Guest Post By Werner Brozek, Edited By Just The Facts
It may appear as if there is a typo in the title, however some of you will know exactly what I am talking about. What we are given in various data sets are anomalies. So depending on the base period, new values for a given year or month are compared to values for 30 or more years in the past.
So let us suppose we have the noon temperature for July 15 for 30 consecutive years. We take the average. Then for the next year, we take the temperature, and if it is warmer than the average, the anomaly is positive and if it is colder than the average, the anomaly is negative. One definition of anomaly is “deviation from the normal”. However that is not our definition here. After all, what is normal? Is the average from 1901 to 1930 normal; or from 1981 to 2010; or from 1901 to 2000? Perhaps none of these are normal. Unlike a body temperature of 37.0 C that is considered normal, we do not have a temperature of Earth that is “normal”. Perhaps “normal” is 2 C warmer than it is today and we are below “normal” now.
As you can see from the graphic above, Earth’s temperature varies by 3.8 C throughout the year. On the average, July is 3.8 C warmer than January. This is despite the fact that Earth is closest to the sun in January and furthest in July. There have been many average temperatures quoted for Earth. Most are between 14.0 C to 15.0 C. One thing that I find troublesome is that anyone can come up with an anomaly if they do not know the temperature. If you use a thermometer, it will give you a temperature. It will not give an anomaly.
Then there is the argument about how meaningless an average temperature is. In addition, it takes much more energy to change a moist 39 C to 40 C than a dry -40 C to -39 C. So a change in anomaly must be taken with a grain of salt. Much can be discussed here, however I want to focus on the title and the graphic. As can be seen, the anomaly for GISS for July 1912 was -0.47. When combined with the graphic above, assuming it is true for the moment, the real average temperature for July 1912 was 15.8 – 0.47 = 15.3 rounded to a single decimal. On the other hand, the real average temperature for January 2007 was 12.0 + 0.94 = 12.9 rounded to a single decimal. Generally speaking, one can say that the coldest July since the start of the Hadcrut4 record in 1850 was several degrees warmer than the warmest January in the 2000s.
When we hear that the last several hundred months were all warmer than the average for the 1900 hundreds, that is only true when considering anomalies. However it is not true when talking about absolute temperatures. During the year, some places on Earth can vary by 60 C or more. During the day, some places on Earth can vary by 20 C or more. And it is even possible for a place in the far north to have a warm January temperature beat a cold July temperature. However that will not happen globally. With natural global swings of 3.8 C every year, and with higher daily and yearly swings, it is hard to imagine that an increase of 2 C over 100 years, even if it occurred, would be catastrophic.
In the sections below, 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 several data sets.
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 2014 to date compares with 2013 and the warmest years and months on record so far.
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. 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.
On all data sets below, the different times for a slope that is at least very slightly negative ranges from 9 years and 5 months to 17 years and 6 months.
1. For GISS, the slope is flat since July 2001 or 12 years, 8 months. (goes to February)
2. For Hadcrut3, the slope is flat since June 1997 or 16 years, 9 months. (goes to February)
4. For Hadcrut4, the slope is flat since December 2000 or 13 years, 3 months. (goes to February)
5. For Hadsst3, the slope is flat since November 2000 or 13 years, 4 months. (goes to February)
6. For UAH, the slope is flat since October 2004 or 9 years, 5 months. (goes to February using version 5.5)
7. For RSS, the slope is flat since September 1996 or 17 years, 6 months (goes to February). So RSS has passed Ben Santer’s 17 years.
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 sloped wiggly line shows how CO2 has increased over this period.
When two things are plotted as I have done, the left only shows a temperature anomaly.
The actual numbers are meaningless since all slopes are essentially zero and the position of each line is merely a reflection of the base period from which anomalies are taken for each set. 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 17 years, the temperatures have been flat for varying periods on various data sets.
The next graph shows the above, but this time, the actual plotted points are shown along with the slope lines and the CO2 is omitted.
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 16 and 21 years.
The details for several sets are below.
For UAH: Since February 1996: CI from -0.041 to 2.392
For RSS: Since November 1992: CI from -0.022 to 1.900
For Hadcrut4: Since October 1996: CI from -0.027 to 1.234
For Hadsst3: Since January 1993: CI from -0.016 to 1.812
For GISS: Since June 1997: CI from -0.016 to 1.258
This section shows data about 2014 and other information in the form of a table. The table shows the six data sources along the top and other places so they should be visible at all times. The sources are UAH, RSS, Hadcrut4, Hadcrut3, Hadsst3 and GISS.
