Thursday, April 13, 2017

TempLS update - now March was warmer than Feb by 0.03°C

Commenter Olof R noticed that the TempLS mesh estimate for March had suddenly risen, reversing the previously reported drop of about 0.06°C to a rise of 0.03°C. He attributed the rise to a change in China data, which, as noted in the previous post had been very cold, and was now neutral.

I suspected that the original data supplied by China might have been for February, a relatively common occurrence. Unfortunately when I download GHCN data it overwrites the previous, so I can't check directly. But the GHCN MAX and MIN data are updated at source less frequently than TAVG, and they are currently as of 8 April. So I checked the China data there, and yes, March was very similar to February, though not identical. GHCN does a check for exact repetition.

Then I checked the CLIMAT forms at OGIMET. I checked the first location, HAILAR (way up in Manchuria). The current CLIMAT has a TMAX of -3°C for March and -13.5°C for Feb, and yes, the 8 Apr GHCN has -13.5. So it seems that is what happened, and has been corrected.

So March is warmer than February, and so warmer than any month before Oct 2015. It is also warmer than the record annual average of 2016, and so then is the average for Q1 of 2017. The result is fairly consistent with the NCEP/NCAR average, which showed a very slight fall. I was preparing a progress plot for the next GISS report, so I'll show that for TempLS. It shows the cumulative average for each year, and the annual average as a straight line. 2017 has not started with the El Nino rush of 2016, but is ahead of the average and seems more likely to increase than decrease.





21 comments:

  1. Well, April seems chilly, and looks to get chillier? The May threshold for ENSO forecast accuracy looms large.

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    1. Chilly? Well, cooler than March, but warmer (NCEP/NCAR) so far (0.502C) than any month from May-Dec 2016. And not much less than the 2016 annual of 0.531C.

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  2. This correction now puts TempLS more in line with the GFS/CFSR change of about +0.03C for March versus February. The adjusted ERAI reported at Copernicus showed little change.

    The global surface temperature anomaly has been running substantially higher than the Tropics zone (30N-30S) anomaly since about September 2016, mainly because of much higher anomalies in the NH temperate and polar areas (30N-90N) and this effect might indicate a continued venting of heat left around after the last El Nino. As that heat is gradually dissipated, the NH and global averages may drop down closer to the tropical average over the next few months. Also, the Arctic generally does not have very large anomalies in the Arctic summer, which should contribute to a drop, even if all other areas remain the same. What happens in the coming Antarctic winter may have a larger influence, as well as what happens in the Tropics zone. Even in La Nina years, the Tropics zone SSTA usually warms a bit during the NH summer and that should add some heat to the system.

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    1. Nick

      There is temperature anomaly data for 2 meters, and for the lower troposphere. Anything in between?

      Seems like knowing what's going on at different of the troposphere would be very enlightening.

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    2. Different levels of the lower troposphere, I should have said.

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    3. Cliff,
      "Anything in between?"
      Only some radiosonde data. The reason is that satellites really can't measure near the surface, because that is itself a big emitter of microwave radiation, which is just noise to this signal. In fact the definition of TLT has been creeping up. UAH V5.6 claimed a peak weight at 2km, but V6 has settled for 4, as does RSS TTT V4. And you may note that John Christy nowadays rarely mentions TLT, but usually TMT. NOAA produces a TMT measure, but not TLT.

      Satellites really have very little ability to discriminate levels. They just have one signal beam coming in, with different channels, and they rely on differential weighting of this channels. Very little depth resolution.

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    4. Interesting. What about all the stations around the world that still send up weather balloons? Couldn't a global mesh or grid model be developed from their readings?

      Or is this an idea climate scientists have considered and decided wouldn't be very useful?

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    5. Cliff,
      The problem with balloons is that there aren't many sites, readings are infrequent (maybe daily) and they are very hard to homogenise. Winds vary, instrumentation does too, and is not as good as surface,. There is a homogenised set RATPAC A - it has 86 sites in total. There are others, but that is the basic problem.

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    6. I think a good exercise would be to vertically weight the radiosonde measurements to match the various satellite channels and then subsample the MSU/AMSU readings to match the location of the radiosondes. Run both through TempLS and compare.

      Good for detecting discontinuities and drift, and a good test of how representative those locations are for estimating the globe.

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    7. I have done this comparison of Ratpac and UAH.
      Comparing original global indices, or apples to apples (TLT weighted and subsampled) makes no major difference. There is a distinct breakpoint when the AMSU-satellites were introduced, after which satellites lose almost 0.2 C/decade on sondes.

      This chart compares different weightings (and subsampling). TTT, TLT or 850-300 are quite similar.

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    8. They don't even know how to interpret the balloon data once they get it. For example, the QBO data is all from radiosondes and the denier Richard Lindzen never was able to figure out that the QBO behavior is lunar forced. Very easy to derive this from the Navier-Stokes primitive equations (in the form of Laplace's tidal equations) and then to precisely phase the lunar draconic cycle as the forcing stimulus. http://contextearth.com/2017/04/10/tidal-model-of-enso/



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  3. Radiosondes agree with satellites, the free troposphere is cooling more than surface.
    Ratpac A 850-300 mbar year-to-date is down 0.26C compared to the annual average 2016, or down 0.61 C compared to year-to-date 2016.

