It is frequently claimed (by skeptics) that the primary cause of "global warming" is the way data is adjusted. The analysis presented below basically supports that claim.

To reproduce this analysis, use the GHCN Temperature Plotter tool and

• Load both the GHCN adjusted and unadjusted (raw) datasets
• Change the default baseline period to 1910 to 1920 - The data before 1910 seems a bit too erratic
• Use the Raw vs Adj Filters tab to select only those sites that are in both datasets

For this analysis, do the following for both the raw and adjusted datasets.

• Set the baseline to 8 years of data between 1910 and 1920
• Filter the sites to require 8 years of data between 2000 and 2010
• Using the Raw vs Adj Filters tab, select only those sites that are in both datasets

These are 2 examples of sites present in both datasets, but not included in the filtered selections. Sites of this type are easy to find - just toggle between the 2 datasets using the provided radio buttons and see which sites (dots) disappear. There should be 68!

On the other hand, the fact that the adjusted data is missing data points (years) where the raw dataset has data indicates a far more serious problem.

To recreate these images

• Select Display both the Raw (blue) and Adjusted (red) data under Stations plot on the Plot Controls tab
• Select the By station radio button
• Click on the station

• From 0.058°C/decade to 0.100°C/decade in the anomaly plot, and
• From 0.051°C/decade to 0.090°C/decade in the actual temperature plot.

The anomaly plot makes it clear that the relative values of the raw data were not changed from 1900 to about 1940 and the actual temperature plot makes it clear that the actual values were not changed from 2000 to 2014.

However, it is clearly obvious that the 1900 to 1940 temperatures were decreased about 0.4°C - thus the adjustments increased the computed rate of temperature increase.

These images were produced via the Hi/Lo button.

• Between 1900 and 1940 the temperatures are reduced about 0.9°C (0.4°C in the previous section), and
• Between 2000 and 2014 the temperatures are reduced about 0.5°C (they were nearly identical in the previous section)

The rest of the images on this page use the less restrictive filter described in the Basic setup section above.

	Trends - °C/decade
	Anomaly	Temperature
Raw	0.058	0.051
Adjusted	0.100	0.090

The plots are generated by averaging the temperatures, or anomalies, for each year and then fitting a trend line thru the results. Because the number of temperature values (number of sites) varies from year to year, and because each site has its own baseline used to calculate the anomaly, the annual average of the baselines varies slightly. It is this that causes the trends to vary. Thus, the anomaly trend for the raw data is different from the temperature trend for the same raw data. (Same for the adjusted data.)

The application also provides a full linear regression (via the Trend Lines tab) using all the data for the selected sites, not just the annual averages. Even that produces slightly different slopes for anomalies vs temperatures.

As a further test, I selected only the sites with data for every year - then the slopes (trends) were identical.

You can argue that it would be better to simply average the individual trends - perhaps, but I think a histogram provides more information.

Does any of this matter? - Well, when the choice of method gives results that vary by 15% or so, I don't think it is reasonable to make a big deal out of a change of only 0.1% (something the press does on a regular basis).

• The Baseline histogram shows that the cooling adjustments were applied to mostly warmer sites.
• This Trend histogram makes it obvious that the "adjustments" have produced a major change in the amount of warming.

These images were produced via the Histograms tab.

As expected, when the adjustments cooled the past, the rate of temperature increase increased.

I checked these differences against all the available x-axis options, but did not see any significant trends worth showing here other than the change in trend verses the raw trend. (Not shown) However, the histogram in the previous section makes that much clearer than the corresponding xy-plot.

By the way, on the xy tab, the charts that plot adjusted vs raw data or the difference between the raw and adjusted data use only the sites selected in the adjusted dataset - it does not matter what sites are selected in the raw dataset. (Every site in the adjusted dataset is also in the raw dataset .. but not vice versa.) For most other plots - it does matter!

These images were produced via the xy tab using automatic bin sizes.

These maps were produced by selecting Baselines on the Raw vs Adj tab and 7 levels on the Bin Colors tab.

The maps can also be used to show trends (Map Trends tab) and the change in trends (Raw vs Adj tab). In each case, the map is updated as soon as the selected date range changes. (Hint - use the mouse wheel and the shift key with the date fields.)

They also make it clear why skeptics want to see exactly how and why the adjustments were done. From my experience, there is not enough data available for anyone outside the field to validate the adjustments, and there is more than enough data to question the techniques used.

By the way, a zero line (Hi/Lo plot on the Plot Controls tab) lies completely within 2 standard deviations of the data - strongly suggesting that the null hypothesis (the Earth is not warming) should be accepted.

These images were produced using version 0.15 of GHCN Temperature Plotter tool and the configurations specified above.

Note:

All the images on this page can be zoomed by simply using the mouse wheel. Double click to toggle full size to default size Restore Image Sizes

URL: http:// mc-computing.com / Science_Facts / Annual_Temperature_Plots / Cooling_the_Past.html