November 2015 Global Surface (Land+Ocean) and Lower Troposphere Temperature Anomaly & Model-Data Difference Update

Guest Post by Bob Tisdale

As you’ll recall from last month’s update, the GISS Land-Ocean Temperature Index jumped upwards more than 0.2 deg C from September to October 2014, assumedly a response to the El Niño.  The NOAA/NCEI and UKMO HADCRUT4 data lag by one month in these updates, and their September to October changes shown below are far from that 0.2 deg C spike.  Maybe we’ll see their upsurges in their November data.

We’re still waiting for the El Niño-related upsurges in the global lower troposphere temperature data.  They should be coming soon.

I’ll provide updates of the annual meteorological (December to November) mean data in an upcoming post, when the NCEI and HadCRUT4 November data are available.

And for those new to these discussions who are wondering why global surface temperature data are showing record-high values in 2015 and in 2014, see General Discussions 2 and 3 of my recent free ebook On Global Warming and the Illusion of Control (25MB).

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This post provides an update of the values for the three primary suppliers of global land+ocean surface temperature reconstructions—GISS through November 2015 and HADCRUT4 and NCEI (formerly NCDC) through October 2015—and of the two suppliers of satellite-based lower troposphere temperature composites (RSS and UAH) through November 2015.  It also includes a model-data comparison.

INITIAL NOTES (BOILERPLATE):

The NOAA NCEI product is the new global land+ocean surface reconstruction with the manufactured warming presented in Karl et al. (2015).

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), 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 6.0 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…updated for all products. The boilerplate is intended for those new to the presentation of global surface temperature anomalies.

Most of the update graphs 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 the post Why Aren’t Global Surface Temperature Data Produced in Absolute Form?

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

GISS LAND OCEAN TEMPERATURE INDEX (LOTI)

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 November 2015 GISS global temperature anomaly is +1.05 deg C.  It’s basically the same as it was in October 2015, with only a -0.01 deg C decline.

01 GISS

Figure 1 – GISS Land-Ocean Temperature Index

NCEI GLOBAL SURFACE TEMPERATURE ANOMALIES (LAGS ONE MONTH)

NOTE:  The NCEI produces only 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 adjustments, see the posts:

And 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 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 (Lags One Month): The October 2015 NCEI global land plus sea surface temperature anomaly was +0.98 deg C.  See Figure 2. It rose (an increase of +0.07 deg C) since September 2015 (based on the new reconstruction).

02 NCEI

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

UK MET OFFICE HADCRUT4 (LAGS ONE MONTH)

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 October 2015 HADCRUT4 global temperature anomaly is +0.81 deg C. See Figure 3.  It increased (about +0.03 deg C) since September 2015.

03 HadCRUT4

Figure 3 – HADCRUT4

UAH LOWER TROPOSPHERE TEMPERATURE ANOMALY COMPOSITE (UAH TLT)

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 anomalies Release 6.4 beta through October 2015 are here. (Because the data have not been updated at that webpage for November 2015, I used the 0.33 deg C November value from the update at Dr. Roy Spencer’s blog here.)

Update:  The November 2015 UAH (Release 6.0 beta) lower troposphere temperature anomaly is +0.33 deg C.  It dropped (a decrease of about -0.10 deg C) since October 2015.

04 UAH TLT

Figure 4 – UAH Lower Troposphere Temperature (TLT) Anomaly Composite – Release 6.4 Beta

RSS LOWER TROPOSPHERE TEMPERATURE ANOMALY COMPOSITE (RSS TLT)

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.

Update:  The November 2015 RSS lower troposphere temperature anomaly is +0.43 deg C.  It dropped a small amount (a decrease of about -0.02 deg C) since October 2015.

05 RSS TLT

Figure 5 – RSS Lower Troposphere Temperature (TLT) Anomalies

COMPARISONS

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.

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 during “the hiatus”, as are the trends of the newly revised HADCRUT product.  See the June update for the trends before the adjustments.  But the trends of the revised reconstructions still fall short of the modeled warming rates.