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    1. I used to build hot-air balloons, and I believe our engineer was one of the guys who originally set up the balloon program for the radiosondes. He had a large number of 1950s photographs on his wall of weather balloons he had deployed in his prior career. Are they all deployed from land?

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    2. In the 1950s, My dad was sent by the navy to a base on the South Pacific island of Yap. Part of his job was to send up weather balloons. I think the navy was worried about typhoons.

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    3. With a constant energy source (the sun), it makes sense to me that if more heat is being trapped near the surface, less heat would be making it's way to higher levels of the atmosphere. Is this too simplistic?

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  4. Gistemp March is out, 1.12 C, up 0.02 from Feb. Year to date average is 1.04 C, 0.06 above the 2016 annual average

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  5. " Unfortunately when I download GHCN data it overwrites the previous, so I can't check directly."

    I have an extensive archive for GHCN-M v3 (TAVG, TMIN, TMAX; qcu and qca) and v4 beta (qcu and qcf), daily for the past three years with just a couple of missing days - offline for a flight to Melbourne and a couple of days due to a fan replacement - less frequently for the preceding three years. If there are some you want let me know and I can burn a DVD. I think my email address is visible to you so you can let me know and supply an address.

    You posted a verification some months ago for Australian GHCN-M data, CLIMAT messages, and the Australian met data. It was for a single date however, which is not necessarily sufficient. Have you noticed the recent addition to the GHCN-M status.txt file:

    03/11/2017

    User feedback indicated a problem with some mean temperature data for select stations in
    Ireland. The problems were traced to a particular data source (MCDW), and for
    the time being until that source is corrected, the data are now being sourced
    to the UK Met Office "Climat" data ("K" source flag"), which are believed to
    be the correct values. The data changeover to the UK Met Office has occurred, but
    the source flag ("K") for the corrected values was inadvertently left out. Those
    source flags should be added within the next production cycle.

    I was responsible for this "user feedback", although I routed it through the Irish Met Office, Met Eireann, to ensure a prompt response (location metadata errors I reported directly in 2010 for GHCN-M v2 still remain uncorrected in v3 - the response "Hopefully some of these can be fixed quickly, but others may take a little longer" reminds me of the old joke: Q. Is there an Irish word corresponding to mañana? A. Yes, a number of equivalents, but none conveying the same sense of urgency)

    The correction referred to has been botched. You can still find six identical rogue monthly values in a single year, both summer and winter, in the raw data, not all of which are caught by quality control, so some survive into the adjusted data. Stations with six or more identical monthly means in the same year can be found in GHCN-M, but all well within tropical latitudes. Whoever examined the data at NOAA did not seem disturbed to find a pattern more characteristic of a tropical rainforest climate zone at 51.85°N! And since the data corruption arises when the source becomes MCDW, having earlier been shown correctly when the source was CLIMAT data from Met Eireann or later via the UK Met Office, I would not share the apparent confidence that the problem is confined to "select stations in Ireland".

    I'm not sure whether I can post an image here by typing the URL, but here (if it works) is the example I provided to Met Eireann: https://oneillp.files.wordpress.com/2017/02/corkcomposite.jpg , and here is the history showing the rogue 10.4° value entering when the source changes to MCDW. Such rogue values were present in recent years for the Irish stations which are still updated in GHCN-M. But it would have been possible to find a month with uncorrupted data for all stations. The "correction" for the station in this image corrects 2013, but leaves rogue values in the raw data for 2014 and 2015.

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    1. I omitted the URL for the "history showing the rogue 10.4° value entering when the source changes to MCDW"

      It is https://oneillp.files.wordpress.com/2017/02/corkcomposite20131.jpg

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  6. oneillpt
    Thanks for that. The immediate need for past GHCN was to check if the first posted China data for March actually was a month out. I think the TMAX settled that. I don't have access to email addresses in the Blogger system (AFAIK). My address is nastokes plus a westnet o com o au.

    On the Australian verification, I was wanting to show that the data passes throgh unadjusted. I don't think the Irish situation is an adjustment, just an error. They aren't handling it very well.

    GHCN error checks for certain specific patterns; they won't pick up qualitative things like lack of seasonality. That's why the China data passed; March was similar but not identical. I've noticed a few similar errors in MCDW; for example Port Hardy on Vancouver Island gets mixed with Clyde River in Nunavat (similar WMO numbers). But I don't think they are very widespread.

    I have a way of looking for exceptions. I plot for each month a shaded map where each node has the right color for the station anomaly. It should be fairly smooth in Europe, so exceptions stand out. If you zoom (right mouse) and then flick through the months, exceptions become fairly obvious. If you zoom Ireland, April 2014, then it does look different to earlier months. Cork, at 10.4, is actually not a large anomaly, but still it shows a little. It would be very noticeable in winter. You can look around the world in this way. I described some of this here; I think we talked about Nitchequon. Overall, there don't seem to be all that many exceptions.

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