Why I Remain Uncertain about Global Warming and Climate Change — Part 3 of 4

What are the warming metrics for water vapor?

Good question. I couldn’t find them.

No precise measurements of water vapor in atmosphere?

As far as I can tell, there is no precise measurement or even vaguely accurate estimate of how much water vapor is in the atmosphere.

Why doesn’t NOAA measure carbon dioxide at Mauna Loa?

The NOAA Earth System Research Laboratory at Mauna Loa volcano in Hawaii measures carbon dioxide in the air, but curiously they don’t measure water vapor at the same time.

What is the global warming impact of carbon dioxide vs. water vapor?

I haven’t been able to find a clear-cut answer to the question of the temperature impact of water vapor relative to carbon dioxide.

  1. What is the total, overall greenhouse effect for a given greenhouse gas.
  2. What is the incremental greenhouse effect for a molecule (or mole or other unit) of a given greenhouse gas.
  1. Water vapor and clouds: 36–72%
  2. Carbon dioxide: 9–26%
  3. Methane: 4–9%
  4. Ozone: 3–7%
  • significant initial forcing vs.
  • fundamental agent of climate change.

Fraction of atmosphere for water vapor vs. carbon dioxide

As per the wikipedia, carbon dioxide comprise about 0.04% of the atmosphere — roughly 400 parts per million.


Clouds are not water vapor per se, but condensed water vapor which forms small droplets of liquid water.

Do clouds make global warming better or worse?

Do clouds reflect sunlight and cool the planet, or do they trap heat and warm the planet? The various answers — from science:

  1. Sometimes they cool.
  2. Sometimes they warm.
  3. Unclear.
  4. Net impact is unknown.
  1. https://www.nsf.gov/news/special_reports/clouds/question.jsp
  2. https://isccp.giss.nasa.gov/role.html
  3. https://www.giss.nasa.gov/research/briefs/delgenio_03/
  4. https://www.skepticalscience.com/clouds-negative-feedback.htm
  5. http://e360.yale.edu/features/investigating-the-enigma-of-clouds-and-climate-change
  6. https://en.wikipedia.org/wiki/Cloud_feedback
  • Clouds cool Earth’s surface by reflecting incoming sunlight.
  • Clouds warm Earth’s surface by absorbing heat emitted from the surface and re-radiating it back down toward the surface.
  • Clouds warm or cool Earth’s atmosphere by absorbing heat emitted from the surface and radiating it to space.
  • Clouds warm and dry Earth’s atmosphere and supply water to the surface by forming precipitation.
  • Clouds are themselves created by the motions of the atmosphere that are caused by the warming or cooling of radiation and precipitation.
  • https://isccp.giss.nasa.gov/role.html
  1. The global climate is such a complex system that no one knows how even a small increase in temperature will alter other aspects of climate or how such alterations will influence the rate of warming.
  2. the understanding of clouds is so rudimentary that no one knows whether climate feedbacks involving clouds will dampen or amplify a warming trend.

Concrete (cement) production

Not many people realize it, but production of concrete (cement) is a significant source of global carbon dioxide emissions. Beyond simply being energy intensive, cement production involves a chemical reaction which directly releases carbon dioxide. This is distinct from the chemical reaction that occurs when wet concrete sets (hydration and curing.)

Land use

I tentatively accept that land use can impact the amount of carbon dioxide that remains in the atmosphere.

Ocean absorption of carbon dioxide

I tentatively accept that the oceans absorb some amount of carbon dioxide from the atmosphere.

No reliable global temperature record

I’ll elaborate my concerns in the sections that follow, but to make a long story short, my single biggest concern over the theory of global warming and climate changes is the simple fact that we don’t have a reliable record for global temperature. Without a reliable record for global temperature, any theory that depends on global temperature will be of dubious quality at best.

Global temperature anomalies

Climate scientists prefer to speak of temperature anomalies rather than absolute temperatures. Mostly this seems to be so that temperature increases around the world can be compared, regardless of the differences in temperature of different regions of the world, or even the differences between valleys and mountains in a specific locale.

