Troy's Scratchpad

July 17, 2012

NOAA and GFDL CM2.1 sea surface temperature trends by latitude

Filed under: Uncategorized — troyca @ 8:27 pm

I saw a post over at Roger Pielke Sr.’s a few days ago with some preliminary analysis of the sea surface trends by latitude, the primary point of which seemed to be that the water vapor feedback may be overestimated, as the warmer waters in the topics – which contribute more to evaporation – were actually heating at a slower rate than other regions.  I was skeptical of a few aspects of this, particularly the analysis with the short period (2003-2011) and the fact that a the width of the latitude bands showing the trends seemed to arbitrary.  Furthermore, what it  showed was a general increase in temperature trend the further North it went over the period 1982-2011, which I seemed to recall was similar in the GFDL CM2.1 model run.

Thus, I decided to compare the monthly NOAA SST anomaly trends by latitude to several of the GFDL CM2.1 model run trends by latitude over the same period (1982-2010 was the overlap here).  I used those GFDL CM2.1 runs for CMIP5 (rather than the CMIP3 runs I had used before), so these should have used historical forcings up until 2005.  I ultimately downloaded 5 of the 10 runs to get a decent sense of variability over that period.  Intermediate data and code for this post is available here…you’ll see that I used 15 degree latitude bands to cut down on some of the noise. 

Anyhow, when it came to reproducing the absolute temperatures by latitude, GFDL CM2.1 did quite well, although perhaps this was to be expected:

noaa_gfdl_temperature_by_lat

However, I was somewhat surprised to see that the spatial pattern of the warming was quite different:

noaa_gfdl_sst_trends

While the model seems to overestimate the SST trends, this was perhaps common knowledge already.  Instead, what is more interesting is that despite the variability in the model runs, almost all of them seem to show the greatest rate of warming near the equator, thus producing the general shape we see in the blue line (the mean from the 5 runs).  Compare it to the NOAA SST, and there appears to be a discrepancy. 

So, what affect will this have on the TOA radiation and the water vapor feedback?  I’m not sure.  My next step, if I find time, will be to compare a GFDL CMIP5 AMIP run (which has the atmospheric component tied to the actual SST observations up till 2008) to that of these coupled runs, perhaps using the GFDL water vapor kernels to convert the atmospheric specific humidity outputs in each into the global TOA radiative effect.  Or perhaps this work is already out there, and I need to search the existing publications.

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10 Comments »

  1. A paper that may be relevant to this post:

    http://www.stanford.edu/~omramom/Ashfaq_CDy_10.pdf

    Comment by troyca — July 17, 2012 @ 9:11 pm

  2. But is the water vapor feedback really driven by increased evaporation? I believe this issue came up a long time ago on Roger’s blog. Issac Held pointed out that the cause of the water vapor feedback in models is apparently actually an increase in the residence time of water vapor, not enhanced evaporation (which does happen, but should be balanced by an increase in the amount of precipitation).

    Comment by timetochooseagain — July 22, 2012 @ 2:44 pm

    • Thanks TTCA, and sorry for the slow response.

      Your comment is interesting, and honestly I don’t know the answer! I keep hoping to find a bit of time to run the tests I mention above, which would at least show the extent to which the observed spatial distribution of the warming affects the amount of radiation trapped by WV versus the “expected” (model-observed) distribution, although if there was a discrepancy I suppose this wouldn’t necessarily imply this has anything to do with evaporation — it may just as easily have to do with the location of clouds or magnitude of upward flux in the areas that see the greater/lesser increase in WV relative to those expectations. Still, at least on the surface such a result may lend support to the hypothesis. If, on the other hand, dR_wv/dT ends up being about the same magnitude, it seems to me it would be a pretty strong argument against it.

      Comment by troyca — July 31, 2012 @ 9:53 pm

  3. I’ve found something interesting, WRT the way the tropical sea surface temperature change may impact sensitivity. It’s an old modeling study where they fixed temperatures in the ENSO region:

    http://eaps.mit.edu/faculty/lindzen/tropingcli.pdf

    This resulted in a sizable reduction in the sensitivity, at least in that model. So it might be the case that where temperature changes impacts the sensitivity.

    Comment by timetochooseagain — August 4, 2012 @ 3:06 pm

  4. Chad,

    Here are RSS lower troposphere trends by latitude. I see no reason to average them over wide bands of latitude, but I could. I just did this quick so it’s land and ocean, but would be worthwhile going back and splitting off the ocean. I wonder how it agrees with the NOAA SSTs.

    http://tinypic.com/r/2ymdgfq/6

    A while ago I did some decadal trend comparison of some GFDL CM2.1 CMIP3 runs vs. GISSTEMP by latitude here:

    Again, all land + ocean.

    Comment by billc — August 6, 2012 @ 1:00 pm

    • er, sorry, Troy

      Comment by billc — August 6, 2012 @ 1:01 pm

    • oh screw it the day was almost done anyway. here’s the graph from above updated to compare NOAA SST with RSS (still land + ocean). I can recreate the RSS ocean data by applying the NOAA land mask to it I guess. criticisms welcome.

      Comment by billc — August 6, 2012 @ 1:38 pm

  5. [...] space and memory, I was finally able to do some of the analysis I had talked about doing in the previous post, and the preliminary results seem quite interesting.  To recap, I wanted to see what effect [...]

    Pingback by Sensitivity of the water vapor feedback to locations of SST trends « Troy's Scratchpad — August 15, 2012 @ 10:52 pm


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