Wednesday, April 20, 2016

NOAA Global index still rising - new record.

Most indices dropped slightly from record February values. But as expected, the global NOAA index held up, and was even slightly warner, at 1.22°C vs 1.19 in Feb. That is the highest anomaly in the record for any month.

I'll show my now usual comparison with 1997/8::

There is a maintained collection of these plots that you can flick through here. In 1998, March fell back from the Feb peak, but here it has risen. HADsst3 is out too, with a rise, which is interesting. February SST dropped, causing some chatter about rapid El Nino decline, but this was premature. I'll show the comparison below the fold.


  1. I have a question. Maybe someone here knows the answer...

    The satellite records tend to be very sensitive to ENSO relative to the surface station records so that if you plot UAH-GISS you get a pretty good approximation of the MEI. The only real exceptions are 1983, 1992, and 2015 (and to a lesser extent 2006). 1983 and 1992 followed the El Chichón and Mount Pinatubo eruptions which may have cooled the stratosphere (or maybe there is another reason), but why is there such a discrepancy over the last year or so? Hopefully this graph illustrates:

    MEI heads up but UAH-GISS goes down in 2015... Why is that?

    1. Looks pretty noisy, not much to say yet but it could be Arctic related.

      Take a look at this paper by Kim [1]. I have been modeling ENSO as a modulated biennial forcing and then noticed that Kim are using the same approach. With just a few parameters, the stationary ENSO behavior is captured effectively

      Strictly biennial oscillations are metastable and so can exhibit phase reversals. Still experimenting with the parameterization, which is very close to Kim's. Its possible that there is a canonical set that will work without being prone to over-fitting.

      [1] Kim, Jinju, and Kwang-Yul Kim. "The tropospheric biennial oscillation defined by a biennial mode of sea surface temperature and its impact on the atmospheric circulation and precipitation in the tropical eastern Indo-western Pacific region." Climate Dynamics (2016): 1-15.

    2. Thanks whut. When you say Arctic related, do you mean that the warming seen in GISS since 2015 is largely in the Arctic where UAH is blind?

    3. Possibly. One of the numbers chasers reading this blog can tell you.

    4. Ok. Thanks. I made a bet that UAH would show 2016 as warmest year on record. I chose UAH because I expected it to react strongly to the El Nino, but it has not...

    5. Layzej,

      The problem is that "UAH" is a constantly changing, indeed protean creature. It has undergone about 15 incarnations within the last 25 years (we're presently at version 6.5). As Nick has shown, , there is a very large discrepancy between the "version 5 family" and the "version 6 family" of UAH series (see in particular the second plot in Nick's post). Since Roy Spencer is yet to submit version 6 for peer review publication it is hard to work out the validity of these adjustments.

      As an alternative you could try repeating the exercise you have done with the latest satellite - derived tropospheric dataset produced by Remote Sensing Systems (RSS) Inc.
      I for one would be interested in the result. Having eyeballed this myself this seems to give much better consistency with the data for 1998 that UAH vs 6 lacks.

    6. Thanks Bill. I've added a switch to toggle between UAH5.6 and RSS. RSS seems about as responsive to the current El Nino as UAH5.6. They don't seem to be reacting the same way as they have during past El Ninos. Maybe I just need to wait another month or two...

  2. Whut,
    Interesting reference for the Kim et al. paper. Unfortunately, paywalled, and I can't tell how they've derived ENSO behaviour. Are they also looking at aliasing.
    On another matter, congrats on your model's prediction of the 2015/6 el Nino. Any predictions for a 2016/7 la Nina?

    1. Bill, I will post a PDF copy on my blog.

      They have a technique called cyclostationary analysis which is described in one of their earlier papers.

      The insight that they and I share is that the strictly biennial oscillation is modulated by longer frequencies such that +/- sideband frequencies are created around the 2-year period. This is not aliasing but essentially a non-aliased frequency modulation of the base cycle.

      Kim: "While the TBO (tropospheric biennial oscillation) is frequently seen as a quasi-biennial oscillation, its phase is strongly locked to the calendar months. Thus, the assumption of the 2-year periodicity seems reasonable"

      That locks the base frequency in place, with the modulation creating what looks like a more chaotic pattern. That's why ENSO has been so stubborn to analysis, in that the number of Fourier frequencies doubles with each modulating term. Yet in reality it's likely half as complicated as most scientists have been lead to believe.

      The most interesting mathematical question surrounding a biennial cycle is that this cycle is metastable with respect to starting on odd or even years. What causes it to pick the parity it chooses, and how stable is that selection?

      The breakthrough is that a likely biennial odd/even phase inversion does occur right around 1980, which is in line with the hiccup that Astudillo observe [1]. So if you aren't expecting these phase inversions, you will have a hard time extracting the signal.

