Comparing NOAA SST Data to UAH and RSS

As Bob Tisdale pointed out . . . FLAWED ANALYSIS

Continuing with my data collection project, I decided that I should analyze what satellite measurements are most reliable.  In 1979, we entered what is called the satellite era, and from that year to the present, we have had two Microwave Sounding Unit (MSU) temperature datasets.  One is run at the University of Alabama at Huntsville by John Christy and Roy Spencer (hereafter referred to as UAH).  The other is run by Remote Sensing Systems (hereafter refered to as RSS) , a private corporation based in Santa Rosa, California.

Both measure temperatures in the lower troposphere, middle troposphere, and lower stratosphere.  They are in relative agreement except concerning the temperature changes in the tropics.  The difference in temperature trends in the tropics is due to different mathematical techniques for analyzing the data received by the MSUs.  Because I have no ability to assess the validity of the two techniques, I am turning instead to sea surface data as a method for confirming UAH or RSS trends.

To do this, I used data extracted from NOAA because it offers a unique and incredibly useful way to extract sea surface temperature trends within your chosen latitudes and longitudes (I attribute this find to Climate Observations (  There are instructions for extracting the data, though it is somewhat outdated, so I will write the instructions here.

1)     Go to

2)     Click “Access.”

3)     Search and click “Reynolds SST.”

4)     In the row that reads, “Smith-Reynolds Extended Reconstructed SST’s,” click “plot.”

5)     Select your desired data range and de-select “Generate control files….”  Click “Build order.”

6)     Click “Plot data.”

7)     The third row down should read “All” under the “cycle” column.  Select that row.  Under “Select Output Mode,” select “Time Series.”

8 )     Chose an “Extra Variable Operation;” I recommend “12 point.”

9)     The rest is self explanatory.  If you’re looking for the data itself, you’re given the option under the graph.

So what exactly are considered “tropics?”  Technically, the region is in between about 23 degrees N and 23 degrees S.  RSS uses 20 N to 20 S for tropics measurements.  It is unclear where UAH defines tropics, but for this analysis, I will assume that it is the same as RSS.  UAH data is easily accessible and user-friendly.  It can be found here:  T2 represents middle troposphere; t2lt represents lower troposphere; t4 represents lower stratosphere.  Under each folder (t2, t2lt, & t4), scroll to the bottom to find a file named “uahncdc.”  RSS data is less helpful.  Here’s lower troposphere data:  There is however, this page, describing their findings:

My logic is as follows.

1)      If the difference between tropic trends of UAH and RSS is caused by a difference in data handling (and not data collection), then we should see the same proportional difference between land and ocean temperatures according to UAH and RSS.  For example, if tropical ocean temperatures rose 2 times more according to RSS as compared to UAH, then we could expect tropical land temperatures to also increase 2 times more according to RSS as compared to UAH.  Even if this assumption is wrong, my conclusion should not be significantly altered.

2)     It would be helpful to compare RSS and UAH tropics data to actual readings by surface stations and sea surface data.  Most of the tropics is ocean, and the only major pieces of land in the tropics are South America and Africa.  Unfortunately, we have seen a very large decline in African and South American surface stations to the point that I would no longer trust any attempt by GISS or Hadley to estimate changes in African temperature.  Therefore, I am looking to NOAA Reynolds Sea Surface Temperature (SST) over the tropics to compare to UAH ocean tropics data.  RSS unfortunately does not divide its tropics data into ocean and land, so I will not be able to include RSS in the comparison.

3)     According to my linear regression of RSS and UAH tropics data, RSS shows 2.43 times the warming UAH shows.  Therefore, based on 1) and based on the fact that most of the tropics is oceanic, we can expect that RSS shows 2.43 times the tropical oceanic warming that UAH shows.

4)     Using data from 1979 to 2007.  UAH tropical oceanic data shows a warming of .07 degrees C per decade.  Extrapolating based on 3), RSS tropical oceanic data would show a warming of .17 degrees C per decade.  NOAA Reynolds Sea Surface tropical oceanic data shows a warming of .08 degrees C per decade.

In conclusion, UAH data better fits actual surface measurements better than RSS does.  While this does not prove that UAH is more reliable, this analysis makes me confident enough to use UAH rather than RSS when determining terrestrial temperature trends.

Below is a graph I created from this GISS resource:  From 1979-Nov 1981, GISS uses Hadley data for SST; from Dec 1981 to the present, GISS uses the same data that I used.  Therefore, this graph should be a rather accurate map of the SST I used.  Maps always help; this one shows us cooling in the East tropical Pacific (due to the trend for increased La Ninas over the past three decades), warming in the West tropical Pacific, and warming in the Indian Ocean.


For comparison, I requested a received a rectangular map of global tempeature trends  (1979-2008 ) from RSS.  Although RSS’s website shows trend maps, they are not rectangular and thus are difficult to read in some areas.  Below is the RSS trend graph – note the tropical warming that does not appear in NASA GISS’s Reynolds-based graph.

Below is a graph of UAH and Reynolds oceanic tropical temperature trends (1979-2007).


4 Responses to “Comparing NOAA SST Data to UAH and RSS”

  1. Bob Tisdale Says:

    1st: Thanks for the reference.

    2nd: Here are links to the RSS MSU ocean and land data sets:

    3rd: You’re comparing air temperature over the oceans (MSU) to sea surface temperatures (ERSST.v2). It’s an apples to oranges thing. You’re better off comparing LST to LST.

    4th: In addition to ERSST data, NOMADS has GHCN data (land surface temperatures) on their site. It’s a couple of rows below the Smith and Reynolds data. Follow the same steps. Where the SST data choices give you the opportunity to select between SST or anomaly, the GHCN choices allow you to pick maximum, minimum or mean anomalies. For your comparison, you’d probably want mean.

    5th: Here’s a link to ONI data about ENSO. I’m offering it since it’s color coded and therefore allows a quick check of the number of El Ninos (red) versus La Ninas (blue).

    You claim there was an increasing trend towards La Ninas over the last 30 years. Since 1978, there were 7 La Ninas and 10 El Ninos. Sounds as if it’s weighted toward El Ninos. I’ve also plotted the NINO3.4 data for the last 30 years, and it’s a positive trend.


  2. carlwolk Says:

    Thanks your help. I also recently realized that I was comparing apples to oranges though I hadn’t gotten around to noting it. It wasn’t until recently that I learned about the different reconstructions relating to El Nino variability, and I figured my assumption about la-nina dominance was wrong after your most recent post. I keep up to date with your blog; your posts are always unique and interesting. Thanks for your help.

  3. Global Tropical Response to ENSO Events « The Science and Politics of Climate Says:

    […] Surface Temperature (SST) for each of the oceans. (Source:  See this post for […]

  4. El Ninos in the Pacific, Atlantic, and Indian Oceans « Climate Change Says:

    […] the instructions in this post to access the data; however, don’t read the read the rest of the post – it’s […]

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