Guest Post by Bob Tisdale
This post provides an update of the values for the three primary suppliers of global land+ocean surface temperature reconstructions—GISS through March 2016 and HADCRUT4 and NCEI (formerly NCDC) through February 2016—and of the two suppliers of satellite-based lower troposphere temperature composites (RSS and UAH) through March 2016. It also includes a model-data comparison.
INITIAL NOTES:
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:
- The Oddities in NOAA’s New “Pause-Buster” Sea Surface Temperature Product – An Overview of Past Posts
- On the Monumental Differences in Warming Rates between Global Sea Surface Temperature Datasets during the NOAA-Picked Global-Warming Hiatus Period of 2000 to 2014
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.
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 March 2016 GISS global temperature anomaly is +1.28 deg C. It made a comparatively small downtick since February 2016, a -0.06 deg C decrease.
Figure 1 – GISS Land-Ocean Temperature Index
NCEI GLOBAL SURFACE TEMPERATURE ANOMALIES (LAGS ONE MONTH)
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 adjustments, see the posts:
- NOAA/NCDC’s new ‘pause-buster’ paper: a laughable attempt to create warming by adjusting past data
- More Curiosities about NOAA’s New “Pause Busting” Sea Surface Temperature Dataset
- Open Letter to Tom Karl of NOAA/NCEI Regarding “Hiatus Busting” Paper
- NOAA Releases New Pause-Buster Global Surface Temperature Data and Immediately Claims Record-High Temps for June 2015 – What a Surprise!
And recently:
- Pause Buster SST Data: Has NOAA Adjusted Away a Relationship between NMAT and SST that the Consensus of CMIP5 Climate Models Indicate Should Exist?
- The Oddities in NOAA’s New “Pause-Buster” Sea Surface Temperature Product – An Overview of Past Posts
- On the Monumental Differences in Warming Rates between Global Sea Surface Temperature Datasets during the NOAA-Picked Global-Warming Hiatus Period of 2000 to 2014
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 (Lags One Month): The February 2016 NCEI global land plus sea surface temperature anomaly was +1.21 deg C. See Figure 2. In response to the El Niño, it rose noticeably (an increase of +0.16 deg C) since January 2016.
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 February 2016 HADCRUT4 global temperature anomaly is +1.06 deg C. See Figure 3. It also increased (about +0.16 deg C) since January 2016, a response to the El Niño.
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 6.5 beta through March 2016 are here.
Update: The March 2016 UAH (Release 6.5 beta) lower troposphere temperature anomaly is +0.73 deg C. It dropped (a decrease of about -0.10 deg C) since February 2016.
Figure 4 – UAH Lower Troposphere Temperature (TLT) Anomaly Composite – Release 6.5 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.
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 March 2016 RSS lower troposphere temperature anomaly is +0.84 deg C. It dropped (a decrease of about -0.14 deg C) since February 2016.
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”. See the June 2015 update for the trends before the adjustments. But the trends of the revised reconstructions still fall short of the modeled warming rates during the hiatus periods.
Figure 6 – Comparison Starting in 1979
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Figure 7 – Comparison Starting in 1998
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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.
AVERAGES
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.
Figure 9 – Average of Global Land+Sea Surface Temperature Anomaly and Lower Troposphere Temperature 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, 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 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 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. 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 any logic 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 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.
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 1940. 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.
RECENT RECORD HIGHS
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).
I have found evidence of dependence in the surface temperature time series.
this property of the data violates the independence assumption of OLS regression
therefore, OLS trends may be unreliable
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2763358
a robust test for trends is proposed.
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2631298
We did not have enough information for past data.
You can’t change that data years later, if you do you make already uncertain data utterly meaningless.
Why can’t they understand that? It boggles the mind.
It is revisionism, changing the past to suit the present.
This is no science, it’s manufacture.
I agree with your observations as would any reasonable person.
But I’ll go even further than that. If the atmosphere’s temperature reduces as we go up in height then the “average” temperature of the atmosphere can’t be on the surface where it is the hottest can it? The average temperature should be well off the ground.
Well, would that not mean the Satellites are the best source of measurement?
How many thermometers were there at the Poles in 1880? Oh sorry I forgot, nobody had been to the poles in 1880. What about Africa or Siberia or the Southern Ocean…what were the climate records like there in 1880? Well…..uh….
It really annoys me that we are constantly forced to discuss this temperature re-construction as if it were real.
Let’s not forget that these people abolished the Medieval Warm Period, and as I recall from Climategate they got rid of the 1940s ‘blip’ too…and did Karl once claim that most of the warming since 1880 occurred before 1930?
We are playing on their field, with their ball…and they keep moving the goal posts.
Charles nelson — good points [I raised this earlier]. Prior 1960s met data as well CO2 data observations were sparse and intermittent disturbed by local wars, migrations, etc.
Dr. S. Jeevananda Reddy
Not only that but …
We still have the problem of lousy surface stations. They should be doing corrections to account for UHI (urban heat island) but instead, the corrections all seem to be in the other direction.
‘what were the climate records like there in 1880?’
What are ‘climate records?’ Do you mean weather data?
charles nelson said:
It is not just the “reconstruction” of selectively chosen temperatures as per originally recorded in the Historical Temperature Record that are highly questionable acts of “junk science” status ……. but it is also the highly questionable contents of the Historical Temperature Record itself.
In 1880, less than (<) 1% of the earth’s surface was being regularly monitored for near-surface air temperatures ……. and it didn’t get much better than that until mid-20th Century.
See: History of the National Weather Service – 1870 to present
@ http://www.nws.noaa.gov/pa/history/evolution.php
No one cared how accurate those “daily” recorded temperatures were simply because their only purpose was for “predicting” short-term (3 to 7 days) weather patterns/conditions. Those recorded temperatures in the Historical Temperature Record, beginning in 1870, were never intended to be used, …… or even imagined to being used, ….. for calculating Yearly Average Surface Temperatures at some future date in the mid-20th Century.
Anyway, you might as well get used to being “constantly forced to discuss temperature re-construction, etc.” …… simply because so many people have carved out their “nitch” of expertise that is directly associated or correlated with the contents of the Historical Temperature Record …… and thus it is highly improbable that any of the aforesaid “experts” will publicly admit that the NTR is comprised of highly questionable data of very little scientific value simply because their admission of said would completely negate and/or destroy their self-proclaimed “nitch” of expertise.
CHALLENGE QUESTION: WHEN WILL GLOBAL COOLING START?
I hope to be wrong about global cooling, because humanity suffers greatly in a cooling world. The current Excess Winter Mortality Rate equals about 100,000 deaths per year in the USA, up to 50,000 in the UK and several million worldwide, even in warm climates. There is NO significant Excess Summer Mortality Rate.
Challenge Question: When will global cooling start?
In 2002 we wrote that global cooling would start by 2020 to 2030.
We now say global cooling will start before 2020, probably by 2017.
[Definition: The commencement of global cooling is deemed to start when the Lower Tropospheric (LT) temperature anomaly as measured by UAH satellite data starts to decline below the +0.2C anomaly and the LT trend then declines further.]
http://www.drroyspencer.com/latest-global-temperatures/
Bragging rights to whoever gets it right.
Ladies and germs – faites vos jeux!
