Are we using bad data?

Discussion in 'Environment & Conservation' started by Bullseye, Jul 27, 2022.

  1. Jack Hays

    Jack Hays Well-Known Member Donor

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    Because you cited it in your #72.
     
  2. Jack Hays

    Jack Hays Well-Known Member Donor

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    Sorry, but your presentation is fiction.
     
  3. Jack Hays

    Jack Hays Well-Known Member Donor

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    And to recap:

    ". . . The findings of both the 2009 and the 2022 Surface Stations studies clearly demonstrate the COOP network’s temperature records—at both USCHN and GHCN stations—have been substantially corrupted. After surveying a comprehensive and representative sample of stations, 96 percent were found to be biased in some way by the heat sink effect, or other heat sources.

    Claims by NOAA, NCDC, and NCEI that this data contamination can be statistically adjusted are disingenuous, especially considering the widescale homogenization of good and bad data. Good data exists in the unperturbed stations demonstrated by Watts et al. in 2015, but the amount of bad data from poorly sited stations overwhelms the accurate data from well-sited stations.

    It is important to note Watts and his fellow authors found a slight warming trend when examining temperature data from unperturbed stations, which cleaved closely to the findings of the University of Alabama-Huntsville’s satellite-derived temperature record.49 This warming trend, however, is approximately half the claimed rate of increase promoted by many in the climate science community.

    USCRN was created for the purpose of accurately measuring climatic temperature trends, yet is not being utilized as such. While the state-of-the-art and professionally operated network has only 17 years of data, it represents an uncontaminated climatic record, and should therefore be given preeminence in official reports. The currently utilized nClimDiv data, however, has been adjusted to USCRN data post-2005, but contains no adjustments prior to 2005. This may very well be why warming trends are present in the nClimDiv data. Despite NOAA’s assertions to the contrary, climatic temperature increases as measured by nClimDiv cannot be effectively isolated from potential confounds such as heat sinks, urbanization, WWTPs, population growth, and other factors. . . . "
     
  4. James California

    James California Well-Known Member Past Donor

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    ~ Ever wonder who checks these "fact checkers " ..? :confuse:'
    Internet "fact sources", social media, government " experts'' and the mainstream news have done a good job dumbing-down a lazy American society.
    AmericanPravda.png
     
    Last edited: Dec 24, 2022
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  5. Jack Hays

    Jack Hays Well-Known Member Donor

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    You Must Assume That All Information Put Out By Our Government Is Corrupt
    December 21, 2022/ Francis Menton
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    • Throughout the agencies of our federal government, an important function is to issue data and information about the state of the country.

    • These data cover a vast array of topics such as population, demographics, income and poverty, the state of the economy, the GDP, employment and unemployment, activities of foreign adversaries, weather and climate, energy production and use, and much, much more. The Congress and states use this information in making important public policy decisions, and the people use it to make decisions for their everyday lives. Not the least of those decisions is how to vote.

    • So is the information issued by the government basically honest and reliable for important decisions? Or, instead, is the output of official information cynically manipulated and corrupted by a government interested mainly in perpetuating and increasing its own power?
    READ MORE

    Manipulation of temperature data to support the narrative of human-caused climate change.

    Long-time readers here are undoubtedly familiar with my series, now of some 30 parts, on what I call the Greatest Scientific Fraud Of All Time. The headline refers to the alteration by U.S. bureaucrats of historical climate records to make it appear that temperatures have closely tracked the ongoing increase in CO2 in the atmosphere, when in fact the actual temperature readings show the opposite. The U.S. climate bureaucracies NASA and NOAA regularly put out excited press releases about the most recent month or year being the “hottest on record,” or something like that. But anybody can go to past information releases to find that those statements only hold if one accepts alteration of prior information to support the narrative.

    My October 20, 2020 post contained the ultimate smoking gun: two NASA charts of U.S. temperatures, one from 1999 and the other from 2019, clearly showing the alteration of early-year temperatures to support the claim that the most recent years are the warmest. Here are those two charts:

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    In NASA’s data in 1999, 1934 was the warmest year in the U.S. temperature record, about 0.6 deg C (1 deg F) warmer than 1998; 1921, 1931 and 1953 were also warmer than 1998. By 2019, 1998 had somehow become the warmest year, through the magical cooling of the earlier years. And thus do we get a claim that there is some kind of dangerous warming going on that requires a full transformation of the U.S. and world energy system, all under the direction of the all-knowing bureaucrats.
     
  6. mamooth

    mamooth Well-Known Member Past Donor

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    We get it. Your propaganda gets debunked, you repeat it again. Over and over.

