UPDATE: 11/11/10 An errata has been posted, see the end of this essay – Anthony
Guest post by Ed Thurstan of Sydney, Australia
Synopsis
This study shows that the NOAA maintained GHCN V2 database contains errors in calculating a Mean temperature from a Maximum and a Minimum. 144 years of data from 36 Australian stations are affected.
Means are published when the underlying Maximums and/or Minimums have been rejected.
Analysis
The Australian Bureau of Meteorology (BOM) provides NOAA with “entirely raw instrumental data via the Global Telecommunications System”. In the process of comparing BOM Max and Min outputs with NOAA “Raw” inputs, some oddities were noticed.
A database of Australian data (Country 501) was set up for each of GHCN V2.Max, V2.Mean, V2.Min. Each record consists of WMO Station ID, Modifier, Dup, Year, then 12 months of data Jan-Dec.
“Modifier” and “Dup” are codes which allow inclusion of multiple sets of data for the same station, or what appears to be the same station. This data is included rather than losing it in case it may be useful to someone. For this exercise, Modifier=0 and Dup=0 was selected.
Only those stations and years where all 12 months of data are present were selected. This results in about 14,000 station-years of monthly data being compared.
A compound key of Station ID concatenated with year was set up.
From Max and Min, an arithmetic mean was calculated to compare with V2.Mean.
Observation 1.
NOAA always rounds up to the nearest tenth of a degree in calculating V2.Mean.
Calculating (Reported V2.Mean – Calculated Mean) mostly gives a result of zero or 0.5 as shown in this example:
This appears to be poor practice, when the usual approach to neutralising bias is to round to the nearest odd or even number. However, the bias is small, as units are tenths of a degree.
This observation led to the discovery of larger errors.
Observation 2.
The difference between reported V2.mean and the calculated mean can be substantial.
Here is a cluster of (Reported V2.Mean – Calculated Mean):
For example, Station 94312 (Note: Port Hedland, Western Australia – Photo added: AW)
In March 1996 shows that the reported GHCN V2.mean figure is 1.15oC lower than the mean calculated from V2.max and V2.min.
There is no obvious pattern in these errors.
As a spot check, the raw data from GHCN V2 for station 94312 in 1996 is as follows:
The arithmetic mean for March should be (377+256)/2 = 316.5
But NOAA has calculated it as 305. An error of 11.5 tenths of a degree.
WMO Station 50194312 is BOM Station 04032.
Here are the monthly averages calculated from BOM daily data:
With one exception, they are within 0.1oC of the NOAA figures. The exception is 0.2oC.
There are 144 years of data from 36 Australian stations affected.
GISS V2 Carries NOAA’s version of V2.Mean. So GISS will be propagating the error.
Full Error List
The full error list of stations is available on request. It comprises 144 years of data from 36 Stations.
Observation 3.
Unless there is a severe problem in transmitting BOM data to NOAA, then NOAA’s quality control procedures appear to reject a lot of superficially good BOM data.
When this happens, NOAA replace the suspect data with “-9999”, and write a QC.failed record.
GHCN V2.mean now contains many instances where a mean is reported, but the underlying V2.max and/or V2.min are flagged -9999. That is, they are not shown.
For example, station 50194312 (BOM 0432) shows:
Spot check. Following is matching raw data from GHCN V2 for checking purposes:
Note that Means are published when corresponding Max and Mins are absent in Jan, Feb and April.
The corresponding BOM raw daily data for 1991, 1995 and 2005 was checked. It is complete, with the exception of three days of 1991 minimums in May 1991. Two of these days have missing results. The third is flagged with a QC doubt. Note that this BOM data comes from the present BOM database, and may not be what went to NOAA in earlier years.
Here is the BOM data corresponding to the NOAA product:
And here are the differences, BOM – GHCN
Here we can see substantial corrections to input data, especially in 2005.
V2.max.failed was checked for data from this station. There is only one entry, for 1951. V2.Mean.failed referred to the same 1951 QC failure. V2.min.failed also has a single entry for October 2004.
Summary
There is a lot of published criticism of the quality of NOAA’s GHCN V2. I now add some more.
In my profession, errors of this sort would cause the whole dataset to be rejected. I am astonished that the much vaunted NOAA quality control procedures did not pick up such gross errors.