Regards to all, Allan
Common sense would suggest that 2017 will be cool relative to 2016 in lower troposphere data, given that 2016 looks likely to be one of the warmest years on record. The question is, what impact will this have on the long term trend? Very little, one would suspect.
If ‘global cooling’ means that temperatures will remain above average, where ‘average’ means the 1981-2010 base, then there’s hardly much to fear from it.
By the way, you still haven’t explained why your confident assertion in 2008 that global cooling had already started from January 2007 went so badly wrong: http://icecap.us/index.php/go/joes-blog/is_this_the_beginning_of_global_cooling/
Compare your UAH chart to Roy Spencer’s latest: http://www.drroyspencer.com/wp-content/uploads/UAH_LT_1979_thru_March_2016_v6-550×318.png
DWR – I did reply to your previous comment re my 2008 post.
Also, I provided a definition of the commencement of global cooling above – kindly try to read it.
Global cooling does not have to be severe to cause many more Excess Winter Deaths.
John Finn – I see you tag-team with DWR – are you and DWR the same person, or possibly Siamese twins, joined at the fundament?
I’ve no idea who DWR is. I’m just heartily sick of the endless stream of cooling predictions I’ve been reading about for the past 10 or 15 years.
Tell you what if you’re so confident about I’m prepared to have a bet with you. I’ll bet you that the mean UAH satellite temperature for 2020-2025 (6 years) is higher than 0.2 degrees above the 1981-2010 mean temperature. We can have +/- 0.5 as NULL bet if you want so if the mean anomaly is 0.25 or above – I win. If it’s 0.15 or below – you win.
John Finn said:
“Tell you what if you’re so confident about I’m prepared to have a bet with you. I’ll bet you that the mean UAH satellite temperature for 2020-2025 (6 years) is higher than 0.2 degrees above the 1981-2010 mean temperature. We can have +/- 0.05 as NULL bet if you want so if the mean anomaly is 0.25 or above – I win. If it’s 0.15 or below – you win.”
___________
Thank you John. Finally, someone is willing to provide a falsifiable hypothesis on this question.
I have changed the dates to 2018-2025 (8 years) and tightened up the definition (UAH Lower Troposphere monthly anomaly), but I agree with your revised bet below:. Please confirm you are in agreement.
John bets that the mean monthly UAH satellite Lower Troposphere temperature anomaly for 2018-2025 inclusive (8 years) is higher than 0.25 degrees C.
Allan bets that the mean monthly UAH satellite Lower Troposphere temperature anomaly for 2018-2025 inclusive (8 years) is lower than 0.15 degrees C.
The year 2025 is a long time from now – I wish you good health.
Regards, Allan
Repeating my previous reply re 2008 for DWR:
http://wattsupwiththat.com/2016/03/05/march-2016-update-of-global-temperature-responses-to-199798-and-201516-el-nino-events/comment-page-1/#comment-2161464
DWR – as I stated before, I hope to be wrong about imminent global cooling, As to the commencement date, whether cooling started in 2005, 2009, 2017 or later, scientists will be debating this point even after we have several decades more satellite data, because Earth temperature data is messy, as I said above.
Questions:
1. Do you care to make any prediction about future warming or cooling, or do you just snipe from the bushes?
2. Do you really believe that the surface temperature data is credible, and if so, which dataset?
3. What is your real name?
Regards, Allan
For the record, I believe the following is true.
Presentation of Evidence Suggesting Temperature Drives Atmospheric CO2 more than CO2 Drives Temperature
September 4, 2015
By Allan MacRae
http://wattsupwiththat.com/2015/06/13/presentation-of-evidence-suggesting-temperature-drives-atmospheric-co2-more-than-co2-drives-temperature/
Observations and Conclusions:
1. Temperature, among other factors, drives atmospheric CO2 much more than CO2 drives temperature. The rate of change dCO2/dt is closely correlated with temperature and thus atmospheric CO2 LAGS temperature by ~9 months in the modern data record
2. CO2 also lags temperature by ~~800 years in the ice core record, on a longer time scale.
3. Atmospheric CO2 lags temperature at all measured time scales.
4. CO2 is the feedstock for carbon-based life on Earth, and Earth’s atmosphere and oceans are clearly CO2-deficient. CO2 abatement and sequestration schemes are nonsense.
5. Based on the evidence, Earth’s climate is insensitive to increased atmospheric CO2 – there is no global warming crisis.
6. Recent global warming was natural and irregularly cyclical – the next climate phase following the ~20 year pause will probably be global cooling, starting by ~2020 or sooner.
7. Adaptation is clearly the best approach to deal with the moderate global warming and cooling experienced in recent centuries.
8. Cool and cold weather kills many more people than warm or hot weather, even in warm climates. There are about 100,000 Excess Winter Deaths every year in the USA, up to 50,000 in the UK and several million worldwide.
9. Green energy schemes have needlessly driven up energy costs, reduced electrical grid reliability and contributed to increased winter mortality, which especially targets the elderly and the poor.
10. Cheap, abundant, reliable energy is the lifeblood of modern society. When misinformed politicians fool with energy systems, real people suffer and die. That is the tragic legacy of false global warming alarmism.
Allan MacRae, Calgary, June 12, 2015
I agree with DWR54 here. These groundless cooling predictions are becoming tedious and do nothing for the credibility of serious scepticism.
Face it – it’s highly probable that increasing CO2 in the atmosphere will result in some warming. However, most responsible sceptics take the view that the warming will not be of the magnitude projected by some GCMs and will, therefore, be much less harmful than predicted.
Of course there will be a fall in temperatures over the next year or two but there’s absolutely no evidence to suggest there’ll be anything other than a continuation of the modest warming trend over the long term.
“Face it – it’s highly probable that increasing CO2 in the atmosphere will result in some warming.”
That, my friend, is highly debatable. In the view of many, CO2 on net, is a cooling agent. There has been no “warming” that can be shown to be due to CO2.
I agree, and moving thermostats underneath magnifying glasses or adjacent to city heat islands is only making mountains from mole’s hills.
In the graphic above 280ppm (preindustrial) transmission to the tropopause by wave number is plotted against 1 meter absorption % at 400ppm for the fundamental bending band 667.4 and its positive and negative rotational sidekicks. This 667.4 band defines the zero transmission flat bottom of transmission in the more general CO2 wabelengths.
The other CO2 significant transitions are also plotted in red and exaggerated several orders of magnitude to even get them to plot against the fundamental. It can be seen that two of these, 618 and 720.8 create their own zero transmission points even at 280 ppm. Dotted lines are provided to show the correspondence between the two remaining bands and their corresponding troughs of reduced transmission.
Since you can’t go below zero transmission, no amount of CO2 can warm the planet further in the fundamental bending bands and the duty will fall to the guys to the left enlarging their respective troughs. These are the much vaunted “wings”.
Below are a few MODTRAN comparisons of tropical atmosphere 280 vs 400ppm CO2 only at different altitudes.
No significant divergence from blackbody temperature at 100 meters.
Five kilometers is where you begin to see a “flat bottom” at blackbody CO2 signature at appropriate temperature for the altitude..The input panel to the left only one ppm shows and the alternate is “background”.
At 20 km MODTRAN sees the flat bottom near the temperature of the tropopause.The point here is that the plots are nearly identical. Ain’t much chicken on them wings.
