Global Temperature down in April, just 7/100ths of a degree above normal

From Dr. Roy Spencer and from UAH, I’m a bit remiss in posting this due to travel, but better late than never – Anthony

UAH V6.0 Global Temperature Update for April, 2015: +0.07 deg. C

NOTE: This is the first monthly update with our new Version 6.0 dataset. Differences versus the old Version 5.6 dataset are discussed here.

The Version 6.0 global average lower tropospheric temperature (LT) anomaly for April, 2015 is +0.07 deg. C, down a little from the March, 2015 value of +0.14 deg. C (click for full size version):

UAH_LT_1979_thru_April_2015_v6

The global, hemispheric, and tropical LT anomalies from the 30-year (1981-2010) average for the last 4 months for the old Version 5.6 and the new Version 6.0 are:

YR MON GLOBAL NH SH TROPICS

v5.6

2015 1 +0.351 +0.553 +0.150 +0.126

2015 2 +0.296 +0.433 +0.160 +0.015

2015 3 +0.257 +0.409 +0.105 +0.083

2015 4 +0.162 +0.337 -0.013 +0.074

v6.0

2015 1 +0.261 +0.379 +0.143 +0.119

2015 2 +0.157 +0.263 +0.050 -0.074

2015 3 +0.139 +0.232 +0.046 +0.022

2015 4 +0.065 +0.154 -0.024 +0.074

The global image for April, 2015 should be available in the next several days here.

The new Version 6 files, updated shortly, are located here:

Lower Troposphere: http://vortex.nsstc.uah.edu/data/msu/v6.0beta/tlt

Mid-Troposphere: http://vortex.nsstc.uah.edu/data/msu/v6.0beta/tmt

Tropopause: http://vortex.nsstc.uah.edu/data/msu/v6.0beta/ttp

Lower Stratosphere: http://vortex.nsstc.uah.edu/data/msu/v6.0beta/tls


 

From UAH via press release:

042015_tlt_update_bar APRIL 2015

Global Temperature Report: April 2015

25th year of GTR begins with revised satellite dataset

Global climate trend since Nov. 16, 1978: +0.14 C per decade

April temperatures (preliminary)

Global composite temp.: +0.16 C (about 0.29 degrees Fahrenheit) above 30-year average for April.

Northern Hemisphere: +0.34 C (about 0.61 degrees Fahrenheit) above 30-year average for April.

Southern Hemisphere: -0.01 C (about 0.02 degrees Fahrenheit) below 30-year average for April.

Tropics: +0.07 C (about 0.13 degrees Fahrenheit) above 30-year average for April.

March temperatures (revised):

Global Composite: +0.26 C above 30-year average

Northern Hemisphere: +0.41 C above 30-year average

Southern Hemisphere: +0.11 C above 30-year average

Tropics: +0.08 C above 30-year average

(All temperature anomalies are based on a 30-year average (1981-2010) for the month reported.)

Notes on data released May 4, 2015:

“After three years of work, we have (hopefully) finished our Version 6.0 reanalysis of the global MSU/AMSU data,” said Dr. John Christy, director of the Earth System Science Center at The University of Alabama in Huntsville. “Many procedures have been modified, or completely reworked, and most of the software has been rewritten from scratch. Version 6 of the UAH MSU/AMSU global satellite temperature dataset is by far the most extensive revision of the procedures and computer code we have produced in more than 25 years of global temperature monitoring.

“The two most significant changes from an end user perspective are (1) a decrease in the global-average lower troposphere (LT) temperature trend from +0.14 C per decade to +0.114 C per decade from December 1978 through March 2015; and (2) the geographis distribution of the LT trends, including higher spacial resolution,” Christy said. “Barring a significant problem, these revised data will be incorporated into the May 2015 Global Temperature Report.”

The beta-test files of Version 6 have been released for review and comments.

A more thorough explanation of the dataset revision process is available here:

http://www.drroyspencer.com/wp-content/uploads/Version-61.pdf

The complete December 1978 through April 2015 version 6 beta lower troposphere dataset is available here:

http://vortex.nsstc.uah.edu/data/msu/v6.0beta/tlt/uahncdc_lt_6.0beta2

Compared to seasonal norms, the warmest average temperature anomaly on Earth in April was around the Kara Sea, north of central Russia. The April temperature there averaged 5.85 C (about 10.53 degrees F) warmer than seasonal norms. Compared to seasonal norms, the coolest average temperature on Earth in April was in Marie Byrd Land in West Antarctica, where the average April 2015 temperature was 3.07 C (about 5.53 degrees F) cooler than normal.

Archived color maps of local temperature anomalies are available on-line at:

http://nsstc.uah.edu/climate/

Anyone accessing the satellite temperature anomaly dataset through the website should be aware that a problem in the code creating the USA49 column of numbers has been identified and corrected, changing the values reported for that column alone.

As part of an ongoing joint project between UAHuntsville, NOAA and NASA, Christy and Dr. Roy Spencer, an ESSC principal scientist, use data gathered by advanced microwave sounding units on NOAA and NASA satellites to get accurate temperature readings for almost all regions of the Earth. This includes remote desert, ocean and rain forest areas where reliable climate data are not otherwise available.

The satellite-based instruments measure the temperature of the atmosphere from the surface up to an altitude of about eight kilometers above sea level. Once the monthly temperature data is collected and processed, it is placed in a “public” computer file for immediate access by atmospheric scientists in the U.S. and abroad.

Neither Christy nor Spencer receives any research support or funding from oil, coal or industrial companies or organizations, or from any private or special interest groups. All of their climate research funding comes from federal and state grants or contracts.