Global mean surface temperature (GMST)

Although scientists prefer to report temperature anomalies, the IPCC refers frequently to global mean surface temperature (GMST). As far as I can tell, this is more of an abstract, conceptual reference rather than a reference to actual temperature data. When the actual data is referenced, it is always as a temperature anomaly.

What is the accuracy of the baseline average used for global temperature anomalies?

NOAA reports the margin of error for global temperature anomalies, but they don’t report the accuracy of the baseline temperature average that is used when calculating the anomalies.

  1. The margin of error for the baseline average. Including math for how that margin was calculated from all of the individual annual (or monthly?) margins of error over the baseline period.
  2. The margin of error for the for the absolute temperatures of the year or month or period being reported.
  3. The combined margin of error for the anomaly of the year or month or period being reported.

The historic temperature record changes when the baseline period is revised

Normally, one would presume that historic data is just that, an immutable (unchanging) record of the past, but with temperature data it gets complicated since temperatures are reported as anomalies or differences from a baseline time period. That would be fine if the baseline period was stable, but scientists like to shift to a new baseline period as the decades pass by.

Dubious quality of measures of earth temperature

I’ve previously cited the NOAA data for temperature of the climate.

  1. Hadley Centre/Climatic Research Unit — HadCRUT4.
  2. NOAA Merged Land–Ocean Surface Temperature Analysis — MLOST.
  3. NASA Goddard Institute for Space Studies Surface Temperature Analysis — GISTEMP.
  1. Northern hemisphere land.
  2. Northern hemisphere ocean.
  3. Southern hemisphere land.
  4. Southern hemisphere ocean.
  5. Northern hemisphere land and ocean.
  6. Southern hemisphere land and ocean.
  7. Global land.
  8. Global ocean.
  9. Global land and ocean. The single temperature of the entire planet.
  1. Africa
  2. Asia
  3. Europe
  4. North America
  5. Oceana
  6. South America
  1. Dubious precision of global temperature.
  2. Primarily the output of complex models rather than actual measurement.
  3. Too few actual measurements fed into models. Not enough weather stations and ocean data buoys.
  4. Too much of Earth not measured at all. See subsequent section.
  5. No empirical validation possible for the resulting estimate of temperature of the planet as a whole.
  6. Dubious statements such as “missing data filled in by statistical methods” when the claim is that global warming is “settled” and “beyond dispute.”
  7. Too much of a hodgepodge of measurement methods — land weather stations, ocean data buoys, satellite remote sensing, some ships — and many gaps. No reliable way to combine those disparate measures. No way to empirically validate the combined data. Lots of judgment required, which may be valid, but who knows for sure?
  8. Dubious quality of older temperature data. Long before modern data sensors. Long before NOAA data buoys (1970’s.)
  9. Dubious to compare older data with modern data. Differences in methodologies. Differences in sensors.
  10. Are seasonal temperatures affected equally? I know Arctic summers are not significantly warmer in summer since 1958, but are significantly warmer in winter.
  11. Confusion over conflicting assessments of the so-called “hiatus” or “stalling” or “pause” of the warming trend between 1998 and 2012.
  12. Change in modeling methodology in 2015. Difficult to determine what the true motive was, which raises suspicion that it seemed motivated by a desire to disprove (or cover up?) the alleged hiatus of warming from 1998 to 2012. More details on the hiatus in coming sections.
  13. Yet another set of updates to the NOAA Extended Reconstructed Sea Surface Temperature (ERSSTv5) dataset in July 2017. This is part of the data that goes into the data that produces the NOAAGlobalTemp dataset. Previous updates to ERSST in May 2015. This pace of data and methodology updates is disconcerting to me for something that claims to be “settled science.”

NOAA Merged Land-Ocean Surface Temperature Analysis (MLOST)

MLOST is the global temperature dataset (what I personally call a model) that NOAA used prior to May 2015. They have now upgraded to a new global temperature dataset (model) called NOAAGlobalTemp.

NOAA Merged Land Ocean Global Surface Temperature Analysis Dataset (NOAAGlobalTemp)

NOAAGlobalTemp is the global temperature dataset (what I call a model) that NOAA has used since May 2015. Previously they used the MLOST dataset.