    Denialism as a whole hasn't come up with anything new in more than a decade. Your old memes bring back fond memories of the internet as it was in 2010. TheParty isn't giving any attention to denialism. They consider it to be obsolete propaganda. The kewl authoritarians have moved on to things like TheStolenElectionBigLie, TheFakeBorderCrisis and TheLiberalsAreGroomers Blood Libel thing.
     
  7. Jack Hays

    Jack Hays Well-Known Member Donor

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    Now I think you've gone off the deep end. I'll stick to the topic.
     
  8. Sunsettommy

    Sunsettommy Well-Known Member

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    It appears you have no counterpoints to offer thus you have NOTHING to offer here but insults.

    No one here denies that it has been warming since 1979 as many here and elsewhere have told you 1,214 times which means there is no denial at all.
     
    Last edited: Dec 28, 2022
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  9. Jack Hays

    Jack Hays Well-Known Member Donor

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    Adjustments.
    HadCRUT Data Manipulation Changes 2000-2014 Warming Trend From 0.03°C to 0.14°C Per Decade
    By Kenneth Richard on 9. January 2023

    Share this...
    Adjustments add significant warming to 21st century temperature trends.
    From 2009 to 2019 there were 90 peer-reviewed scientific papers published on the global warming “pause” or “hiatus” observed over the first 15 years of the 21st century.

    The HadCRUT3 global temperature trend was recorded as 0.03°C per decade during the global warming hiatus years of 2000-2014 (Scafetta, 2022).

    This was increased to 0.08°C per decade by version 4, as the overseers of the HadCRUT data conveniently added 0.1°C to 0.2°C to the more recent anomalies.

    Today, in HadCRUT5, the 2000-2014 temperature trend has been adjusted up to 0.14°C per decade when using the computer model-infilling method.

    So, within the last decade, a 15-year temperature trend has been changed from a pause to a strong warming. After all, when the data don’t fit the narrative, it is time to change the data.

    [​IMG]

    Image Source: Scafetta, 2022
     
  10. Jack Hays

    Jack Hays Well-Known Member Donor

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  11. Jack Hays

    Jack Hays Well-Known Member Donor

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    Urbanization Effects on GHCN Temperature Trends, Part I: The Urbanization Characteristics of the GHCN Stations
    January 14th, 2023
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    I’ve previously posted a variety of articles (e.g. here and here) where I address the evidence that land surface temperature trends from existing homogenized datasets have some level of spurious warming due to urban heat island (UHI) effects. While it is widely believed that homogenization techniques remove UHI effects on trends, this is unlikely because UHI effects on trends are largely indistinguishable from global warming. Current homogenization techniques can remove abrupt changes in station data, but cannot correct for any sources of slowly-increasing spurious warming.

    Anthony Watts has approached this problem for the U.S. temperature monitoring stations by physically visiting the sites and documenting the exposure of the thermometers to spurious heat sources (active and passive), and comparing trends from well-sited instruments to trends from poorly sited instruments. He found that stations with good siting characteristics showed, on average, cooler temperature trends than both the poorly-sited locations and the official “adjusted” temperature data from NOAA.

    I’ve taken a different approach by using global datasets of population density and, more recently, analysis of high-resolution Landsat satellite based measurements of Global Human Settlements “Built-Up” areas. I have also started analyzing weather station data (mostly from airports) which have hourly time resolution, instead of the usual daily maximum and minimum temperature data (Tmax, Tmin) measurements that make up current global land temperature datasets. The hourly data stations are, unfortunately, fewer in number but have the advantage of better maintenance since they support aviation safety and allow examination of how UHI effects vary throughout the day and night.

    In this two-part series, I’m going to look at the latest official global GHCN thermometer (Tmax, Tmin) dataset (Version 4) to see if there is evidence of spurious warming from increasing urbanization effects over time. In the latest GHCN dataset version Tmax and Tmin are no longer provided separately, only their average (Tavg) is available.

    Based upon what I’ve seen so far, I’m convinced that there is spurious warming remaining in the GHCN-based temperature data. The only question is, how much? That will be addressed in Part II.

    The issue is important (obviously) because if observed warming trends have been overstated, then any deductions about the sensitivity of the climate system to anthropogenic greenhouse gas emissions are also overstated. (Here I am not going to go into the possibility that some portion of recent warming is due to natural effects, that’s a very different discussion for another day). . . .
     