Agree with John Finn. There is no freaking point in predicting or rather guessing a cooling to start.
The point to go after is that warming has been smaller than predicted by alarmed people, and consequences of that warming are about nil if not positive. There is no reason to panic. Adapt, don’t be daft and try to stop climate change with provenly inefficient methods.
markstoval April 16, 2016 at 7:09 am
1. If you increase CO2 in the atmosphere you increase the average height at which energy is emitted to space.
2. If the average height at which energy is emitted increases, the temperature at which it is emitted is colder (HIGHER=COLDER).
3. If the temperature is colder, the rate of emission falls (SB formula: E=sigma x T^4)
4. If the rate of emission falls then there is an imbalance between incoming (solar) energy and outgoing LW energy, i.e. more energy is entering the system than leaving it.
5. If incoming energy is greater than outgoing energy then the surface and atmosphere will warm.
gymnosperm April 16, 2016 at 10:59 am
MODTRAN calculations show that doubling CO2 will increase TOA forcing by 3.7 w/m2. Scientists on both sides of the argument accept this figure as broadly correct. The disagreement centres on feedback. The CAGWers think feedback will be strongly positive and significantly enhance CO2 warming. Scientists such as Lindzen, Spencer and Jack Barrett think feedback will be small – perhaps even negative and that warming is unlikely to exceed 1.2 degrees C.
It’s a real and deadly possibility, folks, so warning/reminding about it could mean some people in positions of responsibility will at least not assume the continuation of relative warmth as a given, it seems to me.
John Finn,
As I said, highly debatable. The fact that warmists and luke-warmiists all agree that CO2 warms the planet is not news. But, many real skeptics make a very persuasive argument that you are dead wrong. I would mention one or two but site policy forbids getting into that area.
Gymnosperm said:
Is that not the same as saying, ….. “Ten (10) pounds of lead @ 100 degrees F will contain the same amount of thermal (heat) energy as one (1) ton [2,000 pounds] of lead @ 100 degrees F?”
Or likewise, ….. “Ten (10) pounds of CO2 @ 100 degrees F …. will contain the same amount of thermal (heat) energy …. as one (1) ton [2,000 pounds] of CO2 @ 100 degrees F?”
Me thinks that your “more equals the same” claim ….. is “junk sciency”.
gymnosperm’s analysis is dead on. He clearly understand MODTRAN, modelling and the AGW theory. I have some f/u comments at the bottom of this tread that follow a similar line of reasoning.
https://wattsupwiththat.com/2016/04/16/march-2016-global-surface-landocean-and-lower-troposphere-temperature-anomaly-update/comment-page-1/#comment-2191856
JohnKnight on global cooling:
“It’s a real and deadly possibility, folks, so warning/reminding about it could mean some people in positions of responsibility will at least not assume the continuation of relative warmth as a given, it seems to me.”
Thank you John for your cautionary comment.
In due time, a few thousand years at most, another Continental Ice Age is a virtual certainty. Regrettably, there is no credible evidence that the increase in atmospheric CO2 from (alleged) pre-industrial levels of ~280ppm to the current ~400ppm will delay the advance of continental glaciers. And there goes the neighbourhood…
I am suggesting that a lesser natural global cooling cycle is probable and should start within the next few years.
The natural global cooling cycle from ~1940-1975 tends to disprove the warmist hypothesis that “increasing atmospheric CO2 is the cause of dangerous global warming”. Another similar natural global cooling cycle should convince all but the most fanatical warmists that their CAGW hypothesis is false.
But even moderate global cooling is dangerous to humanity. Veteran meteorologist Joe d’Aleo and I wrote this paper recently. I sincerely hope to be wrong about imminent natural global cooling, because cold weather kills much more that warm weather does, even in warm climates.
Globally, Excess Winter deaths total several million per year, and especially target the elderly and the poor. Excess Winter Deaths in the USA total about 100,000 per year, or two 9-11’s per week for 17 weeks EVERY YEAR – with much less property damage. The United Kingdom has much higher per capita Excess Winter Mortality Rates than the USA or Canada, up to 50,000 per year in a population 1/6th that of the USA.
“When misinformed politicians fool with energy systems, innocent people suffer and die.”
Regards, Allan
__________________________________
“Cold Weather Kills 20 Times as Many People as Hot Weather”
September 4, 2015
By Joseph D’Aleo and Allan MacRae
https://friendsofsciencecalgary.files.wordpress.com/2015/09/cold-weather-kills-macrae-daleo-4sept2015-final.pdf
[excerpts]
Cold weather kills. Throughout history and in modern times, many more people succumb to cold exposure than to hot weather, as evidenced in a wide range of cold and warm climates.
Evidence is provided from a study of 74 million deaths in thirteen cold and warm countries including Thailand and Brazil, and studies of the United Kingdom, Europe, the USA, Australia and Canada.
Contrary to popular belief, Earth is colder-than-optimum for human survival. A warmer world, such as was experienced during the Roman Warm Period and the Medieval Warm Period, is expected to lower winter deaths and a colder world like the Little Ice Age will increase winter mortality, absent adaptive measures. These conclusions have been known for many decades, based on national mortality statistics.
…
Canada has lower Excess Winter Mortality Rates than the USA (~100,000 Excess Winter Deaths per year) and much lower than the UK (up to ~50,000 Excess Winter Deaths per year). This is attributed to our better adaptation to cold weather, including better home insulation and home heating systems, and much lower energy costs than the UK, as a result of low-cost natural gas due to shale fracking and our lower implementation of inefficient and costly green energy schemes.
…
When misinformed politicians fool with energy systems, innocent people suffer and die.
****************
It is SNOWING all over the planet from Eurasia, the mountains in the Middle East, all over the West in the USA with a blizzard in Colorado. On my little NY mountain, we have had a cold, cold April and all my spring flowers froze and died on me, not one daffodil, they are all messed up badly.
Below freezing nights night after night including right now as I type, the sun has been up for two hours and it just reached 32 degrees finally.
Even the national weather service guys are admitting next year the temperatures of much of the US will be way below normal both winter and summer!
Are we on anecdotal evidence again?
Well, it snowed here in Berkshire (England) today. Quite unusual for mid April. Means nothing, of course.
“All over the planet”? Really? There is a Southern Hemisphere you know- and a tropical region. Snow in one or many places on a particular day is just weather. I expect global and many regional temperatures will fall shortly, and well into 2017 and maybe 2018, but that will also be weather. Only if it continues to be relatively cooler for 5 or 10 years (producing a 25-30 year pause) will it cause real embarrassment for Global Warming Enthusiasts.
At the rate you CAGW’ers are “changing-your-tune” …… it will soon be up to a “100 year pause” before it will cause real embarrassment for Global Warming Enthusiasts.
I am just stunned that NASA can alter 1880, or 1850 or any period before 2016 and claim any level of certainty smaller than the adjustments they made.
The uncertainty should be the rage of final minus raw at the very least, meaning half of the warming since 1980 is imo less than 50% certain.
Every time they adjust this record the uncertainty increases, not decreases.
Models minus data (fig 11) looks like the AMO.
Who’d have thunk it?
