August 2016 Global Surface (Land+Ocean) and Lower Troposphere Temperature Anomaly Update

Guest Post by Bob Tisdale

This post provides updates of the values for the three primary suppliers of global land+ocean surface temperature reconstructions—GISS through August 2016 and HADCRUT4 and NCEI (formerly NCDC) through July 2016—and of the two suppliers of satellite-based lower troposphere temperature composites (RSS and UAH) through August 2016.  It also includes a few model-data comparisons.

This is simply an update, but it includes a good amount of background information for those new to the datasets. Because it is an update, there is no overview or summary for this post.  There are, however, summaries for the individual updates. So for those familiar with the datasets, simply fast-forward to the graphs and read the summaries under the heading of “Update”.  

(I’m still on holiday, so I may not get a chance to respond to comments.)


We discussed and illustrated the impacts of the adjustments to surface temperature data in the posts:

The NOAA NCEI product is the new global land+ocean surface reconstruction with the manufactured warming presented in Karl et al. (2015).  For summaries of the oddities found in the new NOAA ERSST.v4 “pause-buster” sea surface temperature data see the posts:

Even though the changes to the ERSST reconstruction since 1998 cannot be justified by the night marine air temperature product that was used as a reference for bias adjustments (See comparison graph here), and even though NOAA appears to have manipulated the parameters (tuning knobs) in their sea surface temperature model to produce high warming rates (See the post here), GISS also switched to the new “pause-buster” NCEI ERSST.v4 sea surface temperature reconstruction with their July 2015 update.

The UKMO also recently made adjustments to their HadCRUT4 product, but they are minor compared to the GISS and NCEI adjustments.

We’re using the UAH lower troposphere temperature anomalies Release 6.5 for this post even though it’s in beta form.  And for those who wish to whine about my portrayals of the changes to the UAH and to the GISS and NCEI products, see the post here.

The GISS LOTI surface temperature reconstruction and the two lower troposphere temperature composites are for the most recent month.  The HADCRUT4 and NCEI products lag one month.

Much of the following text is boilerplate that has been updated for all products. The boilerplate is intended for those new to the presentation of global surface temperature anomalies.

Most of the graphs in the update start in 1979.  That’s a commonly used start year for global temperature products because many of the satellite-based temperature composites start then.

We discussed why the three suppliers of surface temperature products use different base years for anomalies in chapter 1.25 – Many, But Not All, Climate Metrics Are Presented in Anomaly and in Absolute Forms of my free ebook On Global Warming and the Illusion of Control – Part 1 (25MB).

Since the July 2015 update, we’re using the UKMO’s HadCRUT4 reconstruction for the model-data comparisons using 61-month filters.

And I’ve resurrected the model-data 30-year trend comparison using the GISS Land-Ocean Temperature Index (LOTI) data.

For a continued change of pace, let’s start with the lower troposphere temperature data.  I’ve left the illustration numbering as it was in the past when we began with the surface-based data.


Special sensors (microwave sounding units) aboard satellites have orbited the Earth since the late 1970s, allowing scientists to calculate the temperatures of the atmosphere at various heights above sea level (lower troposphere, mid troposphere, tropopause and lower stratosphere). The atmospheric temperature values are calculated from a series of satellites with overlapping operation periods, not from a single satellite. Because the atmospheric temperature products rely on numerous satellites, they are known as composites. The level nearest to the surface of the Earth is the lower troposphere. The lower troposphere temperature composite include the altitudes of zero to about 12,500 meters, but are most heavily weighted to the altitudes of less than 3000 meters.  See the left-hand cell of the illustration here.

The monthly UAH lower troposphere temperature composite is the product of the Earth System Science Center of the University of Alabama in Huntsville (UAH). UAH provides the lower troposphere temperature anomalies broken down into numerous subsets.  See the webpage here.  The UAH lower troposphere temperature composite are supported by Christy et al. (2000) MSU Tropospheric Temperatures: Dataset Construction and Radiosonde Comparisons.  Additionally, Dr. Roy Spencer of UAH presents at his blog the monthly UAH TLT anomaly updates a few days before the release at the UAH website.  Those posts are also regularly cross posted at WattsUpWithThat.  UAH uses the base years of 1981-2010 for anomalies. The UAH lower troposphere temperature product is for the latitudes of 85S to 85N, which represent more than 99% of the surface of the globe.

UAH recently released a beta version of Release 6.0 of their atmospheric temperature product. Those enhancements lowered the warming rates of their lower troposphere temperature anomalies.  See Dr. Roy Spencer’s blog post Version 6.0 of the UAH Temperature Dataset Released: New LT Trend = +0.11 C/decade and my blog post New UAH Lower Troposphere Temperature Data Show No Global Warming for More Than 18 Years. The UAH lower troposphere anomaly data, Release 6.5 beta, through August 2016 are here.

Update:  The August 2016 UAH (Release 6.5 beta) lower troposphere temperature anomaly is +0.44 deg C.  It made a uptick in August (an increase of about +0.05 deg C).


Figure 4 – UAH Lower Troposphere Temperature (TLT) Anomaly Composite – Release 6.5 Beta


Like the UAH lower troposphere temperature product, Remote Sensing Systems (RSS) calculates lower troposphere temperature anomalies from microwave sounding units aboard a series of NOAA satellites. RSS describes their product at the Upper Air Temperature webpage.   The RSS product is supported by Mears and Wentz (2009) Construction of the Remote Sensing Systems V3.2 Atmospheric Temperature Records from the MSU and AMSU Microwave Sounders. RSS also presents their lower troposphere temperature composite in various subsets. The land+ocean TLT values are here.  Curiously, on that webpage, RSS lists the composite as extending from 82.5S to 82.5N, while on their Upper Air Temperature webpage linked above, they state:

We do not provide monthly means poleward of 82.5 degrees (or south of 70S for TLT) due to difficulties in merging measurements in these regions.

Also see the RSS MSU & AMSU Time Series Trend Browse Tool. RSS uses the base years of 1979 to 1998 for anomalies.

Note:  RSS recently release new versions of the mid-troposphere temperature and lower stratosphere temperature (TLS) products.  So far, their lower troposphere temperature product has not been updated to this new version.

Update:  The August 2016 RSS lower troposphere temperature anomaly is +0.46 deg C.  It dropped very slightly (it’s basically unchanged with a decline of only -0.01 deg C) since July 2016.


