Tokyo Surface Temperatures Point to Climate Cooling

Tokyo is a huge, sprawling megapolis on the island nation of Japan. With its great urbanization over the past decades, observers could expect to see some warming at least from the urban heat island effect as well as from the “huge” warming the planet has allegedly seen globally over the past 30 years.

But in Tokyo, this has not been the case, surprisingly. The two charts below depict temperature data of Tokyo over the past years.

The first chart shows the temperature trend for each month, January through December since 1988:

Looking at the chart, we can see that 6 months show a steady or even a cooling trend. Overall over the past 30 years, Tokyo has warmed modestly, but that warming trend, however, is mostly due to the colder years in the late 1980s and early 1990s.

When looking back at the past 24 years, Tokyo has been cooling off:

Even more interesting is the fact that Japan’s capital and largest city has even seen an accelerating cooling over the recent years. The year 2017 was the coldest in over 20 years.

This contradicts claims of runaway warming that we often hear from climate warming alarmists.

Kyoto Cooling

Also, the trend is the same for the city of Kyoto, as is the case for many other cities in Japan:

Kyoto has been cooling for the past 10 years and there’s no significant trend over the past 25 years.

Also, the globe has been cooling since the peak that was brought on by the most recent powerful El Nino.

Read more at No Tricks Zone

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Comments (7)

  • Avatar

    Dr Pete Sudbury

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    My garden has got warmer. So has the next door village. Is that significant, too?

    Reply

    • Avatar

      William Morgan

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      Where’s your evidence? Where’s your graph? Will your data extend backwards 25-30yrs?

      Reply

  • Avatar

    Gordon Wyness

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    Keep up the good work

    Reply

  • Avatar

    Alder

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    There is scope for major consultancy work here for our Australian ‘data experts’
    to teach them how to ‘homogenize’ data to show temperatures increasing at
    approved rates.
    No correction for heat-island-effect has been done. Normal people would think
    that such corrections would tend to give declining numbers, but the usual ‘experts’
    can get it to do the opposite!

    Reply

  • Avatar

    jerry krause

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    Hi Pierre & Pirye,

    This comment is not intended to be critical of your very informative article but I have questions which I hope you will answer. The first question is: From what data were the mean monthly and yearly temperatures calculated? The likely answer I consider possible for the monthly average are the daily mean temperatures for the month and that for the yearly average are the 12 monthly mean temperatures of the year; but I do not want to assume this and be wrong. The second question is: From what data is the daily mean temperature calculated? Here I consider two possibilities could be likely. By adding the maximum and minimum temperatures of the day and dividing by 2. Or, by averaging the 24 temperatures measured on the hour for the day.

    The first figure (mean monthly temperatures) seems to be far more informative than your remarks about gave it credit. For I would have never expected to see that the six pairs of monthly averaged would divide the year (from coldest to warmest) into 6 distinct temperature intervals Now, having lived most of my life at 45 deg. N latitude or higher, I know that the temperatures of January-February and July-August can be quite similar because these pairs are consecutive months. But there 4 months between May-October and 6 months between April-November. And before seeing this mean monthly figure I would have expected each month of each pair to have had more significant opposite trends of increasing and decreasing temperatures.

    However, what I had never read about and therefore did not expect to see was the ‘regular’ oscillatory trends whose periods extended over several years The different temperature scales of the mean monthly and the mean yearly figures create a false image in one’s mind if one does force the brain to acknowledge this scale factor. The difference between the maximum and minimum temperatures of the mean yearly temperatures in the 24 years between 1988-2017 is 1.5 degree Celsius (C) and that of the oscillation of the mean January temperature between 2000-2002 was more than 2.5C while that of the smaller difference of two consecutive periods between 1990-1998 was about 1.3C.

    Attention needs to be directed to that one mean July temperature of one year changes by 5C from one year to the next might by itself result in a significant mean yearly temperature difference from one year to the next. This issue needs to be carefully studied to discover what might cause this observed mean temperature extreme difference from one year to the next during the month of July.

    A final comment. As presented the figure of the mean monthly temperatures is difficult to process because it cannot be studied by same method which the mean yearly temperatures can.

    I will describe in my next comment a method, which I consider unique, with which I study the mean yearly temperatures. But to help me, please answer my questions.

    Have a good day, Jerry

    Reply

  • Avatar

    jerry krause

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    Hi Pierre & Pirye,

    In my Analytic Chemistry I was taught to analyze three sample to evaluate the reproducibility of my analysis by a simple mathematical process.

    First the mean of the 3 results was calculated, Than the 3 differences between the mean and each result was calculated. Than the mean difference (deviation) of these three differences was calculated. Than the differences between the maximum result and the minimum result (already calculated) are compared with the mean deviation. If these two difference were equal to or less than the mean deviation the results had to be accepted as being reproducible with the actual result being within the limits of mean +/- mean deviation. But I was also taught that this test could not detect the presence of a systemic error of the procedure being used. Hence, we analyzed standard samples whose result had been established by chemists much more experienced than we students.

    However, if one of the two differences was greater than the mean deviation, we students had decision to make. Which was why we did the three samples at the beginning. If the second difference was much less than the mean deviation we could probably justify eliminating the outer and calculating a mean result from the two results and reasonably assume that the actual result was within the limits of the new mean +/- the difference between these two results.

    In the figure of the Mean Annual Temperatures are 24 temperatures. We consider these 24 mean annual temperatures all should be the same but it is easy to observe (see) that they obviously are not. So I calculate the mean of these 24 temperatures (16.6C) and their 24 difference between each and the mean of these temperatures. And I calculate the mean of these 24 differences (0.3C). When I scan the differences I find there are 4 which are 0.6C (2 mean deviations) or greater and 1 which is minimally less (0.5C). So I recalculate the 19 remaining temperatures and find the mean of 16.6C (the same as before) and the mean deviation of 0.2C (less than before).

    Which mean deviation (0.2C) about the practical sensitivity of the ordinary laboratory I used in my research in which temperature was a variable influencing the research results. For a practical fact is a temperature difference of even 1.0C will not produce an observable difference in a measureable result sought in many cases of measureable scientific phenomena. Which statement might seem to contradict the removable of the 5 temperatures from the original 24. However, the purpose in this case is not measure something which is influenced by temperature but to measure a temperature itself.

    These 5 temperatures represent a mistake (deviation) from the ‘standard’ system (procedure) which produces temperatures outside of the limits defined by the calculated mean deviation. The years of these five mean annual temperatures are 1996, 2003, 2004, 2013, and 2017. I am aware that during these years El Nino/La Nina events have been observed to have occurred. El Nino: 1994 to 1995, 1995 to 1996, 1997 to1998, 2002 to 2003, 2004 to 2005, 2005 to 2006,2006 to 2007, 2009 to 2010, and 2014 to 2016. La Nina: 1988 to1989, 1995 to1996; 1998 to 2001, 2005 to 2006, 2007 to 2008, 2008 to 2009, 2010 to 2012, and 2016 to 2017 to 2018. 2013 values are consistently negative but the magnitudes to reach the necessary defined levels.
    (http://origin.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_v5.php)

    Yes, there are many more years than 5 during which El Nino/La Nina events occurred. And that is why I would like to have the 24 mean monthly temperatures for each month of the 24 years to analyze as I analyzed the 24 mean annual temperatures of its figure.

    Have a good day, Jerry

    Reply

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