1960’s. My Dad was a full foot taller than my Mom, and the thermometer was not really at eye level for either height. My Mom’s observations were always a degree or two higher than my Dad the same day, because my Dad was looking down on the thermometer because his back hurt and he didn’t bend over far enough to look straight on to the thermometer. What’s a degree or two, they would argue, at least we got the average trend right my dad would argue. My observations were even warmer because I was a foot shorter than my mom so was looking way up to the red mercury.

        I think it very dangerous to put a lot of trust in innocent observation techniques and poor quality thermometers in the past, or the locations of such weather stations. I remember the day I ‘converted’ from advocate of AGW to skeptic many years ago in the early 1990’s, and read about two items of interest to global warming as it was called then. One of the items was a news report about old weather stations being painted with whitewash paint, and new ones being painted with latex paint. Which caused a bit of temperature difference in the readings of the same temperature that very day. The other was the first scientific paper I ever read about diminishing sun spots causing more cosmic rays that ultimately led to more cloud formation and therefore a cooling trend. I knew at that instant that were was a lot more to all this than what was being told then. Fast forward 25 years…I thought it would all be settled by now.

        Or the adjustments that were made to the original raw data for whomever has/had an agenda. I don’t know that I trust the surface temperatures much still, and worry that even the sat data might be corrupted for scientific and political fraud purposes. Maybe I am now a bit paranoid, but probably with good cause!

      • Donald Kasper April 30, 2017 at 2:05 pm

        Undersampling is a problem, which allows the book-cookers to make up “data” for so much of the globe.

      • Don Kasper said, “The dominant problem is not corruption. The dominant problem is undersampling.”

        I would respectfully suggest that the problem is extrapolating temperatures in undersampled regions.

    • it’s a basket case on land-

      WMO- “About 70 countries in the world have inadequate climate services …”

      Africa – one fifth of the world’s land mass
      WMO – “Africa has a network eight times below the WMO minimum ”

      Hasn’t been done but says it all-
      “18 Jun 2009 – … Ericsson, the World Meteorological Organization, and Zain to deploy up to 5000 automatic weather stations at cellular sites across Africa, …”

      • Richard G- it’s even worse than your map-

        WMO – “Because the data with respect to in-situ surface
        air temperature across Africa is sparse, a one year
        regional assessment for Africa could not
        be based on any of the three standard global
        surface air temperature data sets from NOAANCDC,
        NASA-GISS or HadCRUT4. Instead, the
        combination of the Global Historical Climatology
        Network and the Climate Anomaly Monitoring
        System (CAMS GHCN) by NOAA’s Earth System
        Research Laboratory was used to estimate
        surface air temperature patterns”

      • If you said that the temp data for the following countries was just estimated with no temp data at all GISS would be seen as idiots-

        US, China, India, Mexico, Peru, France, Spain, Papua New Guinea, Sweden, Japan, Germany, Norway, Italy, New Zealand, the UK, Nepal, Bangladesh and Greece.

        All these countries would fit into Africa.

        And then add on another 70 countries with inadequate temp data- makes you weep for the sheer stupidity of the politicians who keep this fraud going.

    • Funny. To macks point. I live in Bay Area and there are a dozen weather stations all over our hilly area in San Mateo county. Temps vary by 3F from station to station sometimes more. What is the average temp for our region? I have no clue how you could calculate that.

  1. I know regionally, in the pacific north west, the temps so far has been very cool compared to last year for e.g.
    A year ago today, Fort McMurray was burning down in sweltering windy heat during tail end of a super El Nino. This spring, much much cooler than the long term average over north western parts of Canada and USA. Which appears the cooler continental air mass up north is clashing with all that warm moist humid heat and feeding the tornadoes in Texas and the US midwest. Looking like a bad season for tornadoes because of the steeper temperature gradient between north and south combined with a lot of hot humid air from the Gulf of Mexico.

    One thing about getting older, is that I am starting to see patterns of the same weather that blows in from the Pacific over a multi decadal time frame. Other than super ENSO events, it appears to me the solar cycle is the driving force in cloud formation in the Gulf of Alaska that predominates much of the weather patterns throughout much of north western NA. Most days I see the Sun in spotless and has been for some time now, which is very handy to see over to the right on this page, along with the ENSO and Atmospheric maps.