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  12. Jack Hays

    Jack Hays Well-Known Member Donor

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  13. Jack Hays

    Jack Hays Well-Known Member Donor

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    More data fiddling down under.
    Hyping Maximum Daily Temperatures (Part 2)
    January 24, 2023 By jennifer

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    Available Australian Bureau of Meteorology parallel maximum temperature data for Mildura – temperatures recorded from both a mercury thermometer and a platinum resistant probe on the same day in the same shelter – show no equivalence. They are … [Read more...]
     
  14. Jack Hays

    Jack Hays Well-Known Member Donor

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    Yet more down-under fiddling.
    Hyping Maximum Daily Temperatures (Part 3)

    January 28, 2023 By jennifer

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    If maximum temperatures are the same, whether measured by platinum resistance probes or mercury thermometers, why does the Bureau make an adjustment of 0.5 °C in the homogenisation of temperatures from Cape Otway Lighthouse? On Friday (3rd … [Read more...]
     
  15. Jack Hays

    Jack Hays Well-Known Member Donor

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  16. Jack Hays

    Jack Hays Well-Known Member Donor

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    Urbanization Effects on GHCN Temperature Trends, Part II: Evidence that Homogenization Spuriously Warms Trends
    February 7th, 2023
    In Part I I showed the Landsat satellite-based measurements of urbanization around the Global Historical Climate Network (GHCN) land temperature-monitoring stations. Virtually all of the GHCN stations have experienced growth in the coverage of human settlement “built-up” (BU) structures.

    As an example of this growth, here is the 40-year change in BU values (which range from 0 to 100%) at 1 km spatial resolution over the Southeast United States.



    [​IMG]
    Fig. 1. The 40-year change in urbanization over the Southeast U.S. between 1975 and 2014.
    How has this change in urbanization been expressed at the GHCN stations distributed around the world? Fig. 2 shows how urbanization has increased on average across 19,885 GHCN stations from 20N to 82.5N latitude, at various spatial averaging resolutions of the data.

    [​IMG]
    Fig. 2. Average forty-year change (1975 to 2014) in Landsat-based urbanization (BU) values over 19,885 GHCN stations from 20N to 82.5N at five different averaging scales of the 1 km BU data.
    NONE of the 19,885 GHCN stations experienced negative growth, which is not that surprising since that would require a removal of human settlement structures over time. In all of the analysis that follows, I will be using the 21×21 km averages of BU centered on the GHCN station locations.

    So, what effect does urbanization measured in this manner have on GHCN temperatures? And, especially, on temperature trends used for monitoring global warming? . . . .

    My very preliminary calculations so far (using the UHI curves in Fig. 4 applied to the 21×21 km urbanization growth curve in Fig. 2) suggest the UHI warming averaged over all stations is about 10-20% of the GHCN trends. Small, but not insignificant. But that could change as I dig deeper into the issue.
     
  17. Jack Hays

    Jack Hays Well-Known Member Donor

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    Hyping Maximum Daily Temperatures (Part 5)

    February 8, 2023 By jennifer

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    When the Bureau called a new record hot day for 23rd September 2017, based on the instantaneous spot value from a platinum resistance probe in an automatic weather station at Mildura, I wanted to know the maximum temperature recorded by the mercury … [Read more...]
     
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  18. Jack Hays

    Jack Hays Well-Known Member Donor

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    Hyping Maximum Daily Temperatures (Part 7)

    February 17, 2023 By jennifer

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    I’ve been assured over the last few years, including by the director of the Australian Bureau of Meteorology Andrew Johnson, that the change from mercury thermometer to platinum resistance probe is not the cause of, nor a contribution to, global … [Read more...]about Hyping Maximum Daily Temperatures (Part 7)

    Hyping Maximum Daily Temperatures (Part 6)
    February 16, 2023 By jennifer

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    On 11th November 2011, the Australian Bureau of Meteorology replaced the probe in the automatic weather station measuring temperatures at the Alice Springs airport and the number of days with temperatures recorded above 40 degrees Celsius increased … [Read more...]
     
  19. Jack Hays

    Jack Hays Well-Known Member Donor

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  20. Jack Hays

    Jack Hays Well-Known Member Donor

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  21. Jack Hays

    Jack Hays Well-Known Member Donor

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    Urbanization Effects on GHCN Temperature Trends, Part III: Using Population Density, 1880-2015
    March 17th, 2023
    This is the third in my (never-ending, it appears) series on measuring the effect of Urban Heat Islands (UHI) on land surface temperature trends.

    In Parts I and II I emphasized the Landsat-based “built-up” structure dataset as a proxy for urbanization, which I’m sure we will continue to examine as part of our Department of Energy grant to examine (mostly) satellite-based methods and datasets for testing climate models and their predictions of global warming.