06 Comparison 1979 Start

Figure 6 – Comparison Starting in 1979

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07 Comparison 1998 Start

Figure 7 – Comparison Starting in 1998

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08 Comparison 2001 Start

Figure 8 – Comparison Starting in 2001

Note also that the graphs list the trends of the CMIP5 multi-model mean (historic and RCP8.5 forcings), which are the climate models used by the IPCC for their 5th Assessment Report.

AVERAGE

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 average only includes the GISS product.

09 Surface v TLT Averages

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

MODEL-DATA COMPARISON & DIFFERENCE

Note: The HADCRUT4 reconstruction is now used in this section.  [End note.]

Considering the uptick in surface temperatures in 2014 (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 growing 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 filters to reduce the monthly variations. 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.

10 HadCRUT4 Model-Data Comparison

Figure 10

It’s very hard to overlook the fact that, since before the turn of the century, climate models are simulating way too much warming and are diverging rapidly from reality.

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 in the monthly surface temperature anomalies. Also included in red is the difference smoothed with a 61-month running mean filter.

11 HadCRUT4 Model-Data Difference

Figure 11

The greatest difference between models and reconstruction occurs now.

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 mid-1940s. 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.

MONTHLY SEA SURFACE TEMPERATURE UPDATE

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 in 2014 and the reasons for them in the post On The Recent Record-High Global Sea Surface Temperatures – The Wheres and Whys.

NEW EBOOK

Just in case you missed the earlier link, I recently published my new ebook On Global Warming and the Illusion of Control (25 MB .pdf).  IT’S FREE. The post that introduces it is here (cross post at WattsUpWithThat is here).

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36 thoughts on “November 2015 Global Surface (Land+Ocean) and Lower Troposphere Temperature Anomaly & Model-Data Difference Update

  1. Is it just me or is GISS starting to look fake. What I mean is, I have been looking at temperature data for a long time. If you handed me that GISS graph unlabeled a few years ago I would have been confident it was not temperature data.

    • Joseph Murphy December 14, 2015 at 5:37 pm
      “If you handed me that GISS graph unlabeled a few years ago I would have been confident it was not temperature data.”
      And you would have been right!
      michael 🙂

    • With all the imaginary data from no longer operating weather stations and the host of “adjustments” they did to the raw data that lies at the core of the GISS/HadCRUT assumptions…..
      Considering the flawed and fraudulent methodology behind the two sets, to continue to use GISS and HadCRUT now that we have a strong period of satellite data is just pure farce.

  2. According to the Modis satellites, the November average Land temperature was just 0.03C above the 2001-2010 Base period.
    While in GISTemp, the average Land temperature was 0.427C above the 2001-2010 average. So, Gavin is just running a temp series designed to exaggerate the warming.
    http://neo.sci.gsfc.nasa.gov/view.php?datasetId=MOD_LSTAD_M
    http://s1.postimg.org/gl71soxbj/Nov_15_Surface_Temp_Satellite_0_03_2001_2010_ba.jpg
    Now add in the extra adjustments to the sea surface temperature from Karl et al 2015 and we have people making stuff up. They believe so strongly in this theory and/or want to protect their positions so much that they have sacrificed integrity. In the long-run, it will come back to haunt them.

  3. If you torture the data long and hard enough, it will confess to anything ! It’s called ” The Schmidt Effect “, first developed in 1930’s Germany !!

  4. The Lower temp surge is well underway. The NCEP CFSv2 which amazingly gets ignored but has been nailing the warming and cooling for 35 years now, has us now in the highest running 90 day means in its record. The model initializes the temp every 6 hours and one can simply look at this link. There is no if ands or buts about it. It is seeing this enso event in real time, just like it saw all the others ( I am just showing last 10 years) along with the cooling that followed 06-07 and 09-10. and will this one too. But there is plenty more warming and you can see it in real time here
    http://models.weatherbell.com/climate/cfsr_t2m_2005.png
    It is a great tool, unless you want to tell NCEP their model cant initialize the temps, But its nailing the warming, just like it nailed post enso cooling. ITS HERE AND ITS HERE BIG TIME . NOVEMBER WAS WARMEST IN ITS RECORD AND DECEMBER WILL BE TOO.
    Why we are not using this tool never ceases to amaze me.