    • Well do I recall the strange winter of 1977. Looking back, I can see the PDO flip as it happened.

      I also recall well the remarkably frigid winter of 1968, when WA State sets its record low.

      • The winter of 1955-56 was also cold and snowy in Washington State. My dad bought snow skis for the whole family, and taught us what he had learned at Berchtesgaden, Germany after World War II was over.

    • Ron,
      RE: “Which appears the cooler continental air mass up north is clashing with all that warm moist humid heat and feeding the tornadoes in Texas and the US midwest.”

      We called that ‘spring and summer in Wisconsin’, when I was living there from 1955 – 1987. I saw a water spout on Big Green Lake when I was 8 years old. In the summer of 1975, I witnessed a horizontal rotor cloud that made a ‘tearing’ noise as it passed over a field I was working in. On June 23, 2004, we had to clear tornado damaged trees from the local church parking lot in the morning, before we could proceed with a funeral in the afternoon. The church as undamaged.

      It is truly a tragedy when people are harmed…. but tornadoes are all natural weather in ‘Tornado Alley’, none the less. Of course, we didn’t have to worry about volcanoes, tsunamis, or earthquakes in Wisconsin…..

  2. Chimp–That was correct yesterday but we are living in Orwellian times now.

    I just downloaded the new RSS v4.0 and their new slope is now 50% higher than UAH (0.18 vs. 0.12 per decade). RSS v3.3 WAS close to UAH at 0.135 but no longer. This has long been threatened by the RSS people. We are left with UAH as the sole outlier. (Probably also the sole correct estimate).

    • You’re right. RSS has decided to join the Borg, as it seems its director has long wanted to do.

      UAH’s days were probably numbered had Trump not been elected. The search for objective, empirical reality is hanging by a slender thread.

    • The RSS v 4.0 isn’t measuring the same quantity as the v3.3 nor UAH. Both RSS and UAH have found increasing difficulties with the TLT measurement and have switched to a higher altitude using a different combination of sensors. In his recent testimony to the House Committee Christy only talked about the MT quantity not the TLT.

    • MT is not the same as RSS 4.0 TTT. As of the last time I checked, MT (middle troposphere) uses one sensor and some of its reading is from the stratosphere. TTT (temperature total troposphere) uses a combination of sensors and reads the stratosphere less than MT.

  3. Here is the RSS 4.0 graph vs v3.3. Up to about 2000, they are not too different but then the upward adjustments take over.

  4. Ten years ago, RSS, UAH, HADCRUT & GISS used to agree more or less with each other. Now it looks like they don’t .

    You can’t make of that whatever you want to.


    • Plot showing the average of monthly global surface air temperature estimates (HadCRUT4, GISS and NCDC) and satellite-based temperature estimates (RSS MSU and UAH MSU)

      • It looks like the adjustments to GISS NCDC and to a lesser extent HadCRUT are to gradually over time iron out the steps and bumps so as to make the overall trend conform more closely to the theory of dominant constant CO2 forcing.

      • There would seem to be no way, even with the most intricate parameterisation, to make the models reproduce those ‘steps and bumps’ you mention, which of course they would have to do if their basic assumptions are correct. One can certainly be forgiven for being suspicious.

    • Good! Twenty years ago they used to fight each other as to who had the best ‘product’. Then two remarkably different metrics started a sort of inverse cofrelation. The closer the individual global temp data sets agreed with each other the greater the funds to their development increased.

      Simples

  5. Oops–just noticed that the link Walter provided was to RSS TTT v4.0 , not TLT. I think they have not yet moved to TLT v4.0.

    • About as warm as the ME warm period, possibly a little warmer than 1930’s, well below what it was 2000 years ago.

      • I don’t think that the Current Warm Period has yet had a single 50 year interval as warm as three or four such half centuries during the Medieval WP, which was, as you note, cooler than the Roman WP, which was cooler than the Minoan WP, which was cooler than the Holocene Climate Optimum. Thus, Earth has been in a long term cooling trend for at least 3000 years, and arguably since the end of the HCO, ~5000 years ago.

      • Chimp said: “No. All the other “sets” are wrong. UAH and I are right.

        Now RSS has joined the bogus “surface sets” as partners in corruption.”