It is really eye opening to see how a few months can change the same picture and conclusion. What people need to focus on is “how can CO2 causes that temperature pattern.” Whether we are warming is irrelevant, the key question is whether or not we are warming due to CO2. CO2 over that time period has a linear increase in trend, has a non-linear decaying rate of energy absorption, and fixed IR absorption band. The fraud is so obvious is the way they are “adjusting” the data. The reason they need a linear increase in temperature is because CO2 increases in a linear manner. Plug in non-linear temperature as the dependent variable and linear CO2 and you have real problems with your model, as the IPCC Model Results prove. They then have to make temperature more linear to match the CO2 variability to the temperature variability, and that will boost the model’s R^2. Problem is the nit-wits lack a basic understanding of modeling. The critical factor isn’t the level of CO2, the critical factor is the change in energy absorbed by CO2, and that is non-linear and decays. If they keep trying to make temperature linear, it won’t match reality. CO2’s impact on temperature declines per unit as its level increases (in economics it is called the law of diminishing returns). The very fact that they are clearly manipulating the data in a manner to make CO2 match temperature demonstrates that they are manipulating the data to make the model spit out a higher R^2, but the way they are doing it exposes that it is fraud. There is no way for CO2 to explain the variability of temperature, there is no way for CO2 to cause spikes in temperature, and there is no way to CO2 to result in cooling. Those are the key questions people need to start asking. Don’t debate if we are warming or not, that is irrelevant. The key question to ask is how does CO2 cause that much variability? It can’t.
Here is the problem the climate alarmists face, and this is why they are “adjusting” the data to make it more linear.
?w=500&h=355
CO2 has basically an unaltered linear trend.
http://alanbetts.com/image/1/1200/0/uploads/co2_data_mlo2015-565b415052348.jpg
The only way to create a model of ΔT=ΔCO2 is if either CO2 becomes non-linear or temperature becomes linear. Making CO2 non-linear doesn’t help their case, so they make temperature more linear.
The problem is, CO2’s impact on warming isn’t linear, CO2 energy absorption shows a logarithmic decay.
http://notrickszone.com/wp-content/uploads/2012/08/Caryl_11.png
The very fact that they are “adjusting” temperature in a manner that makes it better fit temperature instead of modeling temperature against changes in energy absorbed by CO2 pretty much proves they are trying to get a CO2 driven model a higher R^2. Ironically by proving CO2 is tied to Temperature they are accidentally proving CO2 isn’t the cause of the warming. Their model is simply misspecified.
Why would you expect a 100% correlation between CO2 and temperature? This argument is ridiculous. Even if atmospheric CO2 remained constant temperatures would still vary. There will, therefore, be times when natural variability amplifies any CO2 effect and times when it offsets CO2.
That is the whole basis of the AGW ‘Theory’.
http://www.ucsusa.org/global_warming/science_and_impacts/science/human-contribution-to-gw-faq.html#.VxJoA_krK00
90% to me means an R^2 of 90 for the model ΔT=ΔCO2. CO2 increases on a linear basis, heat absorption does not. They are adjusting temperatures to make them linear.
@CO2isLife You should re-read the quote you use from the IPCC report. It does not says that 90% of the warming is due to CO2. (even if it would have said that, still no reason to assume from that sentence that it should be linear…)
This is not only for CO2 and temp
The models could not produce the MWP, so they attacked the MWP with the Hockeyschtick with some classic revisionism.
The models cannot deal with the 1930s warming and the cooling later on in the 70s. So NOAA and NASA disappeared those trends. Again revisionism at work.
Karl et al carried out yet more revisionism on SST
Global meteorological records were also victims of GISS, Hansen and Schmidt in the past 15 years, many records have been changed to what the final product actually looks like. In other words cooling or no trend data suffers the same fate as Mann’s Finland sediment proxy 😉
The LIA, revisionism dealt with that as far as the green circle peer review jerk (and those that depend on it ala Sks) while in the real world, it is established quite well as is the MWP.
The real tragedy is there is so many people willfully ignoring these inconvenient facts, and that says a lot about their state of mind as it is utterly self delusional, kind of a whipped up hysteria. No wonder many of them are seeing shrinks for “pre traumatic stress” lol “I’m stressed about the possibility of getting stressed” lol, or as we call it paranoia
This chart shows CO2 versus global surface temperature over the period of their joint instrument measurement (from March 1958): http://www.woodfortrees.org/plot/gistemp/from:1958.17/mean:12/normalise/plot/esrl-co2/mean:12/normalise/plot/gistemp/from:1958.17/trend/normalise
Both data sets have a 12 month smooth to remove the seasonal signal from CO2. They are ‘normalised’ so that they can be compared directly on a meaningful level. I have added a linear trend line to the surface data.
There is a clear correlation between global surface temperature increase and increased atmospheric concentrations of CO2. It is statistically significant according to Excel correlation analysis.
That is my point, having a high correlation with temperature and CO2 proves there is a flaw in the theory. If you have a high correlation between CO2 and Temperature it is either due to coincidence, multi-correlation or deliberate tampering of the data, none of which make a good model. Climate Alarmists must have never taken Econometrics 101. There are very specific ways to make a valid model. First, CO2 doesn’t change temperature, the absorbed radiation does. The Model which the IPCC uses is ΔTemperature is a function of ΔCO2, or ΔTemperature = ΔCO2. Temperature is the dependent variable and CO2 is the independent variable. They claim that that model can explain 90% of the variation in temperature, or in other words has an R^2 of 90. That model is a model a 2 year old would create in a school science fair. The model that is valid is ΔTemperature is a function of ΔEnergy Absorbed by CO2. CO2 doesn’t cause the warming, the trapped radiation causes the warming. To model it properly you have to model the Δ Energy trapped, that is the whole purpose of the MODTRAN program. Clearly the climate alarmists don’t understand the very tools they have to make their case. They keep using CO2 and ignore the MODTRAN data for anything buy making nice graphics. Anyone with a 2nd grade education in econometrics would understand why nearly 100% of the IPCC models overestimate temperature. That is the exact answer you would give on a test that asked the question “If you have a model with a positive linear sloped independent variable and a non-linear dependent variable that hovers around 0, what would the expected outcome be?” “What would the expected R^2 be?” 100% of A students would answer that the model will overestimate the dependent variable and have a very low R^2. That is exactly what you get with the IPCC models. They have to make the temperature graph linear to make the model have any chance what so ever of being valid. Problem is, it isn’t CO2, it is trapped energy that needs to be modeled. Their model is misspecified. Econometrics 101. I can’t believe people at that level are so incompetent, so I have to assume they are deliberately misleading the public.
co2islife April 16, 2016 at 9:30 am
No it isn’t.
That’s not what the IPCC statement means. I don’t know how familiar you are with statistics but the IPCC are referring to values based on probabilities from a Normal Distribution.
For example, if you have Normal distribution with mean=80 and SD=23.4 the probability of getting a value of 50 or below is about 0.1 (10%). Assuming this is roughly the distribution used then the IPCC are effectively saying that 80% of the warming is the most likely value for the CO2 contribution – with the probability of it being less or more being the same (50%).
Their distribution would actually indicate that the there is a 20% chance that the CO2 contribution is more than 100% of the warming. This might sound daft but it’s not. The argument is that forcing to date has left an imbalance at the Top of the Atmosphere which represent more warming to come.