Down the column, are the following:
1. 13ra: This is the final ranking for 2013 on each data set.
2. 13a: Here I give the average anomaly for 2013.
3. year: This indicates the warmest year on record so far for that particular data set. Note that two of the data sets have 2010 as the warmest year and four have 1998 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.
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 is followed by the last two numbers of the year.
9. Jan: This is the January 2014 anomaly for that particular data set.
10.Feb: This is the February 2014 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. However if the data set itself gives that average, I may use their number. Sometimes the number in the third decimal place differs slightly, presumably due to all months not having the same number of days.
12. rnk: This is the rank that each particular data set would have if the anomaly above were to remain that way for the rest of the year. It will not, but think of it as an update 10 minutes into a game. Due to different base periods, the rank is more meaningful than the average anomaly.
If you wish to verify all of the latest anomalies, go to the following:
For UAH, version 5.5 was used since that is what WFT used, see: http://vortex.nsstc.uah.edu/public/msu/t2lt/tltglhmam_5.5.txt
For Hadcrut3, see: http://www.cru.uea.ac.uk/cru/data/temperature/HadCRUT3-gl.dat
For Hadsst3, see: http://www.cru.uea.ac.uk/cru/data/temperature/HadSST3-gl.dat
To see all points since January 2013 in the form of a graph, see the WFT graph below.
As you can see, all lines have been offset so they all start at the same place in January. This makes it easy to compare last January 2013 with the latest anomaly.
In this part, we are summarizing data for each set separately.
The slope is flat since September 1996 or 17 years, 6 months. (goes to February) So RSS has passed Ben Santer’s 17 years.
For RSS: There is no statistically significant warming since November 1992: CI from -0.022 to 1.900.
The RSS average anomaly so far for 2014 is 0.212. This would rank it as 11th place if it stayed this way. 1998 was the warmest at 0.55.
The highest ever monthly anomaly was in April of 1998 when it reached 0.857.
The anomaly in 2013 was 0.218 and it is ranked 10th.
The slope is flat since October 2004 or 9 years, 5 months. (goes to February using version 5.5)
For UAH: There is no statistically significant warming since February 1996: CI from -0.041 to 2.392.
The UAH average anomaly so far for 2014 is 0.182. This would rank it as 10th place if it stayed this way. 1998 was the warmest at 0.419.
The highest ever monthly anomaly was in April of 1998 when it reached 0.662.
The anomaly in 2013 was 0.197 and it is ranked 7th.
The slope is flat since December 2000 or 13 years, 3 months. (goes to February)
For HadCRUT4: There is no statistically significant warming since October 1996: CI from -0.027 to 1.234.
The HadCRUT4 average anomaly so far for 2014 is 0.403. This would rank it as 14th place if it stayed this way. 2010 was the warmest at 0.547.
The highest ever monthly anomaly was in January of 2007 when it reached 0.829. The anomaly in 2013 was 0.486 and it is ranked 8th.
The slope is flat since June 1997 or 16 years, 9 months. (goes to February)
The HadCRUT3 average anomaly so far for 2014 is 0.367. This would rank it as 13th place if it stayed this way. 1998 was the warmest at 0.548.
The highest ever monthly anomaly was in February of 1998 when it reached 0.756. One has to go back to the 1940s to find the previous time that a Hadcrut3 record was not beaten in 10 years or less. The anomaly in 2013 was 0.459 and it is ranked 6th.
The slope is flat since November 2000 or 13 years and 4 months. (goes to February).
For HadSST3: There is no statistically significant warming since January 1993: CI from -0.016 to 1.812.
The HadSST3 average anomaly so far for 2014 is 0.325. This would rank it as 12th place if it stayed this way. 1998 was the warmest at 0.416.
The highest ever monthly anomaly was in July of 1998 when it reached 0.526. The anomaly in 2013 was 0.376 and it is ranked 6th.
The slope is flat since July 2001 or 12 years, 8 months. (goes to February)
For GISS: There is no statistically significant warming since June 1997: CI from -0.016 to 1.258.
The GISS average anomaly so far for 2014 is 0.575. This would rank it as 11th place if it stayed this way. 2010 was the warmest at 0.67.
The highest ever monthly anomaly was in January of 2007 when it reached 0.94. The anomaly in 2013 was 0.60 and it is ranked 6th.
Anomalies only give the departure from an average. The base period for this average varies from one data set to the next. So if the base period was cooler, the newer anomalies will be positive and will have a larger magnitude. All anomalies since 1850 are rather small compared with the absolute temperature change for the earth during the year.
A positive anomaly does NOT mean the earth has a fever. It just means it is warmer than a long term average.