CFSR Global Temperature Trends through November 2015

I have been tracking the University of Maine (UM) Climate Change Institute (CCI) daily and monthly global temperature anomaly estimates based on reanalysis of the Global Forecast System (GFS) initialization data, also know as the Climate Forecast System Reanalysis (CFSR).  Daily estimates through November are plotted in Figure 1 for 2015 so far and in Figure 2 for 2014 through 2015 so far.

Global temperature anomaly estimates 2015

Figure 1. UM CCI CFSR daily global temperature anomaly estimates for 2015 January through November

Global temperature anomaly estimates

Figure 2. UM CCI CFSR daily global temperature anomaly estimates for 2014 through 2015 November

These daily estimates show an overall flat trend through most of 2014 and 2015, with a sharp upward jump in October 2015 that continues high into November 2015.  I suspect this jump is related at least in part to the peaking El Niño in the Pacific as it exerts influence on temperatures around the globe.  These short-term changes are weather and not climate.  It will be interesting to see how much longer this small upward spike lasts.

The UM CCI currently has final CFSR monthly estimates through June 2015 and daily estimates through October 2015.  I compiled the final daily estimates into monthly estimates for July through October 2015 and compiled a preliminary November 2015 estimate from preliminary daily estimates.  All of the UM CCI estimates presented here have been normalized to the most recent standard climatological reference period 1981 through 2010.

Figures 3 and 4 show the monthly global temperature anomaly trends for this century so far, 2001 through November 2015, and for the satellite era at the end of the last century 1979 through 2000 respectively.

Global temperature anomaly trend 2001-2015

Figure 3. UM CCI CFSR monthly global temperature anomaly trend for 2001 through 2015 November

Global temperature anomaly trend 1979-2000

Figure 4. UM CCI CFSR monthly global temperature anomaly trend for 1979 through 2000

The recent spike in global temperature anomaly has not significantly changed the downward slope for the 21st century so far, but has reduced the coefficient of determination, indicating a less certain trend.  The indicated trend of -0.0012 degrees Celsius (C) per month corresponds to a trend of -1.44C per century if it continued through the remainder of this century, which is not likely.  For comparison, the trend for the satellite era at the end of the 20th century, 1979 through 2000, is +0.0007C per month which corresponds to +0.84C per century if sustained.

Another way to view the CFSR estimate period is to break it at the intense 1997-1998 El Niño as shown in Figures 5 and 6.  Figure 5 shows the most recent 1997 through November 2015 portion covering nearly 19 years and including the 1997-1998 El Niño .  Figure 6 shows the previous 18 year period period for 1979 through 1996.

Global temperature anomaly trend 1997-2015

Figure 5. UM CCI CFSR monthly global temperature anomaly trend for 1997 through 2015 November

Global temperature anomaly trend 1979-1996

Figure 6. UM CCI CFSR monthly global temperature anomaly trend for 1979 through 1996

Both of these periods show essentially a flat trend with no overall increase or decrease, but with a higher step offset of about +0.3C for the most recent period.  However, during this entire 37 year period, carbon dioxide (CO2) continued to increase steadily with no indication of a step trend.  This data indicates that the relationship of CO2 to global temperature is not at all direct over this long of a time scale, which casts into serious doubt whether it has any significant effect at all.

For for the latest CFSR daily updates to key figures, see the Daily Updates page accessible from the menu bar at the top of this page.

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13 responses to “CFSR Global Temperature Trends through November 2015

  1. Any reason to use CFSR over ECMWF data?
    Do they lead to different conclusions?
    I am a little bit puzzled by the warming seen between 2001 and 2009 that is not reproduced by other temperature records. It means that while everybody was discussing the pause, this database showed no pause (figure 5, first half of the graph).
    Everybody is picking their favorite database and reaching conclusions, but that can hardly be called science. Unless we have a clear reason to discard a database, we must only reach conclusions supported by all databases.

    Thanks

    • Javier, I chose the CFSR because I found a source (UM CCI) that is current. That same source has the ERA based on ECMWF data but it is not current. Using all the different data sets helps to identify uncertainty in the estimates, which I suspect is large, on the order of 0.3C to 0.5C or more for recent annual estimates of global temperature anomaly.

  2. When you use UAH, are you using version6.0?

  3. Oz
    The UMaine and WxBell CFS series have a spurious cooling of 0.2 to 0.3 C in 2010/11 when CFS was updated to CFSv2, hence the decreasing trend in Figure 3. I encourage you to compare CFS to other surface temperature and reanalysis datasets in 2010 and 2011 so you can judge for yourself. The best use of the CFS series is to check short-term trends using the CFSv2 portion.