Figure 5 – RSS Lower Troposphere Temperature (TLT) Anomalies


Introduction: The GISS Land Ocean Temperature Index (LOTI) reconstruction is a product of the Goddard Institute for Space Studies.  Starting with the June 2015 update, GISS LOTI uses the new NOAA Extended Reconstructed Sea Surface Temperature version 4 (ERSST.v4), the pause-buster reconstruction, which also infills grids without temperature samples.  For land surfaces, GISS adjusts GHCN and other land surface temperature products via a number of methods and infills areas without temperature samples using 1200km smoothing. Refer to the GISS description here.   Unlike the UK Met Office and NCEI products, GISS masks sea surface temperature data at the poles, anywhere seasonal sea ice has existed, and they extend land surface temperature data out over the oceans in those locations, regardless of whether or not sea surface temperature observations for the polar oceans are available that month.  Refer to the discussions here and here. GISS uses the base years of 1951-1980 as the reference period for anomalies.  The values for the GISS product are found here. (I archived the former version here at the WaybackMachine.)

Update:  The August 2016 GISS global temperature anomaly is +0.98 deg C. According to the GISS LOTI data, global surface temperature anomalies made a noticeable uptick in August, a +0.13 deg C increase.


Figure 1 – GISS Land-Ocean Temperature Index


NOTE:  The NCEI only produces the product with the manufactured-warming adjustments presented in the paper Karl et al. (2015). As far as I know, the former version of the reconstruction is no longer available online. For more information on those curious NOAA adjustments, see the posts:

And more recently:

Introduction: The NOAA Global (Land and Ocean) Surface Temperature Anomaly reconstruction is the product of the National Centers for Environmental Information (NCEI), which was formerly known as the National Climatic Data Center (NCDC).  NCEI merges their new “pause buster” Extended Reconstructed Sea Surface Temperature version 4 (ERSST.v4) with the new Global Historical Climatology Network-Monthly (GHCN-M) version 3.3.0 for land surface air temperatures. The ERSST.v4 sea surface temperature reconstruction infills grids without temperature samples in a given month.  NCEI also infills land surface grids using statistical methods, but they do not infill over the polar oceans when sea ice exists.  When sea ice exists, NCEI leave a polar ocean grid blank.

The source of the NCEI values is through their Global Surface Temperature Anomalies webpage.  Click on the link to Anomalies and Index Data.)

Update: The July 2016 NCEI global land plus sea surface temperature anomaly was +0.87 deg C.  See Figure 2. It decreased slightly (a drop of about -0.03 deg C) since June 2016.


Figure 2 – NCEI Global (Land and Ocean) Surface Temperature Anomalies


Introduction: The UK Met Office HADCRUT4 reconstruction merges CRUTEM4 land-surface air temperature product and the HadSST3 sea-surface temperature (SST) reconstruction.  CRUTEM4 is the product of the combined efforts of the Met Office Hadley Centre and the Climatic Research Unit at the University of East Anglia. And HadSST3 is a product of the Hadley Centre.  Unlike the GISS and NCEI reconstructions, grids without temperature samples for a given month are not infilled in the HADCRUT4 product.  That is, if a 5-deg latitude by 5-deg longitude grid does not have a temperature anomaly value in a given month, it is left blank. Blank grids are indirectly assigned the average values for their respective hemispheres before the hemispheric values are merged.  The HADCRUT4 reconstruction is described in the Morice et al (2012) paper here.  The CRUTEM4 product is described in Jones et al (2012) here. And the HadSST3 reconstruction is presented in the 2-part Kennedy et al (2012) paper here and here.  The UKMO uses the base years of 1961-1990 for anomalies.  The monthly values of the HADCRUT4 product can be found here.

Update (Lags One Month):  The July 2016 HADCRUT4 global temperature anomaly is +0.74 deg C. See Figure 3.  It is unchanged from June to July 2016.

03-hadcrut4Figure 3 – HADCRUT4


The GISS, HADCRUT4 and NCEI global surface temperature anomalies and the RSS and UAH lower troposphere temperature anomalies are compared in the next three time-series graphs. Figure 6 compares the five global temperature anomaly products starting in 1979.  Again, due to the timing of this post, the HADCRUT4 and NCEI updates lag the UAH, RSS, and GISS products by a month. For those wanting a closer look at the more recent wiggles and trends, Figure 7 starts in 1998, which was the start year used by von Storch et al (2013) Can climate models explain the recent stagnation in global warming?  They, of course, found that the CMIP3 (IPCC AR4) and CMIP5 (IPCC AR5) models could NOT explain the recent slowdown in warming, but that was before NOAA manufactured warming with their new ERSST.v4 reconstruction…and before the strong El Niño of 2015/16.

Figure 8 starts in 2001, which was the year Kevin Trenberth chose for the start of the warming slowdown in his RMS article Has Global Warming Stalled?

Because the suppliers all use different base years for calculating anomalies, I’ve referenced them to a common 30-year period: 1981 to 2010.  Referring to their discussion under FAQ 9 here, according to NOAA:

This period is used in order to comply with a recommended World Meteorological Organization (WMO) Policy, which suggests using the latest decade for the 30-year average.

The impacts of the unjustifiable adjustments to the ERSST.v4 reconstruction are visible in the two shorter-term comparisons, Figures 7 and 8.  That is, the short-term warming rates of the new NCEI and GISS reconstructions are noticeably higher than the HADCRUT4 data.  See the June 2015 update for the trends before the adjustments.


Figure 6 – Comparison Starting in 1979



Figure 7 – Comparison Starting in 1998



Figure 8 – Comparison Starting in 2001

Note also that the graphs list the trends of the CMIP5 multi-model mean (historic through 2005 and RCP8.5 forcings afterwards), which are the climate models used by the IPCC for their 5th Assessment Report.  The metric presented for the models is surface temperature, not lower troposphere.


Figure 9 presents the average of the GISS, HADCRUT and NCEI land plus sea surface temperature anomaly reconstructions and the average of the RSS and UAH lower troposphere temperature composites.  Again because the HADCRUT4 and NCEI products lag one month in this update, the most current monthly average only includes the GISS product.


Figure 9 – Average of Global Land+Sea Surface Temperature Anomaly Products


As noted above, the models in this post are represented by the CMIP5 multi-model mean (historic through 2005 and RCP8.5 forcings afterwards), which are the climate models used by the IPCC for their 5th Assessment Report.

Considering the uptick in surface temperatures in 2014, 2015 and now 2016 (see the posts here and here), government agencies that supply global surface temperature products have been touting “record high” combined global land and ocean surface temperatures. Alarmists happily ignore the fact that it is easy to have record high global temperatures in the midst of a hiatus or slowdown in global warming, and they have been using the recent record highs to draw attention away from the difference between observed global surface temperatures and the IPCC climate model-based projections of them.