The error is compounded in the sense that it propagates via V2 into the GISS database, and other users of GHCN V2.
Appendix – Source Data
The GHCN V2 database, giving Annual and Monthly data, is available at ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/v2. The file create date of the set used in this study was October 15, 2010.
The Australian Bureau of Meteorology (BOM) supplies raw instrument data to NOAA electronically. This data is accessible on the interactive BOM site at:
http://www.bom.gov.au/climate/data/
This is daily max and min data, and should be the data supplied to NOAA.
Ed Thurstan
October 20, 2010
=================================================================
UPDATE VIA EMAIL:
In the section where I compare BOM data against GHCN data to highlight corrections made to GHCN input data, I inadvertently compared 2005 GHCN to 2007 BOM data. The offending data for 2005 should read
2005 39.4 38.2 38.4 38.2 33.3 26.4 27.9 28.6 31.4 33.6 37.2 36.3
BOM MIN Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2005 26.7 27.3 26.4 23.7 18.5 14.7 14 13.8 15.6 18 20.8 25
BOM MEANJan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2005 33.05 32.75 32.4 30.95 25.9 20.55 20.95 21.2 23.5 25.8 29 30.65
DIFFERENCES
MAX Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2005 0.0 0.0 0.0 – 0.0 0.0 0..0 0.0 0.0 0.0 0.0 0.0
MIN Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2005 0.0 0.0 0.0 – 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
MEAN Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2005 1.2 0.9 0.9 1.0 0.8 0.7 0.8 0.7 0.7 0.7 0.7 0.8
Apologies to all for the error.
I have a model of a real bridge that I would like to sell you. No I do not want to sell the model it is just there so you can see what the bridge would look like if you could see it. I also need the model for future sales. Of course the model represents real data from the bridge that has been point by point quality controlled. Of course, because of time going by you cannot see the actual data, I have misplaced some of it somewhere. You need not worry about the integrity of the bridge it has been certified by GISS and Hansen. How much should Australia pay for the bridge? Wait I have a counter offer form another viewer, the US. Story to be continued after the next election finishes the job.
Ladies and Gentlemen. I hope I’m not going to do damage to anyone’s psyche here.
Oh, heck. Why not.
I’m almost 53. I say that because in 1972, I was staring down the barrel of a HUGE Science Report, I was to construct for first year high school. It was a 6 week project.
I procrastinated even beyond my norm and ‘suddenly’ it was the night before my research paper was due. I vividly remember sitting at my little desk and creating my data by reviewing a few books (yes, it was supposed to be footnoted, and I did that, as well) and making up statistics outta the ‘clear blue’.
Somewhere in my (totally human) reasoning, I somehow understood that one teacher reading 40 research papers, couldn’t possibly check all the books and all the footnotes…soooooooooo……. ‘Up Up and Away’ my little project creatively went, till I actually began enjoying (oh, let’s call it ‘The George Soros-ness’ of being a little god in my own little room, creating my own little data to reach my ‘own little conclusions’.
Assuming you, as well as I, are of a mature age, having been around the block a time or two ~ you can most probably guess what marks I received for my (let’s delightfully call it, my creative genius? or ~ we could call it CHEATING? warm smiles…) Yeah. That’s right, my Scientist friends ~ I got a B+ on my research paper.
Now ~ the reason I’m sharing is not because I began to ‘fleece the system’ in high school (for one can suppose rightly that I became more learned in this process through the next 3 years) but, to simply put a finger upon exactly what humans
are capable of (and were I to be paid for it….gosh, who KNOWS what I’d’ve done…hmmm?)
So, PLEASE. All of you great guys an’ gals of ethical mores ~ GET TOGETHER AND HOLD THESE SO CALLED ‘EXPERTS’ ACCOUNTABLE, for perhaps eventually they will in due time find their own epiphany, of sorts ~ like say…….PUBLIC SCORN AND HUMILIATION…normally does the trick… and perhaps ~ someday, like myself,
they will be able to research without someone double-checking their stats. I suggest this whole debacle being quite cathartic…reminding me of my school days…when one of the only weirdos that graduated one year after me was George Stephanopolis… yeah, admittedly ~ sadly, we didn’t have the highest of standards… alas, it’s now up to you to hold them accountable, and I KNOW you can do it. I’ll agree to cheer lead and pray from the sidelines as you deftly eliminate this ‘smoke on the water’ or the skies that they’re ‘blowin’ in the wind’…
Cynthia Lauren
(ex-cheat and junior trouble-maker at large)
I feel several of you correspondents have got it all wrong when you suggest that Gavin should give up blogging and concentrate on his day job.