— 30 —

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143 thoughts on “Global Temperature down in April, just 7/100ths of a degree above normal

    • “Global Temperature down in April, just 7/100ths of a degree above normal”
      This site used to decry warmists using the term ‘normal’ , what is the ‘normal’ temperature of the Earth ??!
      There is no reason to call the mean of the last 30 y or whatever ‘normal’. It is not more normal than 1870-1900 was ‘normal’.
      It’s meaningless but plays into the warmists game that there is something abnormal about current global mean. I’m surprised to see that our host has adopted this stupid biases phraseology.

      • You beat me to it. “Normal” was a bad choose of words. The next thing we’ll hear is that it is xxx deg. above ‘ideal’.

      • 30 yrs average is the “normal” decided by UN’s World Meteorological Organization. I’m sure they wish they hadn’t done it that way. But using it is the only way to be on the same page as CAGW proponents and the worlds meteorologists.

    • Most of this seems to be taken verbatim for Spencer’s site. But he is not silly enough to adopt the warmists’ meme:
      “The global, hemispheric, and tropical LT anomalies from the 30-year (1981-2010) average….”

  1. After 4 months, UAH would rank in 8th place if the new average were to hold for the rest of the year. As well, the pause with April is now 18 years and 4 months on UAH.
    But with the pause being 18 years and 4 months on version 6, I would say Nick’s time for statistically significant warming would increase by 4 years to over 22 years.
    RSS dropped from 0.255 to 0.174. Its pause is 18 years and 5 months. If the new average of 0.281 holds, RSS would end up in 6th place for 2015.

  2. 7/100ths!! Are you serious?
    What is the realistic margin of error behind these measurements?

  3. What is plain to see from figure 1 is that since 1979, there is no first order correlation between CO2 and temperature.
    Rather than seeing the running centred 13 month average superimposed, I would sooner see a plot of accumulated manmade emissions, or CO2 levels superimposed..

    • Richard
      Bearing in mind the great store set on satellites for sea levels we need to ask how accurate this atmospheric data set is and how relevant it is. If it is both we then need to ask why it is not as widely used (and credible in official eyes) as the sea level data.
      tonyb

    • Here you go.
      1. Temperature anomalies regressed on the atmospheric CO2 concentration, 1850-2014: http://i.imgur.com/2ZkFRsv.png?1
      The regression predicts the annual temperature anomaly (relative to the 1951-1980 mean) is the CO2 concentration x .0087 -2.80. The standard error of the residuals is .12, so the regression predicts the anomaly will be within +-.12 degrees of the estimate around 2/3rds of the time.
      2. Temperature anomalies regressed on the time index (Jan 1850 = time index value 1, Mar 2015 = time index value 1983): http://i.imgur.com/JtjOopp.png?1

      • Interesting regression. Frankly, I was expecting a logarithmic regression. And without the correlation coefficient or the coefficient of determination we do not know how good do they correlate. Does not seem to be close to 1, though.
        Two questions,
        Why is the temperature anomaly used?. Seems to me that the absolute temperature should be used.
        Where do they get the data of the global CO2 concentrations from 1850 to nowadays? Mauna Loa records only start on 1959.

    • As the half-life of CO2 in the atmosphere is about 5 years, there is no accumulated human emissions. The oceans with 50 times as much dissolved CO2, drive the atmospheric CO2. Even while coolng, the oceans will continue to out gas until they cool to a temperature that promotes absorption.
      It is also true that glaciers melt when it is getting warmer and continue to melt while it cools until they reach a temperature that promotes growth.

      • As the half-life of CO2 in the atmosphere is about 5 years, there is no accumulated human emissions.

        Sure yes. Are you talking about gas exchange rate, or the rate at which CO2 is taken by long-time sinks?
        Because yes, individual CO2 molecules do change rapidly, but the amount of CO2 is does not. If CO2 was suddenly halved every five years, we’d be all dead in ten years.
        The gas exchange rate as such has nothing to do with the effective lifetime of human CO2 emissions.