There are a number of ways to present how poorly climate models simulate global surface temperatures.  Normally they are compared in a time-series graph.  See the example in Figure 10. In that example, the UKMO HadCRUT4 land+ocean surface temperature reconstruction is compared to the multi-model mean of the climate models stored in the CMIP5 archive, which was used by the IPCC for their 5th Assessment Report. The reconstruction and model outputs have been smoothed with 61-month running-mean filters to reduce the monthly variations.  The climate science community commonly uses a 5-year running-mean filter (basically the same as a 61-month filter) to minimize the impacts of El Niño and La Niña events, as shown on the GISS webpage here. Using a 5-year running mean filter has been commonplace in global temperature-related studies for decades. (See Figure 13 here from Hansen and Lebedeff 1987 Global Trends of Measured Surface Air Temperature.)  Also, the anomalies for the reconstruction and model outputs have been referenced to the period of 1880 to 2013 so not to bias the results.  That is, by using the almost the full term of the data, no one with the slightest bit of common sense can claim I’ve cherry picked the base years for anomalies with this comparison.


Figure 10

It’s very hard to overlook the fact that, over the past decade, climate models are simulating way too much warming…even with the small recent El Niño-related uptick in the data.

Another way to show how poorly climate models perform is to subtract the observations-based reconstruction from the average of the model outputs (model mean). We first presented and discussed this method using global surface temperatures in absolute form. (See the post On the Elusive Absolute Global Mean Surface Temperature – A Model-Data Comparison.)  The graph below shows a model-data difference using anomalies, where the data are represented by the UKMO HadCRUT4 land+ocean surface temperature product and the model simulations of global surface temperature are represented by the multi-model mean of the models stored in the CMIP5 archive. Like Figure 10, to assure that the base years used for anomalies did not bias the graph, the full term of the graph (1880 to 2013) was used as the reference period.

In this example, we’re illustrating the model-data differences smoothed with a 61-month running mean filter. (You’ll notice I’ve eliminated the monthly data from Figure 11. Example here.  Alarmists can’t seem to grasp the purpose of the widely used 5-year (61-month) filtering, which as noted above is to minimize the variations due to El Niño and La Niña events and those associated with catastrophic volcanic eruptions.)


Figure 11

The difference now between models and data is almost worst-case, comparable to the difference at about 1910. 

There was also a major difference, but of the opposite sign, in the late 1880s. That difference decreases drastically from the 1880s and switches signs by the 1910s.  The reason:  the models do not properly simulate the observed cooling that takes place at that time.  Because the models failed to properly simulate the cooling from the 1880s to the 1910s, they also failed to properly simulate the warming that took place from the 1910s until the 1940s. (See Figure 12 for confirmation.) That explains the long-term decrease in the difference during that period and the switching of signs in the difference once again.  The difference cycles back and forth, nearing a zero difference in the 1980s and 90s, indicating the models are tracking observations better (relatively) during that period. And from the 1990s to present, because of the slowdown in warming, the difference has increased to greatest value ever…where the difference indicates the models are showing too much warming.

It’s very easy to see the recent record-high global surface temperatures have had a tiny impact on the difference between models and observations.

See the post On the Use of the Multi-Model Mean for a discussion of its use in model-data comparisons.


Yet another way to show how poorly climate models simulate surface temperatures is to compare 30-year running trends of global surface temperature data and the model-mean of the climate model simulations of it. See Figure 12. In this case, we’re using the global GISS Land-Ocean Temperature Index for the data.  For the models, once again we’re using the model-mean of the climate models stored in the CMIP5 archive with historic forcings to 2005 and worst case RCP8.5 forcings since then.


Figure 12

There are numerous things to note in the trend comparison. First, there is a growing divergence between models and data starting in the early 2000s. The continued rise in the model trends indicates global surface warming is supposed to be accelerating, but the data indicate little to no acceleration since then. Second, the plateau in the data warming rates begins in the early 1990s, indicating that there has been very little acceleration of global warming for more than 2 decades.  This suggests that there MAY BE a maximum rate at which surface temperatures can warm. Third, note that the observed 30-year trend ending in the mid-1940s is comparable to the recent 30-year trends. (That, of course, is a function of the new NOAA ERSST.v4 data used by GISS.)  Fourth, yet that high 30-year warming ending about 1945 occurred without being caused by the forcings that drive the climate models.  That is, the climate models indicate that global surface temperatures should have warmed at about a third that fast if global surface temperatures were dictated by the forcings used to drive the models. In other words, if the models can’t explain the observed 30-year warming ending around 1945, then the warming must have occurred naturally. And that, in turns, generates the question: how much of the current warming occurred naturally? Fifth, the agreement between model and data trends for the 30-year periods ending in the 1960s to about 2000 suggests the models were tuned to that period or at least part of it. Sixth, going back further in time, the models can’t explain the cooling seen during the 30-year periods before the 1920s, which is why they fail to properly simulate the warming in the early 20th Century.

One last note, the monumental difference in modeled and observed warming rates at about 1945 confirms my earlier statement that the models can’t simulate the warming that occurred during the early warming period of the 20th Century.


The most recent sea surface temperature update can be found here.  The satellite-enhanced sea surface temperature composite (Reynolds OI.2) are presented in global, hemispheric and ocean-basin bases.


We discussed the recent record-high global sea surface temperatures for 2014 and 2015 and the reasons for them in General Discussions 2 and 3 of my recent free ebook On Global Warming and the Illusion of Control (25MB).   The book was introduced in the post here (cross post at WattsUpWithThat is here).


80 thoughts on “August 2016 Global Surface (Land+Ocean) and Lower Troposphere Temperature Anomaly Update

  1. Lots of good stuff thanks for posting these updates.

    The land portion of GISS and HADCRUT use Min Max values to produce temperature averages which is what’s presented in their data sets.

    One Mr. Tony Heller on his blog constantly and consistently hammers away at the summer time Maximums which in many if not most cases have decreased over the last several decades. Any warming that has occurred mostly comes from the Minimum temperature of the day. Night time humidity and afternoon rains must certainly be a contributing factor to that observation. Indeed, a check of NOAA’s Climate at a Glance confirms the general increase in precipitation.

    But, we are treated almost daily to stories in the press about drought and the hottest ever months and years when anyone who goes outside once in a while knows that these types of reports aren’t really true. There seems to be a disconnect between reality and what we’re being told.

    • anyone who goes outside once in a while knows that these types of reports aren’t really true

      Based on my experience, it’s been getting colder on both sides of the North Atlantic over the past 7-10 years. On the east side of the pond, in addition to my overall impressions (like there being no real spring some years – and cool summers the past 3 years), I’ve seen real snowfall where I am during the past 5 years (but not this past winter) – while snow here was unthinkable 10-15 years ago. So I’m pretty sure my impressions aren’t ‘psychosomatic’. So unless someone can explain to me how a pretty good swath of earth became detached from the world climate system, I’d have to agree with this statement:

      There seems to be a disconnect between reality and what we’re being told.