I’m not particularly supporting their argument. I’m just explaining how they arrive at their conclusions. You’re not the only one who has misinterpreted these figures.
OK, I went back and read the quote. I should have said 50%+ of the warming, or R^2 of 50+. Here is the quote. But in reality, just what does this quote mean? It claims that there is “90% certainty” that man made CO2 has caused “most of the observed increase.” Give that to any stats professor and it will leave them scratching their head. Just what hypothesis are they testing and how? The 90% certainly is language used in a hypothesis test, where the mean of the data is outside 2 standard deviations from the Null. That is what you do for a cross sectional test, where you collect data and see if it differs from zero. ΔTemp=ΔCO2 is a time series model, it is a linear regression, the ANOVA output would be things like Alpha, Beta and R^2. You talk of explainitory power, or R^2, not confidence level. In the time series model you are analyzing the variation and the correlation with other variables, that is why they are called ANOVA tables, and not confidence tables. Anyway, can someone explain this quote in any way that makes sense to a scientist?
Here is another quote that speaks to a time series output.
http://www.theguardian.com/environment/climate-consensus-97-per-cent/2013/sep/27/global-warming-ipcc-report-humans
That clearly states man made CO2 caused 100% of the warming over 60 years
That is clearly defining the R^2 as 100, the independent variable as man made CO2 and the period of the time series as 60 years. That is how real scientist speak when they build time series regression and forecast models, and proves that my understanding of statistics is quite adequate.
No. – still not right. The CO2/Temperature correlation is about 85% to 90%. However the percentages quoted by the IPCC are nothing to do with the R^2 coefficient.
I’m not going into the methodology used to obtain the IPCC numbers, I’m just providing the correct interpretation of their statement.
,
No it’s not. You’re confusing the warming trend with .every wiggle of the temperature record. There are cyclical effects which cause local peaks and troughs in the temperature record but over the period of the last 60 years the IPCC, rightly or wrongly, say these factors sum to zero.
Here’s a simple – though not perfect – analogy. Imagine you are standing on the edge of a jagged cliff above a beach . You then throw a rock and watch it fall. Gravity tells us the rock should fall to the bottom and we can calculate it’s path quite accurately. However when the rock falls it’s path to the bottom might be interrupted by the jagged surface of the cliff. If we plot the height of the rock above sea level at, say, 0.1 second intervals, we might find that the rock actually jumps up (gains height) at times or even PAUSES on it’s downward path.
The correlation between the model gravity calculation and the actual readings won’t necessarily be 100%.
However we will be 100% confident that gravity has caused the rock to fall to the bottom of the cliff.
There is 0.00000% chance that CO2 and Temperature have a correlation anywhere near 0.85 to 0.90. Anyone can download the temperature and CO2 data and run a correlation and it won’t be anywhere near 0.85 ot 0.90. Over the past 18 years CO2 has increased by 25 to 30% on a geometric increase of about 3%/yr and temperatures have been flat or falling much of that time. There many be times when you can cherry pick a time period where there is a high correlation, but that is coincidence, not correlation.
The IPCC is wrong and their models prove it. They have tested their theory and nearly 100% of them overestimate temperature. That proves a bias and flaw in their theory. On Wall Street if you publish data that is knowingly flawed and overestimate expected returns you go to jail ie Mayoff. Once again, there are methods to model things and there are outputs to test those relationships. Multi-variable modeling is a way to statistically control for numerous variables without putting them in a test tube. If the IPCC had models that worked to prove their therory they wouldn’t be making nonsensical claims like 95% certain and man causes most of the warming. That means nothing. If they had a model that means something they would be able to say our model has an R^2 of 90 that shows that man made CO2 is the sole driver of temperature controlling for all other factors. They would publish the model, publish the data, and anyone could test the theory and data themselves. I’ve never seen the IPCC publish an ANOVA table for their models. Never. Can someone point to one in the most recent IPCC AR? Where are the claims that CO2, controlled for natural sources, shows man made CO2 is the main driver of temperature? Where are the R^2 values, where are the F-Scores, where are the coefficients on each factor of the model?
http://www-rohan.sdsu.edu/doc/matlab/toolbox/stats/anova2_m.gif
That is pure nonsense. The way these models work is that you would have an independent variable (time an object takes to reach the bottom of the cliff), you would then collect independent variables like 1) surface area/volume 2) shape of the object(an aerodynamic variable) 3) weight 4) wind resistance/air density. You would then run a multi-variable regression using a program like SAS, and it will control for each factor, and produce an ANOVA table that gives you the confidence of each variable, its coefficient, the adj-R^2 of the model and the F-Score. There is no doubt that man made CO2 has some impact on temperature and climate, that statement is meaningless. They make a claim that 100% of the warming over the last 60 year is 100% due to man made CO2. That is a testable hypothesis, and the IPCC has produced no models to demonstrate that, zero. If they had a model that controls for natural CO2, and has an R^2 of 100 over the past 60 years, where is the ANOVA table? Where is the model? Where is the data? It doesn’t exist. They wouldn’t be “adjusting” the data is they had a model that works. BTW, if they had a model that did work, and then they “adjust” the data, the R^2 of the model will change, and if they already had 100, it can go no where but down.
BTW, climate models are multi-variable models, you don’t use t and z Scores, you use f and p Scores. You aren’t looking at the significance of a single factor you are looking at how all the factors interact together to influence the dependent variable. You also get an adjusted R^2 instead of an R^2. The adjustment is made for the number of variables in the model. Climates are like economies, you can’t put them in a test tube, so you need statistical methods to “control” the factors in the model.
CO2 dude
Your Mauna Loa chart does not look linear to me.
CO2 dude
Your Mauna Loa chart does not look linear to me.
Actually you are correct, it is a geometric growth rate chart that increases by about 3% each year. Because CO2’s absorption has a logarithmic decay in its rate of increase, it makes no difference. The results of using CO2 as the independent variable won’t change. You need CO2 changing by a factor of 1, 2 or 3X, not by a factor of 0.03/year.
co2islife – April 16, 2016 at 6:16 am said:
How does one make these past temperatures more linear to match the CO2 increase?
http://i1019.photobucket.com/albums/af315/SamC_40/1979-2013UAHsatelliteglobalaveragetemperatures.png
This chart makes my case. Read many of the comments I’ve addressed. Some people claim CO2 and temperature have a high correlation, in fact some claim upwards of +0.85 to +0.90. That is pure horse manure. Any 2 year old can see there is basically no correlation at all. CO2 is near linear, temperature is almost random. In 1980 CO2 was 367ppm, the temperature deviation was 0.00°C. In 2008 CO2 was 387ppm, the temperature deviation was 0.00°C. In 1998 CO2 was 371ppm, the temperature deviation was 0.4°C. In 2000 CO2 was 371ppm, the temperature deviation was -0.1°C. There isn’t a computer in the world that would spit out a high correlation for those two variables. In any case CO2 is the wrong variable. CO2 is irrelevant. Energy absorbed is what matters. The marginal increase in energy trapped by CO2 from 367 to 387 looking down from 0.1k is immeasurable.
?w=700
http://i1019.photobucket.com/albums/af315/SamC_40/1979-2013UAHsatelliteglobalaveragetemperatures.png
CO2 does not impact surface measurements.
