7/10/2021: THE QUESTION

MY ANSWER

Contentious issues in science cannot be settled with opinion debates and this is why the opinion debate in climate change just goes on and on like a rolling stone with no direction home. A science debate must address the data, the methodology, data analysis, the statistical details, and adherence to objective and unbiased scientific inquiry. In this context, I would like to use specific LINKS to my blog to present my critical evaluation of the proposed theory of anthropogenic global warming by way of fossil fuel emissions.

LIST OF LINKS (AGW = THEORY OF ANTHROPOGENIC GLOBAL WARMING)

LINK#1: DATA SELECTION BIAS IN AGW THEORY: https://tambonthongchai.com/2020/10/09/a-data-selection-bias/

SUMMARY: WHAT WE SEE IN CLIMATE SCIENCE IS THAT THEIR CLAIM TO UNDERSTAND INTERGLACIAL TEMPERATURE CYCLES IN TERMS OF THE GREENHOUSE EFFECT OF CO2 CAN ONLY BE APPLIED SELECTIVELY. OF THE MANY TEMPERATURE CYCLES OF THE HOLOCENE THEY CAN ONLY EXPLAIN THE ONE THEY HAVE CHOSEN TO EXPLAIN. AND EVEN THEN, THEY CANNOT EXPLAIN THE WHOLE OF THAT CHOSEN TEMPERATURE CYCLE BUT ONLY THE PARTS THEY CAN EXPLAIN. THE EARLY PART OF THE CURRENT WARMING CYCLE IS EXEMPTED FROM CONSIDERATION BECAUSE IT CANNOT BE EXPLAINED WITH THE THEORY THAT EXPLAINS THE REST OF THE WARMING CYCLE UP TO THE PRESENT AND THAT EARLY PERIOD IS THEREFORE EXEMPTED FROM CONSIDERATION AS THE SO CALLED ETCW: LINK: https://tambonthongchai.com/2020/10/09/the-etcw-issue-in-climate-science/

LINK#2: DATA SELECTION BIAS BIBLIOGRAPHY: https://tambonthongchai.com/2021/06/15/data-selection-bias/

SUMMARY: SELECTION BIAS IS THE BIAS THAT IS INTRODUCED BY THE SELECTION OF A SUBSET OF THE DATA FOR ANALYSIS THAT SUPPORTS THE THEORY PROPOSED. PROPER RANDOMIZATION IS NOT ACHIEVED. THE MANNER OF DATA SELECTION ENSURES THAT IT WILL SUPPORT THE THEORY PROPOSED ALTHOUGH THE DATA DO NOT REPRESENT THE RELEVANT POPULATION THE DATA IS ASSUMED TO REPRESENT.

LINK#3: THE UNCERTAINTY ISSUE: LINK: https://tambonthongchai.com/2020/04/22/climate-science-uncertainty/

SUMMARY: IN STATISTICS AS IN INFORMATION THEORY, HIGH VARIANCE MEANS LOW INFORMATION CONTENT. UNCERTAINTY MEANS THAT WE DON’T REALLY KNOW BECAUSE OUR INFORMATION LIES SOMEWHERE BETWEEN KNOWING AND NOT KNOWING. IN TERMS OF THE VARIANCE PARAMETER WHAT THIS MEANS IS THAT THE HIGHER THE VARIANCE THE LESS WE KNOW BUT A HIGH VARIANCE ALSO YIELDS LARGE CONFIDENCE INTERVALS THAT CAN CREATE SCARY HIGH VALUES THAT THE ANSWER COULD BE. THE USE OF CONFIDENCE INERVALS IN THIS WAY BY CLIMATE SCIENCE VIOLATES STATISTICAL PRINCIPLES AND PRINCIPLES OF UNBIASED AND OBJECTIVE SCIENTIFIC INQUIRY. THIS KIND OF “LOOK HOW DANGEROUSLY HIGH IT COULD BE” CLIMATE SCIENCE FEAR MONGERING IS CLEARLY A FORM OF ACTIVISM AND NOT SCIENCE.

THE LESS WE KNOW THE HIGHER IT COULD BE AND IN PERFECT IGNORANCE IT COULD BE AS HIGH AS INFINITY BECAUSE THE ANSWER IS NOT CONSTRAINED BY INFORMATION. HIGH VARIANCE IS AN INDICATION OF LOW INFORMATION CONTENT AND THE USE OF HIGH VARIANCE TO PRESENT THE DANGER OF LARGE CONFIDENCE INTERVALS IN TERMS OF HOW HIGH IT COULD BE IS EITHER IGNORANCE OF STATISTICS OR A DELIBERATE ABUSE OF STATISTICS TO PUSH THE FEAR OF FOSSIL FUEL EMISSIONS AND ITS CLAIMED CLIMATE CATASTROPHE.

