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Guest Post By Walter Dnes

In continuation of my Temperature Anomaly projections, the following are my June projections, as well as last month’s projections for May, to see how well they fared.

Data Set Projected Actual Delta
HadCRUT4 2017/05 +0.770 +0.665 -0.105
HadCRUT4 2017/06 +0.583
GISS 2017/05 +0.93 +0.88 -0.05
GISS 2017/06 +0.81
UAHv6 2017/05 +0.264 +0.453 +0.189
UAHv6 2017/06 +0.384
RSS v3.3 2017/05 +0.402 +0.482 +0.080
RSS v3.3 2017/06 +0.486
RSS v4.0 2017/05 +0.497 +0.608 +0.111
RSS v4.0 2017/06 +0.539
NCEI 2017/05 +0.92 +0.83 -0.09
NCEI 2017/06 +0.76

The Data Sources

The latest data can be obtained from the following sources

The Latest 12 Months

The latest 12-month running mean (pseudo-year “9999”, highlighted in blue in the tables below) ranks anywhere from 2nd to 4th, depending on the data set. The June 2017 NCEP/NCAR anomaly is 0.10 to 0.12 lower than for June 2016 (global and satellite data sets). This implies that the June 2017 anomalies will be lower than the corresponding 2016 values, further cementing the decline of the 12-month running mean. This will make it even harder for 2017 to beat 2016 as the warmest year ever. June marks the 9th consecutive month with NCEP/NCAR global and satellite anomalies lower than 12 months ago.

The following table ranks the top 10 warmest years for earch surface data set, as well as a pseudo “year 9999” consisting of the latest available 12-month running mean of anomaly data, i.e. June 2016 to May 2017.

HadCRUT4 GISS NCEI
Year Anomaly Year Anomaly Year Anomaly
2016 +0.775 2016 +0.985 2016 +0.944
2015 +0.761 9999 +0.907 2015 +0.903
9999 +0.708 2015 +0.868 9999 +0.873
2014 +0.576 2014 +0.749 2014 +0.743
2010 +0.558 2010 +0.713 2010 +0.703
2005 +0.545 2005 +0.688 2013 +0.671
1998 +0.537 2007 +0.658 2005 +0.659
2013 +0.513 2013 +0.657 2009 +0.638
2003 +0.509 2009 +0.643 1998 +0.637
2009 +0.506 2012 +0.634 2012 +0.624
2006 +0.505 1998 +0.634 2006 +0.615

Similarly, for the satellite data sets…

UAH RSS v3.3 RSS v4.0
Year Anomaly Year Anomaly Year Anomaly
2016 +0.503 2016 +0.574 2016 +0.779
1998 +0.484 1998 +0.550 9999 +0.629
9999 +0.353 2010 +0.474 1998 +0.611
2010 +0.333 9999 +0.423 2010 +0.556
2015 +0.258 2015 +0.383 2015 +0.514
2002 +0.217 2005 +0.336 2002 +0.422
2005 +0.199 2003 +0.320 2014 +0.412
2003 +0.186 2002 +0.315 2005 +0.401
2014 +0.177 2014 +0.273 2013 +0.396
2007 +0.160 2007 +0.253 2003 +0.385
2013 +0.130 2001 +0.247 2007 +0.334

January-through-May of 2017 were all cooler, in all data sets, than the corresponding months in 2016. Therefore, June-through-December 2017 would have to be warmer than the corresponding months in 2016 to beat the 2016 annual values and make 2017 “the warmest year ever”. Here are the numbers…

  • HadCRUT4 2016 Jun-Dec was +0.664; 2017 needs to be +0.778
  • GISS 2016 Jun-Dec was +0.860; 2017 needs to be +0.995
  • UAH 2016 Jun-Dec was +0.384; 2017 needs to be +0.641
  • RSS 3.3 2016 Jun-Dec was +0.430; 2017 needs to be +0.688
  • RSS 4.0 2016 Jun-Dec was +0.674; 2017 needs to be +0.932
  • NCEI 2016 Jun-Dec was +0.837; 2017 needs to be +0.960

The Graphs

The graph immediately below is a plot of recent NCEP/NCAR daily anomalies, versus 1994-2013 base, similar to Nick Stokes’ web page. The second graph is a monthly version, going back to 1997. The trendlines are as follows…

  • Black – The longest line with a negative slope in the daily graph goes back to late May, 2015, as noted in the graph legend. On the monthly graph, it’s June 2015. This is slowly growing ever longer but nothing notable yet. Reaching back to 2005 or earlier would be a good start.
  • Green – This is the trendline from a local minimum in the slope around late 2004, early 2005. To even BEGIN to work on a “pause back to 2005”, the anomaly has to drop below the green line.
  • Pink – This is the trendline from a local minimum in the slope from mid-2001. Again, the anomaly needs to drop below this line to start working back to a pause to that date.
  • Red – The trendline back to a local minimum in the slope from late 1997. Again, the anomaly needs to drop below this line to start working back to a pause to that date.

NCEP/NCAR Daily Anomalies:

NCEP/NCAR Monthly Anomalies:

Miscellaneous Notes
At the time of posting, the 6 monthly data sets were available through May 2017. The NCEP/NCAR re-analysis data runs 2 days behind real-time. Therefore, real daily data from May 31st through June 28th is used, and June the 29th is assumed to have the same anomaly as the 28th. For RSS and UAH, subsets of global NCEP/NCAR data are used, to match the latitude coverage provided by the satellites.

In search of better results, I’ve tweaked the data set projection algorithm again. The monthly anomaly difference (current month minus previous month) in the corresponding NCEP/NCAR subset anomalies is multiplied by 0.5 and added to the previous month’s anomaly for that data set. This applies to all 6 data sets.

via Watts Up With That? http://ift.tt/1Viafi3

June 30, 2017 at 05:32PM

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