CO2’s energy absorption is logarithmic. Small changes mean absolutely nothing, and they mean even less when H20 is added to the mix.
http://www.hindawi.com/journals/ijas/2013/503727.fig.0023.jpg
I note that HADCRUT and GISS make the 1997-98 El Niño mostly go away, while RSS and UAH do not. I wonder what else NASA and the UKMO made go away.
The “blip” apparently.. 😀 @climategate
Revisionism is where all the warming comes from, the effect is so influential on the data that it overpowers natural variability.
“Global warming” is definitely caused by humans, humans working at CRU, NASA and NOAA
I sympathize with emsnews April 16, 2016 at 4:58 am
I have been noting this for years here and at Spencer’s blog…something is wrong between data and observation.
Self-serving bias aside–when “cold” is breaking many more records than heat all over the world for years and past records continue to be adjusted..and we keep finding problems with land-sea-satellite sensor equipment–we know we are playing in “their” court as was said above…I’m not sure I believe anything claimed by these government agencies or government funded agencies–I want to live long enough to see what happens–when will the time come when we can expose the rewritten history?
I mean so reasonable people will get it?
Shelly, that’s one of the reasons I cling on to life, so that eventually I shall be able to gloat and say to all the nodding idiots “I told you so”.
There’s been year after year of record hot temps and recently several months in a row of record hot temps all over the world…
March temperature smashes 100-year global record.
http://www.theguardian.com/environment/2016/apr/15/march-temperature-smashes-100-year-global-record
you mean a line on a graph going higher up the graph than other lines representing other years claims that it shows this. if you believe the mish mash of algorithms , adjustments and extrapolations ,sprinkled with a relatively few measurements ,over hundreds of thousands of square kilometres of land and ocean accurately represents some notional global temperature,well good for you. me ? i am not convinced.
There’s been year after year of adjusting the past temps to look cooler so that current temps look hotter–surely you know this much? Remember that 1936 used to be the hottest? In 1998 we knew that 1936 was the hottest year–then slowly it was adjusted down down untill 1998 morphed into a hotter year than 1936. Then 2012 and then 2015…
You say years and years–well that wasn’t so in 2014
http://tiny.cc/recordlows
I expect there to be years where there are more record highs and others where there are more reocrds lows with the highs gaining slightly as we emerge from the LIA. But with the adjustments being so dishonest, I don’t trust the “official” claims–especially when we see so many record cold breakers and snow in numerous places that haven’t seen snow for 100 years, and ice in the great lakes like hasn’t been seen for 125 years or more and late into the spring–and then we hear how we are roasting!
I simply do not believe it. I read the report on the weather you referenced, “described by scientists as a “shocker” and signalling “a kind of climate emergency””, and almost have to laugh at the hyperbole. Can’t you see it????
The real “shocker” was:
Even if the past records had not been tampered with, we are talking 1 degree!!!! And only a little over 100 years which you KNOW is nothing. Many past warming periods have been higher than this–any real scientist has to admit it. We know this, despite the hockey stick follies.
If you look at the larger picture, we are simply warming from the last LIA and nothing much has happened here except the climate scientists discrediting themselves. It’s the changing records that are a “shocker” not the changing weather.
For all Bob Tisdale’s hard work (above) which I really DO applaud (somebody’s got to do it, to expose the mendacity of the warmists), I fail to get interested or involved.
Colour me stupid or non-science but I simply cannot get up any enthusiasm for records which, given the life of the Earth, are so short and have been unbelievably manipulated by those who wish to rule us.
Luc
I know I’m stating the obvious, but the argument isn’t just over how the (admittedly short-term) weather records are kept, the real concern is the politicians who knowingly use this drivel to increase taxes spent on corrupt scheme to “save us”.
Bob, As the latest UAH dataset is still a ‘beta’ update to version 6, its more correct to label it 6.0b5 or 6.0 beta 5, not version 6.5 beta. Once UAH pronounce it as a final release it would become 6.0.
Actually, figure 11 is very interesting: I see you used a 61 month smoothing filter for the red line, which reduces uncertainty in these residuals over a longer time frame: clearly there are periods of years at a time where these residuals oscillate from both above to below the zero line, although I’m guessing if you put a regression line through the whole data set, the slope would be pretty small. But the problem with that type of simple moving average filter is that its end point will lag the present by years, and its pretty clear even from the satellite data that we have recent warming in the last couple following the predominantly La Nina years from mid 2010 which gave way to neutral / El Nino since early mid 2014. Only time will tell if the current El Nino ‘spike’ which has actually brought the most recent residuals back to negative values (around -0.2 for the most recent points on your graph) leads to a sustained step up in temperatures as was seen after 1998, and thus whether that red line in your graph will continue to head south. But I would be interested in what a regression line would look like if you superimposed it on this plot for the overall trend fitted to the raw residuals (not the smoothed, so that it includes these most recent points), for the period since 1970 which is claimed to be the onset of CO2 induced warming.
We do not know what GISS will be in April, but according to the following after 14 days:
http://www.moyhu.blogspot.com.au/p/latest-ice-and-temperature-data.html#NCAR
My best guess so far would be 1.18, or a drop of 0.1 from March.
I’m used to reading stock charts, so maybe I’m missing something. I have to wonder, though, how these folks are discriminating the increase (assuming it’s legitimate and not an artifact of data manipulation) in 2015 (in Figure 1 or 2 or 3 of OP, for instance) from the front side of the spike in 1990, or 1995, or 1997, or….
Eric Hines
2016 looks set to be yet another hottest year on record…
http://s24.postimg.org/gpy3f52dh/temps.jpg
https://twitter.com/climateofgavin/status/721084941405184001
Why is he using a baseline of 1880 to 1899? That was a cool trend period.
i have no idea 🙂
It’s so simple, you just need to read! The comment’s author wanted to show the increase since the pre-industrial level, not more not less.
If the baseline had been chosen at 1951-1980 (GISS, Berkeley Earth) or even 1981-2010 (UAH), it would have been much more complicated for the reader to grasp the stuff, as many anomalies then would have had a negative value.
More over, the baseline level difference between 1880-1899 and 1951-1980 is -0.214 °C, whereas that between 1951-1980 and 1981-2010 is +0.428 °C.
After 3 months, the difference between the January to March average and the previous record
for GISS is 0.39.
For Hadsst3, it is 0.084.
For UAH6.0beta5, it is 0.219.
For RSS it is 0.278.
For Hadcrut4.4, after 2 months, it was 0.233.
The climate scientists are so blind they can’t see the forest through the trees. Take a look at this MODTRAN output and ask, where are all the ground measurements? They are all within 100m of the earth’s surface. According to MODTRAN, the bible of climate science, CO2 has absolutely no effect in the first 100m from the surface. Surface measurements have absolutely nothing to do with the lower 100m, so record high ground measurements prove incoming radiation, not CO2 is the cause of warming. This “science” is a complete joke.
Here is more trouble for the AGW theory. CO2 can’t warm the oceans, and that is where the warming is. The oceans are warmed by the incoming radiation. My bet is the passage of the clean air act is why we have all this warming. Cleaner air means more visible radiation reaches earth.
https://www.sciencedaily.com/terms/global_warming.htm
We may be overly concerned about fine scale issues related to daily observations and adjustments. Zoom out.