        Lol, so RSS was correct until the data showed a warming trend, then it was incorrect. Because Chimp says it is cooling, and therefore it is cooling. Since skeptics love to trot out Latin phrases on this site, what is Latin for “it must be true because I said it is true”?

    • Define “steadily”?

      My tomato plants will love a higher temperature — and as soon as it warms up, I’ll plant them.
      Daffodils are blooming — there is hope.
      Hope is not a plan!

    • No, it’s not.

      It has warmed since the depths of the LIA over 300 years ago, but the long-term trend is still down.

      CO2 took after WWII. During that time, Earth cooled dramatically from 1945 to c. 1977. Then it warmed slightly for about 20 years, accidentally coinciding with continually rising CO2. Since the late ’90s, global temperatures have remained about flat. The 2016 super El Nino has reintroduced an upslope, but things are rapidly cooling off again, just as after the 1998 super El Nino.

      • Chimp…”but things are rapidly cooling off again, just as after the 1998 super El Nino.”

        No they are not. You are backed into a corner only using UAH. All other sets say you are wrong.

      • No. All the other “sets” are wrong. UAH and I are right.

        Now RSS has joined the bogus “surface sets” as partners in corruption.

        In the real, world, it’s cooling. Just ask the Arctic Ocean, where sea ice is melting with “unprecedented” slowness.

        Average ice extent loss in March is 173 thousand sq km. This year it was 152 K. April will come in at around 860 K v. normal median of 1.175 million.

      • If the super El Nino we just had that peaked in 2016 has now wound down and was a spike in global temps, then how could it not be cooling off again? A little common sense should apply to your statement. Or a better explanation on how it continues to warm? Are you saying the 2016 El Nino was a permanent step up in temps with no cooling after it flipped to La Nina?

        We are now out of the little La Nina we just had and just starting again to look like maybe another small El Nino forming, but has to stay that way for 3 months, which it hasn’t yet.

      • Chimp

        If you are so sure that the other data sets are wrong… provide proof. I know of no independent study that agrees with you. Not a one. So… let’s hear it. Note, by independent I mean not from a blog or opinion piece.

      • As far as I know, UAH is the only group left accurately reporting results. All the others are bogus. As would be expected, given that the Team always sing off the same hymnals.

        All proxy data show that earth is still cooling, as my instance of the Arctic Ocean shows. NOAA admits grudgingly that the sea is cooling. It has to, since the ice is melting so slowly. The Southern Ocean around Antarctic is if anything even colder than normal. I haven’t checked the latest anomalies there.

        The Team is as always cooking the books, and the chefs in the climate kitchen have been joined by Mears.

      • Simon,

        There are no studies finding that the world is cooling off either faster or slower now than after the prior super El Nino. All there is at the moment are the supposed “data” sets. In all the cases except UAH, these are not actual observations but bogus constructs designed to support the CACA story.

        But even if there were a study with valid proxies finding that we’re warmer now than at the same point after the late ’90s super El Nino, it would probably be a pack of lies, too, just like the alleged “data” sets other than UAH.

      • Chimp

        So I get you have an opinion, but the data(except for one set… sort of) doesn’t support what you say. It’s my understanding that there have been a few attempts by skeptics to look at and discredit the data. The latest was by the Global Warming Policy Foundation. Unfortunately for reasons only they know, it never got past first base. There was also the Berkeley Earth work. Skeptics championed it was going to prove all those nasty scientists wrong. We all know what happened there. Like I say, I know of no in depth study that discredits the current data sets, that are now showing more than just a little warming.

      • You don’t need an in depth study. All you need to do is compare NOAA’s reconstruction of past temperatures from the 1970s with those today and in between. The manipulation is glaringly obvious.

        Jones has admitted rigging the SSTs to agree with the adjusted land “data”, and that the ’30s were warmer than the ’90s, in reality. HadCRU’s “data” aren’t even scientific, since they’re lost and can’t be reproduced. We know that GISS’ UHI algorithm warms rather than cools, as it should. We have Karl’s own former colleague blowing the whistle on his bogus “pause buster”.

        We know that there is a cabal of climate conspirators, thanks to the Climategate emails, as if they were even needed. We can see Mann’s chicanery and tricks for ourselves. Or you could if you bothered to look.

        There can be no doubt that consensus climate science is corrupt to its core, not just in the GIGO models, but the “data” as well.

