Guest Post by Werner Brozek, Excerpted From Nick Stokes, Edited by Just The Facts:
Image Credit: Nick Stokes
Before beginning the discussion, I just want to comment on the authors. It is said that you are entitled to your interpretation, but not to your facts. Werner Brozek and Nick Stokes are presenting you with just the facts. You cannot argue with the facts. However you may attach completely different significances to those same facts. Please let us know what significance you attach to the facts. I will reserve the right to include selected replies as part of the introduction to my next post.
The top diagram shows the monthly changes to RSS during the last large El Nino in 1997 and 1998. As well, it shows where 2016 is starting from, which is much higher than where 1998 started from. If similar changes occur in 2016 as in 1998, the present pause of over 18 years on the satellite data sets will soon be gone.
The following table gives some information to compare 1997/1998 with 2015/2016 on the five data sets I have been tracking. In addition, there are two different average values where the average of the five differences is given. As well, four monthly ENSO values are given.
Row 1 gives the 1997 average anomaly for each of the five data sets. (Please see section 3 for all URLs.)
Row 2 gives the 1998 average anomaly for each of the five data sets.
Row 3 gives the difference between these anomalies for each data set along with the average of these five numbers.
Row 4 gives the December 1997 anomaly for each of the five data sets along with the ENSO value for that month.
Row 5 gives the January 1998 anomaly for each of the five data sets along with the ENSO value for that month.
Row 6 gives the February 1998 anomaly for each of the five data sets along with the ENSO value for that month.
Row 7 gives the difference between the December 1997 and February 1998 anomalies for each data set along with the average of these five numbers. Note the difference between December and January for the satellites versus the others. However by February 1998, all had made significant jumps from December 1997 except for Hadsst3.
Row 8 gives the 2015 average anomaly for each of the five data sets.
Row 9 gives the December 2015 anomaly for each of the five data sets along with the ENSO value for that month.
Row 10 gives the January 2016 anomaly for each of the five data sets.
Row 11 has all February anomalies in ( ). These numbers were obtained by adding the December 2015 anomalies (row 9) to the difference between the December 1997 and February 1998 anomaly (row 7). It will be interesting to compare these values to what will actually happen in February.
ENSO values were taken from here. It should be noted that with an error margin of 0.3 C, the ENSO values from May 1997 to December were the same as those from May 2015 to December.
Nick Stokes’ post from a month ago is well worth reading. I will excerpt the following from that post and then comment on the implications now that we have the January data. It applies to RSS:
“If the January anomaly exceeds about 1.3°C, the Pause is gone. This is unlikely.
If the Jan and Feb anomalies exceed on average about 0.77°C, the curve will be above the axis. For reference, the Dec anomaly was 0.543°C. I think this is quite likely.
If the first three months exceed 0.59°C on average, that would suffice to extinguish the pause. That is barely above the December value, and I think very likely indeed.
If Jan-April exceed 0.5°C, that will also suffice.”
The January anomaly was 0.66 C for RSS. So to reach an average of 0.77 C for January and February, the February anomaly needs to be 0.88 C. So if the February anomaly is under 0.88 C, the pause of over 18 years will still remain for at least another month. How likely is a jump of 0.22 C? The jump from January 1998 to February 1998 was 0.186. The jump from March 1998 to April 1998 was 0.272. So a jump of 0.22 cannot be ruled out. As well, the projection in the above table gives a value of 0.977, so the pause can certainly end in February.
What happens if the February anomaly is under 0.88? According to Nick’s numbers above, the average for the first three months needs to be 0.59 to extinguish the pause. In other words, J + F + M = 0.59(3). Since January was 0.66, the equation reduces to
March = 1.11 – February. This sets the maximum value that the March anomaly can be to keep the pause intact should the RSS pause not end in February. Therefore the RSS anomalies do not even have to increase over the next two months from January in order for the pause to disappear with the March anomaly.
Suppose February comes in at 0.882? If you are curious whether this is enough to kill the pause, go to Nick’s site here, click RSS, then using the blue >, move the blue ball to February 2016. If you see numbers and not “Some data not yet available”, it has been updated. Then use the red > to move the red ball to the earliest date where you know the pause started in January which would be June 1997. If the rate is negative, the pause still exists from June. If the rate is positive, advance a month at a time and see if the rate becomes negative over the next several months. Should the rate not become negative soon, you may wish to try from 2001.
If you want the latest slopes and times of no statistically significant warming for other data sets such as UAH6.0beta5, NOAA, BEST, etc, Nick Stokes’ site is excellent! This is in contrast to WFT that has not updated BEST since 2010 and which still uses UAH5.6 and which has not updated Hadcrut4 since May, 2015.
What about UAH6.0beta5? When the January number for 2016 came in and applied to UAH6.0beta4, it looked like the pause was over. However changes to other earlier values allowed the pause to hang on from October 1997. But unless there is a huge drop in the February anomaly to 0.315 or lower, the UAH pause will be over. Based on the projection in the table above, it will not even be close.
A rather interesting coincidence on all five data sets is that the January 1998 anomaly (row 5) was close to or equal to the 1998 average (row 2). Should this also be the case for 2016, then 2016 would set a new record on all five data sets.