    • Your wish is my command.
      http://www.phy.duke.edu/~rgb/Toft-CO2-vs-MME.jpg
      There is a strong first order correlation between CO2 and temperature running all the way back to 1850. Your choice of 1979 is particular unfortunate, as that is just about at the start of the single strongest warming trend in the last 165 years (which occurred over the 15 year stretch from 1983 to the 1998 super-ENSO).
      As you can see, I plot this with the total acknowledged HadCRUT4 95% confidence interval — which I don’t believe for a minute, because it only doubles in size going from 2014 back to 1850, which is absurd — but at the very least you can see the general scale of uncertainty and the size of the local ~5 year fluctuations around some sort of mean behavior. You can also see the oft-noted sinusoidal with its 67 year period modulating the underlying, nearly “perfect” fit between temperature and CO_2 concentration using precisely the predicted logarithmic numerical form of greenhouse warming as a function of CO_2 concentration. For final grins, I plot the AR5 MME mean in red. To the trained eye, the red curve utterly fails to fit the data, especially given that the only place where there is a halfway decent fit is over the reference period where the contributing models are tuned to reproduce the climate with their particular set of internal parameters. Outside of that, it runs too hot almost everywhere and too cold almost nowhere, including over the vast majority of its hindcast.
      My current interpretation of this is that almost all of the models are (unsurprisingly) useless predictors of the climate in any sense whatsoever, including in the meaningly multimodel ensemble mean, probably because they:
      a) Use an exaggerated number for the cooling impact of aerosols. A recent, very carefully done paper dropped the estimated cooling impact of aerosols by over a factor of 2, especially relative to the highball numbers used in some of the models. This is actually directly visible in this graph and even moreso in various other plots, where the models consistently and significantly overshoot the impact of volcanic eruptions. Volcanoes actually have remarkably little — pretty much invisible — impact on global temperatures until they are VEI 5 or greater, and their effect is also remarkably transient. I’m surprised that they get them as wrong as they do given the direct data on atmospheric transmittivity at Mauna Loa, but they do. Even Pinatubo had a minor effect that the models generally badly overshot.
      b) Get the integrated effect of water just plain wrong. In particular, they overestimate the warming produced by water vapor feedback in order to cancel the exaggerated cooling effect of the aerosols, and very likely don’t correctly account for small-scale (smaller than their cell size) phenomena that transport a lot of heat rapidly, e.g. thunderstorms (papers again estimate that they could be off by around a factor of two in this contribution), cloud modulated albedo shifts, and the variation of tratospheric water vapor and its impact on longer term trends in the troposphere and on the surface. They are completely useless for even predicting the general regions where drought or flood are more likely or trends in the patterns of rainfall.
      c) Were built with a reference period that happened to lie square on the (green line) increasing half-period of the sinusoidal variation superimposed on the general log trend (blue line). This, as I said above, is a particularly unfortunate choice, as it increased the slope of the fit region by at least 0.1C/decade relative to the baseline log behavior, and, due to errors a) and b), attributed this extra “warming” almost entirely to high CO_2 sensitivity with strong water vapor feedback.
      d) Couldn’t realistically have been expected to work anyway. With minimum granularity of 100x100x1x300 km^3-sec, they are thirty orders of magnitude away from the Kolmogorov scale for atmospheric dynamics, let alone the dynamics of the coupled ocean. Whether or not one takes the Kolmogorov scale for turbulent flow as being “necessary” for reasonable congruence between Navier-Stokes solutions and reality, there isn’t any really good reason to think that a computation 30 orders of magnitude off of it is likely to yield a good result. It has been pointed out (by Nick Stokes) that CFD computations have managed to get right answers as verified by e.g. wind tunnel measurements with grids that are not at the Kolmogorov scale, but this comparison is naive in the extreme, given that the successful computations: i) used an adaptive grid, and did indeed go down close to the KS at points where turbulent drag was strong; ii) used slip conditions for smooth/non-bluff surfaces so that almost all of the flow was laminar. Cars and jets are streamlined for a reason. Try using CFD to simulate the dynamical trajectory of an irregularly shaped semi-porous rock with random surface structures covering it and no slip condition using a coarse non-adaptive grid 30 orders of magnitude larger than the KS, then we’ll talk; iii) were trying to predict things like average drag coefficient — macroscopic quantities averaged over turbulence — in cases where there was a single branch of turbulent behavior and with enormously smooth external conditions (basically constant speed single direction oncoming winds hitting the streamlined surfaces head on). Modeling the climate is nothing like this — the problem is truly absurdly more difficult in almost every sense that it can be.
      But we’ll see. At the moment, the models, with a very few individual exceptions, are diverging in their future predictions quite systematically, even compared to their systematic error in most of their hindcast. They haven’t reached the 0.4 C peak error they exhibited back around 1910, but they are off by as much or more than they were across the rest of the first half of the 20th century, and that is collectively. It has to be. If we looked at individual model results, or even the average results of individual models, we would laugh hysterically. It is only by averaging out the absurdities in the many individual model results that AR5 can present a result that looks to the untrained eye like it might have some relevance, at least until you are told where the reference period is.
      Sadly, there are actually a few models in CMIP5 that are not terrible, or at least are less terrible. One could radically improve CMIP5 by just applying a hypothesis test to the individual models and throwing out the losers. You’d lose at least 2/3 of the models that way, and you’d drop estimates for TCS back down to well under 2 C (my blue curve is 1.8 C) per doubling. If the new results on aerosols are eventually accepted, it will probably drop TCS even more, to between 1 and 1.5 C. This is almost perfectly in alignment with the multidecadal average rates observed in the two lower troposphere data sets, and if one removes some of the “adjustments” made to HadCRUT4, adds an actual UHI adjustment (currently omitted), and comes up with plausible error bars for the remote past that are more than twice those of the present (seriously!) then it would easily be within the range of plausibility for the surface temperature as well, not that it isn’t already with an unknown and uncomputable natural variability and almost completely unknown initial state mixed in with the additional CO_2 in any sort of more complex model than the one I present above.
      rgb

  4. This has really been a strange quasi double peak El Nino cycle, which has persisted for well over a year and looks like it still has some legs.
    The Ridiculously Resilient Ridge (RRR), “The Blob” and this strange double-peak weak El Nino cycle will likely further delay the onset of the next La Nina cycle until the end of this year or even early next year.
    Once the next La Nina cycle does occur, global temps should drop significantly, because historically, La Nina events during 30-yr PDO cool cycles are colder, longer and more numerous than during 30-yr PDO warm cycles.
    Ya neva knowwww.,,,, (famous Cajun life philosophy)

    • I don’t like the scam tone used in relation with NOAA. It polarizes discussion plus opens door to talk on conspiracy ideation.
      Could we call it awfully bad science? History being rewritten in an undocumented manner?
      I have hard time imagining they’d do this on purpose, but of course it does not matter what I think. NOAA should explain what is going on, it is their duty after all.

      • The difference between being stupid and fraud is intent or motivation. And of course stupidity and wrong-doing are not mutually exclusive.
        If the NOAA has a political agenda driving its stupidity than the term scam may fit.

    • Making corrections or revisions based on new knowledge is not criminal, doing so without proper documentation of why, how and time of change potentially is. It also could be potentially incredible incompetence. Whatever the case, new leadership is needed. If legal action is the only way to get proper stewardship of the historical data, than so be it. As it is now there is little reason to trust the NOAA data, never mind their conclusions.

    • Thanks, Eliza. We get what we pay. But we didn’t pay for THAT.
      Best regards – Hans

      • johann wundersamer

        Thanks, Eliza. We get what we pay. But we didn’t pay for THAT.

        Well, we always get what we pay for.
        But, do we actually want what (the unelected bureaucrats and dictators) actually pay for?