On the other hand few observers are focused on this interstadial peak like Bob. His step function (which I think is at work here in this new temperature peak) will I believe, hold the top accepted global warming theory in due time. CO2 is just along for the ride up.
http://onlinelibrary.wiley.com/doi/10.1002/2015RG000482/full
Thank you Pamela Gray for this hint on a very interesting paper, even if it will cost me quite a lot of energy to grasp.
Lolz we just dont have enough resolution to be assessing the global temp to within 0.01 degrees.
This is all so hilarious.
Also, Schmidt and Mann seem obsessed with weather.
As said above, the NH land is not showing this warming, spring has been delayed by cold in much of the US and Europe.
No one is feeling this record heat, except maybe fish in the sea 😀
Apparently only surface stations matter because “that’s where people live” but not when the land surface stations are showing no records lol, then SST are entirely relevant.
These people need to pick one story and stick to it. It’s a parody.
Schmidt and Mann have to be obsessed with weather, they’ve got nothing else.
Mark it’s not a parody it’ s a cover up . Lives lost , $$billions wasted over a complete unscientific fraud .
At it’s most basic level the public is sold scary global warming stories based on very suspect estimates,
demonstrably failed model projects and more than a little pinch of greed .
We better hope it continues to warm and if humans help that is a good thing not bad as they try to sell it .
The 1970’s global cooling scare was supposed to be based on science too . At least they picked a real fear factor to work with . Plants and animals will do just fine with a warming earth while it lasts .
Again we have a plot of observations vs CMIP5 predictions that is:
a) smoothed and fails to show the recent uptick in temps (and also by eye seems to not make it to 2015)
b) does not include updated forcings (that actually happened – and not as predicted as the GCM’s were run).
This is the real state of play….
Enough with Cowtan & Way. They have been thoroughly deconstructed. Do a search and you will get reams of evdience showing they’re off-base.
And the recent uptick is due to El Nino, not to human GHG emissions.
Nothing to with C & W.
Everything to do with GISS and Hadcrut.
And a disengenuous representation of them vs CMIP5 both with smoothing out the recent uptick and not comparing the GCM predictions with forcings that actually occurred.
You do agree that that is legitmate?
Of course you do as it is obviously so.
You cannot decry forecasts when they are integrated forwards with incorrect data.
Like doing NWP (weather) forecasts using a starting point of (say) a high over the UK instead of the reality of a Low.
So yes the uptick is currently due to the now waning EN…. Yet it is ~ 0.4C higher than Mar ’98.
Now I wonder (don’t) why that is?
Hello!!! These are ground temperature measurements, ie surface,/b> Once again, what is the claim? The claim is CO2 is the cause of the warming. Once again, CO2 is the cause of the warming. I’ll repeat, CO2 is the CAUSE of the warming. Where is the warming? THE SURFACE. How do we calculate the impact of CO2 on the surface? We use MODTRAN. What does MODTRAN calculate the impact of CO2 is on the surface temperature? ABSOLUTELY ZERO.
This is the MODTRAN output for looking down from 100 meters. What percent of ground measurements are taken within 100 meters from the surface? 100%, there is a 100% certainly, there is an R^2 of 100 when testing if the temperature measurement was taken within 100 meters from the surface. According to MODTRAN surface measurements are unaffected by CO2. The computer doesn’t lie. Once again, these Einsteins in the field of climate “science” don’t even understand the data and variables that they are dealing with. No wonder their models are pure garbage. As I’ve said nth^10000 times, the increase in surface and ocean temperatures are due to incoming radiation not trapping outgoing IR between the range of 13 and 18µ, and MODTRAN proves it.
I just checked my calculations to make sure I was right. Looking down from 0.1km, if you change CO2 from 280ppm to 400ppm the change in W/M^2 is IMMEASURABLE. I repeat immeasureable, ie 0.000 W/M^2. The level of incompetence of these climate “scientists” is astronomical. Don’t take my word for it, check the numbers yourself.
http://climatemodels.uchicago.edu/modtran/
What kind of nit-wit would do a scientific study of temperature and CO2 and use measurement gauges located in the area of the atmosphere where CO2 has no impact? That is like doing a study on lung cancer and smoking, and choosing a population of young non smokers. All, 100% of these ground measurements are taken in the area of the atmosphere where the impact of CO2 CAN’T BE MEASURED. The level of malpractice is mindblowing.
Other areas of scientific malpractice.
1) CO2 can’t warm the oceans, yet they claim the warming is due to CO2.
2) CO2 can’t cause a record high daytime temperature. Daytime temperatures are due to incoming radiation.
3) CO2 isn’t the independent variable, energy absorbed is.
4) There is no warming in Antarctica over the past 50 years, the cold dry air of Antarctica is an ideal control for the impact of higher CO2 levels.
5) I’ve seen no evidence that the spread between day and night in the dry deserts has been narrowing. The dry deserts are another control for CO2.
The more you look into this AGW theory, their data, their measurements, and their MODTRAN the more nonsensical it becomes. Here is a saturation graph of atmospheric H2O. At about 299°K or 26°C, saturation is about 20 millibars.
http://www.ldeo.columbia.edu/~martins/climate_water/slides/vapor_p.gif
If you plug 20 millibar into the MODTRAN program, that is Water Vapor Scale = 1, you will see that at 0.1km, the atmosphere basically matches the black body radiation. H20 however declines with altitude both due to the thinning of the atmosphere and precipitation. H20 reaches 0.00 mbar at 14 KM, or basically 0.00%. At 14km the air is very dry, and very cold, or -64°C. CO2 however remains 400ppm all the way up to 70km, in fact the program stops at 70km, so CO2 even goes higher. Spectralcalc has it 400ppm all the way up to 80km.
If you change the vater vapor scale to keep water vapor at 20 mb for each level of altitude you look down from , you see that adding H20 will keep the atmosphere basically in line with the black body. What causes the stalactite like spike due to CO2 is the result of H20 precipitating out of the atmosphere. As you reduce the H20, the CO2 signature is exposed. At higher altitudes the only GHG is CO2 and O3, and the O3 band starts at 20k and ends at 70k. According to MODTRAN, CO2 doesn’t impact surface temperatures at all. If there is a CO2 signature you would have to go above the water vapor at about 10 to 14km, or the upper troposphere/lower stratosphere. To prove man made CO2 is causing any warming at all, you would have to control for the H20, O3 in the atmosphere, and the warming due to CO2 would be discovered between 10 and 14km. Even if CO2 does cause warming of the stratosphere, who cares? What impact would that have on earth? None.
The Nit-Wit climate “scientists” claim CO2 will cause stratospheric COOLING.
Global Warming Causes Stratospheric Cooling
https://www.wunderground.com/resources/climate/strato_cooling.asp
That is pure nonsense, MODTRAN demonstrates that higher CO2 levels would cause the warming of the stratosphere, simply look down from 14km and change CO2 from 280 to 400 ppm. Their conclusion is completely refuted by MODTRAN, and defines the common sense logic outlined above. Higher CO2 levels would lower the altitude at which CO2 impacts temperature, but CO2 is completely irrelevant when H2O is involved. MODTRAN proves it.
My impression of looking at this, and I think your conclusion is similar if I’m reading this right, is that the main heating from IR is what hits the ground or surface of the earth. The rest seems like a distraction into tiny heating possibilities, completely overwhelmed by the actual heating if they actually exist.
