I’ve moved to WordPress. This post can now be found at RSS MSU TLT Anomalies February 2011 Update and A Look At Version 3.3###########################
FEBRUARY 2011 UPDATERSS TLT anomalies continue to drop in response to the 2010/2011 La Niña. RSS MSU TLT anomalies are now at 0.051 deg C, Figure 1.
RECENT VERSION UPDATE
RSS recently updated their MSU Lower Troposphere Temperature (TLT) anomaly data with a new version, v3.3. This was discussed last month at Watts Up With That? in the post RSS global temp drops, version change adjusts cooler post 1998. At that time, RSS had not described the changes. They now have at their website on their data description webpage.
Refer to the Version Notes. Here’s what RSS has to say:
RSS Version 3.3 Channel TLT, TMT, TTS, and TLS – January, 2011
Change from 3.2 to 3.3:
* Additional satellites are now included in the merge. Version 3.2 only used data from one AMSU instrument, NOAA-15. For TLT, TMT, and TLS, Version 3.3 includes data from the AMSU instruments on NOAA-15, AQUA, NOAA-18, and METOP-A. AMSU channel 7 exhibits unexplained drifts in METOP-A, so for TTS, data from METOP-A is not used.
* Comparisons with other AMSU satellites are now used to detemine [sic] the AMSU merging coefficients.
* When merging MSU and AMSU together, the data for each generation of satellites is weighted by the number of satellites with valid data for that month. This has the effect of de-emphasizing MSU data after the advent of the AQUA satellite in June 2002. Since the 2002-2004 period is when there is an unexplained warming drift in MSU channel 2 data from NOAA-14 relative to AMSU data, this change has the effect of lowering the overall warming in TMT and TLT during the post 2002 period.
* The changes also result in a reduction of sampling noise and “orbital striping” for periods when data from more satellites is used.
* Data from NOAA-16 is not used because all 3 channels show unexplained drift throughout it’s [sic] lifetime. NOAA-17 was only operational for a short period of time, thus it’s [sic] data is of little use for climate studies. We plan to begin including data from NOAA-19 after 3 years of operation.
Figure 2 compares the anomaly data and linear trends of the new RSS TLT Version 3.3 to the obsolete Version 3.2. The update lowered the linear trend since 1979 from approximately 1.6 deg C to 1.5 deg C per Century, Figure 2.
The difference between the two datasets is shown in Figure 3.
Figure 4 is a .gif animation that compares the2010 anomaly maps for the new and old versions when using 1979-1980 as the base years. Basically both maps are showing the change in TLT anomalies from the average of the years 1979 and 1980 to the year 2010. The patterns for both datasets are similar, but there are minor changes in the variations.
COMPARISON TO UAH MSU TLT DATA
The linear trends of the RSS version 3.3 and the most recent version of UAH TLT anomaly data (v5.4) are basically the same: 1.47 versus 1.44 deg C per Century. Refer to Figure 5. Note that I’ve switched to KNMI climate Explorer as the source for both datasets, so that I could limit the UAH latitudes to those used by RSS, 70S-82.5N.
Figure 6 shows the difference between the two datasets.
And Figure 7 is a gif animation similar to Figure 4, but this compares RSS (v3.3) to UAH (v5.4) TLT anomaly data.
THE ENSO-INDUCED STEP CHANGES
I illustrated and discussed the ENSO-induced rises in the RSS MSU TLT anomalies for the data north of 20N in the post RSS MSU TLT Time-Latitude Plots... Show Climate Responses That Cannot Be Easily Illustrated With Time-Series Graphs Alone. I further discussed the likely cause for the upward steps in the post The ENSO-Related Variations In Kuroshio-Oyashio Extension (KOE) SST Anomalies And Their Impact On Northern Hemisphere Temperatures.
Figure 8 illustrates Volcano-adjusted RSS TLT anomalies north of 20N in “raw” form and smoothed with a 13-month running-average filter. Also included are the period average temperature anomalies of -0.187 for 1979 to 1987, -0.016 for 1988 to 1997, and 0.268 for 1998 to present.
I adjusted the data for the linear effects of the two major volcanic eruptions, El Chichon and Mount Pinatubo. To determine the scaling factor for the volcanic aerosol proxy, I used a linear regression software tool (Analyse-it for Excel) with global RSS TLT anomalies (v3.3) as the dependent variable and GISS Stratospheric Aerosol Optical Thickness data (ASCII data) as the independent variable. The scaling factor determined was 2.9.
And in Figure 9 the “raw” data has been deleted to help show the ENSO-induced upward steps in this dataset. So the revisions have not changed these to any great extent, so I won't go back and update the earlier posts.
The following are links to the data use to create Figures 1, 2, and 3.
All other data were downloaded, and the maps were created, using the KNMI Climate Explorer Monthly observations webpage.
(Many thanks to Dr. Geert Jan van Oldenborgh of KNMI for the quick update to RSS TLT version 3.3.)