      • RACookPE1978
        May 9, 2015 at 5:55 am
        johann wundersamer
        But, do we actually want
        what (the unelected
        bureaucrats and
        dictators) actually pay for?
        ____
        Racook: insinuerating question, thanks.
        And yes: NO! WE never got what we paid for, that money ever was invested for better reasons, the future of unknowns unknown children, pink barbie dolphins or vegetarian nurtured white sharks.
        / first time sarc for me to apply
        RCK – to You!

  5. Don’t worry, later this year in Paris global warming will rise from the dead, looking hotter than ever before.
    Too many people want global warming to be true.

  6. Is the AMO a natural phenomenon, or is it related to global warming?
    Instruments have observed AMO cycles only for the last 150 years, not long enough to conclusively answer this question. However, studies of paleoclimate proxies, such as tree rings and ice cores, have shown that oscillations similar to those observed instrumentally have been occurring for at least the last millennium. This is clearly longer than modern man has been affecting climate, so the AMO is probably a natural climate oscillation. In the 20th century, the climate swings of the AMO have alternately camouflaged and exaggerated the effects of global warming, and made attribution of global warming more difficult to ascertain.
    Monthly Atlantic Multidecadal Oscillation (AMO) index values since January 1979. The thin line indicates 3 month average values, and the thick line is the simple running 11 year average. By choosing January 1979 as starting point, the diagram is easy to compare with other types of temperature diagrams covering the satellite period since 1979. Further explanation in text above. Data source: Earth System Research Laboratory at NOAA. Last month shown: March 2015. Last diagram update: 14 April 2015.
    http://www.climate4you.com/images/AMO%20GlobalMonthlyIndexSince1979%20With37monthRunningAverage.gif

    • Ren: are you still grasping at straws. !50 years of AMO caused by CAGW. Talk about swallowing camels and straining at gnats.

      • TedM, ren did not say “CAGW”.
        He said “global warming”.
        The world has warmed since the end of the Little Ice Age. So it is a question worth asking.

    • Put the ordinate in 10ths. This is the scale we argue on. Warming proponents probably designed this graph in degrees to flatten down this important effect.

  7. Guess what? I am Sooooooo not going to lose any sleep over an anomaly of seven one-thousandths of a degree.

  8. Not directed to Dr. Spencer but…
    Define “normal”. Describe why it is considered normal. Defend why it can be the one “normal”. Discuss other possible normals. Explain why the one normal is more acceptable than any others. Explain why the accepted normal is applicable to evaluating time frames other than that used to produce the “normal” reference point. Explain how a “normal” can include a well-identified cooling period but not a well-identified warming period. Anybody?

    • I agree that the word “normal” is misused here. Normal human body temperature is 98.6F as shown by empirical and experimental evidence over centuries; strong deviations from that temperature will bring serious and dangerous results. Normal doesn’t mean average or usual; it means what something is supposed to be. I’ve pointed out in earlier posts the incident of playwright George Bernard Shaw’s eye exam, undertaken at the urging of some friends: The oculist, after examining Shaw’s eyesight, pronounced it normal (i.e., 20/20), and noted, “That condition is very rare.” For the weather, we cannot pronounce a “normal” condition. Is a rainy day normal? Around here, rain falls, on average, eight or nine days a month (trace or more), ranging from four to thirteen days (2013 to now); that means that, on average, about 21 days per month are rain-free. Which condition is normal? Obviously, neither one, because a norm can’t be set. It used to be that a family was a mommy and a poppa and [let us say] 2.3 children, on average; but was it normal? Can’t say. It’s very difficult for a mommy to have and maintain 3/10 of a child, so if 2.3 children were ever considered “normal,” it would be impossible to achieve. A norm is a standard of what conditions should exist in a given situation, which means that knowledge exists concerning that situation, including what happens (or doesn’t) when that standard is not reached. Our weather simply doesn’t have such standards.

    • Defined by UN’s World Meteorological Organization (30year avg is the normal). Yeah I know. Its stupid but if you are going to argue in this game, you better use the same basis as Big Climate.

    • ‘Normal’ would be 180 – 280 ppm of CO2 in the atmosphere, which Homo Sapiens Sapiens has always lived with and under. Anything else is not ‘normal’.

      • splendid; and now please do this for Dow Jones. Thanks for documented trying.

  9. I agree with DP, what is normal for the planet? Also, 7/100th of a degree was measured? I fond that hard to believe!

    • “Normal” is what it was like when “they” (the warmistas) were growing up.
      Whaddaya mean, “they” still haven’t grown up yet?

      • Ren,
        The height of the tropopause is a great indicator for illustrating the relative heat flux in the system. Over 80% of the solar energy for the entire earth is in the tropics with very little left for the polar climate zones, just as the tropopause shows.

  10. The altitude of the tropopause, and thus the thickness of the troposphere, varies considerably. Typical altitudes are 55 000 feet in the tropics with a temperature of –70 °C and 29 000 feet in polar regions with a temperature of –50 °C. Because of the very low surface temperatures in polar regions and the associated low level inversion, the temperature lapse profile is markedly different to the mid-latitude norms. In mid-latitudes the height of the troposphere varies seasonally and daily with the passage of high and low pressure systems.
    In the chart above an exaggerated environmental temperature lapse rate profile has been superimposed to illustrate the temperature layer possibilities starting with a superadiabatic lapse layer at the surface, a normal lapse rate layer above it then a temperature inversion layer and an isothermal layer.
    http://www.pilotfriend.com/training/flight_training/met/images2/17.gif
    http://www.pilotfriend.com/training/flight_training/met/hm_temp.htm

      • You can see that the temperature changes at the surface determines the amount of water vapor. This is influenced primarily wind power over the oceans. It turns out that the increase in solar activity increases the force of the wind.

      • That was the most polite of ways of telling ‘I did not understand how this comment is related to anything.’
        For the records, I have that problem often, too.

      • Specifically it is superadiabatic lapse layer at the surface and the lower troposphere. The water vapor due to the high heat capacity slows heat loss to the upper atmosphere.

