Annual Temperature Plots
UCAR & Keeling CO2 Tab
The UCAR & Keeling CO2 Tab of the
GHCN Temperature Plotter tool
controls the display of data I obtained from
UCAR's
The Very, Very Simple Climate Model
and CO2 data from Mauna Loa (Keeling data).
There are 4 checkboxes, one data entry field,
and a year-select field.
The purpose of this page is to explain what each of those is for
and to provide a simple tutorial on how to use them in combination
with some of the other plotter controls.
- The first 3 checkboxes are straight forward
- Display or hide one of 3 different datasets
- The next checkbox controls the x-axis
- Display data starting in 1900 or 1800
- Climate Sensitivity - data entry field
- This is the expected change in temperature for a doubling of CO2
- Base year - Select one of the values
- When computing temperature anomalies, this is the reference year where ΔT=0
On the default plot (1900 to present, sensitivity equals 3°C) the correlation between temperature increase and
CO2 increase is almost perfect - CO2 could be controlling the climate.
However, when the additional data back to 1800 is displayed - not so much
(depending on the selected base year and climate sensitivity).
Data
| Anomalies
| Climate Sensitivity
| Temperatures vs Anomalies
| Why Filtered?
| Keeling Curve
| Trends
Data
The UCAR data comes from their
The Very, Very Simple Climate Model
calculator.
It is a flash application that I disassembled to extract the data
and the algorithm they used to predict temperature based on CO2 concentration.
Concentration is a bit of a misnomer - it normally refers to the molarity,
the number of moles per unit volume.
A better term is abundance which refers to parts per something -
CO2 in normally expressed in parts-per-million (ppm).
The Keeling CO2 data comes from the
Scripps CO2 Program
and is provided as Atmospheric CO2 concentrations (ppm).
Anomalies
A temperature anomaly is found by
- Defining some base period
- Determining the average temperature for that period
- Subtracting that temperature from each provided temperature
In the GHCN Temperature Plotter tool, anomalies are computed for each site and
then the anomalies are added to find an average anomaly for each year.
The UCAR data is already averaged with values spaced
every 10 years before 1960 and every 5 years after.
Therefore, the program provides a combobox to select the baseline (zero anomaly) year.
By experimentation, I found that a base year of 1975 and a sensitivity of 3°C/doubling
produces an almost perfect overlap between the UCAR historical temperature data
and the expected temperature based on the CO2 concentration
from 1975 to 2005.
This fit (correlation) is so close that everyone could (should) believe that
CO2 controls the climate.
Expanding the analysis to the period 1900 to 2010 adds a little noise, but the
correlation is still pretty good.
Since the UCAR data actually goes from 1800 to 2010, I decided to see
what the data would show.
As shown in the plots below -
Not even close!
UCAR Historical and CO2 based temperatures
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1900 to present
| 1800 to present
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To compute the CO2 controlled expected temperature difference, the following equations were used.
The base year is 1975, the target is 1800 (which is why ΔT is negative),
and the climate sensitivity is 3.0°C/doubling (their default).
The discrepancy is the difference in the temperature UCAR provided for 1800
and the one calculated using their formula.
ΔT = Sensitivity * log2(Ccurrent/Cbase)
ΔT = 3 * log2(280/331.08) = -0.725°C
T = Tbase + ΔT
T = 13.920 - 0.725 = 13.195°C
Tdiscrepancy = 13.798 - 13.195 = 0.603°C
|
To summarize, where the Temperature and CO2 columns contain
values provided in the UCAR data
Year | Temperature
| CO2
| ΔT
| Tbase + ΔT
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Base year 1975
| 13.920°C | 331.08 ppm | 0 | 13.920°C
|
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1800
| 13.798°C | 280 ppm | -0.725°C | 13.195°C
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As mentioned elsewhere, changing the base year just moves
the historical temperature plot up and down.
However, it does change the separation between the actual and expected.