Another interesting coincidence is that the average difference between 1997 and 1998 anomalies (row 3) for the five data sets is very close to the average difference between the December 1997 anomalies and the February 1998 anomalies (row 7).
All January anomalies on all five data sets are record highs for the month of January. In addition, for GISS and HadSST3, the January anomalies are the highest ever compared to any month in the past.
(P.S. Typing the letters “Stokes” puts your comment into moderation.)
In the sections below, as in previous posts, we will present you with the latest facts. The information will be presented in three sections and an appendix. The first section will show for how long there has been no warming on some data sets. At the moment, only the satellite data have flat periods of longer than a year. The second section will show for how long there has been no statistically significant warming on several data sets. The third section will show how January 2016 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.
This analysis uses the latest month for which data is available on WoodForTrees.com (WFT). All of the data on WFT is also available at the specific sources as outlined below. We start with the present date and go to the furthest month in the past where the slope is a least slightly negative on at least one calculation. So if the slope from September is 4 x 10^-4 but it is – 4 x 10^-4 from October, we give the time from October so no one can accuse us of being less than honest if we say the slope is flat from a certain month.
1. For GISS, the slope is not flat for any period that is worth mentioning.
2. For Hadcrut4, the slope is not flat for any period that is worth mentioning.
3. For Hadsst3, the slope is not flat for any period that is worth mentioning.
4. For UAH, the slope is flat since October 1997 or 18 years and 4 months. (goes to January using version 6.0beta5)
5. For RSS, the slope is flat since June 1997 or 18 years and 8 months. (goes to January)
The next graph shows just the lines to illustrate the above. Think of it as a sideways bar graph where the lengths of the lines indicate the relative times where the slope is 0. In addition, the upward sloping blue line at the top indicates that CO2 has steadily increased over this period.
Note that the UAH5.6 from WFT needed a detrend to show the slope is zero for UAH6.0.
When two things are plotted as I have done, the left only shows a temperature anomaly.
The actual numbers are meaningless since the two slopes are essentially zero. No numbers are given for CO2. Some have asked that the log of the concentration of CO2 be plotted. However WFT does not give this option. The upward sloping CO2 line only shows that while CO2 has been going up over the last 18 years, the temperatures have been flat for varying periods on the two sets.
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 1 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 February 1993: Cl from -0.031 to 1.685
This is exactly 23 years.
For RSS: Since May 1993: Cl from -0.012 to 1.625
This is 22 years and 9 months.
For Hadcrut4.4: Since October 2001: Cl from -0.016 to 1.812
This is 14 years and 4 months.
For Hadsst3: Since January 1996: Cl from -0.013 to 2.142
This is 20 years and 1 month.
For GISS: There is no statistically significant warming for any period worth mentioning.
This section shows data about 2015 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.
6. ano: This is the anomaly of the month just above.
7. y/m: This is the longest period of time where the slope is not positive given in years/months. So 16/2 means that for 16 years and 2 months the slope is essentially 0. Periods of under a year are not counted and are shown as “0”.
8. 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.
9. sy/m: This is the years and months for row 8.
10. Jan: This is the January 2016 anomaly for that particular data set.
11. rnk: This is the rank that each particular data set would have if the January anomaly was also the average anomaly at the end of the year.
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.
The slope is flat since October 1997 or 18 years and 4 months. (goes to January using version 6.0beta5)
For UAH: There is no statistically significant warming since February 1993: Cl from -0.031 to 1.685. (This is using version 6.0 according to Nick’s program.)
The UAH anomaly for January is 0.543. 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 0.742. The average anomaly in 2015 was 0.264 and it was ranked 3rd.
The slope is flat since June 1997 or 18 years and 8 months. (goes to January)
For RSS: There is no statistically significant warming since May 1993: Cl from -0.012 to 1.625.
The RSS anomaly for January is 0.663. 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. The average anomaly in 2015 was 0.358 and it was ranked 3rd.
The slope is not flat for any period that is worth mentioning.
For Hadcrut4: There is no statistically significant warming since October 2001: Cl from -0.016 to 1.812.
The Hadcrut4 anomaly for January is 0.894. This would set a record if it stayed this way. The highest ever monthly anomaly was in December of 2015 when it reached 1.005. The average anomaly in 2015 was 0.745 and this set a new record.
For Hadsst3, the slope is not flat for any period that is worth mentioning. For Hadsst3: There is no statistically significant warming since January 1996: Cl from -0.013 to 2.142.
The Hadsst3 anomaly for January is 0.728. 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.
The slope is not flat for any period that is worth mentioning.
For GISS: There is no statistically significant warming for any period worth mentioning.
The GISS anomaly for January is 1.13. This would set a record if it stayed this way. The highest ever monthly anomaly was in December of 2015 when it reached 1.11. This is prior to 2016. The average anomaly in 2015 was 0.86 and it set a new record.
Using the definition of the longest time with a negative slope, the pauses on all data sets have either ended or will end soon. What significance should be attached to this fact? Should it be considered as just an El Nino blip that is best ignored or should a huge amount of importance be attached to this fact?