      • ren
        May 7, 2015 at 6:53 am
        Specifically it is superadiabatic lapse layer at the surface and the lower troposphere. The water vapor due to the high heat capacity slows heat loss to the upper atmosphere.

        I’m not sure that follows. Once convection takes place, a wet atmosphere moves a lot more heat than a dry atmosphere.
        The problem is that we’re dealing with a dynamic system. In the tropics, in the morning, a lot of heat is stored in the moist atmosphere. Then convection happens. Then we get tropical thunderstorms. A lot more heat gets moved around than is the case during a typical summer day in Moose Jaw (where it’s pretty dry).

  11. Lovely picture of The World we’ve got up with its brown and yellow contours but, sorry, its wrong.
    My local Met Office station at Newton Rigg (and they run even warmer than Wunderground stations) says that my part of the world is 0.25 degC cooler than the 30 year 1981-to-2010 average for the 1st 3 months of the year. (They haven’t released April 2015 data yet – still adjusting it probably so I’ve only compared Jan, Feb and March all the way through)
    The lovely globe picture says between 0.5 and 1.5 degC warmer for Newton Rigg in N. Cumbria
    Does anyone know what we are even measuring here.
    Then, the datalogger in my garden says this April was, on average, 2 degC colder than April 2014.

    • Peta, the UAH record is a measure of Lower Tropospheric temperature, not ground level.

      • From the article:
        “The satellite-based instruments measure the temperature of the atmosphere from the surface up to an altitude of about eight kilometers above sea level.”

      • They measure the trop from ground to ~8Km and then use that data to give global temps on the same page as HadCrut, GISS, etc. It’s supposed to be a proxy for ground. Go to Roy’s page and see the temps at different levels. Since they are reporting in \ “anomalies” it gives fairly accurate results.

    • Note that the global chart is for temperatures in the lower troposphere, not for those at ground level, which would be what your datalogger recorded for your garden. The lower troposphere extends up to tens of meters above ground level.

    • Peta,
      Maps with colored areas showing regional features are based on regional averages and tell us nothing about specific locations. I recently ran into an amusing example in a social studies textbook being used in one of my (California) classes. The map showed California with the customary regional areas: Central Valley, Mountains, Deserts, etc. The question to the student: Which is higher, Monterey or Fresno? Since Monterey was shown in a mountainous region (the Coastal Range) and Fresno was in the Central Valley, the publisher’s answer was that Monterey was higher than Fresno. John Steinbeck (author of Cannery Row) would have been very surprised….

  12. Lost in the talk about 7/100 of a degree rise or fall is that there has never been any real evidence that mankind’s activities has much to do with the planetary wide cycles of climate. We also can not really measure the planet’s temperature with any accuracy anyway. On top of that, the ever changing temperature of the atmosphere is hardly worth our attention while we can not measure the total energy in the system from the top of the atmosphere down to the core of the planet. Are we gaining energy or are we losing energy over time? At what rate? Anyone have a guess for me?
    One investigator I read pointed out that as far as we know, when the temperature goes up in one local area it goes down in another area. He claimed that the overall temperature stays the same but that we get a lot of local variation. That was like saying that “weather is local and so is climate”. I don’t know about that theory, but I do wonder what these data sets are showing other than what various political groups need shown.

    • Stefan Mittich has a theory = That the Troposphere provides an elegant dispersion of all additional heat to the void at -90 C. That the Troposphere rises and falls to attain the void or the cold upper atmosphere and shrinks to conserve heat at the poles. This is a purely mechanical system based on pure and simple physics but may yet prove to be a profound explanation for the lack of heat.
      https://globalwarmingdenier.wordpress.com/climate/

      • This is a purely mechanical system based on pure and simple physics but may yet prove to be a profound explanation for the lack of heat

        RE451, are you refering to the so-called “missing heat”. This heat that somehow has crept into the depths of the sea, that heat?

    • I think the reason for the divergence may be the blob. NOAA did a study and found it to be the result of low winds. This suppresses evaporation and allows the surface to warm. By the same process the heat will not rise into the lower troposphere where it would be measured by satellites. The main part of the divergence started to appear when the blob first formed. If I’m right the divergence should disappear when the blob dissipates.

      • Wind increases evaporation and simultaneously distributes heat around the planet. The key to climate change may be the wind, which may depend on solar activity. Weak solar wind – the wind weaker – weaker evaporator – decrease temperature in the troposphere.

  13. The Australian UAH data is quite interesting.
    There are distinct jumps in 1998, 2002, 2009, 2012, with very obvious cooling trends between.
    Basically no overall trend since beginning of 1998.
    Would be interesting to figure out why.

  14. first they tell you the LIA ended around 1850……then they tell you that was the perfect normal temperature
    …then they tell you it’s a few 100th of a degree above that

  15. As an interesting side note I looked at the April anomaly for RSS and found it to be the lowest during an El Nino since 1992 (which was cold due to the Pinatubo eruption). If that has any meaning at all the next La Nina could also be one of the coldest in years and drive the pause to over 20 years very quickly.

  16. Can anyone explain what has happened to the Arctic sea ice now that the Arctic sea ice map has been updated?. It appears that the Arctic sea ice has suddenly got a holes in it.

  17. 2015 1 +0.261 +0.379 +0.143 +0.119
    2015 2 +0.157 +0.263 +0.050 -0.074
    2015 3 +0.139 +0.232 +0.046 +0.022
    2015 4 +0.065 +0.154 -0.024 +0.074

    If that trend continues, global temps should be negative by June, and global warming gone by this time next year. Whew! I’ll cancel my order of culinary bugs.

  18. There is a three month cooling trend, ongoing that AGW believers are silent on.

  19. “Global Temperature down in April, just 7/100ths of a degree above normal” . And that is one big factor in the global warming charade, the word “normal”. Compared to what? This is an interglacial period, no? Junk science must not be allowed to define the terms.