    Much of the original research on the UHI effect (e.g. T.R. Oke, 1973 and later) related warming to the total population of towns and cities. Since population datasets extend back in time much further than the satellite period, they can provide information on the UHI effect going back well before 1900. In the last few weeks I’ve taken a detour from using the Landsat-based diagnoses of human settlement built-up structures as a proxy for urbanization, to population density (PD). Along the way I’ve had to investigate issues related to low correlations, and linear regression (specifically, regression dilution). I decided not to cover that here because it’s a little too technical.

    The deeper I dig into this project, the more I learn. . . .
     
  22. Jack Hays

    Jack Hays Well-Known Member Donor

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    There are mysteries in the the temperature record of Tasmania.
    Re-imaging Tasmania’s Temperature History, Part 1

    March 26, 2023 By jennifer

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    My good friend Patrick Lloyd, enamoured with the new Artificial Intelligence ChatGPT, sent me maximum temperatures for Tasmania as individual annual averages of all the daily values for all 155 weather stations since 1882. He had downloaded these … [Read more...]
     
  23. Jack Hays

    Jack Hays Well-Known Member Donor

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    How bad data survive.
    One small error for a physicist, one giant blunder for planetary science
    [​IMG]

    For a decade, scientists have been scratching their heads when trying to put a date on primeval events like the crystallization of the magma ocean on the moon or the early formation of Earth’s continental crust.

    Their problem? A revised estimate of the half-life of a radioactive isotope called samarium-146 that is used to gauge the age of ancient rocks.

    The updated value, published in 2012 in Science, shortened samarium-146’s half-life by a whopping 35 million years, down to 68 million years from the standard estimate of 103. This reset the clock on the solar system’s early history and suggested the oldest rocks on Earth could have formed tens of millions of years earlier than previously thought.

    Continue reading
     
  24. Jack Hays

    Jack Hays Well-Known Member Donor

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    Wiley and Hindawi to retract 1,200 more papers for compromised peer review
    [​IMG]

    Hindawi and Wiley, its parent company, have identified approximately 1,200 articles with compromised peer review that the publishers will begin retracting this month.

    Jay Flynn, executive vice president and general manager of the research division at Wiley, which acquired Hindawi in 2021, wrote about the forthcoming retractions in a blog post at Scholarly Kitchen yesterday.

    The plan to retract 1,200 articles, which the publisher expects to take a few months, follows Hindawi’s announcement last September that it would retract 511 articles across 16 journals for manipulated peer review. (We’ve tracked 501 retractions from 23 Hindawi journals since the announcement.)

    Continue reading
     
  25. Jack Hays

    Jack Hays Well-Known Member Donor

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    Classifying Land Temperature Stations as Either “Urban” or “Rural” in UHI Studies Proves Nothing about Spurious Temperature Trends
    April 8th, 2023
    As I spend more time working on a research project, the more time I have to reflect on things that others have simply assumed to be true. And in the process I sometimes have an epiphany than clarifies my thinking on a subject.

    As I continue to investigate how to quantify urban heat island (UHI) effects for the purpose of determining the extent to which land surface temperature trends have been spuriously inflated by urbanization effects, there is one recurring theme I find has not been handled well in previously published papers on the subject. I’ve mentioned it before, but it’s so important, it deserves its own (brief) blog post.

    It has to do with the common assumption that “urban” thermometer sites experience spurious warming over time, while “rural” sites do not.

    Obviously, at any given point in time urban environments are warmer than rural environments, especially at night. And urbanization has increased around temperature monitoring sites over the last 50 to 100 years (and longer). Yet, a number of studies over the years have curiously found that urban and rural sites have very similar temperature trends. This has led investigators to conclude that temperature datasets such as the Global Historical Climate Network (GHCN), especially after “homogenization”, is largely free of spurious warming effects from urbanization.

    But the conclusion is wrong…all it shows is that temperature trends between rural and urban sites are similar… not that those trends are unaffected by urbanization effects.

    Instead, studies have demonstrated that the greatest rate of warming as population increases is for nearly-rural sites, not urban. The one-fourth power relationship found by Oke (1973) and others (and which I am also finding in GHCN data in the summer) means that a population density increase from 1 to 10 persons per sq. km (both “rural”) produces more warming than an urban site going from 1,000 to 1,700 persons per sq. km.

    Thus, “rural” sites cannot be assumed to be immune to spurious warming from urbanization. This means that studies that have compared “rural” to “urban” temperature trends haven’t really proved anything.

    The mistake people have made is to assume that just because urban locations are warmer than rural locations at any given time that they then have a much larger spurious warming impact on trends over time. That is simply not true.
     

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