I feel it would be better if he concentrated full time on blogging, where his heart obviously lies.
He should give up his day job.
Then someone more qualified could take a stong hand and improvide reliability of what is a most important if not vital resorce.
Gavin’s blog, with all its susceptability to human error is not quite so important.
He can be trusted to keep writing his blog.
“””” Mike says:
November 10, 2010 at 12:39 pm
The average value of a continuous function f(t) over an interval [a,b] is the integral from a to b of f(t) divided by (b-a). It is not equal to the average its maximum value and its minimum value. For example (I just covered this in class today) the average value of sin(t) over [0,pi] is 2/pi which is about 0.6366. The max is one and the min is 0, which average to 0.5. The shape of the function matters.
Here is a simpler discrete example. Suppose f(1) =1, f(2) = 1, f(3) =1 and f(4) = 9. The average is (1+1+1+9)/4 = 3 not (1+9)/2 = 5.
I do not know what method is used by BOT. I’m just exampling the basic math. “””””
Well Mike, what you say is true; and I have raised this issue so many times WRT the daily average temperatures reported for the GISS and other networks.
They DO in fact simply average the daily max and min Temperatures and report that single number for that day and that location.
And if the actual daily Temperature cycle did follow a sinusoidal function, then (max+min)/2 would give the correct average; and it also just conforms to the Nyquist sampling theorem, since the signal would be a band limited signal with a 1/24 hour signal bandwidth, so two equally spaced samples suffices to obtain the average.
However the appearance of any time assymmetry f(t) not equal f((T/2)-t) would imply the presence of at least a second harmonic component raising the band limit to 1/12 hours. In this case Nyquist is violated by a factor of two if you do min/max averaging; and with a factor of two undersampling; the aliassing noise spectrum folds all the way back to zero frequency; so the average is no longer recoverable.
And perish the thought that clouds would result in an even more ocmplex daily temperature cycle.
Incidently; I am sure that there is no natural physical process that would follow a half sinusoid cyclic behavior like a rectified sine wave; so as big a discrepancy as 0.5 to 0.636 (2/pi) probably doesn’t arise in practice.
But climatists seem totally oblivious to the laws for sampled data systems; and the Nyquist theorem. The global Temperature sampling regimen doesn’t follow the rules for either the time variable, or the spatial variable; where Nyquist is violated by orders of magnitude.
So much for knowing the average Temperature of this planet.
Steve Mosher & Graeme W.:
Are you saying that Ed’s article is BS? That his “errors” are misinterpretations? What’s the bottom line, fellas?
You being PC or cherrypick complaining?
NO Accuracy Applied
In the spot check using 1996 data, it seems that all the data is wrong on the average. This would suggest that there is more data than just the max and the min that go into the average calculation. But this is where the alarmists/function people fall on their face. The stations don’t record more than the max and the min or shouldn’t because there would most likely be a bias. This shows up in that the station always gets checked at noon over lunch and might add a warming bias. If a “function” of more sampling than that occured, it’s logical to assume that some averages would be lower and some would be higher than the average of the max/min due to seasonal changes.
Also, if you look at the data in obs 3. The tabulated data of max/min/average for 1991….suggests that only use of the max and min is required to get the 1991 average.
All I’ve done is to try to confirm the values he listed as being the original BOM data. I was surprised to find that the values I looked at didn’t match what’s on the BOM website.
Given what I found, the section of his article that reports “Gross” data errors between GHCN maximum data and BOM maximum data is just plain wrong.
I didn’t check the minimums to see if they agreed or were also wrong. The BOM website doesn’t have a mean temperature, so no direct comparison there is possible – you have to calculate the ‘BOM mean’ yourself, with the issues that others have already raised (do you average the mean max/min, or do you average the daily max/min, and then take the mean of all those daily averages?)
I haven’t checked any of the other sections of his article. I only checked that one because the errors were so large, and I wanted to provide the links to the raw data so everyone could see the error for themselves. As it turns out, I found that the raw data between BOM and GHCN agrees for March 2005, which is a direct contradiction to what is stated in the article above.