    • If one just takes this “normal” as granted, then the warmistas have lost .07 degrees does not a catasstrophe make.
      The warmistas need a new normal. Which they will undoubtedly achieve through the so-called “adjustments” to historic MEASURED temperatures. goverment influence and government itself is doing this.
      Those historic temperature records should have been held sacrosanct. Changing them is wrong. Worse yet,the motivation behind changing them is scary..

      • Hard to believe that even if the numbers are not adjusted, measurement technology and its implementation are sensitive to .07 degrees. Votes, power and, ultimately, money are, as in most cases, the driving motivation.

  20. Well, 7/100th of a degree is enough of an anomaly to throw a lot of parties in Paris. That might even be the spring board for starting another international agency based there. They know the drill and there are dozens of similar agencies scattered around Paris.

  21. “Normal” is being defined as the “average from 1981 to 2010” (a most recent 30 year period, as shown on the graphic.
    I agree that too much of the nomenclature, descriptions, and talking points seem to aid the CAGW folks even if only implying that the CAGW position is worthy of discussion.
    Maybe I’m wrong, but I don’t look at this as showing absolute temperature, I see it as being the basis of any possible trend and the trend is slightly up over the 30 year period but somewhat flat over the last half of that period. “Global Warming” which was apparent in that first half has now stopped.
    None of this implies or reinforces the possibility that human CO2 emissions into the atmosphere are causing, or even contributing to, a warming climate. Nor does it refute that possibility.
    Just my take.

  22. I am still seeking a normal human being, never mind normal temperature. Of course using myself as the baseline for “normal” has led to some inherent difficulties.

  23. Than god that the El Ninometer is at 1.1 else we’d be turning up the thermostat.

  24. Not sure where they get that +2ºc blob over Spain from. It never seemed to be that warm. These are just the simple mean temperatures from Wunderground:
    Valencia
    Year …. Max …. Avg …. Min
    2015 …. 21 …. 16 …. 11
    2014 …. 23 …. 18 …. 13
    2013 …. 21 …. 15 …. 8
    2012 …. 21 …. 17 …. 13
    2011 …. 24 …. 17 …. 14
    2010 …. 19 …. 15 …. 11
    2009 …. 18 …. 14 …. 8
    2008 …. 21 …. 17 …. 8
    Avge …. 21 …. 16 …. 11
    Same goes for Madrid too, which was slightly cooler than average.
    Madrid
    Year …. Max …. Avg …. Min
    2015 …. 17 …. 14 …. 7
    2014 …. 20 …. 16 …. 11
    2013 …. 18 …. 12 …. 5
    2012 …. 14 …. 11 …. 7
    2011 …. 19 …. 16 …. 11
    2010 …. 20 …. 14 …. 9
    2009 …. 16 …. 11 …. 7
    2008 …. 19 …. 13 …. 8
    Avge …. 18 …. 13 …. 8
    I certainly see nothing here that is 2ºc warmer. I presume that Lower Troposphere will equate well with surface temps – or is that too simplistic? The winds were easterly and noreasterly for much of the time, so I cannot see the lower troposphere being warm.
    R

  25. 7/100 of a degree above normal? That is, if one defines the 1981-2010 baseline as normal. That time period makes a nice 30 year baseline for a dataset that only exists for 1979 to now, but it seems a stretch to call that normal.

    • Normal is based on the past 30 years. It will be updated. But you do understand why they chose is like this right? In case you don’t, it’s because you’re right, there’s no normal per se, but we need a baseline to identify trends.

  26. There is no such thing as “normal”…we can calculate an “average”, or a “mean” …referring as “normal” then means everyday is “abnormal”. Please stop using “normal”