    • Hi Steve,
      As you stated night temperatures are rising. Hence even if daytime temperatures are falling the average
      temperature overall can still be increasing. This then gives rise to the disconnect you see between “reality”
      and what you are being told. Perhaps if you went out more at night you might notice more of a change.

      • Diurnal rates of change in temperature is interesting. If…I say if, CO2 was a major contribution, then the influence should be the same on both day and night. But no, they show divergent rates. Hmmmm.

      • Macha,
        the statement that CO2 should have a similar effect during the day and night is
        I think false. CO2 and other greenhouse gases stop the earth from cooling rather
        than causing it to heat up. Daytime temperatures are determined by the number of
        sunlight hours. The amount of cooling at night then depends strongly on clouds and other
        insulators such as CO2. Thus if CO2 is warming the earth then we would expect night time temperatures to warm more (actually cool less) than daytime temperatures.

  2. Question from a layperson: in Figure 9, why does the green line (avg land, air and sea surface) show so small an impact from the 97/98 El Nino? I thought that was a big one by historical standards, and not dramatically smaller than the most recent El Nino (which the green line does show as quite large in terms of warming impact). In contrast, the satellite datasets appear to show the two El Ninos as comparable in impact.

  3. As I understand it, the ‘warmest year ever’ was mainly due to parts of the Arctic being 10˚C above average in February… i.e. the temperature in Siberia jumped to MINUS 12˚C when it would have normally been MINUS 22˚C. Anyone with any knowledge of the mechanics of heat transfer would understand that the winter warming of the Arctic was in fact a major cooling event. (i.e.the incursion of large amounts of warmer wetter air into a frigid zone, with resultant snowfall/frost.)
    The ‘measurement’ we’re being offered does not represent this.
    As long as we accept their preposterous graphs of ‘global’ ‘temperature’ without appropriate caveats then we are simply playing the Warmist Game.

  4. August was dominated by unusual warmth (or less cold) in Antarctica, following a cold July. This is reflected differently in different indices, as I’ve discussed here. The satellites have poor coverage near poles. GISS is normally sensitive to Antarctica and rose by 0.13°C, but as commenter Olof noted at Moyhu, they seem for some reason to be missing the S Pole (Amundsen-Scott), which was 4°C above normal. My TempLS index (above link) rose by 0.21°C (mostly due to Antarctica), and BEST land/ocean. rose by 0.22°C. I would expect NOAA and HADCRUT to be less sensitive to Antarctica than GISS.

    • Nick,
      Any ideas on a mechanism that could create this most unusual S Pole anomaly?
      If it is connected with the 2015_6 temperature peak elsewhere, it is hard to see its influence move so quickly to such a remote site protected by miles of cold ice and circum-polar winds, while the stations on the fringe of the Antarctic landmass do not show such a strong anomaly, if any.
      Such a difficult anomaly to envision with global warming hypotheses, esp if it is correct that more GHG will lower temperatures over the ice mass which is cooler than the air above most of the time.
      And Australia not warming very much at all in the UAH satellite era.
      Can we rule out GHG/ global warming hypotheses? I think so, but I don’t know so.

      • A first response to
        And Australia not warming very much at all in the UAH satellite era

        Having a look at

        you can see that UAH6.0’s globe trend for the satellite era is at 0.12 ± 0.01 °C / decade, while for Australia it is at 0.15 ± 0.03 °C, i.e. about 25% higher.

        So yes: it warms a little bit in Downunder, even if by far not as much as in the arctic region with 0.24 ± 0.02 °C / decade. And the obsolete RSS3.3 TLT gives even this:

      • Bind,
        Why not compare land with land ?
        Australian trend is till way below the forecasts of many and GCMs.
        And most of the warming is of Tmin.
        And anyhow, rainfall affects the BOM temperature readings, water cools.
        No significant evidence of global warming for Australia in the satellite era.

      • Geoff,
        “Any ideas on a mechanism that could create this most unusual S Pole anomaly?”
        No. It’s just that one warm month, so far. Antarctica had been unusually cold, which is why the change made a big increase to the global. Here (from here, scroll frame down) is a graph of the contributions of various regions to recent monthly averages. Antarctica is the light blue:

      • Thanks Nick.
        But even if it is one warm month, there still has to be a mechanism to get the extra energy to the South Pole. Or a reduction in outgoing. It seems an unlikely location for an anomaly given the thermal inertia of that great glob of ice sitting on the Plateau surrounded by protective winds and a thin atmosphere that would have to work hard to counter the ice.

      • All things weather and temperature in Antarctica can be explained by ozone at https:\\ The vortex is truly amazing in that some atmospheric levels are warmer in winter than summer. No UV there then

      • Macha,
        I have been reading your blog comments. In the climate business there are so many possible effect perturbing the ideal theory with its settled science that it will beyond my lifetime before they are sorted out to an acceptable degree. Yes, your ozone observations need more work, but when will it happen? Geoff.

      • Geoff Sherrington, I didn’t understand your reply: I wrote about 0.15 °C / decade for UAH’s regional Australia readings.

        Of course you may argue: what is this little 1.5 °C per century? Peanuts!

      • Bind,
        Maybe you do not want to understand my reply.
        There are many locations in Australia away from UHI centres, where the ground temperatures before adjustment show very little rise or falls.
        A theory of GHG has to explain why it does not apply to these places. It is too systematic to say they are just excursions in the noise.
        The low trend in the satellite record is backed up by these observations. BTW, all of these trends are horribly sensitive to choice of start and end times. The recent peak has had quite an effect on that figure you quote. Two years ago it was much lower.
        But these are old arguments that should by now be unnecessary, kept alive to counter repeated efforts of obfuscatory re-offending malcontents to avoid accepting the obvious.

      • Geoff Sherrington on September 13, 2016 at 5:10 pm

        Maybe you do not want to understand my reply.

        Geoff, I always want to understand.
        What is evident is that troposphere measurements never will help you in filling the gap between a global average over Downunder and the local places you mention.

        Thus I’ll try to get this gap become somewhat filled as soon as I have time to do.


      • Thanks Bind,
        But you are the one that needs the help. To accept observations that make you uncomfortable. I have been over and over the figures for years. Really elementary stuff is pushed under the carpet and precedence given to artificial complexity that carries invented peer review status barriers.

    • Hello Nick,

      I looked in GHCN’s unadjusted monthly TAVG record, and extracted all data measured from 1979 till present
      – in the whole Antarctic;
      – at Amundsen-Scott.

      Below you see an Excel chart comparing these two with UAH6.0beta5’s Antarctic record (“SoPol”); all data of course wrt UAH’s baseline at 1981-2010.