NASA GISS Surface Temperature Analysis (GISTEMP)

NASA’s Goddard Institute for Space Studies (GISS) produces the GISTEMP global temperature dataset (what I call a model):

HadCRUT4 global temperature dataset

The IPCC uses the HadCRUT4 temperature dataset (what I call a model) extensively. Sometimes they use the NOAA and NASA datasets as well.

Separate global land and ocean temperature datasets

Land and ocean temperatures are two different concepts, are measured differently, and have two different datasets (what I call models), even if the two datasets are ultimately combined into a single dataset (model) for global temperature across both land and ocean.

  1. GHCN for land temperature. Global Historical Climatology Network Monthly (GHCN-M) database.
  2. ERSST for ocean (sea) temperature. Extended Reconstructed Sea Surface Temperature (ERSST) dataset.

Is it a dataset or a model?

Data is data, whether its source was a direct measurement, a simple conversion, a simple calculation, or a complex modeling or analysis process. So, technically, even the output of a complex model is still simply a dataset.

Temperature simulation model vs. temperature model

Sometimes people use the term model to refer to a simulation of future behavior of a system.

Global temperature datasets and models

The climate science community refers to their calculations of global temperature data as a dataset or analysis, while I refer to it as a model.

No empirical validation possible for global temperature

Even if you have great confidence in the sensor data for temperature and really believe in the modeling process used to derive that single number for global temperature of the entire planet, the essential problem is that it simply isn’t possible to empirically validate that number.

Dubious model of Earth temperature

I have some more general, abstract concerns with how one would go about modeling the temperature of the Earth:

  1. Half the planet is is sun, half in darkness, always, at the same time. What’s the model of total planet surface temperature in that situation?
  2. How to model temperature across seasons?
  3. How to model temperature as planetary precession progresses?
  4. How to adjust or model satellite-based measurements based on orbits that are not always the same precise altitude or pass over the same precise points at the same precise times of day?
  5. How to model temperature when measurements from ships are not in the same place on successive measurements or over extended periods of time?
  6. How to model temperature when measurements from drifting buoys are not in the same place on successive measurements or over extended periods of time?
  7. How to properly measure sea surface temperature in littoral areas (shallow water) when tides result in significant changes in depth and lateral movement of masses of water?

Dubious precision of global temperature

My main problem with the data concerning global temperature is the dubious claims about its precision. Given all that we know about the difficulty of measuring just about anything on a global scale, I simply don’t find claims about the precision of global temperature to be even close to being credible.

  • 2013: Land: 0.19 C, Ocean: 0.03 C, Combined: 0.09 C
  • 2014: Land: 0.20 C, Ocean: 0.04 C, Combined: 0.09 C.
  • 2015: Land: 0.18 C, Ocean: 0.01 C, Combined: 0.08 C
  • 2016: Land: 0.15 C, Ocean: 0.16 C, Combined: 0.15 C

Why was ocean temperature accuracy 0.01 C in 2015 but 0.16 in 2016?

I’m not sure which is the bigger and more significant question or problem:

  1. How was NOAA able to measure (model) global ocean temperature to within 0.01 C in 2015?
  2. Why was NOAA then only able to measure (model) global ocean temperature to sixteen times that margin of error, 0.16 C, in 2016?
  3. What happened to cause and account for the dramatic shift

What is the natural variability of global temperature?

Scientists, activists, and science communicators chat up a mantra that the temperature anomalies are not due to natural variability, but don’t bother specifying natural variability. Like an actual number, as well as the science and math used to derive that number.

How does solar rotation affect incoming solar radiation?

The sun rotates on its own axis in addition to the Earth revolving around the sun, and each with a different angular velocity, so they are not in sync. Whether or how this affects the amount of incoming solar radiation is unclear.

  1. Natural variability of solar output, as in solar cycles.
  2. Variability that results from solar rotation.

How accurately can scientists measure the temperature of the Earth?

Seriously, as a simple question, a practical matter, if you could ask scientists how accurately they could measure the temperature of the Earth, how accurately would they say they could do it? Without peeking at the global temperature datasets to see what NOAA, NASA, et al are actually claiming.