This is because the ratio between the provided temperature
and the log of the ratio of the CO2 abundance (concentration)
is not constant.
Since the entire 20th century warming is about 0.7°C,
having a delta in 1800 between historical and theoretical temperatures of about
0.603°C pretty much disproves any theory correlating CO2 and temperature.
The 2 values are simply too close together.
On the other hand, using 1965 as the base year and setting the sensitivity to
1.8°C/doubling produces a pretty good fit over a much longer period.
The UCAR flash model uses 2000 as the fixed baseline year.
(The user can not modify this.)
At any rate, the point of my calculator is that you can vary the parameters yourself
and make up your own mind.
By the way, the baseline for the GHCN data is controlled on the Basic Filters tab.
The default baseline is the average over the range 1961 to 1990.
When changing the baseline year on the CO2 tab,
be sure to adjust the GHCN baseline so the 2 temperature curves stay aligned.
I chose 1975 as the UCAR baseline year because it was near the middle of the default range
and causes the temperature curves have a good overlap.
Climate Sensitivity
Climate Sensitivity is the number of degrees centigrade that the
temperature is expected to increase for a doubling of CO2 in the atmosphere.
The data entry field on the CO2 tab allows values from -2.0 to 7.0
(it just seemed like a reasonable range).
Some extremists suggest the likely value is around 7, the skeptics
like positive values under 2.
The UCAR
The Very, Very Simple Climate Model
uses a default of 3.0, which is also the default for my application.
UCAR data showing different Climate Sensitivities
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Climate Sensitivity = 2
| Climate Sensitivity = 5
| | |
Temperatures vs Anomalies
It is very seldom that
AGW
articles contain graphs that plot temperatures -
instead, it is almost always anomalies.
(How they are computed was described above.)
Since the GHCN Temperature Plotter has the ability to plot either anomalies or the actual temperatures,
for comparison, I plotted the GHCN temperatures and the UCAR temperatures on the same graph.
I never expected that - there is about a 2°C difference between the 2 data sets!
UCAR Historical temperatures and GHCN Temperatures
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Notice that the temperatures are about 2°C
apart.
Move the mouse over the image to see the trendlines.
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To be perfectly clear
- When plotting anomalies, the 2 datasets are pretty close
(as shown in all the other images on this page)
- When plotting the actual temperatures, there is a large, approximately 2°C, difference
The procedure to recreate the above plots is a bit more complicated than usual.
(The order of the steps is not important except that the Hi/Lo button
needs to be clicked after the steps above it are completed.)
- On the Basic Filters tab, click the first 3 buttons in the table
- Compute New Baseline must be first
- Filter to require at least 8 sites between 1900 and 1910
- Filter to require at least 8 sites between 2000 and 2010
The checkbox to Hide filtered sites is already checked
- In the control area, under the map
- Uncheck Align stations on common baseline
- Click Select all
- Click Hi/Lo (this must be after all the steps above)
- On the CO2 tab, check the box to display the UCAR historical temperatures
(This page was written, and the images made, for version 0.10 of the application.
Since then, 2 additional filters were added to the table on the Basic Filters tab.
In version 0.15,
clicking all 5 buttons with their default values limits the selection to 388 sites, but the
anomaly plot is almost identical to the one made with 520 sites, and to the one made with only the baseline selected - 4,561 sites.
However, the actual temperature plots are quite different.
This is because the number of included stations varies a lot each year without the stricter
filters. See the next section.)
As you can see, the UCAR data is between 13.5°C and 14.0°C
while the "official" GHCN data is between 11°C and 13°C.
I have no way to explain this. The official temperature is supposed to be 15°C.
For comparison,
- The UCAR temperature
in the 1920's is about 13.7°C
- The filtered GHCN data in the same period appears to be about 11.6°C
- The IPCC uses both 14°C and 15°C
I can't remember ever seeing a plot of real temperatures in any of the reports. All they ever show is "anomalies". Maybe this is why!