        A study finding all these facts would not pass pal review.

        Were these charlatans practicing in the private sector, say for a drug company, they’d all be in jail, which is where they belong, having robbed the world of trillions in treasure and millions of lives.

      • “Jones has admitted rigging the SSTs to agree with the adjusted land “data”, and that the ’30s were warmer than the ’90s, in reality. HadCRU’s “data” aren’t even scientific, since they’re lost and can’t be reproduced. We know that GISS’ UHI algorithm warms rather than cools, as it should. We have Karl’s own former colleague blowing the whistle on his bogus “pause buster”.”

        None of those is true.

      • Simon and Nick,

        All true. The Kool-Aide drinking and Tin Hat wearing are all yours.

        Nick, instead of just asserting a falsehood, how about actually searching for reality. Jones in on Youtube admitting that rigging of SST to match the cooked book land “data”.

        You’re both in serious d@nial. Please seek help.

      • Nick,
        Just gave it to you.
        How can you live with yourself, knowing that you have participated in, aided and abetted a monstrous criminal conspiracy, a ho@x which has cost the world trillions of dollars and millions of precious lives?
        Bear in mind that Jones is the same anti-scientist who didn’t want to share his “data” with the hoi poloi, because we “just wanted to find things wrong with it”. At least he had the common decency to feel suicidal after the enormity of his transgressions were finally made public.

      • Simon says, “Chimp. Tin foil hat time I think.”

        In other words, pay no attention to the mann behind the curtain…

      • “Just gave it to you.”
        Where? I saw no quote? And I’m not going to listen to a 1-hour lecture to try to find some phrase that you might have twisted to your “rigging” notion.

      • Chimp

        I’m with Nick…. there is no such quote in that clip that justifies what you have said. But you knew that.

      • Isn’t it amazing that, between 1939 and 1945, factories world-wide were building, and using, armaments (tanks, aircraft, warships, bombs, artillery shells (and setting the latter off) that 1) zero CO2 generation took place, and 2) the earth’s temperature fell? Which of the climate models can explain that?

      • Simon:

        You say

        It’s my understanding that there have been a few attempts by skeptics to look at and discredit the data.

        Your understanding is wrong.

        What we have is numbers that are asserted to represent global average surface temperature anomaly (GASTA). But there is no agreed definition of GASTA.

        Each team that generates values of GASTA uses its own unique definition of GASTA and frequently alters its definition with resulting changes to its determined values of past GASTAs; see e.g. this.

        Also, if there were an agreed definition of GASTA then there is no possibility of a calibration standard for it.

        In other words,
        all the time series of GASTA only represent the transient assertions of their compilers.

        If you want more understanding of these matters you can obtain it by reading this especially its Appendix B. (At present you are parroting untrue propaganda.)

        Richard

      • Nick & Simon
        the first quote comes @ ~6min
        “We have to adjust sea data else it wont match land data.”

      • 1saveenergy
        Oh come on for goodness sake, he is explaining to a public audience why they needed to do what they did. This is hardly some secret conspiracy to falsify the data. What nonsense. What are you guys going to do when there are no more straws to grasp?

      • But he’s not saying they adjust the sea temperatures to match land. He’s saying how they have to adjust the buckets of various types for their varying characteristics. And he says that without adjustment they wouldn’t match land. They wouldn’t match each other either. That’s the point of adjustment, to get it right. Otherwise different readings just can’t line up.

        What they do use to get consistency is NMAT.

      • Nick Stokes:

        You really are a funny man and this provides one of your best laughable comments ever

        He’s saying how they have to adjust the buckets of various types for their varying characteristics. And he says that without adjustment they wouldn’t match land. They wouldn’t match each other either. That’s the point of adjustment, to get it right. Otherwise different readings just can’t line up.

        He claims he knows what the measurement results would be if they were “right”.
        That means he has no need for the measurement results.
        He can adopt any value whatever he thinks is right because that provides the same as “adjustment” of the data to make it become what he thinks is right.

        I would be interested to know what you call this charlatanry of “adjustments” because by no stretch can it be claimed to be science.

        Richard

      • Chimp April 30, 2017 at 4:52 pm
        In the real, world, it’s cooling. Just ask the Arctic Ocean, where sea ice is melting with “unprecedented” slowness.