  • To 0.1 C (which is essentially the implied claim right now)?
  • To 0.01 C (as they claimed for the ocean in 2015)?
  • To 1 C?
  • To 2 C?
  • To 5 C?
  1. How many measurements go into the model?
  2. How much coverage do those measurements provide?
  3. How precise (and accurate) is any interpolation between measurements?
  4. How precise (and accurate) are actual measurements?
  5. How are measurements actually combined in the model?
  6. How does precision evolve as measurements are combined?
  7. How incomplete data series are dealt with — older series without recent data and newer series without older data?
  8. How to cope with different precisions for different data series and different measurement technologies?
  9. How to cope with differences between land and ocean?
  10. How to cope with calibration of measurement instruments?
  11. How to cope with night vs. day — half the Earth is in sun, half not, so how is temperature for the whole planet even defined?

Is global temperature based on seawater at the surface or air above the water?

Scientists refer to SST or Sea Surface Temperature when discussing how global temperature is measured and modeled, but I haven’t been able to find any clarification whether they are measuring water at the surface or air right at the surface.

Change in global temperature modeling methodology in 2015

I am especially sensitive to changes in methodology, either strategic or tactical.

  1. The actual temperature sensor readings from individual weather stations. To me, this is the real or true data.
  2. The results or output data produced from the global temperature models that take the real, weather station data, and then massage and otherwise adjust the data and then combine all of that adjusted data using algorithms to piece and fit and interpolate and extrapolate this data to combine it all into a seemingly uniform and consistent model of reality. The final results that they report.

Extended Reconstructed Sea Surface Temperature Version 4 (ERSST v4) dataset

As previously noted, NOAA global temperature modeling switched to using data from the Extended Reconstructed Sea Surface Temperature Version 4 (ERSST v4) dataset in 2015. I consider ERSST to be a model rather than pure measurement of temperature.

Extended Reconstructed Sea Surface Temperature (ERSSTv5) dataset

In July 2017 NOAA introduced a further batch of changes to their Extended Reconstructed Sea Surface Temperature (ERSSTv5) dataset. As before, I consider ERSST to be a model rather than pure measurement of temperature.

International Comprehensive Ocean-Atmosphere Data Set (ICOADS)

As per NOAA:

Global weather stations used for global temperature modeling

Global temperature is modeled by combining temperature data from thousands of weather stations around the globe.

Do we have enough weather stations to accurately model global temperature?

According to NASA GISS (or my reading of their charts, I should say), as of 2016, about 20% of the area of the northern hemisphere is not within 1200 km (746 miles) of a weather station, and about 27% of the area of the southern hemisphere is not within that same range of a weather station. Is that a lot? Who’s to say, but it does raise some concern on my part.

Risks of extrapolation from small samples

My big concern is that NOAA has insufficient instrument measurements to extrapolate or model the temperature for the entire planet.

How many ships provide sea surface temperatures?

NOAA does supplement that hard data from data buoys with data from ships travelling the oceans, but I haven’t been able to find hard data on how many ships and for how long. I haven’t seen any data reported publicly. Hundreds of ships? Thousands? I need to see some data.

How accurate are ship sea surface temperatures?

Are ship-based sea surface temperature (SST) readings as accurate as NOAA data buoys, less accurate, or maybe more accurate? There is no publicly available information that answers this question, but an answer is needed.

Lack of location consistency of ship temperature sensors

Even if a temperature sensor on a ship is very accurate, the mere fact that ships are generally moving continuously precludes the possibility of having a consistent data series of temperature measurements for any given location by a given sensor.

Technology of ship temperature sensors

What temperature sensor instrument technology or technologies are being used for ship-based temperature readings?

Accuracy, precision, margin of error, and calibration

It is so easy to confuse or conflate accuracy, precision, and margin of error. In fact, I do it too frequently myself. I’ve probably done it a few places in this paper.