  5. Thanks, Bob, Good view of the Pacific.
    Now the NOAA/NCEI data set is having the same divergence problem as the IPCC models; Way too much warming while the planet stays put.
    Since the big El Niño in 97/98 things started to go bad for the alarmists, now they have to revise the data, again.

  6. Where can I find the CMIP5 data and is it also possible to find regional data for the south pole?

  7. I know this might be viewed as heretical (at this site), but … if one gets over the idea that the Al Gores and Hansens of this world are out to hype the trendline more than it is likely to grow … is there any reason to believe, really, that it isn’t going to continue to rise?
    The baseline hypothesis is simple enough: more CO₂ in atmosphere confirmed by instrumental measurement, ought to increase the infrared blanketing effect, subtly redistributing IR emission of the earth toward a modestly higher equilibrium of heat down here, ‘dirtside’. Sure enough, the instrumental measures seem to confirm this, albeit rather weakly. Yet … they do.
    If instead of estimating “0.166° C/decade”, we multiply it out to the century scale, then it looks like 1.6°/century. And that would be at the present emissions rates of CO₂ by the planet’s various economies. Thing is… most projections I see (and would rather believe than scoff…) also point to higher CO₂ production in the future, as around the world economies become more generally prosperous thru the rest of the century.
    I mean that much is pretty obvious: between The Internet democratizing access to all nature of information, between rather outstanding and hopefully duplicatable examples like China blazing forth in their new-made prosperity, whilst burning FAR more coal than they once did, with giants such as India poised to expand in their own right, and mega-regions like Africa, Central and South America the same, I don’t think any hypothesis that holds CO₂ production as steady, or declining in the foreseeable future is even remotely realistic.
    So, if Occam’s Razor (“the simplest or shortest explanation is most likely the true explanation”) is applied to HADCRUT, CMIP–5 and the rest of the datasets, then +1.6°/century is very likely on the short side. Taking an inexorably growing CO₂ production for the whole Earth as likely, then even +1.6°/century may well be short of the mark.
    Unless, of course, we get over our patently ridiculous unwillingness to stage some really large scale open-ocean iron-fertilization experiments to see if some of the CO₂ can be sequestered … while potentially providing Earth’s people with an abundant new fish-stock source. Just saying … the answer may well live in giant piles next to each and every titanium-dioxide refinery. Basically free.
    GoatGuy

    • But the logarithmic decline in CO2’s blanketing ability should be borne in mind. Plus the negative feedbacks that Willis and others have described.
      re “our patently ridiculous unwillingness to stage some really large scale open-ocean iron-fertilization experiments to see if some of the CO₂ can be sequestered ….”
      Who’s us, green man? We contrarians, and you too, would love to see more of those in the area where it’s been successful–the Gulf of Alaska. There’s no danger–if anything untoward occurs, the process would be stopped, and recovery would be swift.

