Guest Post by Werner Brozek, Comment Included From David Hoffer, Edited by Just The Facts:
In the above graphic, the green line is the slope since May 1993 without consideration of error bars. When including error bars, the range could be as low as zero as indicated by the blue line. It could also be an equal amount above the green line as indicated by the purple line.
The numbers that were used to generate the above graphic are from Nick Stokes’ Temperature Trend Viewer site.
For RSS, the numbers are as follows:
Temperature Anomaly trend
May 1993 to Feb 2016
CI from -0.022 to 1.764;
Temp range 0.118°C to 0.316°C
So in other words, for 22 years and 10 months, since May 1993, there is a very small chance that the slope is negative.
For UAH6.0beta5, the numbers are as follows:
Temperature Anomaly trend
Jan 1993 to Feb 2016
CI from -0.009 to 1.830;
Temp range -0.001°C to 0.210°C
So in other words, for 23 years and 2 months, since January 1993, there is a very small chance that the slope is negative.
As mentioned in my January post, there is now no period of time going back from February 2016 where the slope is negative for any period worth mentioning on any of the five data sets I am analyzing.
As a result, my former Section 1 will not be shown for the foreseeable future.
My last post had an excellent comment by David Hoffer that I would like to share to give it wider exposure and for you to give your thoughts:
March 2, 2016 at 10:11 am
1. The “Pause” hasn’t disappeared. It now just has a beginning and an end. But it is right there in the data where it always was, and it doesn’t cease to exist merely because we can’t calculate one starting from the present and working backwards.
2. The “Pause” was never significant in terms of showing the CO2 doesn’t heat up the earth. It only became significant because the warmist community (Jones, Santer, etc) said that natural variability was too small to cancel the warming of CO2 for more than a period of 10 years…er 15…er 17 and made a big deal out of it.
So regardless of the “Pause” having ended or not, what we have is conclusive evidence that the models either:
a) grossly under estimated natural variability or
b) grossly over estimated CO2 sensitivity or
In all three scenarios above, natural variability dominates in terms of any risk associated with a changing global temperature. That’s what we should be studying first and foremost. Once we understand it, then we can determine how much CO2 changes natural variability. Trying to determine CO2 sensitivity without first understanding the natural variability baseline that it runs on top of is a fool’s errand. Unfortunately, fools seem determined and well funded, and so they continue to try and do just that.
The world has been warming for 400 years, almost all of it due to natural variability. It will continue to warm (I expect) and most of the warming will be due to natural variability, which we just learned from this last 20 years of data is a lot bigger deal than CO2.
(End of David’s post)
In the sections below, we will present you with the latest facts. The information will be presented in two sections and an appendix. The first section will show for how long there has been no statistically significant warming on several data sets. The second section will show how 2016 so far compares with 2015 and the warmest years and months on record so far. For three of the data sets, 2015 also happens to be the warmest year. The appendix will illustrate sections 1 and 2 in a different way. Graphs and a table will be used to illustrate the data.
For this analysis, data was retrieved from Nick Stokes’ Trendviewer available on his website. This analysis indicates for how long there has not been statistically significant warming according to Nick’s criteria. Data go to their latest update for each set. In every case, note that the lower error bar is negative so a slope of 0 cannot be ruled out from the month indicated.
On several different data sets, there has been no statistically significant warming for between 11 and 23 years according to Nick’s criteria. Cl stands for the confidence limits at the 95% level.
The details for several sets are below.
For UAH6.0: Since January 1993: Cl from -0.009 to 1.830
This is 23 years and 2 months.
For RSS: Since May 1993: Cl from -0.022 to 1.764
This is 22 years and 10 months.
For Hadcrut4.4: Since October 2001: Cl from -0.016 to 1.812 (Goes to January)
This is 14 years and 4 months.
For Hadsst3: Since May 1996: Cl from -0.002 to 2.089
This is 19 years and 10 months.
For GISS: Since March 2005: Cl from -0.004 to 3.688
This is exactly 11 years.
This section shows data about 2016 and other information in the form of a table. The table shows the five data sources along the top and other places so they should be visible at all times. The sources are UAH, RSS, Hadcrut4, Hadsst3, and GISS.