      [1]H. Astudillo, R. Abarca-del-Rio, and F. Borotto, “Long-term non-linear predictability of ENSO events over the 20th century,” arXiv preprint arXiv:1506.04066, 2015.

    2. The version of the Kim paper that Nick linked to appears private. Here is a version attached to my recent blog post on the topic Biennial Mode of SST and ENSO -- Kim PDF

      Kim is I believe a PhD from the FSU meteorology department, where most of the key ENSO players such as Clarke and O'Brien have hung out. I have gained most of my insight into the behavior of ENSO from that school.

      I have a feeling that this is close to the breakthrough needed in finding a deterministically stationary basis to ENSO.

    3. Allan Clarke of FSU suggested that the characteristic period for ENSO sloshing is 4.25 years [1]. If one looks at the residual spectrum after a modulated biennial forcing model is compared to SOI, there is a broad peak a little over 4 years. That is consistent with the natural response of whatever white forcings remain after the mod biennial forcing is applied.

      [1] A. J. Clarke, S. Van Gorder, and G. Colantuono, “Wind stress curl and ENSO discharge/recharge in the equatorial Pacific,” Journal of physical oceanography, vol. 37, no. 4, pp. 1077–1091, 2007.

  3. Nice work as usual Nick. It would be interesting to compare monthly average global net radiation estimates over these periods as well. Have you compiled that data?

    It would also be interesting to see a long-term time series of the monthly average global net radiation estimates. If CO2 is the main driver of the global radiation balance, the time series should track CO2 concentrations well and should indicate an increasing net retention of radiation over time - unless the uncertainty in the estimates is larger than the impact from CO2, in which case the CO2 signal will be hidden by the uncertainty noise. But that would at least put an upper limit to the CO2 impact, assuming all of the impact is from CO2 and none is natural - which might be a stretch. There obviously have been relatively large natural net radiation imbalances in the past that drove the glacial cycles of the last million years, as well as shorter and less intense climate cycles in the Holocene. To me it seems global net radiation is the best way to evaluate the CO2 impact on the radiation balance rather than looking at global temperature anomalies.

    The accuracy of global temperature anomaly estimates is not likely to be any greater than the net radiation estimates, and may possibly be less. My best guess based on over 40 years of working with temperature measurements is that the global temperature anomaly estimates in the satellite era probably have an overall uncertainty of plus or minus at least 0.3C and possibly as high as 0.5C. That uncertainty only increases as you go farther back in time. In the 1800's, the uncertainty might be 1C or higher because of the sparsity and lower accuracy of the data. But I digress.

    I was just looking at monthly global maps of net radiation and aerosol optical depth here:

    So I am sure someone must already be looking at the trends but so far I have not found any global net radiation trend data.

    1. Bryan
      "It would be interesting to compare monthly average global net radiation estimates over these periods as well. Have you compiled that data?"
      Thanks for kind words. haven't looked at OLR series. I presume you are thinking of reanalysis data. NCEP/NCAR has it, so it is possible. With reanalysis you have to worry about long term homogeneity.

      I don't know what you would expect from it. I think you are suggesting that it would show CO2 retaining radiation. But the GHE doesn't say that is a long-term effect; rather that the OLR that balances insolation will require warmer surface temperatures to be emitted against the GHG impedance. My understanding is that you can currently with great difficulty see a drop due to the heat that is going to warm the oceans.

    2. I'm thinking about the CERES based net radiation estimates. See the NASA Earth Observatory link that I provided above for monthly global maps of net radiation from 2006 through March 2016. The Loeb PDF link that I posted below has some CERES net radiation time series plots, but only goes to 2006. It also discusses some of the limitations.

    3. It's hard to get CERES numbers though. As you say, maps to present, but no numbers, or at least not there.

      There is also the issue of "net". Time variation might well be more solar than OLR.

    4. If I stumble across any links to CERES gridded data I will pass them on. It would be great to see the net radiation contours on a spinning globe. I still need to go back through that Loeb PDF to learn more and hopefully find some more recent info as well.

      Changes in TSI should be easy to account as there seems to be plenty of TSI time series data. Getting the calibration straight is another matter, although recently I have seen claims of settling that issue.

    5. Better to look at the ocean heat content data to estimate the earth's energy imbalance. Recently the oceans have been gaining roughly one times 10 to the 22nd calories per year that is equivalent to roughly 0.7 watts per square meter of earths surface assuming 90% of energy imbalance is going into the oceans. That is the same forcing that would be produced by a sudden 17% increase in CO2.


  4. Just found this nice overview presentation on "Determination of the Earth's Radiation Budget from CERES". It's a bit out of date from 2006, but interesting nonetheless. If they have updated this presentation, I haven't found it yet.