Why Filtered?
When working with anomaly data, filtering the stations does not make a very big difference.
However, when plotting the actual temperatures - it does.
UCAR Historical temperatures and Filtered GHCN Temperatures
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Filtered to include only the 520 stations with over 100 years of data
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Filtered to include the 4,565 stations with at least 15 values in the range 1961 to 1900
| | |
The difference should be fairly obvious. I have left the UCAR data in the plot for reference only.
In the 4,565 station plot, the temperature has 2 step increases (discontinuities)
- One where the number of stations rapidly increases
- A second, larger step where a number of colder station were suddenly dropped
As a result, it is necessary to only use data filtered to include the 520 stations with over 100 years of data.
(This page was written, and the images made, for version 0.10 of the application.
Since then, beside the additional filters mentioned above,
7 sites identified as ship have been removed by default
- of these, only 4 meet the default baseline requirement.
They can be restored via the Filters tab
as well as 2 obviously bad sites that were already removed.
As a result, as of version 0.15,
the basic baseline filter contains only 4,561 sites,
not the 4,565 sites shown in the images.)
Keeling Curve
The only reliable CO2 abundance (concentration) record is the
Keeling data,
available from 1958 to present
and derived from in situ air measurements at Mauna Loa, Observatory, Hawaii.
Since I just wanted to see if that data was similar to the UCAR data,
I selected one month of the CO2, seasonally adjusted filled
values as representative of the year,
and used August since those values were close to the UCAR values.
Using the associated checkbox on the CO2 tab, you can see that the
temperatures predicted using those values
are almost identical to those predicted using UCAR's CO2 values.
The tool does not plot the CO2 values, only the associated predicted changes in temperature
which are proportional to ln([CO2]) -
logarithm of the CO2 concentration.
(The base of the logarithm is irrelevant - it only affects a constant multiplier.)
Note: |
| The UCAR CO2 data before 1958 is highly questionable since there is no long term
record from a single site. The same for temperatures before about 1870 - reliable long term records simply do not exist.
|
Trends
The Show trend on period... checkbox on the Hi/Lo graph turns
off and on trends on most of the data series -
including both UCAR datasets (Temperature and CO2) as well as the Keeling CO2 data.
The following charts show trends for the following temperature series
- UCAR data
- GHCN raw data
- GHCN adjusted data
When comparing the "adjusted and "unadjusted" (raw) GHCN data, the current temperatures are about the same while the 1900 raw data is about 0.5°C warmer. The slopes are also significantly different - 0.102°C/decade vs 0.054°C/decade
or about half of the measured global warming of the twentieth century.
That is a well known problem, but it is never explained.
The UCAR data is somewhere between these.
In addition,
the following charts compare the use of temperatures verses anomalies.
UCAR Historical and GHCN Temperature Anomalies
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Notice that the adjusted and raw values look about the same.
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- The GHCN data is filtered for sites that have over 100 years of data
- The top graph shows the data plotted as an anomaly based on the 1961 to 1990 average
- The bottom graph shows the actual temperatures
- In both cases, passing the mouse over the image will show the trend lines
- Double click the images to make the data easier to read.
- Green is the "raw" (unadjusted) GHCN temperature data
- Red is the adjusted GHCN temperature data
- Blue is the UCAR temperature data
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UCAR Historical and GHCN Temperatures
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Notice that the raw and adjusted temperatures are
about the same in the present and that the adjusted temperatures get colder in the past.
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As you can see, using anomalies hides the fact that the "adjustments"
tend to make the past colder. This is not just a result of averaging the data.
If you look at data from individual sites, you will see that many
have the same characteristic - the adjustments tend to make the past colder.
At some point, those making the adjustments will have to explain why this is happening.
But so far, those explanations have not been provided!
Note: |
| All the images on this page can be zoomed by simply using the mouse wheel.
Double click to toggle between full size and default size.
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Author:
Robert Clemenzi