Down the column, are the following:
1. 15ra: This is the final ranking for 2015 on each data set.
2. 15a: Here I give the average anomaly for 2015.
3. year: This indicates the warmest year on record so far for that particular data set. Note that the satellite data sets have 1998 as the warmest year and the others have 2015 as the warmest year.
4. ano: This is the average of the monthly anomalies of the warmest year just above.
5. mon: This is the month where that particular data set showed the highest anomaly. The months are identified by the first three letters of the month and the last two numbers of the year. The 2016 records are not included here.
6. ano: This is the anomaly of the month just above.
7. sig: This the first month for which warming is not statistically significant according to Nick’s criteria. The first three letters of the month are followed by the last two numbers of the year.
8. sy/m: This is the years and months for row 7.
9. Jan: This is the January 2016 anomaly for that particular data set.
10. Feb: This is the February 2016 anomaly for that particular data set.
11. ave: This is the average anomaly of all months to date taken by adding all numbers and dividing by the number of months.
12. rnk: This is the rank that each particular data set would have for 2016 without regards to error bars and assuming no changes. Think of it as an update 10 minutes into a game.
If you wish to verify all of the latest anomalies, go to the following:
For UAH, version 6.0beta5 was used. Note that WFT uses version 5.6. So to verify the length of the pause on version 6.0, you need to use Nick’s program.
For Hadsst3, see: http://www.cru.uea.ac.uk/cru/data/temperature/HadSST3-gl.dat
For GISS, see:
To see all points since January 2015 in the form of a graph, see the WFT graph below. Note that UAH version 5.6 is shown. WFT does not show version 6.0 yet. Also note that Hadcrut4.3 is shown and not Hadcrut4.4, which is why many months are missing for Hadcrut.
As you can see, all lines have been offset so they all start at the same place in January 2015. This makes it easy to compare January 2015 with the latest anomaly.
In this part, we are summarizing data for each set separately.
For UAH: There is no statistically significant warming since January 1993: Cl from -0.009 to 1.830. (This is using version 6.0 according to Nick’s program.)
The UAH average anomaly so far for 2016 is 0.688. This would set a record if it stayed this way. 1998 was the warmest at 0.484. The highest ever monthly anomaly was in April of 1998 when it reached 0.743. This is prior to 2016. The average anomaly in 2015 was 0.263 and it was ranked 3rd.
For RSS: There is no statistically significant warming since May 1993: Cl from -0.022 to 1.764.
The RSS average anomaly so far for 2016 is 0.819. This would set a record if it stayed this way. 1998 was the warmest at 0.550. The highest ever monthly anomaly was in April of 1998 when it reached 0.857. This is prior to 2016. The average anomaly in 2015 was 0.358 and it was ranked 3rd.
For Hadcrut4: There is no statistically significant warming since October 2001: Cl from -0.016 to 1.812. (Goes to January)
The Hadcrut4 average anomaly so far is 0.978. This would set a record if it stayed this way. The highest ever monthly anomaly was in December of 2015 when it reached 1.009. This is prior to 2016. The average anomaly in 2015 was 0.745 and this set a new record.
For Hadsst3: There is no statistically significant warming since May 1996: Cl from -0.002 to 2.089.
The Hadsst3 average anomaly so far for 2016 is 0.668. This would set a record if it stayed this way. The highest ever monthly anomaly was in September of 2015 when it reached 0.725. This is prior to 2016. The average anomaly in 2015 was 0.592 and this set a new record.
For GISS: There is no statistically significant warming since March 2005: Cl from -0.004 to 3.688.
The GISS average anomaly so far for 2016 is 1.25. This would set a record if it stayed this way. The highest ever monthly anomaly was in December of 2015 when it reached 1.10. This is prior to 2016. The average anomaly in 2015 was 0.86 and it set a new record.
Warming does not become catastrophic just because we cannot go back from February 2016 and find a negative slope. This is especially true since it was a very strong El Nino and not CO2 that was mainly responsible for the negative slope disappearing for now.