    • Chubbs, how do you know the current CFS estimates are “spurious”? There are plenty of changes in recent years in the other surface estimates as well, including those from NCEI, GISS, and HADCRUT and these changes may have been politically motivated and decreased their accuracy. I view all of these discrepancies as further indication that these estimates are not all that accurate and the uncertainty is much larger than most sources suggest.

  4. That conspiracy stuff is silly. Look at the other re-analysis series – NCEP, ERA, MERRA – none agree with CFS in 2010/11. CFS is the odd man out.

  5. Chubbs, today I pulled the latest ERAI data through 2014 from UM CCI and compared it to the CFSR. The largest discrepancies are for the period 2002 through 2009 when the CFSR is higher. I have not seen an assessment of this discrepancy period. Were GFS weather forecasts terrible during this period?

    Otherwise, the CFSR and ERAI annual estimates match fairly closely. All of the differences, including 2002-2009, are within plus or minus 0.3C which is at the low end of what I consider a reasonable uncertainty range of 0.3C to 0.5C for recent annual global temperature anomaly estimates. Consequently differences and trends within the uncertainty range are very low confidence and practically meaningless.

    I said nothing about “conspiracy”. I suspect what has happened is a form of confirmation bias. When complex homogenization routines are developed and tweaked, the tweaks that produce the “expected” results are the ones favored and this biased approach has probably lead to less accurate results.

  6. Chubbs, I’m sure you have seen this temperature stability diagram, which shows a full 0.25C added since 2008 to the difference between the global January temperature for 2000 versus 1910 in the GISS estimates. It begs confirmation bias.

  7. That chart is misleading. Per Nick Stokes recent blog the adjustments to GISS have been very small compared to the large recent downward adjustment for UAH: http://moyhu.blogspot.com/2015/12/big-uah-adjustments.html. All of these adjustments are made to improve data analyses. Scientists are trying to remove bias in the temperature and satellite data. On the other hand CFS is frozen – the developers made no attempt to ensure consistency during the transition to CFSv2 and there has been no bias evaluation. No scientist uses CFS for trend analyses. The good news is that problems in the 2010/11 transition to CFSv2 will slowly become less important with time. Confirmation bias is real no doubt – the planet is clearly warming yet the picture is fuzzy to many. .

  8. Chubbs, I don’t believe Ole Humlum’s chart is misleading. Nick’s recent post that you reference did not cover data before 1979 and therefore would not show the very large change in the GISS data that occurred in early 2013 which greatly enlarged the difference for January 2000-1910. Here is another perspective showing even more changes to the NASA estimates since 1981, which greatly and possibly artificially increase the upward temperature trend:

    Below is another example that strongly suggests confirmation bias or possible willful tampering in adjustments to USHCN data. What are the odds that legitimate adjustments for real problems in the measurements would show such a perfect match to CO2?

    I looked at the WxBell time series graphs of daily global temperature anomalies back to 1979 and I do not see any evidence of a sudden step jump somewhere in 2010 or 2011 to indicate where the change from CFSR to CFSRv2 took place. If it was so dramatic, I would expect to see a clear marker of the switch in the estimates in the form of a sudden large jump.

    I do believe it is likely there has been a relatively small upward trend in global temperature since 1850 (not much different than many similar recent Holocene increases), but considering the large uncertainties, especially in the older estimates, the exact amount of the upward trend is indeed quite “fuzzy”.

  9. Oz

    Your own Figure 3 In your recent “Satellite Era Global Temperature Anomaly Comparisons” is an excellent depiction of the problems with CFS in the 2010/11 timeframe. When you describe the Figure you state “the GHCN NCEI estimates have suddenly departed substantially higher than the GFS UM CCI estimates by a fairly constant offset near 0.2C”. Of course looking from a different perspective one can also say – the GFS UM CCI series has suddenly departed substantially lower from the GHCN NCEI estimates by a constant offset of 0.2. You will find that CFS has a similar departure when compared to other surface temperature and re-analysis datasets in the same time period. It would be uncanny if the NOAA scientists and the scientists working on the other datasets focused all of their “confirmation bias” into the short period of time when CFS was changing to CFSv2.

    PS – don’t take any chart from Ole Humlum at face value
    .

  10. OK Chubbs. I won’t take this one at face value.

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