      We see on the chart that recent anomalies for Amundsen-Scott (+3.87, preceeded by -3.97) are small compared with e.g.
      2013 9: +7.94
      1983 1: +7.80
      1987 8: -6,93
      2004 7: -7,07

      Surprising: the OLS trends for 1979-2016, in °C / decade

      UAH6.0Beta5 SoPol: -0.01 ± 0.03
      Amundsen-Scott: +0.16 ± 0.11
      Antarctic: +0.28 ± 0.07

      But Antarctica is very cold indeed: GHCN’s OLS trends starting with 1903 (or… 1998) are pretty negative.

      Nevertheless: we can see in sorts of the extracted data that for Amundsen-Scott, 10 of the 20 highest monthly anomalies were recorded after 1999, and even 12 of 20 for Antarctica. It’s a bit like a leitmotiv.

      • Bindidon,
        Your plot emphasises how variable a single station can be even relative to the average of its region. It’s hard to read the right end, but it seems to show the big swing last month. NOAA’s page on A-S is here. They have adjusted the last few years down by a degree.

        Remember, UAH SoPol is 90-60S, so includes a lot of ocean. They say they don’t see beyond 85°S, but I think that may be optimistic; RSS only claims to 70°. TLT also can have trouble with latitudes over 1500m.

      • Nick in your answer to Bind you said this : “It’s hard to read the right end, but it seems to show the big swing last month.”. That swing ( at Amud-Scott) seems to big but since 1979 there were ( at quick count), at least 8-9 larger, over the period that is 25 % so nothing “big” about that ( enlarged the frame).

      • Nick, Toby Smit is right here. Please look at the top ten for A-S since january 1979:

        2013 9 7.94
        1983 1 7.80
        2007 6 7.08
        2009 5 6.76
        2013 8 6.57
        2005 9 6.54
        2002 7 6.53
        1996 8 6.27
        2013 6 6.08
        1982 11 6.06

        At position 36:

        2016 8 3.87

        My emphasis was rather the inverse: to show that though UAH’s trend is negative, GHCN’s for Antarctica is not, and that even A-S (one of the coldest places on Earth) has a warming trend during the satellite era.

        Interesting nevertheless: 7 of the top 10 monthly averages were in the last two decades.

        Probably the very last place to show a negative trend in GHCN will be Vostok.
        I’ll have a look at that :-)

  5. OT but this is probably worth keeping an eye on:

    “Over the past weeks NTZ has assisted in a comprehensive analysis of a large body of climate science literature. At this point I can only say that the results have one climate science’s central claims going down in flames. Tomorrow the results of that analysis will be published and once again it will reveal science that was shoddily, sloppily and deceptively done, and thus produced a totally erroneous conclusion. It involves a higher profile actor in climate science.”

  6. again the very nice update as usual.

    i can’t help but notice that a question remains: how does it come that this El nino spike is so visible in the surface data while all other spikes are far more pronounced in the satellite data?

    it’s a bit strange to me that all of the sudden the el nino gets so pronounced in the surface data. Of course i keep in mind that “the blob” could have been responsible for this.

    • Frederik Michiels at 5:18 am
      … i keep in mind that “the blob” could have been responsible…
      Is that the Climate Mob?

    • That’s similar to my question above. Note that the surface data doesn’t spike much with the 97/98 El Nino, but spikes a lot with the most recent one. As to the former, I thought perhaps an El Nino doesn’t do much to ocean temperatures worldwide, muting the depicted increase in global temperature. But the most recent El Nino is shown as a big spike, suggesting a big increase in land and ocean temperatures.

      • @ Dc 6:08 am 9/13 My guess is that data somehow HAS to show ( for some -one I guess) a big spike compared to the 1998 event to do some more pause busting, btw I am confused as well after you pointed it out, re-read the part and it is actually quite obvious, as a layman it looks like two different sets of data are being used.

    • Especially when – as I understand it – the climax involves heat release from the surface into the troposphere. This makes the troposphere spike very understandable – but certainly not an equivalent spike in the surface temperatures.

    • … how does it come that this El nino spike is so visible in the surface data while all other spikes are far more pronounced in the satellite data?

      That depends on which satellite dataset you look at:

      Here you see that indeed there is a far stronger GISS peak for 2015/16 as it was in 1997/98.

      And you see also that
      – all temperature records bypass the ENSO index MEI (downscaled to the temperature anomaly levels);
      – GISS even bypasses UAH6.0beta5;
      but that
      – the recent RSS revision 4.0 shows, for the entire troposphere, the highest peak of all.

      • well no surprise for me to see this el nino spike as the biggest in sat records. the north pacific blob and record positive PDO did all contribute to that. it gave a rising baseline for this El nino spike that was starting in 2015 with the almost el nino conditions whole year long.

        however GISS never did surpass any of the sat records by any other El nino: in fact the tropospheric data set responds more dramatic to the heat release of an El nino then the surface temperature. count the blob region and the extreme high PDO and the record satellite spike is easy to understand.

        but then i wonder how “hottest year ever” and this surface record spike does exist when europe saw record cold temperatures in the first two weeks of august, with summer snow in the Alps and Sweden. Even belgium was just 0.1°C shy of the lowest august temperature since recordings did begin.

        in belgium we had the luck that Gaston broke the blocking and brought a late august heatwave. Hermine brought the september heatwave. Without the last few blistering hot days of august having a heatwave the temperature would have been 2°C below average. In all the summer was here for lots of countries “normal” (between +0.5 and -0.5 degrees from average

        all i know is that the difference between what GISS plots for Uccle and what the RMI does plot is reaching record differences.

        i’m sure that at our RMI they can’t read thermometers anymore do i need to add sarc tags to this last line?)

      • Frederik Michiels on September 14, 2016 at 7:06 am

        Hello from Berlin, quite near you…

        but then i wonder how “hottest year ever” and this surface record spike does exist when europe saw record cold temperatures in the first two weeks of august, with summer snow in the Alps and Sweden. Even belgium was just 0.1°C shy of the lowest august temperature since recordings did begin.

        Why should you wonder about that? Europe is no more than little 10 millions of km², about 2% of Earth’s surface!

        Why should such a little corner like ours show the same temperatures as the rest of the world?
        I’m afraid you’re also confounding local meteorology over the year and global climate over a century.

        Maybe you spend some time on this nice little tool made by Tokio’s Climate center?
        That helps!