  • Accuracy is how close a measurement, calculation, or estimate is to the true value of the quantity being measured, calculated, estimated, or modeled.
  • Precision is how fine a granularity a measurement or estimate is, typically characterized as a number of significant digits or a number of decimal digits.
  1. Claimed accuracy is how close a measurement, calculation, or estimate is believed to be. This is the stated margin of error. This is an exact synonym for margin of error.
  2. True accuracy is how close the actual, real value of a quantity is to a measurement, calculation, or estimate that purports to represent the true value of that quantity.
  1. Claimed margin of error is the stated margin of error. Generally a synonym of margin of error.
  2. True margin of error is the margin of error relative to the actual value of the quantity being measured, calculated, estimated, or modeled.

How many data points are needed to measure global temperature to a given precision?

Oops… I just spent a whole section explaining how accuracy and precision are different, but already I make the slip-up myself! I should have worded the title of this section as “… given accuracy” rather than “… given precision”, but I kept it as is to simply reinforce the point of the previous section.

  • How many data points are needed to measure global temperature to a given accuracy?
  • How many data points are needed to measure global temperature to a given true accuracy?
  • How many data points are needed to measure global temperature to a given claimed accuracy?
  • How many data points are needed to measure global temperature to a given true margin of error?
  • How many data points are needed to measure global temperature to a given margin of error?

What time of day is temperature measured?

How many temperature measurements are made each day in the process of obtaining the temperature of the day that is recorded in the temperature datasets?

  1. Pre-1958
  2. 1958–2000
  3. 2000 — today

How accurate are satellite temperature measurements?

There are a number of areas of concern that I have with satellite measurements of temperature:

  1. Area resolution. How fine a grid or spot can be measured?
  2. Accuracy. Of the actual temperature measurement. Or, actually, the deduced or inferred temperature given that it is really a measure of irradiance.
  3. Margin of error. Given the size of the area.
  4. Coverage throughout the day for each location, to get minimum, maximum, and average or mean.
  5. Is there any possibility of empirical validation between a particular satellite measurement and a surface sensor at precisely the same location?
  6. How do the area resolution, accuracy, and coverage get reflected in the modeling process needed to blend this disparate data in with traditional land and sea temperature data, including the impact on the margin of error for global temperature.
  7. To what extent is satellite temperature data used in the NOAA, NASA, and HadCRUT global temperature analyses? Is it a significant factor or a minor factor? Is it critical or simply an extra benefit?
  8. Could they model the temperature of the entire Earth using only satellite temperature data? If not, why not?
  9. What criteria are used to determine when satellite temperature data is used when modeling global temperature?

How much satellite data is included in global temperature?

I haven’t been able to find any hard data on the extent to which satellite temperature data is used by NOAA, NASA, et al when calculating global temperature.

How long are datasets that use the exact same measurement instruments and methodologies?

Technologies for measuring environmental data have changed dramatically since the 19th century. I am concerned that every time we change the technology it means that we shorten the length of the dataset which was captured using a particular measurement technology. In particular, for all of the data series that go into the current global temperature models, how long are each of those data series, that were captured with the same instruments and methodologies?

  • Electronics
  • Digital
  • Software
  • Remote sensing
  • NOAA data buoys
  • Satellites
  • Deep ocean measurements
  • Continual software updates
  • Multiple generations, revisions, updates, and variations of each of the above

Dubious stability of temperature data and models

With somewhat frequent updating of the global temperature models and datasets and ongoing updating of the actual temperature sensors and their siting, including ships in motion, I am very concerned about the stability of temperature data, both the datasets from year to year and decade to decade, as well as the output temperatures from the evolving models.

Accuracy of temperature sensors

I would like to see solid data on the accuracy of the temperature measuring technology used for the various temperature sensors used by NOAA for its global temperature network.

Calibration of instruments

Calibration of instruments has always been a big issue for scientists.

Sample NOAA data buoy data

The NOAA Data Buoy Center lets you check up on the latest data from individual data buoys.

Temperature sensor accuracy over broad temperature range

Temperature sensors have some variability of accuracy over the full range of temperatures they will be exposed to. This variability needs to be examined and reported for each of the various temperature sensor technologies that are deployed in the global temperature sensor network.

