Al Gore: ‘Bitter cold’ is ‘exactly what we should expect

education, guidance and a strong will.

We currently destroy the mediterranean laziness in greece and force them to be a better country. We achieve this with gifts at one side and harsh punishments on the other.

 

It is not theoretical.

It is all bogus.

1. If you measure the temperature of one the rooms 100 times with +-1 accuracy you may use Standard Mean Error equation and you may be closing on the true value of the temperature with -+.01 accuracy.

2. But If you measure temperature in each of the 100 rooms by 100 different thermometers with+-1 accuracy each one time (which is the case) or a number of times (which is not the case) Standard Mean Error equation is not applicable. You have to use Propagation of Error equations.

1. and 2. are totally different things. Using Standard Mean Error equation for 2. is not theoretical it is a total illiteracy in any theory.



Weather stations on the earth are those 100 rooms with temperatures measured once a day or an hour, and the true value temperature in each of the rooms changes every hour.

The models claiming 1.51F increase over a century or .41 increase over a decade is absolutely bogus as any other statement made by IPCC, NASA, NAS and 265 academies of science.

Sure, if one knows nothing about nothing and has no ability and no need to learn anything one can believe IPCC, NASA, NAS and 212 academies of science and live by blind beliefs.



Another aspect is the physical value of the mean temperature of 100 rooms.

A patient’s body has 102F temperature and a doctor’s body has 98F temperature, the mean is 100F.

What body does have 100F?

And what is the purpose of averaging the patient and the doctor?



“Calculating uncertainty for a result involving measurements of several independent quantities

If a variable Z depends on (one or) two variables (A and B) which have independent errors ( and ) then the rule for calculating the error in Z is tabulated in following table for a variety of simple relationships. These rules may be compounded for more complicated situations.”

http://lectureonline.cl.msu.edu/~mmp/labs/error/e2.htm

https://chem.libretexts.org/Core/An...ature/Significant_Digits/Propagation_of_Error

Propagation of Error when you calculate a mean temperature of 100 rooms (multiple variables) each measured by a different thermometer with its own standard error (standard deviation.):

Let’s start from 3 rooms, 3 temperatures a, b and c were measured by 3 ideal thermometers with +-1C accuracy (standard error б=2) each.

The average temperature x = |1/3 |(a+b+c) has Propagation of Error =square root of (2^2+2^2 +2^) =б =3.46 +-1.73 accuracy.

The average of 4 temperatures has Propagation of Error = square root of (2^2+2^2+2^2+2^2) =б4 = +-2 accuracy

The average of 8 temperatures has Propagation of Error= 5.66 or +-2.83 accuracy

The average of 100 rooms has Propagation of Error =40 or +-20 accuracy.

The inaccuracy compounds with an increase of the number of independently measured temperatures you are averaging.

The claim of 1.51F increase over a century or .32 increase over a decade is absolutely bogus as any other statement made by IPCC, NASA, NAS and 265 academies of science.

 

These are facts............There were Herbivore Dinosaurs and the vegetation to support them between 400 to 1200 miles from the North Pole about 60 Million years ago. The fossilized remains of both don't lie. Something cause the Earth to warm to that extent, man didn't exist and the fossils for oil were still walking around and growing from the ground. So what caused the Earth to warm that much? We know through indisputable fact that there were Herbivore Dinosaurs and the vegetation to support them between 400 to 1200 miles from the North Pole about 60 Million years ago. So prove man is causing the latest warming and what happened to the dinosaurs isn't happening again.

http://www.pbs.org/wgbh/nova/arcticdino/about.html

 

Then you must accept that the IPCC he shared the Nobel Prize for the same thing is the same idiot.

 

False. You have totally misinterpreted the propagation of error principle. Propagation of error is used when you combine measurements together to form a new (and different) kind of measurement. For example, if you want to find the area of a rectangular surface you have to take two measurements A and B and then multiple A*B. That's when you use propagation of error. Or, if you want to know the distance between two points and you only have a meter stick to do it you have to repeatedly measure by moving the stick each time and then summing up each length individually. The error of the final result is indeed computed using the propagation of error formula you posted. This is not how you find the error in a mean though. It doesn't matter if you're measuring 1 thing N times or N things 1 time. It doesn't even matter if the do the later with 1 instrument or with N different instruments. The math doesn't care.