I just had the thought to see if the 33.6 figure appears in the BOM data for March of a different year, and it does – 2007. Indeed, all of the data he listed for BOM 2005 maximum temperatures are, in fact, the 2007 figures according to the BOM site.
I believe that the most likely reason for the errors is simply transcription. The BOM website doesn’t provide a contiguous table from 2010, but has heading breaks after 1972 and 1997. I suspect that Ed copied the tables into a spreadsheet, and had a copy error and shifted the later data by two years. He was thus comparing the 2005 GHCN data with the 2007 BOM data… which, not surprisingly, didn’t agree.
The problem is not an average calculation problem. The problem is that he’s accidentally compared the wrong years.
My understanding is that the BOM takes automatic half-hourly temperature measurements, not just twice a day.
I believe previously they used thermometers that allowed them to record the maximum/minimum in the previous 24 hours, not just two measurements at particular times. I have a vague recollection of seeing such a thermometer (at least for the maximum). It had something that was pushed up by the mercury as the temperature rose, but that something didn’t fall back if the temperature dropped. That meant it showed the maximum temperature since it was last reset. It was reset on a daily basis (presumably when the readings were taken) so it would show the maximum temperature over the full 24 hours.
That sort of technology means that there’s no significant TOBS bias. The only time there would be the chance of a TOBS bias is if there was a significant temperature change just around the time of observation (eg. if the temperature is significantly dropping at 8:30am, for example, just as the observation is taking place, which may result in a bias in the minimum temperature being recorded). However that should be rare and this there should not be any significant TOBS bias in the data.
Doug Proctor says:
November 10, 2010 at 7:06 pm
Steve Mosher & Graeme W.:
Are you saying that Ed’s article is BS? That his “errors” are misinterpretations? What’s the bottom line, fellas?
You being PC or cherrypick complaining?
###########
1. I am holding everyone to the same standard. I would need to see the code to understand how he did things.
2. three years ago I did a similar exercise with GHCN because I was concerned about the rounding NOAA was using. I looked at US stations and found nothing like Ed found. Thats just an observation.
3. I spent about 3 months looking at some of the ins and outs of GHCN and made numerous mistakes before I found out the way they did things didnt cause the problem I thought there was. So, I never rule out auditor error.
I have no opinion on whether or not he made and error or GHCN did. I know my past work hasnt found such errors. So, I’d have to see the code
Graeme W says:
November 10, 2010 at 5:53 pm
Actually, Steven, I wasn’t even trying to replicate what Ed had done. I was simply doublechecking his figures that he said were the BOM figures. I quickly found out that they weren’t. That Mar 2005 maximum temperature of 33.6 isn’t what’s listed on the BOM website, and I can’t see any way that it could be derived from the raw daily data for Mar 2005.
If he’s used the wrong data from BOM, then all the BOM to GHCN comparison’s he’s listed are meaningless.
############
as I noted above I had done a similar exercise 3 years ago with US stations and found nothing like what Ed has found. There is also a problem with simply choosing dup 0 but I didnt want to get into that.
A bunch of us started a discussion of the duplicate problem a while back, but I’m not going to get into that. It also kinda looks like spreadsheet work which involves manual steps that can really screw things up ( personal experience).
George E. Smith says:
November 10, 2010 at 7:01 pm
“””” Mike says:
November 10, 2010 at 12:39 pm
The average value of a continuous function f(t) over an interval [a,b] is the integral from a to b of f(t) divided by (b-a). It is not equal to the average its maximum value and its minimum value. For example (I just covered this in class today) the average value of sin(t) over [0,pi] is 2/pi which is about 0.6366. The max is one and the min is 0, which average to 0.5. The shape of the function matters.
#######
while technically true its really beside the point. The average obtained by sampling min/max is just an estimate of the number you would get by integrating.
Its not intended to represent the true average, but rather to estimate it.
The question is does this method give you an unbiased estimator. And does it give you an unbiased estimator over time.
This issue bother me as well, so I just looked at real data. temperature data that had been taken at short intervals and compared the answers you get looking at it both ways. Now its trivially true that the answers are different. The question is : is there a high or low bias? AND does that bias shift over time. Well, little did I know that I was re doing work that had been done before. Its not a biased estimator and it doesnt change over time.