  1. Near freezing.
  2. Well below freezing.
  3. Polar cold.
  4. Minimum surface temperature.
  5. Tropical heat.
  6. Desert heat.
  7. Maximum surface temperature.
  8. Sea surface temperature (SST) before, during, and after seawater freezing.

Accuracy of global temperature model relative to sensor accuracy

Note: I’m using the term accuracy loosely in this section. I should be using margin of error to be technically correct. But the general intent is still the accuracy of global temperature measurements and anomalies.

The hiatus of 1998–2012

For those of us carefully monitoring the annual temperature data as it came out back in 2009, 2008 was a real surprise. It was well below the previous two years and below all of the previous seven years. Not enough data for a conclusive trend, but it really stood out.

Rebuttal of the hiatus of 1998–2012

In June 2015 a collection of climate scientists from NOAA published a paper that essentially rebutted the notion of any hiatus of global warming from 1998 through 2012.

Dubious NOAA methodology changes in response to the Hiatus

Buried in that June 2015 paper that rebutted the 1998–2012 hiatus is the following:

  1. These changes have resulted in a time-dependent bias in the global SST record, and various corrections have been developed to account for the bias.
  2. Recently, a new correction was developed and applied in the Extended Reconstructed Sea Surface Temperature (ERSST) data set version 4, which we used in our analysis.
  3. ERSST version 4 also considers this smaller buoy uncertainty in the reconstruction.

More methodology changes to come?

I believe firmly in the test of time. The elapse of time is the only way to firmly and solidly validate any scientific theory or methodology.

Was BRIC development the cause of the hiatus?

I have my own theory (I call it a conjecture) as to what caused the hiatus: development in the BRIC countries, notably India and China, where rapid acceleration of the use of coal power plants and dirty motor vehicles caused a dramatic rise in particulates, which exert a cooling effect, not as great as in the 1940 to 1970 period, but possibly enough to cause the appearance of the hiatus.

Why did the scientists bungle 1998 so badly?

Whether the hiatus of 1998–2012 can be vanquished for good depends very heavily on how the temperature data for 1998 is treated. If 1998 is considered statistically significant, at least some remnant of the hiatus remains. If 1998 is treated as an aberration, a true outlier that should be discarded, then the status of the hiatus is significantly weakened. But which is the proper approach?

  1. In 1999, scientists made a big deal about how 1998 was the warmest year on record, without noting any concerns about any statistical significance difficulties with the year. This cemented the status of 1998 as being statistically significant. Was that judgment on their part wise or imprudent?
  2. It was only after critics started making a big deal about the hiatus that anybody started to question that status of 1998 as being statistically significant.
  3. It was only after the IPCC AR5 Physical Science Basis assessment report in 2013 that NOAA felt any pressure to do something about the perception of a hiatus from 1998 through 2012.
  4. It was only in May 2015 that the scientists at NOAA finally acknowledged that yes, Houston, we do have a problem.
  5. Even now, scientists have not acknowledged that they made a mistake in 1999 by not immediately raising concern about whether 1998 was truly statistically significant.

IPCC on the 1995–2000 portion of the hiatus

To be fair to the scientists, the IPCC AR5 assessment report Technical Summary from 2013 did focus some attention on the 1995 to 2000 sub-period within the hiatus, as to what may have been contributing factors to the perception of a pause or hiatus in global warming:

Truth about the hiatus?

A few key points to close out this discussion of the hiatus:

  1. It was real, but it’s significance continues to be a matter of debate.
  2. The temperature data of 2014, 2015, and 2016 effectively showed a break out (my own words) from whatever hiatus may have been in place from 1998 through 2012. If the global temperature model results are to be believed, which is a huge question mark in my view.
  3. Is the hiatus gone for good? Maybe, maybe not. Who’s to say which was the true aberration, the 15 years from 1998 through 2012 or the last three years? Seriously, nobody knows the answer to that. We can all speculate, but even the speculation of scientists is not the same as whatever truth the future actually holds.

Continued in Part 4 of 4

Continue to Part 4 of 4 and Conclusion.



Freelance Consultant

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