LINK#4: CONFIRMATION BIAS: LINK: https://tambonthongchai.com/2020/06/29/diffenbaugh-2017-extreme-weather-of-climate-change/

SUMMARY: Event Attribution Science is a methodology of using climate model simulations to attribute extreme weather events such as heat waves, floods, and droughts, post hoc, (after the fact) to anthropogenic global warming thought to be driven by fossil fuel emissions and thereby ultimately to the use of fossil fuels. The procedure suffers from several weaknesses including confirmation bias, circular reasoning, and the extreme localization in time and space in the interpretation of a theory about long term trends in global mean temperature. Confirmation bias in this procedure invalidates the findings that must be understood as a creation of confirmation bias because the data analysis begins with the assumption that the extreme weather event was a creation of climate change and then looks for supporting evidence in multiple climate model runs.

LINK#5: CLIMATE SCIENCE VS STATISTICS: https://tambonthongchai.com/2021/05/18/climate-science-vs-statistics/

SUMMARY: Here we note that climate science presents the causation relationship between global mean surface temperature and atmospheric CO2 concentration in two different ways, first in climate sensitivity as a logarithmic relationship between the logarithm of atmospheric CO2 concentration and surface temperature and again in the TCRE {transient climate response to fossil fuel emissions} as a linear relationship between cumulative emissions and surface temperature. In the related post we show that these two different mechanisms proposed as the fundamental causation relationship upon which all of the rest of AGW climate science rests, are inconsistent such that they can’t both be true. We propose that this inconsistency in the science of anthropogenic global warming and climate change invalidates the science of anthropogenic global warming and climate change. The proposed causation relationship can be either linear or logarithmic but it can’t b e both.

LINK#5 CONTINUED: https://tambonthongchai.com/2021/05/18/climate-science-vs-statistics/

We further note in terms of statistics that “

CLIMATE SCIENCE CONTAINS A BIAS FOR THE TRUTH OF THAT WHICH IS TO BE PROVEN AND THAT THEREFORE CLIMATE SCIENCE CANNOT BE CONSIDERED TO BE UNBIASED AND OBJECTIVE SCIENTIFIC INQUIRY.

SPECIFICALLY, IN OBJECTIVE UNBIASED SCIENTIFIC INQUIRY, THAT WHICH IS TO BE PROVEN MUST BE THE ALTERNATE HYPOTHESIS AND ITS NEGATION THEN BECOMES THE NULL HYPOTHESIS. THE UNBIASED DATA COLLECTION MUST THEN PROVIDE SIGNIFICANT EVIDENCE TO REJECT THE NULL IN ORDER TO ACCEPT THE TRUTH OF THAT WHICH IS TO BE PROVEN. THE TRUTH OF THAT WHICH IS TO BE PROVEN WHEN TAKEN AS THE NULL HYPOTHESIS CONTAINS A BIAS AND IT VIOLATES THE SCIENTIFIC METHOD SUCH THAT THE RESEARCH FINDINGS OF THIS METHODOLOGY CANNOT BE TAKEN AS THE PRODUCT OF OBJECTIVE AND UNBIASED SCIENTIFIC INQUIRY. THE ODD LOGIC IN CLIMATE SCIENCE DESCRIBED AS “THE LESS WE KNOW THE SCARIER IT GETS” DERIVES FROM THIS STATISTICAL ERROR. THE TRUTH OF THAT WHICH IS TO BE PROVEN STANDS AS TRUTH UNTIL PROVEN WRONG. THIS BIAS IS OFTEN ACKNOWLEDGED AND THEN DEFENDED WITH THE PRECAUTIONARY PRINCIPLE.

CONCLUSION: SIGNIFICANT VIOLATIONS OF STATISTICAL PRINCIPLES AND OF THE METHODOLOGY FOR UNBIASED AND OBJECTIVE SCIENTIFIC INQUIRY IN CLIMATE SCIENCE RAISE SERIOUS QUESTIONS ABOUT THEIR CONCLUSIONS THAT HAVE NOTHING TO DO WITH REPUBLICANISM, THAT EXXON KNEW, THAT DENIERS ARE TOOLS OF THE FOSSIL FUEL INDUSTRY, OR THAT DENIERS ARE UNEDUCATED OR UNINTELLIGENT PEOPLE SIMPLY CARRYING OUT PRO FOSSIL FUEL ACTIVISM OR FOR THE GOOD LIFE THEY ENJOY WITH FOSSIL FUELS AND WITHOUT THE NEED TO SAVE THE PLANET FROM FOSSIL FUELS. THIS KIND OF EVALUATION OF SKEPTICISM MUST FIRST EXPLAIN THE STATISTICAL ISSUES PRESENTED IN THE DOCUMENT LINKED BELOW.

LINK: https://tambonthongchai.com/2021/05/18/climate-science-vs-statistics/

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