Guest Post by Werner Brozek, Edited by Just The Facts:
The comment referred to in the title is the following by Kevin Trenberth regarding heat in the deep oceans:
“The centre of action is the Pacific Ocean but the main places where heat goes deep into the ocean are the Atlantic and Southern Oceans rather than the Pacific,”
The following equation demonstrates how the temperature change of an object relates to the number of joules applied to the object versus the mass and specific heat capacity of the object. The equation is H = mcdt where H is the energy in joules; m is the mass in kilograms; c is the specific heat capacity in joules/(kilogram x C); and dt is the change in temperature in C.
Assume we have a 4.0 kilogram shot put made of iron and a 4.0 gram marble made of the same iron, illustrated by the image above. Now let us assume we apply the same quantity of heat to each. In this case, H will be the same and c will also be the same. The same amount of heat that will raise the temperature of the 4.0 kilogram shot put by 1.0 C, while it will raise the temperature of the 4.0 gram marble by 1000 C.
What would happen in a closed system if just the shot put was raised by 1.0 C and it then touched the marble? Answer: The marble would go up in temperature by 1.0 C and the affect on the shot put would not be measurable.
What would happen in a closed system if just the marble was raised by 1000 C and it then touched the shot put, once equilibrium was reached? Answer: The shot put would go up in temperature by 1.0 C and the marble would go down by 999 C ignoring significant digits for now.
Now we will apply the above equation to Earth’s air. The total mean mass of the atmosphere is 5.1 x 10^18 kg. We will assume the specific heat capacity of air is 1000 J/(kg C). Now, we will calculate how much heat it would take to raise the temperature of the air by 1.0 C. H = mcdt = 5.1 x 10^18 kg x 1000 J/(kg C) x 1.0 C = 5.1 x 10^21 J.
Now we will apply the above equation to Earth’s oceans. The total mean mass of the oceans is 1.4 x 10^21 kg. We will assume the specific heat capacity of the oceans is 4000 J/(kg C). Now, we will calculate how much heat it would take to raise the temperature of the oceans by 1.0 C. H = mcdt = 1.4 x 10^21 kg x 4000 J/(kg C) x 1.0 C = 5.6 x 10^24 J.
Keeping the ratios simple, we see it takes about 1000 times as much energy to raise the temperature of the oceans by 1.0 C than to raise the temperature of the air by 1.0 C.
What would happen to Earth’s air temperature if we warmed Earth’s oceans 1.0 C? Answer: The air temperature could stay the same (See next paragraph.) or it could go up by 1.0 C at the most.
At the present time, the deep oceans are at about 3 C. Let us just for discussion sake assume it warmed by 0.1 C in 60 years. And let us further assume the average air temperature is 14 C. That would mean the deep oceans need to warm by about 10 C before they start affecting the air temperature. At the rate of 0.1 C in 60 years, it would take 6000 years for the oceans to warm by 10 C.
And what would happen if we were to raise the temperature of Earth’s atmosphere by 10.0 C? Answer: The oceans would act as a huge heat sink and would warm by 0.010 C once equilibrium was reached. Of course, this may takes decades or centuries. However the greater the difference in temperature, the faster the hotter object loses heat.
I am fully aware of the fact that I am making many assumptions here. For example, I am assuming the average human emissions of CO2 over the next 6000 years will the same as for the last 60 years. As a result, rising temperatures in the oceans could accelerate if it were not for the logarithmic affect of additional CO2. This also assumes that there will be enough fossil fuels to last that long.
But regardless of any other unstated assumptions you may find fault with which could push things in either direction, I believe it is clear that my grandchildren (two so far) and the grandchildren of James Hansen will not be negatively affected by heat going into the deep oceans:
“The title of the book, Storms of My Grandchildren, refers to the ferocious and stormy weather events that will occur next generation if fossil fuel use continues in the way it has.”
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 of 2015 compares with 2014 and the warmest years and months on record so far. For three of the data sets, 2014 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. Note that WFT has not updated Hadcrut4 since July and it is only Hadcrut4.2 that is shown.
3. For Hadsst3, the slope is not flat for any period that is worth mentioning.
4. For UAH, the slope is flat since February 2009 or an even 6 years. (goes to January using version 5.6 and based on Walter Dnes’ calculation.)
5. For RSS, the slope is flat since December 1996 or 18 years, 2 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.
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 14 and 22 years according to Nick’s criteria. Cl stands for the confidence limits at the 95% level.