The stratosphere has been cooling. That is 100% contrary to MODTRAN calculations. If the stratosphere is cooling, and the trpposphere is warming, it isn’t due to CO2…unless MODTRAN is completely useless.
http://hadobs.metoffice.com/hadat/images/update_images/global_upper_air.png
OK, I think I’ve found a way to explain just how awful the IPCC Models are, and why they are and will continue to be wrong, even if they adjust the data.
1) The ground measurements they use do not isolate the impact of CO2, in fact the impact of CO2 is immeasurable at the level of the ground temperature gauges. If you are going to measure the level of rainfall in India, you don’t put your water traps in Death Valley. The CO2 signature would be identified in the upper troposphere/lower stratosphere, above 8 km and below 20km. This area of the atmosphere has basically 0.00% H2O, 0.00% O3 and 400 ppm CO2. It is a natural control for CO2, so is Antarctica and the dry deserts. MODTRAN calculates that increasing CO2 should warm that region of the atmosphere. Measurements show that it is cooling.
2) When creating a valid model you need valid variables. If I do a study on weight loss and measure “exercise” and “food intake” my model will fail completely. Why? Because “exercise” and “food intake” are poorly defined. The problem is some people may consider eating exercise, playing video games exercise, 12 oz curls as exercise, and some people may consider a bottle water food intake, a rice cake food intake and a diet coke as food intake. That is what measuring CO2 does, it misses the point of the experiment. The real model would be weight loss is a function of caloric intake and caloric expenditure. That way you measure the true inputs calories eaten and calories burned, highly quantifiable objective variables. Climate models should use energy trapped, not CO2 levels. CO2 is like eating/drinking a bottle of water and considering it a meal.
http://greenlichen.com/wp-content/uploads/2013/08/1bottledWater.jpg
Bingo!!!! I’ve made the comment that Antarctica and the Dry Deserts are natural controls for the impact of CO2. Believe it or not, there is an actual climate scientists with enough common sense to figure that out and actually test for the impact of CO2 over the polar regions. The results are as expected, CO2 makes no measurable impact. I’m not a climate scientist, but I could easily identify the flaws in their models and theories. Each time I find data from a valid model it refutes the claims of the alarmists. CO2 based AGW is simply very very very very bad science. Either the people in the climate science departments are hopelessly incompetent, or they are deliberately violating sound scientific practices for political/personal or other selfish gains. When a complete novice can outline an alternative theory and identify flaws in existing models and understandings and then find data that proves those alternative views, it pretty much proves climate science and AGW is a joke.
http://www.hindawi.com/journals/ijas/2013/503727/fig21/
http://www.hindawi.com/journals/ijas/2013/503727.fig.0021b.jpg
Regarding Figures 10 and 11: Am I understanding correctly that the graph for modeled temperature increase is the average of the CMIP5 RCP8.5 models? When does the graph transition from hindcast to forecast? I have not been able to find a definitive date by doing web searching, but it seems to me to be around 2006.
Meanwhile, I think RCP 6.0 is more realistic for “business as usual” than RCP 8.5, mostly due to atmospheric methane increasing less than projected in IPCC assessment reports up to and including 5.
I’m always stunning about the fact that so many people see these poor surface temperatures being target of huge adjustments upwards all the time, but that so few people look at what happened to UAH last year, as Roy Spencer announced the trasition from revision 5.6 to revision 6.0beta.
Here is a comparison of UAH’s adjustments with those made by GISS, plotted by the Australian scientist Nick Stokes:
Feel free to download the data from the UAH site by your own, and to compare them as I did, so you see that Nick Stokes comparison is accurate:
– UAH6.0beta5 tlt: http://vortex.nsstc.uah.edu/data/msu/v6.0beta/tlt/uahncdc_lt_6.0beta5.txt
– UAH5.6 tlt: http://www.nsstc.uah.edu/data/msu/t2lt/uahncdc_lt_5.6.txt
But if now you additionally compare the global differences between the two revisions with their differences in the polar regions, you will wonder quite a bit more: the latter differences are even bigger in comparison with the globe’s.
http://fs5.directupload.net/images/160409/npuhgte5.jpg
In red: the diff plot for the global data;
In blue and green: the diff for north and south pole respectively.
You see that the global diffs suddenly appear minimal in comparison with the polar diffs (the same holds for the comparison of tropics diffs with the polar diffs).
Interestingly, I could never read a statement by Roy Spencer clearly explaining the difference between the changes in the north polar region and those in the south Pole: while the latter keeps the overall diff trend relatively constant, the changes at north Pole moved UAH there from 30% warmer than RSS to 30% cooler!
Imagine the revision 6.0beta5 had made UAH’s data not cooler, but warmer 🙂
Thus yes: adjustments were made for surface measurements, especially in the arctic region. It was not the first time, and won’t be the last time.
Please remember that big differences appeared between HadCRUT3 and HadCRUT4: this was mainly due to the fact that hundreds of stations in arctic Russia were added to CRUTEM4. All these stations were not accounted for in the preceeding revisions.
And right now we are in front of a major revision of RSS which of course EVERYBODY here would have immediately accepted… if it made the new data represent a trend to cooler temperatures !!!
For me there is only one rule, regardless where the changes go to: Que le meilleur gagne!
co2islife April 17, 2016 at 6:46 am
…
Other areas of scientific malpractice.
Are you a scientifically educated person able to make the difference?
1) CO2 can’t warm the oceans, yet they claim the warming is due to CO2.
Nobody ever told that.
2) CO2 can’t cause a record high daytime temperature. Daytime temperatures are due to incoming radiation.
Nobody ever told that.
…
4) There is no warming in Antarctica over the past 50 years
This is simply wrong.
See among other papers:
Steig EJ, Schneider DP, Mann ME, Rutherford SD, Comiso JC, Shindell DT
Warming of the Antarctic ice-sheet surface since the 1957 International Geophysical Year
Nature 457, 459-462 (22 January 2009), reviewed paper.
Some papers indeed see no warming at all in East Antarctica; but all share the fact that not only the Peninsula but the WAIS as well are warming, especially through the ocean.
See “Antarctic Temperature and Sea Ice Trends over the Last Century” by George Taylor (private opinion !!!). It is visible that he misunderstands the close relation between sea ice increase and local warming.
… the cold dry air of Antarctica is an ideal control for the impact of higher CO2 levels.
You are so fixed on people pretending that CO2 is the origin of warming that you forget all the others having clear doubt about that.
Extremely so, but not is climate science.
Really, then why do they use Land and Ocean Temperature Graphs to make their case? The whole purpose of the AGW Theory is to point to anthropogenic CO2 as the cause of the warming.
They why does Al Gore and the media hype up record DAYTIME temperatures?
The context of that comment is the inner Antarctica away from the coast and oceans to isolate the dry air removed of the impact of H2O. That is why I specifically stated “the cold dry air of Antarctica is an ideal control for the impact of higher CO2 levels.” Real scientists look for “controls” and the dry deserts and Antarctica offer those controls.
http://www.john-daly.com/ges/surftmp/stations/amundsen.gif
“Extremely so, but not i[n] climate science.”
Thus the best for all of us would be that you stop doing all the time as if you were.