      • bind, you missed the point: the point was actually in the last two short paragraphs: GISS plotted the temperature anomaly for our region up to record +2.0°C in their gridpoint then it actually was, and the difference between the data of our RMI and GISS became so adjusted that they plot the actual temperature 0.7°C too hot then the official plot of our RMI.

        the sarcastic ending was that this year GISS will plot again for sure a record high for Uccle while till now everything was just…. average

        the truth i fear is if this example that i am following very closely is already a fact, how reliable is GISS? imvho i do not considder the GISStemp graph as trustful anymore. even more: in their raw plot there are gaps with “no data” but when i go and check that month on our RMI site i see a below average value.

        note that our RMI uses the WMO standards, so in fact there’s no need for adjustments.

        because even if this 2% of surface is so tampered with, how much has been tampered with the other 98% of the surface readings?

        that of course aside from Bob’s magnificent work but should be something to investigate.

    • “it’s a bit strange to me that all of the sudden the el nino gets so pronounced in the surface data. Of course i keep in mind that “the blob” could have been responsible for this.”

      It’s really quite simple: The Climate Change Gurus who draw these charts have manipulated the data to make it look like the temperatures are getting hotter every year as a way to further their CAGW narrative. The satellite data is the correct profile.

      The high point of this El Nino topped out at one-tenth of a degree higher than the highpoint of 1998, but that is not reflected in the GISS chart. The only way the “Blob” is responsible for this is if the Blob is named Gavin.

      The Climate Change Gurus are rigging the game. They are creating propaganda charts to fool people into believing things that are not true.

  7. Bob … this post is further proof of my position that we cannot measure the global temperature to a level of accuracy that is meaningful. The 5 data sets show a range of change between -0.03C decrease to a 0.13C increase. As such a 0.16C change in temperature is meaningless, as it gets lost in the uncertainty associated with the mathmatical methods used to “derive” [note: not measure] the global temp.

    As I’ve always said … there can only be ONE true global temp …. which of these five is the “real” global temperature??? ….. I say none of them. They are all just rough estimates with uncertainties that are probably greater than 0.16C. ….. and they want to claim an increase or decrease to the 0.01C level.

    It’s snake oil.

  8. The land+ocean TLT values are here. Curiously, on that webpage, RSS lists the composite as extending from 82.5S to 82.5N, while on their Upper Air Temperature webpage linked above, they state:

    “We do not provide monthly means poleward of 82.5 degrees (or south of 70S for TLT) due to difficulties in merging measurements in these regions.”

    No, on the website you referenced as the source of the data the column is clearly indicated as extending to 70ºS.

  9. Does anyone remember when, back in the innocent early 2000’s – we could clearly see from the “evidence” that the 1990’s “data” showed and alarming acceleration in warming.
    But, compare this view which was touted back then as “evidence” with the same period under the new Karlization re-invention of history. (Karl elevating himself to the status of wannabe Lysenko.) So look at the pause-buster for the 1990’s (in Bob’s article, above). Where has the frightening warming acceleration gone? We all remember how it was quite clearly there at the time. Or so we were all lead to believe, such that moderate voices such as Lindzen could be drowned out by the hysterical screaming.
    They had their frightening 1990’s warming acceleration. just as ordered. And yet now it’s vanished.
    Borrowed, in effect. Transplanted forward in time to the present.
    So it seems that somebody stole the 1990’s adjustments and carried them forward in time to use them to create an alarming warming in the 2000’s. Leaving the 1990’s warming looking unremarkable. Even though it was touted as quite remarkable at the time.
    Is this going to be the state of play for the next 50 years? Are NOAA and NASA simply going to continually repeal the warming of the past by borrowing it and sticking it in the present?
    In order to frighten folk who suffer from memory loss. (i.e. most folk, it seems.)
    How long can they keep doing this for before the anti-skeptical mainstream morons raise an eyebrow and say – “Gee, this is a bit strange.”
    Anyway, here’s what the 1990’s looked like just after it had finished. According to the master manipulators.
    History, it isn’t what it used to be. If you don’t check-in with the “historical consensus” on a daily basis, then you can find yourself remembering the false history. i.e. the one that was there at the time.
    Anyone remember the terrible 1990’s warming acceleration, The one in this graph.
    Of course, “we’ve always been at war with Eastasia” and there never was a commisar:

    • “Is this going to be the state of play for the next 50 years?”

      It will last about four more months, if we are lucky.

  10. RCP 8.5 is IPCC’s worst, worst, worst, worst case scenario. Atmospheric CO2 of 1,000 ppmv +/-. Is that realistic? Doesn’t that require the rapid near term combustion of more fossil fuel than actually exists?

    • Why is it a lie? Temperature in the lower troposphere differs from temperature at the surfaces.

      But the 1930’s were the hottest evah, right?

      • “Why is it a lie? Temperature in the lower troposphere differs from temperature at the surfaces.”

        The GISS chart is a propaganda tool meant to make it look like things are getting hotter every year in furtherance of the CAGW narrative. Of course, you know that.

        “But the 1930’s were the hottest evah, right?”

        Absolutely, according to the Climate Change Gurus. Hotter than today. You doubt their word?

        The same Climate Change Gurus that have bastardized the current surface temperature charts to push a political agenda. The 1930’s didn’t fit in with their narrative, so they conspired to creat our current surface temperature charts and changed the 1930’s from being hotter than today to being a lot cooler than today. The GISS chart even demotes the high temperature year of 1998. Bastardization, pure and simple. The satellite record is the only record that should be considered accurate. The politicians and the climate crimnals haven’t gotten hold of them yet.

      • The satellite record is the only record that should be considered accurate.

        Of course TA!

        But I guess you mean ONLY UAH6.0beta5, isn’t it?
        An certainly NOT RSS4.0, isn’t it?

        Maybe because they are karlized warmists, making like GISS
        everything hotter every year in furtherance of the CAGW narrative?

        Hmmmh. Sounds quite a little bit paranoid, huh?

      • Bindidon: “But I guess you mean ONLY UAH6.0beta5, isn’t it?
        An certainly NOT RSS4.0, isn’t it?”

        UAH and RSS look pretty much the same to me. I know some adjustments were made to RSS, but they are minor when you compare UAH and RSS, so yes, I accept the RSS chart, too, as being legitimate. The GISS chart distorts the years between 1998, and 2016, whereas, both UAH and RSS, even after adjustment, does not, or at least not enough to change the basic profile. That cannot be said for GISS.

        Bindidon: “Maybe because they [RSS] are karlized warmists, making like GISS everything hotter every year in furtherance of the CAGW narrative?”

        RSS isn’t close to looking like the bogus GISS chart (it’s kind of hard to see the RSS chart when you have multiple charts all jumbled up, like in that chart of yours). RSS is not making every year look hotter and hotter. It still shows 1998, as being the second highest in the satellite record. The GISS chart does not.

        Bindidon: “Hmmmh. Sounds quite a little bit paranoid, huh?”