If you like go download CRN data ( 5 minute intervals) and see for yourself, or look at Jerry Bs work over on John Dalys old site.. 190 stations, sampled every hour with the average calculated two different ways (min max) and integrated. We call the “integrated approach” Tmean and the min max approach Tave.
Simply, “average” doesnt mean mean.. its an unbiased ESTIMATOR of the mean.
If he’s from New Jersey, probably not. 😉
I believe for the last year or so blogging is and has been Gavin’s day job. He spends so much time defending the indefensible he can’t possibly have time for actual work.
NOAA is still putting 999.9 error codes into the GHCN database, which is then being used by GISS, even though BoM data is available for the relevant month.
The wonderful Jo Nova has allowed me to make some points at:
http://joannenova.com.au/2010/10/bom-giss-have-record-setting-bugs-affecting-a-million-square-miles/
To summarise, I point you to one of the Western Australia locations with BoM data “missing” from GHCN and GISS – the goldfields town of Kalgoorlie-Boulder. Check the GISS database:
http://www.waclimate.net/501946370000.txt
Note the 999.9 error for September 2009 down the bottom of the database. Now check the BoM record for September 2009:
http://www.bom.gov.au/climate/dwo/200909/html/IDCJDW6061.200909.shtml
The mean temp for Sep 2009 was 13.9 C. That means the Spring (S-O-N) 2009 average for Kalgoorlie-Boulder was 19.4 C.
GISS calculates it as 20.6 C . That’s 1.2 C above reality.
In turn, this means the annual average was 19 C , not 19.38 C as calculated by GISS. All 30 days in Sep 2009 were recorded by the BoM for Kalgoorlie-Boulder, so the monthly mean is valid.
Incidentally, I noticed and calculated the Kalgoorlie-Boulder error for September 2009 on Oct 4, 2010. I came back to check my numbers the day after, Oct 5, and found the mean for every month in 2009 had been shifted up overnight by .1 C, so the Spring and annual averages also shifted up .1 C. I don’t know if every month in the entire database back to 1939 was adjusted up by .1 C because I hadn’t paid any attention to them on Oct 4. More than nine months after 2009, it’s difficult to understand why every month last year needed an upward adjustment for this particular recording location.
So BoM has the data, for some reason it isn’t included by NOAA in the GHCN, and for some reason the incorrect error is passed by NOAA to GISS which then substitutes it with a mystery temperature to overcome the problem, but lifts the seasonal mean by 1.2 C above what should have been received from BoM in the first place.
Does anybody at BoM, NOAA or GISS check their figures? Over the past year, hasn’t anybody noticed or wondered why a month is “missing” for a major country town (shire population near 30,000)?
More at http://www.waclimate.net/giss-adjustments.html
And since I’m talking about Kalgoorlie-Boulder, check my graph of all temperature records for the town back to 1897, comparing historic BoM raw, BoM HQ adjusted, GISS and HadCRUT 3.
http://www.waclimate.net/giss-bom-kalgoorlie.html
Notice how much warmer the raw data is (blue line) compared to the HQ adjusted data (yellow line) in the first half of the 20th century?
What caught my eye first off is that for some reason, the raw temperatures are stored in the database as integers, with what I presume is a one significant digit decimal. 273 becomes 27.3, 315 becomes 31.5, etc.
I’ve been a database developer for 25 years now, and I’m stumped to think of a reason for those temperatures to be stored in that manner. By using that transformation, someone somewhere has to keep the metadata to let future generations know that’s 31.5 and not 3.15 or even 315 degrees. Were they trying to save space by using integers instead of floating-point reals? /sarcasm /
Looking at how they came up with means where there were missing max or min values makes me wonder if their algorithm was not clearing out the accumulator when a “-9999” value was found. Without seeing the code there’s little chance of figuring out their process, but you can sure tell that something’s wrong somewhere!
I’ve read EVERY COMMENT thus far. I’m TRYING TO understand what you guys
are saying ~ mostly, though, I’m crossing my eyes, getting more coffee, and asking why you can’t simply ASK THEM FOR THE ‘CODE’ that will ~ Am I correct in this? ~ unlock the mysteries of their numbers that are lacking the floating decimals that prohibit anyone from coming back to their work (like future warmist prodigy?) to see watts up? (please forgive the pun)
Okay, okay ~ I’ll jus’ shut up and sip my coffee quietly. You guys are better than my favorite Soap in the 70’s… Dark Shadows… regardless, I believe you will eventually uncover their (door #1, 2, or 3): Error/Momentary (monetary?) Indescretion/oooor ~ Fraud. Regardless, I’m ‘rapt’ as you blokes say. God continue to bless Australia!