  27. If one wishes to gain a “heads-up” as to imminent developments in ENSO and possible beginnings of an el Nino or La Nina event, I would advise turning to the Peruvian anchovy as an important but often overlooked oracle to the oceanography of the anchovy’s home ocean, the Pacific.
    The Peruvian anchovy or “anchoveta” is an important fish to the global economy and to the diet of most of us. It is the world’s single largest fishery by landed tonnage, and is a principal component of fishmeal which is a major agricultural feed for farmed fish and animals. One can even order them direct as a pizza ingredient (the “Napoli” pizza for instance).
    http://en.wikipedia.org/wiki/Peruvian_anchoveta
    The anchovy is a filter feeder like a mini-whale, swimming with its mouth agape like a Guardian-reading greenie. This is the key to its huge success in exploiting the massive plankton productivity of the equatorial eastern Pacific off the coast of Peru. It is the archetypal pelagic (free-swimming) filter-feeder.
    http://i60.tinypic.com/2a8oj60.jpg
    The anchovy (E. ringens) is a pelagic filter-feeder – there are lots of them off the coast of Peru.
    Anchovy – the ENSO fish
    The Latin classification of the Peruvian anchoveta is Engraulis ringens (Jenyns, 1842). Like almost no other species on earth (certainly not your average Homo) the anchovy has an astonishing and profound instinctive knowledge of the ebb and flow of the El Niño Southern Oscillation – the ENSO. One could indeed reasonably call the anchovy the “ENSO fish”. The migrations, dispersals and gatherings, and year to year biomass peaks and crashes of the anchovy fishery in the eastern Pacific off Peru are tuned with exquisite sensitivity to ENSO itself. In particular it is the Peruvian upwelling, one side of the Bjerknes feedback (the other being the trade winds) which both couple intermittently to provide the bursts of positive feedback that drive El Niño and La Nina episodes. These two systems are characterised by weakening and strengthening respectively of this upwelling.
    The first to know of any developments in the dark deep ocean currents way off the Peruvian coast, signifying portentous shifts in the upwelling stemming from the Humboldt current from Antarctica, is Engraulis the anchovy. Long before any clanking crass fish-imitating Argo floats (and their data-bothering PhD students), before any TAU or TRITON moored bathyscaphes, or satellite imagery, still longer before any armchair climate punditry, the anchovies respond in real time to upwelling changes with variations in the first-feeding survival and size of their juvenile year classes and their spatial distributions. Thus it was inevitably the Peruvian fishermen, heirs of the ocean abundance provided by E. ringens, who were discoverers of what they called El Niño (“the boy” in Spanish), the periodic anomalous warming of the eastern Pacific surface waters. This event is accompanied by a crash in the anchoveta numbers and catches, and typically occurs in December-January, the time of the celebration by the Christian Church of Christmas, the incarnation of the Christ-child.
    El Niño is bad for the Peruvian fishermen since it is bad for the anchovy. Why then, one must speculate, did the Peruvians name this cursed event after the divine infant of their religion? Was there a streak of resentment or protest against their Catholic faith and its priests and offices? Or, perhaps, were so many fisherman heard to shout in frustration “Oh Cristo! Su cálida de nuevo!” (Oh Christ! – it’s warm again!) – like skeptical WUWT posters after every uptick in the global temperature anomaly – that the event became named after the blasphemously invoked member of the Holy Trinity.
    The baleful influence of El Niño on the anchoveta is related to the transport of nutrients from deep to surface waters which accompanies upwelling, and which fuels the phytoplankton bloom which in turn provides the primary production which nourishes the vast shoals of anchovy which teem off Peru’s coastline and in fishermen’s nets. This is basic first-year marine biology. Primary production, the photosynthetic algal base of the marine food chain, is nutrient limited and thus one talks of blooms, and also of “bloom-and-bust”, as for example with spring sunshine, in temperate waters, the phytoplankton first grow rapidly but then run out of nutrients and die back abruptly (Paul Ehrlich should have been a marine biologist).
    This is why coastal regions are the most biologically productive seas where ocean floor topography causes the upwelling essential to bring nutrient rich cooler bottom water up to fertilise the depleted upper layers. The vast expanses of the oceans by contrast have nutrient limited surface water – therefore the strikingly visible transition from green to blue colour of the sea as you move from fertile coastal water to the barren ocean deeps. The world’s most productive seas are in places such as the south west coast of Africa and, biggest of all, the Peruvian west coast of south America, where cold deep water originating in Antarctica and the Humboldt current wells up to sustain the world’s largest fishery, that of Engraulis ringens the anchovy.
    http://i57.tinypic.com/1zv2xww.jpg
    http://i61.tinypic.com/312iozs.jpg
    Microscope images of phytoplankton single-celled algae, foundation of the marine food pyramid. They are beautifully sculpted microscopic creatures with exotic names like diatoms (upper) and foraminiferans (lower) as well as and radiolarians, dinoflagellates and coccolithophores.
    In the presence of this upwelling, the east equatorial Pacific is cooler than surface waters further west, setting up a temperature and pressure gradient that drives the prevailing pattern of trade winds, the east to west (“easterly”) winds that for millennia have carried intrepid human seafarers from the Americas to populate the Pacific islands. As well as being impelled by this sea surface temperature difference, the trade winds further amplify the eastern Pacific upwelling by dragging the surface water westward, and this reinforcing positive feedback – the Bjerknes feedback – lies at the heart of the El Niño southern oscillation (ENSO).
    However, this positive feedback can cut both ways. From time to time, initiated by no-one knows quite what (although hypotheses abound and swarm like the anchovies themselves) Kelvin waves of warm water surge eastward, interrupting the Peruvian upwelling. This warms the east Pacific surface water, reducing the temperature gradient on which the trade winds depend and thus choking them off, resulting in the dreaded “doldrums” – no wind and reduced upwelling off Peru. This slackening part of the Bjerknes feedback is the El Niño event. And in turn, the reduced upwelling is bad news for the anchovy as he has to stay deeper to access life-giving nutrients, and the Peruvian fishermen once more cry “O Cristo – El Niño!”.
    El Niño now? What does the anchovy have to say?
    So what significance does all this have to the current conditions in the Pacific? For more than a year now, ENSO-watchers have been on the edge of their seats waiting expectantly for El Niño to arrive (I call this “waiting for el Ninot”, theatrically adapted from http://samuel-beckett.net/Waiting_for_Godot_Part1.html ).
    But El Niño has stubbornly resisted all entreaties to manifest itself like in the good old days of 1998 and even 2010. Now, again, the Nina3.4 index is rising into what on paper is El Niño territory so that those who feel the need, can proclaim that El Niño is here. But something is missing.
    The problem is that the anchovy, the ENSO fish, does not seem to agree that El Niño is here. The latest on the Peruvian anchovy fishery can be found in the following article from the website “Undercurrent News” which gives up to the minute news on fisheries and fish markets around the world:
    http://www.undercurrentnews.com/2015/04/24/peru-fishmeal-trading-on-hold-as-market-players-await-price-correction/
    What is happening is this. Last year, the abortive El Niño conditions pushed the Peruvian fishery authorities to suspend anchovy fishing due to fears that a developing El Niño could cause a decline in anchovy numbers that would make the fishery susceptible to over-fishing. The Peruvian anchovy fishery is closely managed, in the wake of the famous and spectacular crashes of the fishery in the 1970’s and especially in 1982-83 caused by a combination of a strong El Niño event and poorly managed massive seine-net over-fishing. Despite strengthened fishery management following those crashes, the record-breaking El Niño in 1997-1998 again hit the fishery hard with significant societal impacts for Peru.
    http://www.ucar.edu/communications/gcip/m12anchovy/m12html.html#6_4
    So early this year, in the month of January-February when an annually phase-locked El Niño by rights ought to occur, Peruvian fishery ministry survey boats tentatively checked out the anchovy fishery – how many shoals of anchovy were out there, and where? What they found was that in spite of all the feverish talk of El Niño, the anchovy fishery was in surprising rude health. This caused them to cancel a previously considered suspension of the whole fishing season (a relatively frequent occurrence for the anchovy fishermen of Peru) and allow a full quota season to proceed.
    http://i57.tinypic.com/2i1fhnb.jpg
    Seine-net industral fishing for anchovy off Peru.
    The latest news as of April 24 is that the fishing fleet is proceeding quite rapidly toward catching the entire season quota of anchoveta. However what is also interesting is what the fish meal market is doing. As mentioned in the introduction, the Peruvian anchovy dominates the global supply of prime fish meal and, as might be expected, China dominates the demand. When there is a discrepancy between what a commodity is expected to do and what it actually does, markets sometimes pause to take stock and see what will happen. Right now, contrary to predictions of the fishery being hit by the long-expected El Niño, the fishery is strong and sustaining high catch volumes. Since this will cause the price to decline, the market is anticipating this and holding back on prime fishmeal orders. In the words of a Peruvian exporter:
    “We don’t want to take risks and close at a price now, as we don’t know the development of the fishing season. We hope to finish the fishing season in May, a month earlier than it is supposed to end, as catches are good so far.”
    Of course, there is still the expectation of renewed surges of Kelvin waves and the final, long awaited epiphany of El Niño. This is causing uncertainty among those with an interest in the fishery since on the one hand, it is currently in robust health, but on the other, there is this ongoing expectation of el Niño crashing in to spoil the party.
    In my view, however, the continued strength of the anchovy fishery indicates that upwelling is still strong and yet to be interrupted by Kelvin waves and a nascent el Niño. It is possible that the inception of a proper, full-on el Niño requires not just meteorological conditions or other surface factors, but a simultaneous development in the ocean currents and mixing, linked to the thermohaline ocean circulation, to entrain the Bjerknes feedback to trigger a pause in the upwelling.
    Conclusion
    My conclusion is just this – if we are interested in the ENSO status of the Pacific and what might lie ahead, where better to turn than the wise and all-knowing Engraulis ringens?
    Therefore – might it be an idea to add, to the already impressive resources of climate reference information (ocean, atmosphere, ice, sun, magnetism etc.) at WUWT, a link to the spot price of prime fishmeal, and the latest on the Peruvian anchovy?