        Well, If I were espousing that particular RSS conspiracy theory, then it would sound pranoid, I suppose.. Of course, I’m not doing any such thing. That’s a figment of your imagination.

      • TA on September 14, 2016 at 6:51 pm

        It still shows 1998, as being the second highest in the satellite record. The GISS chart does not.

        Sorry TA, but if you don’t understand the basic difference between a troposphere record and a surface record, nobody can help you. The troposphere has, for example, a stronger reaction to ENSO than does the surface.

        Why should measurements of oxygen microwave emissions at about 7 km altitude show exactly the same as thermometric measurements 2 m above the surface?

        And you amazingly seem to deliberately ignore that while UAH6.0 and RSS3.3 both show a low trend during the satellite era, RSS4.0 shows the same trend as GISS!

  11. I would like to point to one of the central fallacies of data analysis committed by Mann and others, that being the use of “anomaly” graphs. It is striking that we are being presented with graphics of various averages based on different arbitrary time periods such as 1951 to 1980, 1981 to 2010, 1901 to 2000 and so forth. All of these time periods are cherry picked to induce a significant anomaly result. One could just as easily cherry pick a time that shows cooling using anomalies say from 1934 to 1979, etc. What will you do when the current 30 year average slides the anomaly temps cooler as time progresses? Say from 1985 to 2015? Or 1998 to 2028? Whatever arbitrary statistical data analysis that may have been relevant has ceased being so given the climate of dishonesty and greed by AGW green profiteers.

    The de facto admission of scientific corruption is the insistence of departing from the raw data to some indirect method using 2nd and 3rd order massaging of the data to support a theory. While it might be useful to see a trend for a specified period of time, it should now be obvious that using these indirect methods to prove anything is patently unethical and unscientific. IF the data cannot support the theory’s predicted conclusions, the use of cherry picking methods only confirms the invalidity of the theory in question. I fully expect to hear every statistician scream at that statement, however, when your indirect method of analysis so easily lends itself to deceiving people then it’s time to question the validity of the methods used to promote a hoax.

    There is only one graphic that is valid to reasonably represent the earth’s temperature, that is the actual temperature for the time period of the Minoan Warming until now to determine the effect of human civilization upon climate. Not the arbitrary 30 year averages or 2nd order departures.

    We don’t have actual temperatures from thermometers, but we do have a proxy called O18/16. So either cease making claims about the temperature record or stick to an agreed upon standard of temperature measurement and shout down all indirect methods of data massaging. If you really believe in 2nd order analysis then analyze the trend from the height of the Minoan Warming to today’s height and tell me why increasing levels of CO2 are not in fact COOLING the earth. AGW is a fraud and it is time to start calling it that at every opportunity.

    • “One could just as easily cherry pick a time that shows cooling using anomalies say from 1934 to 1979, etc. “
      Have you tried it? All changing the anomaly period does is add or subtract a constant (actually a constant for each month, but it doesn’t change trend). The periods are usually chosen for prosaic reasons. There is a case for using the most recent 30 year period. But there is also a case for not changing often, since you then have to keep explaining which period the data published in the past covered, and doing conversions. So GISS uses 1951-80, because that was the most recent 3-decade when they started. NOAA used 1961-90 for a long time, for the same reason, but then they decided to shoot for a century, and used the most recent. Satellites use the only 3-decade period they have. And so on – the thing is that it matters very little. Just changes the base constant.

      • Nonsense, the trend from 1934 to 1979 is a NEGATIVE temperature trend NOT positive. The use of statisticianal jibberish to rationalize away the obvious only confirms how corrupted/misused the methods have become. Anomaly graphs are merely a way to divert focus upon minutia away from the big picture. AGW is a scientific fraud.

        And I notice you omitted the real issue, the trend from the Minoan Warming to the current temperature optimum, IT IS NEGATIVE, that’s what the big picture tells us. The temperature optimum of the Minoan Warming was much higher than today with a LOWER CO2 percentage in the atmosphere. You can not make a scientific claim that CO2 is a climate driver when the data says otherwise. AGW as a theory is obviously WRONG.

      • “Nonsense, the trend from 1934 to 1979 is a NEGATIVE temperature trend NOT positive.”

        No, the trend from 1934 to 1979 was 0.236 °C/Cen (GISS). I thin k you are muddling global with ConUS. But more importantly, the trend during the anomaly base period has nothing to do with the effect of anomalies. All you do with that base period is take a reference average. That takes no account of whether the trend is up or down.

        It may well be that the temperature 3000 years ago was warmer than now. That doesn’t contradict AGW, which simply says that if you put a whole lot of CO2 in the air, it will get warmer. We did, and it has. And all indications are that we’re going to keep on burning, and it is going to get warmer and warmer.

      • Nick,

        Surely you must know that GISS is a pack of lies.

        Look at what the trend for that period was back in the late 1970s, when it was ending. In fact the ’40s to ’70s suffered pronounced cooling.

        GISS and the other paid liars have so adjusted the “data” that the books are thoroughly cooked to a crisp.

      • Which fact explains why there was so much concern in the ’70s over global cooling.

        GISS is worse than worthless and its perpetrators should be fired, at best. Which thank God is likely under a Trump Administration. The fraudsters’ only possible saving grace is being located in NYC.

      • “Nick,
        Surely you must know that GISS is a pack of lies.”

        In fact, I know that it isn’t. How? I go to the published unadjusted GHCN data and work it out for myself, and compare with the adjusted that GISS uses. It makes very little difference to the trend.

        Anyone can do this, but the people who say it is all lies never bother. Do they ever put up? Remember this WUWT post?

        London, 26 April 2015 – The London-based think-tank the Global Warming Policy Foundation is today launching a major inquiry into the integrity of the official global surface temperature records.
        An international team of eminent climatologists, physicists and statisticians has been assembled under the chairmanship of Professor Terence Kealey, the former vice-chancellor of the University of Buckingham

        So what did they find? Nothing!. Three weeks after closing of submissions, they decided they would not write a report. Nothing else has been heard.

      • Gabro: ““Nick, Surely you must know that GISS is a pack of lies.”

        Nick: “In fact, I know that it isn’t. How? I go to the published unadjusted GHCN data and work it out for myself, and compare with the adjusted that GISS uses. It makes very little difference to the trend.”

        Nick, does that GHCN “unadjusted” data show the 1930’s as being hotter than 1998? If not, then the GHCN data has *already* been adjusted before you got ahold of it.

        You are basing your conclusions on bogus data, according to the Climate Change Gurus who said the 1930’s was hotter than 1998, before they conspired to change the data (your GHCN) to make the 1930’s look cooler than 1998. The database you really need is the one the Climate Change Gurus were using which showed the 1930’s being hotter than 1998.