C.L. Thorpe
By way of cross checking, I used a BOM version of temperature data from Port Hedland airport 04032 that was available before March 2007.
I selected Year 1966, daily observations of Tmax and Tmin, and made the Excel spreadsheet shown at
http://www.geoffstuff.com/Monthly%20from%20CD.xls
The conclusion is that the Tmean for 1966 is about 1 degree C higher from the BOM version than is shown above in the Ed Thurstan version. I used his data from his table following the line “As a spot check, the raw data from GHCN V2 for station 94312 in 1996 is as follows:”
This must be about post number 10 in 3 years where I have pointed to difficulties in discovering which Australian versions go from BOM to whom and when, then what more is done and why.
A one deg C difference in a year is enough to hide a decline.
PJP says:
November 10, 2010 at 1:42 pm
Government engineers … spend millions on a spacecraft, then find out after it has been launched that half the plans were metric and the other half imperial.
No doubt they also measure temperature in a mixture of Celsius and Fahrenheit; wind speed in a mixture of knots and feet per second and rainfall in a mixture of mm and inches 🙂
“In my profession, errors of this sort would cause the whole dataset to be rejected. I am astonished that the much vaunted NOAA quality control procedures did not pick up such gross errors.”
Mine too. On top of that, had i been responsible for presenting/collecting it, i’d loose my job.
In France, Courtillot (the main sceptical climatologist there) said something very true:
“from a thermodynamic point of view, averaging temperatures has no meaning. If you have two rooms, same volume, one is at 20 degrees C, the other is at 10 degrees C, and you open the door between the rooms and let the temperature stabilize, the final temperature will not be 15 degrees C”
Temperatures do not sum or average…but energy does. So if first you switch from temperature to radiated energy assuming the part of the earth from which you measured temp. is like a black body, then you can average these radiated energies, and come back to average temperature.
CL Thorpe,
Like you I need simple answers to very simple questions. E.g. Since the world’s future hangs in the balance and squillions of dollars ride on the outcome why don’t we have a proper, real high quality set of recording stations. Stations that are really compliant to the requirements of the 100 foot rule. Then we wouldn’t have these interminable discussions about the need for and methodology of adjustments.
I’m still having difficulty with a heavier than air gas floating high in the atmosphere rather than close to the surface.
FWIW, I think the method used by NOAA is a ‘average the daily means’ where what’s done here is to compare with the ‘monthly min / monthly max average’ and so will diverge. ( If I followed the article correctly at this late hour…)
Also, FWIW, you must know the “Vintage” of the data you are comparing at least down to the month. GHCN has Zombie and Lazarus thermometers who’s data show up at strange and wondrous times. So you can have large gaps that are then suddenly filled days, weeks, months, and even years later. And sometimes never shows up.
So unless you have a specific vintage that is the same in both sets, you may just be measuring the time instability of the data..
JamesS says: November 10, 2010 at 11:04 pm
I’ve been a database developer for 25 years now, and I’m stumped to think of a reason for those temperatures to be stored in that manner.
And data is persistent, so as soon as code is written to the format the problem becomes entrenched. I hear the US still uses imperial…
Absolutely, Lawrie.
If enough of these ‘anomalies’ are world-wide and so…..so……basically inept ~ and that’s what we’re pinning the ‘hope of the world’ upon……as the story goes……. the ONLY thing that makes sense here, is that ‘they’ really own egos that blind them to the fact that truly knowledgeable people will eventually hold their ‘science’ to account.
Sorry if when I ‘sound off’ I seem to be a cynic. I’m truly not. It’s just that ol’ axiom ~
fool me once, etc… I essentially have great faith in fellow humans ~ but, basically only when their hearts have been humbled in some manner. God did that to me twenty years ago. While the process did hurt a bit, ego-wise… I heartily recommend humility to all. ‘Cause with God’s Wisdom an’ our ‘guts’ to stand as we should… this world is a much more congenial place for everyone ~ regardless the temperature.
Cynthia Lauren