    • Good points GoatGuy.
      I think the skeptic consensus position goes something like this.
      1/. Sure CO2 is a greenhouse gas with a logarithmic effect and by and of itself it should account for about (IIRC) 0.5C for every doubling of CO2 (logarithmic response). I may have the wrong actual figure here, but no one who has any pretensions to cliamte science disputes this proposition.
      2/. However this alone does not account for various warming periods last century. This again is probably a statement no one disagrees with.
      3/. The controversy then arises because two options now exist (well infinite options really, but I’ll group them into two) as to why this theory dont fit the facts. The warmist position is that warming is down to CO2, so we merely have to select the right multiplier to :
      (a) fit the warming data curve
      (b) produce a scary prediction to attract more funding and justify government intervention.
      Note that this multiplier is in effect the ‘positive feedback due to ?water vapour? that gets wittered about.
      Whereas the skeptics position is that:
      (a) such positive feedback would produce hotspots that simply do not exist
      (b) if there was inherent positive feedback in the climate due to water vapour, it would multiply any driver, not just CO2, like aerosols from volcanoes, and this simply doesn’t happen.
      (c)Ergo, something else more important than CO2 is driving climate, and CO2 is really nothing to be concerned about. And that something else is an additional effect, not a multiplier.
      And that’s where the argument stands. The data doesn’t really support AGW at all, but obviously something is going on, and always has been. Opinions are divided between the sun, cosmic rays and or simply chaotic fluctuations in cliamte itself (i.,e NAO, el Niño etc etc.), as the cause of the changes. Its probably all of them.
      The one factoid that is emerging, is that its almost 100% certain that CO2 is not a major driver of climate and that the overall water cycle is in fact negative feedback, not positive.
      Which is good news for us, and the planet, and bad news for Greens, climate scientists and of course World Government and agenda whatsitsame. Who will have to dream up a new excuse to create the One UN Ring To Rule Them All. And in the Darkness Bind Them.
      You may wonder why they bother, when they could be relaxing in a nice sauna, having hot sex and watching reruns of Disney cartoons. Well you only have to look at Merkel for example to realise why there wont be any hot sex. Lets face it, watermelons are an unlovely bunch, and Freudian sexual frustration probably has a lot to do with it. I have also noticed a preponderance of beards amongst the left and green elements. As my grandmother used to say ‘its a sign of weak chins dear, and lack of virility’.
      Its their revenge on us who actually had a life, that they didn’t. They want to make us miserable and suffer. Because they dont have anything in themselves, they lust after power, status, being noticed and all that juvenile wet dream stuff.
      Not enough infant cuddles, and you get to be a Green.
      Mothers have a lot to answer for.

      • Great summary of the debate as it stands.
        Although hidden in this argument is the concept that the surface is 33C warmer due to DWLIR from GHGs. This is “accepted” science underlying both of your camps (warmists & skeptics/lukewarmers), which begs some unanswered questions:
        How can tropical water reach 49C when LWIR cannot penetrate the surface layer?
        Why does the moon surface reach daytime higher temperatures without the +33 from an atmosphere?
        How come Mars (at 97% CO2) does not show any semblance of a runaway greenhouse effect?
        Why do planets of varying atmospheric compositions demonstrate similar temperature profiles from the tropopause to the surface?
        There is some work to be done to prove the 33C stool that CO2 warming stands in.

    • the problem with that goat guy is the multi nationals funding the push against commercial fishing.it would not fit in with their long term view of ending all commercial fishing bar that to supply fish for meal to feed the farmed fish.

  8. Mr/Dr/Prof Tisdale (please enlighten as to an appropriate salutation!)
    I started to read your e-book and one constructive criticism I have for you is this:
    It might be helpful to have right at the beginning a discussion of the following:
    ‘How do scientists go about measuring ‘temperature’?’
    ‘What indices are commonly used in the global warming debate?’
    ‘What are the current divergences seen between them?’
    I say this as someone who was a practicing professional scientist/collaborator with scientists for 20+ years but not in the field of climate science or physics i.e. an educated amateur.
    I personally think it’s extremely important to understand the difference between:
    1. Land-based thermometer measurements.
    2. Ocean-based Sea-Surface-Temperature measurements.
    3. Above-ground measurement of temperature in the gaseous phase (be that stratosphere, troposphere or the like), measured by radiosonde balloons, satellite instruments or the like.
    4. Proxy data sets, which are the only way to estimate historical temperatures going back before 1750, be they tree rings, ice cores, deep sea cores, stalactites/stalagmites etc etc.
    All the arguments have at their root how scientists choose to measure ‘temperature’, how they choose to aggregate it and how they try to take account of sub-optimal measurement regimes, change in environmental conditions in some places but not others etc.
    After all, if you’re prepared to read 700 odd pages of material, I’m sure 3 or 4 pages summarising that at the start wouldn’t be a chore. In fact, it might make reading the other 700 pages significantly easier!
    I hope this is helpful….
    Regards
    RTJ

  9. EXCELLENT!
    (how in the world could those “rate this” stars not be a solid 5 for excellent… for the life of me…. mutter, mutter, mutter…..)
    And
    Merry Christmas, Bob!
    #(:))
    Thank you for all you do for science realism (thus, for freedom).
    Gratefully,
    Janice

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