Dr. Ross McKitrick has also commented on these parts and has slightly different numbers for the three data sets that he analyzed. I will also give his times.
The details for several sets are below.
For UAH: Since July 1996: CI from -0.019 to 2.225
(Dr. McKitrick says the warming is not significant for 16 years on UAH.)
For RSS: Since December 1992: CI from -0.000 to 1.753
(Dr. McKitrick says the warming is not significant for 26 years on RSS.)
For Hadcrut4.3: Since June 1997: CI from -0.015 to 1.132
(Dr. McKitrick said the warming was not significant for 19 years on Hadcrut4.2 going to April. Hadcrut4.3 would be slightly shorter however I do not know what difference it would make to the nearest year.)
For Hadsst3: Since April 1995: CI from -0.006 to 1.710
For GISS: Since August 2000: CI from -0.007 to 1.412
Note that all of the above times, regardless of the source, with the exception of GISS are larger than 15 years which NOAA deemed necessary to “create a discrepancy with the expected present-day warming rate”.
This section shows data about January 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. 14ra: This is the final ranking for 2014 on each data set.
2. 14a: Here I give the average anomaly for 2014.
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 2014 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. Depending on when the update was last done, the months may be off by one month.
10. McK: These are Dr. Ross McKitrick’s number of years for three of the data sets.
11. Jan: This is the January 2015 anomaly for that particular data set.
12. rnk: This is the rank that each particular data set would have for 2015 without regards to error bars and assuming no changes. Think of it as an update 5 minutes into a game.
If you wish to verify all of the latest anomalies, go to the following:
For UAH, version 5.6 was used. Note that WFT uses version 5.5 however this version was last updated for December 2014 and it looks like it will no longer be given.
For Hadsst3, see: http://www.cru.uea.ac.uk/cru/data/temperature/HadSST3-gl.dat
For GISS, see:
To see all points since January 2014 in the form of a graph, see the WFT graph below. Note that Hadcrut4 is the old version that has been discontinued. WFT does not show Hadcrut4.3 yet. As well, only UAH version 5.5 is shown which stopped in December. WFT does not show version 5.6 yet.
As you can see, all lines have been offset so they all start at the same place in January 2014. This makes it easy to compare January 2014 with the latest anomaly.
In this part, we are summarizing data for each set separately.
The slope is flat since December, 1996 or 18 years, 2 months. (goes to January)
For RSS: There is no statistically significant warming since December 1992: CI from -0.000 to 1.753.
The RSS anomaly for January 2015 is 0.367. This would rank it as 3rd place. 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 2014 was 0.255 and it was ranked 6th.
The slope is flat since February 2009 or an even 6 years according to Walter Dnes. (goes to January using version 5.6)
For UAH: There is no statistically significant warming since July 1996: CI from -0.019 to 2.225. (This is using version 5.6 according to Nick’s program.)
The UAH anomaly for January 2015 is 0.351. This would rank it as 3rd place. 1998 was the warmest at 0.42. The highest ever monthly anomaly was in April of 1998 when it reached 0.663. The anomaly in 2014 was 0.27 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 June 1997: CI from -0.015 to 1.132.
The Hadcrut4 anomaly for January 2015 was 0.686. This would set a new record if it stayed this way. The highest ever monthly anomaly was in January of 2007 when it reached 0.835. The anomaly in 2014 was 0.564 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 April 1995: CI from -0.006 to 1.710.
The Hadsst3 anomaly for January 2015 was 0.440. This would rank 2nd if it stayed this way. The highest ever monthly anomaly was in August of 2014 when it reached 0.644. The anomaly in 2014 was 0.479 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 since August 2000: CI from -0.007 to 1.412.
The GISS anomaly for January 2015 is 0.75. This would set a new record if it stayed this way. The highest ever monthly anomaly was in January of 2007 when it reached 0.93. The anomaly in 2014 was 0.68 and it set a new record.
For all intents and purposes, the deep ocean is an infinite heat sink. And if some of our presumed AGW ends up there, that is good news. Or am I missing something?
About the Author: Werner Brozek was working on his metallurgical engineering degree using a slide rule when the first men landed on the moon. Now he enjoys playing with new toys such as the WFT graphs. Werner retired in 2011 after teaching high school physics and chemistry for 39 years.