      • ‘Nick, does that GHCN “unadjusted” data show the 1930’s as being hotter than 1998?’
        For goodness sake, this is just a giveaway of ignorance. The 1930’s were not hotter than 1998. Nowhere near.

        Maybe in part of the US, but not globally.

      • TA: ‘Nick, does that GHCN “unadjusted” data show the 1930’s as being hotter than 1998?’

        Nick:For goodness sake, this is just a giveaway of ignorance.”

        Ignorance? I’m just quoting the Climate Change Gurus. Are you saying they were lying to each other when they conspired to change the *global* temperature record, which included cooling the 1930’s to insignificance?

        Nick: “The 1930’s were not hotter than 1998. Nowhere near.”

        And you know this how? GHCN?

        “Maybe in part of the US, but not globally.”

        Maybe in part? You are throwing cold water on that, too?

      • “And you know this how?”
        OK. your turn:
        “If not, then the GHCN data has *already* been adjusted before you got ahold of it.”
        What are you talking about? And how do you know?

      • Nick Stokes September 19, 2016 at 11:34 pm wrote:

        TA: “And you know this how?”

        Nick: OK. your turn:

        TA: “If not, then the GHCN data has *already* been adjusted before you got ahold of it.”

        Nick: “What are you talking about? And how do you know?”

        Nick, if you are not showing the 1930’s as being hotter than 1998 on your charts, then you are not using the same database the Climate Change Gurus used and changed. The one they used showed the 1930’s being hotter than 1998. They said so in their Climategate emails.

        And how do I know? The Climate Change Gurus told me so. You don’t deny they conspired to change the global surface temperature record do you? You don’t think they just made up this conspiracy they engaged in, do you?

        The data you are using has been modified by those people. I understand that is the only database you have to work with, so you do the best you can, but any data you are using before the satellite era has been bastardized to uselessness.

        The surface temperature data after the satellite era is also suspect, but at least we can trace how that was bastardized, and we have the satellite records themselves to show us the difference between good data from the satellites, and the surface temperature data created for a CAGW political agenda (making each year seem hotter than the last, is their trick).

        Demoting 1998, to an also-ran in the surface temperature record is a travesty that cannot be justified. The Climate Change Gurus are so arrogant and blatant that they make these changes right in front of our eyes and then dare us to complain. Well, I’m complaining.

      • What that plot/cartoon shows is that whilst we can trace our ancestors back say some 4 million years (Lucy/ Eve etc), and modern man back say about 200 to 250,000 years, almost all human advancement has taken place in the Holocene and nearly all of that post the Holocene Optimum.

        The plot/cartoon shows the advantage of warmth. It is no coincidence that the time line of the advance of civilisations is temperature dependent, and no coincidence that the Egyptians were able to construct the Great Pyramid (which is so wonderous that we still today do not know precisely how it was constructed) whilst those in colder climes could only put a ring of posts in the ground, or perhaps a circle of small stones.

        I do not wish to deride the accomplishment of Stonehenge (which was constructed after the Pyramids) but its pales in comparison to the temples and pyramids that the Egyptians were building. The reason for this is that in the warm climate and benign conditions enjoyed by the Egyptians they had free time to and to develop writing and skills and pass these from father to son, whilst in the UK the dominant skill set was survival and this was a full time job, and thus there was no time to develop other educational skill sets.

        It is no coincidence that greatest bio diversity is in warm wet climes such as tropical rain forests, and least in dry arid climes such as the Antarctic.

        Everything we know points to warmer world being a better world. The planet is presently far too cold, and would greatly benefit from some warming.

        The planet also has too low a level of CO2, and would significantly benefit from more CO2 as the greening of the Sahel confirms. If by some happy chance this increase in CO2 brings with it some additional warmth, that would be a win win scenario.

  12. Academically extremely well done and appreciated by the choir, but far too complex to use for educating political representatives and news reporters, editors. How about providing a summary that could serve for this/

  13. I have noticed the arctic above 80 degrees latitude has cooled since the 1950s. Why would that be if the rest of the arctic has warmed so much?

  14. Bob Tisdale,

    Hi Bob,
    I think your multi-plot graphs would be much enhanced if you reduced the line weight to 1.5 or less. If you use EXCEL, go to: Format>Shape outline>Weight.

  15. dscott on September 13, 2016 at 8:25 am

    These ‘anomalies’ (what a ridiculous name for deltas) have some deeper reason: to remove the annual cycle (this boring, harsh up and down of absolute temperature records making smooth period comparisons simply impossible).

    Let me show an example based on the only dataset based on absolute temperatures I have in my computer (all others are anomaly based). It is the Global Historical Climatology Network (GHCN).

    Here is a plot of an averaging of their monthly unadjusted record collecting, for over 7,000 land stations, the monthly average of their daily measurements: it’s nearly raw data.

    (all decimal points are here commata as I live in Germany).
    If you simply shift the dataset by the average value over a time period like 1951-1980, you will also simply shift the plot by this value. Nothing is changed.
    Now compare (exactly) the same data with a removal of the annual cycle:

    dscott, I could show you the incredible chaos you obtain when comparing
    – some surface datasets showing an average absolute temperature of 15 °C with
    – troposphere datasets showing an average absolute temperature of 264 K i.e. -24 °C and
    – radiosonde datasets obtained at even lower temperatures.
    But it makes really few sense.

    Let me show you instead an anomaly based comparison of these:

    That’s exactly what people need when they want
    – to accurately compare how different temperature measurements behave, or
    – to build an average of these values to provide data on the fly for sites like
    giving a nice interpolation of temperatures measured sometimes quite a bit far of the selected corner.

  16. Bob: Above you suggest that there may be a limit to how fast the Earth can warm (30 year trend). Why?

    For the whole planet, the rate of surface/atmosphere temperature change is determined by:

    1) The difference between the incoming and outgoing radiative fluxes divided by the heat capacity of the ocean in equilibrium with the surface/atmosphere. Daily and seasonal warming rates are around 10K per day and 5K per month. For a blackbody, a 1% change in temperature (ca 3 K) is associated with a 4% change in radiative cooling. No limits here.

    2) Fluctuations in heat transfer between the surface and deep ocean (unforced/internal variability). El Ninos are – at least in part – a consequence of a slow down in such heat transfer. The rate of heat transfer by conduction and radiation increases as temperature changes, but convectivity heat transfer is not directly driven by a temperature gradient.

    D/O events (?) show rapid regional climate change – 10K per decade – in Greenland.

  17. I am more interested in the approx 20 yr periods of stability separated by the upward steps associated with ENSO. Seeing what is happening is one thing. Understanding why is another. Will the same pattern emerge within the near future? i.e. another slightly elevated pause.

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