        Average ice extent loss in March is 173 thousand sq km. This year it was 152 K. April will come in at around 860 K v. normal median of 1.175 million.

        Less ‘loss’ because it was already starting with lower extent in the first place:

        “Arctic sea ice extent for March 2017 averaged 14.43 million square kilometers (5.57 million square miles), the lowest March extent in the 38-year satellite record.”

      • “He can adopt any value whatever he thinks is right”
        Adjusting for the various SST measurements is not particularly difficult. Canvas and metal buckets cool at different rates. You can take buckets of the two types and measure the discrepancy. Or you can take the many measurements that were taken with simultaneous NMAT readings and see if there is significant discrepancy. If there is, you have to adjust for it. There isn’t a choice.

      • simon ,regarding arctic sea ice ,yes the winter extent was lower than previous years .the problem with your assertion that monthly loss reductions are due to this would only hold up should current extent be below previous years,it is not.
        at this time of year sea temp is still the main factor on ice melting within the arctic(note i say melting,not loss. transport out of the arctic has this effect). the low extent during winter allows more heat from the ocean to escape to space .it will be interesting to see the effect of this come september.

      • i have no doubt various buckets cool at different rates. the question for me is were/are the water temperatures taken with equipment that would show a difference ? how long does a bucket of water have to be out of the ocean to cool 0.5c ? how long were buckets left on the deck before the temp readings were taken ? i doubt this was consistent across the various ships these measurements were taken.

      • Nick Stokes: “And he says that without adjustment they wouldn’t match land. They wouldn’t match each other either. That’s the point of adjustment, to get it right.”

        Ah, the science of sausage making. Put the data through the grinder and adjust the seasoning until you get just what you want, a consistent product with a warm finish. The best sausage that science can buy.

      • Phil. May 1, 2017 at 4:48 am

        Winter maximum was ever so slightly lower than in other recent years, thanks to the super El Nino. And it reached maximum a bit later than usual. But that can’t explain why the melt has been so slow since maximum. Except that having more water without an insulating lid of ice on it allowed more heat to escape to space, cooling the Arctic Ocean and adjoining seas.

        The slow melt this year thus is indirectly linked to the lower maximum, but not in the way that you suppose. The fact is that the Arctic Ocean and other northern seas are colder now than normal.

      • Nick Stokes April 30, 2017 at 10:25 pm

        It’s fairly early on. I’m surprised you’ve never seen this lecture before.

        Sorry for not pointing to the minute at which he discusses matching SSTs to the already cooked land “data”. As noted by a helpful comment above, it’s at around the six minute mark.

        Apparently you found it.

      • Simple Simon, so you are arguing that the earth is still the same temperature that it was at the height of the recent El Nino?
        Are you really as dumb as you sound?

      • richardscourtney May 1, 2017 at 4:13 am

        I would be interested to know what you call this charlatanry of “adjustments” because by no stretch can it be claimed to be science.

        It’s what scientists call ‘calibration’ and is an essential part of science.

      • Nick Stokes:

        Calibration consists of comparing a measurement system to a calibration standard.
        It does NOT include “adjusting” data.
        You would know these things if you were a scientist.

        Richard

  6. Walter, surely you can’t be serious! (you are serious and i won’t call you shirley… ☺) These numbers make it look like the bottom is falling out of these records. Last month was surprisingly low and this month is going .2C (+ or -) lower. If you’re right this could get very interesting. (very interesting indeed)…

  7. The Energy Anomaly at 65N Latitude went negative 3000 years ago which means the warmest part of the holocene is history and the Earth is cooling down toward the oncoming ice age at about 1 degree C/Millennium. This is natural climate change no amount of CO2 can prevent or delay because it’s happened 8 times in the past 1 million years.

  8. Well Some people have ‘other methods’ of adjusting the thermometer reading.
    Of course they are ‘anomalies’

  9. The idiots that believe in climate change will believe it is getting hotter till 1 mile thick glaciers cover Canada.

  10. Probably this

    RSS v3.3 2017/03 +0.437 +0.349 -0.088
    RSS v3.3 2017/03 +0.115

    should be
    RSS v3.3 2017/03 +0.437 +0.349 -0.088
    RSS v3.3 2017/04 +0.115

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