Satellite Temp. Homoginization Using GISS
Posted by Jeff Id on January 19, 2009
RSS and UAH have differing 30 year trends which lie outside my calculated measurement error for the data. Subtraction of the two measures leaves a step located at about 1992. Since they both use the same dataset, the question becomes. Which series is right?
After reading several papers and some short emails to some smart people, I have come to understand the bulk of the trend difference to this single step point in the data which corresponds to the time when satellite NOAA-12 began adding data into the trend.
Below is a graph of the RSS-UAH data where the step is quite visible. The flatness of the slope on either side fo the step is a good indicator that most of the data is in good agreement between the satellite processing algorithms.
The graph below is a plot of the raw data and a filtered difference and the overall trends of the data. You can see the trends are crossed and divergent.
The correction is applied at the center of the circle above, the green line is again the difference between RSS and UAH. The method used for correction this time is improved over my last method in that more data is taken into account to produce a higher degree of accuracy in the trend. To match the GISS data to satellite record the curve was first de-trended linearly over a 14 year window in the range shown in the gray box in the graph below. This was done by a linear least squares fit to the data. The slope is subtracted from the data (residuals) the data is then multiplied by the lower troposphere satellite to GISS amplification factor of 1.23. Detrending the satellite data and overlaying gives the good match to the amplitude of the curve as seen below and predicted by climate models. The small green section is the region identified by Dr. Christy as being in question due to a transition between NOAA-11 and NOAA-12 (Oct 1991-March 1992), because we want to change the data as little as possible this is the area I focused on. GISS should be a good metric to correct the trend as it is comprised of hundreds of temperature measurements creating a smoother trend. Large sections of GISS data would not have been as useful due to UHI effects but since we are looking at trendless data over such a short section, it should work well.
The same procedure was repeated again for RSS.
Please note that the graphs are allowed to diverge outside the slope match area as seen in the endpoints.
The next step was the big difference from my last calculations, I used the mean of half year windows (6 monthly values) on either side of the defect region in trendless data from all three datasets. I assumed trendless GISS was correct over this short timeframe and corrected RSS and UAH to match. Below is what the corrections look like.
These curves were added directly to the RSS and UAH data. The RSS correction again was of greater magnitude (the same as my previous attempt), however this time the corrections fell in line with Dr Christy’s analysis of the RSS and UAH data as compared to radiosonde (weather balloon) data. According to this GISS analysis the change in the temperature across the step for UAH was downward by -0.001deg C after the step. RSS was downward by -0.037C after the step. The step is in the center of the data length today so the net trend is strongly affected by small changes at this point.
The corrected curves look like the graph below.
The RSS curve and UAH lay very much on top of each other now. The step in the difference between the metrics (green line in circle) is not visible any more.
The corrected slope for UAH is 0.126 DegC/decade – down from 0.127 Deg C/decade.
The corrected slope for RSS is 0.136 DegC/decade – down from 0.157 Deg C/decade.
After homoginization the difference in trend is only0.01C/decade which is within my stated measurement error from my previous ARMA analysis posts of about 0.02 C/decade at 95%. This instrumental error level is substantially smaller than any other error I have ever read on any blog or paper. That’s because it is related only to the noise level of the instrumentation as computed by ARMA difference analysis from GISS and UAH residuals. The actual slope created by non-random error can be outside this limit. Still, since these measures use the same data as a source, we would expect very tight agreement as the homogenized data shows.
This is another confirmation that the RSS data is in error at the point in question, the same conclusion reached by Dr. Christy using sonde data in his paper.
Tropospheric temperature change since 1979 from tropical radiosonde and satellite measurements
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 112, 2007
I believe that my work has now resulted in a much more accurate correction than my first attempt. This result is verified by a couple of methods, first it matches Dr. Christy’s result in the paper above, second it compares favorably to the uncorrected trends after the step.
UAH after step — 0.123 C/Decade
RSS after step — 0.129 C/Decade
After digging into the data for endless hours, I now believe the UAH trend is the superior dataset of all three metrics. Until I find a reasonable explanation for the difference in short term temperature variations in sat data being 1.23 times greater than GISS (which is predicted by models), I also believe that the 30 yr temperature trends need to be divided by 1.23 in order to achieve a suitable match to GISS ground measurements. This places the heavily corrected GISS metric well outside of a reasonable difference from satellite measures having a 30 year value of 0.183 C/Decade for the last 30 years!
As I understand it today, if the UAH trend as confirmed by the short term variation and models are accurate the GISS trend should be only 0.103 degrees C/decade. What percentage of that is man made is anyone’s guess.