  28. As usual, much ado about nothing. Next thing you’ll have kittens about is how today’s Temps are cooler than yesterdays temps, and how that debunks AGW.
    Sheesh.

  29. The world temperature anomaly map (not the glowing coals we see from NOAA, NASA, etc), is a perfect example of negative feedbacks. Note the cooling around the equatorial zone where 80% of the solar energy is imparted to the earth. Were it not for strong negative feedback this picture would not be possible. Note the anomalously warm regions are the temperate to polar which only get 20% of the suns energy. The polar regions are receivers and emitters of heat to outer space.
    I was in Lagos, Nigeria – 4 degrees north of the equator in 1965 and the temperature was, basically the same then as now. I visited it again in 1998 and the temperature was once again about the same. Here, from 1949 if you want to see a narrow temp variation:
    https://weatherspark.com/history/28568/1949/Ikeja-Lagos-Nigeria
    ” The hottest day of 1949 was March 24, with a high temperature of 34°C. For reference, on that day the average high temperature is 33°C and the high temperature exceeds 34°C only one day in ten. The hottest month of 1949 was March with an average daily high temperature of 33°C.”
    And:
    “The coldest day of 1949 was September 23, with a low temperature of 22°C. For reference, on that day the average low temperature is 24°C and the low temperature drops below 23°C only one day in ten. The coldest month of 1949 was February with an average daily low temperature of 24°C.”
    And today in May 2015 (an intermediately warm month)?
    High 32 low 24/25 !!
    I would like to note that the population of Lagos in 1960 was <800,000 and in 2015 it was 23 million. There is NO UHI IN LAGOS, NIGERIA DESPITE A 30-FOLD INCREASE IN POPULATION. In the ITCZ (equatorial topics), no matter where the heat comes from, a negative feedback gets rid of it. Is this something noted by climate science before? No UHI in the tropics.

  30. Are you going to post every time there’s a colder month? Seriously, what kind of website is this… It’s called CLIMATE not WEATHER!!

    • Look above to compare the ice cover in May 2014 and 2015 in the northern hemisphere. It is important how much ice and snow will melt until September.

    • There is a WUWT post with every month’s global temperature update.
      Just learn to take the rough with the smooth.

    • “…Its called CLIMATE not WEATHER!!”
      Please mention this to the main stream media, which includes all of the liberal/progressive weather “information” sites (e.g. “Weather Underground” and “The Weather Channel”). Thanks!

  31. March temperatures (revised):
    Global Composite: +0.26 C above 30-year average Northern Hemisphere: +0.41 C above 30-year average Southern Hemisphere: +0.11 C above 30-year average
    ————-
    Shouldn’t “30-year average Southern Hemisphere: +0.11” be “-.11” which would properly calculate the +.26 c above 30 -year average??? Am I just confused?

  32. Thanks, Eliza. We get what we pay. But we didn’t pay for THAT.
    Best regards – Hans

  33. wall street is a subsystem of north america is a subsystem of the globe is a subsystem of the sun system is a subs….
    Sole Models, operating just 1 hedgefond sustainable – where to buy?
    ____
    incremented to / incremented to / inc…. where to buy?

  34. you see the consequences – that modelling wall street, for nix, ruins wall street competitors to nix.
    And all them metasystem heading metasystem heading …
    ____
    the winner always is the 1st winner of 1 small advantage.

  35. 7/100ths of a degree!!!!! In some places like Alice Springs, the temperature in winter can vary by 20 degrees in a day starting off cold early in the morning to warm by lunch time. And people worry about 7/100ths of a degree determined only by arithmetic calculation because it is undetectable on a thermometer.

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