Your explanation doesn't even make sense conceptually. Think about it. If you want to know the mean temperature of your house and you divide your house into equally spaced cells you are claiming that the fewer divisions you make the better. You are literally saying that taking one reading with one instrument is better than taking 1000 readings with 1000 instruments simultaneously. Again, that statement doesn't even make sense on a first principle basis. And what about the error you get from the propagation of error formula? It doesn't make sense either. If we divide the Earth into 500,000 cells and we assume a standard error of 2 (your example) that yields a propagation of error of +/- 1400C. So if I computed a mean temperature of say 20C you're claiming that the real temperature could actually be 20C - 1400C = -1380C which isn't even a real temperature!

Or think about it this way. If you want to know the average height of humans is it better to take the mean from just 1 person or a bunch of people? Of course it's a bunch of people...duh! And it doesn't matter if you use the same tape measure or a different one each time. How can you not possibly understand this?

Don't believe me. Do the experiment yourself!

 

All your govt and even super douchy agw sites accept the science... but whatevs.
https://www.aims.gov.au/impact-of-runoff
https://oregonstate.edu/ua/ncs/arch...tion-impact-coral-reefs-–-and-offers-solution

Eutrophication... its th next big bandwagon after agw... need to get on board!

 

Someone want to remind Gore that according to him, we should all be dead by now due to Global Climate change.

 

All the warmers will tell you that Gore is an idiot, but back in 2000, they were all on board and almost made him president.

 

Your example with the average height is perfect; it put me in the right direction:

1. If you measure 1 person once the accuracy of your measurement will never be more than +- of the scale of your tape measure.

2. If you measure a bunch of people with the same tape measure once the accuracy of the mean will never be more than +- of the scale of your tape measure.

3. If you measure a bunch of people with different tape measures of different accuracies once the accuracy of the mean of your measurements will be never more than a mean of accuracies of your tape measures.

Here is a simple and clear illustration:

http://www.radford.edu/~biol-web/stats/standarderrorcalc.pdf

How can you not possibly understand this?

1.1 If you measure 1 person N times you can use the 'root mean square error”, equation and you may have the mean with accuracy exceeding the accuracy of the tape measure, because you have a true value of the real height of the person (it is exactly what RMSE is meant for).

1.2 If you measure a bunch of people with different tape measures of different accuracies you cannot use RMSE equation because you do not have the true value of your measurements you want to close on. The accuracy of your mean result cannot exceed the mean accuracy of tapes measures.

1.2.2. If you measure heights of bunch of people with different tape measures of different accuracies and heights vary from 0 to 150 you cannot use RMSE equation because you do not have the true value of your measurements you want to close on and the percentage of inaccuracy will increase if to compare to measuring heights varying from 150 to 180.

How can you not possibly understand this?

I accept that Propagation of Error equations are not applicable neither and I am no expert on statistics, but that does not change the simple facts numbered above.

http://www.radford.edu/~biol-web/stats/standarderrorcalc.pdf

Does somebody have time to do it in Excel so everyone can play with it?

As one can see the claim made by NASA, NAS, NAS and 222 academies of science that the mean global temperature can be calculated with +-.01 accuracy from independent data with +-1 accuracy is absolutely bogus.

Now, that all is in an ideal world. In the real world and ideal technology:

Below is a description of temperature measurement error sources and some suggestions on minimising these errors.

Sensor calibration. ...

Thermal gradients. ...

Heat conduction in sensor leads. ...

Radiation. ...

Sensor self-heating. ...

Thermal contact. ...

Thermal time constant. ...

Read-out errors.

More items...

http://www.capgo.com/Resources/Temperature/TempHome/TempMeasurement.html

In the real world the claim that the mean of recorded temperatures of world’s weather stations increased 1.51C for the last century is nothing more than a clear and direct statement that with all machinations and all extreme bias there has been no sensible change in the mean global temperature for the last century.

Don't believe me. Do the experiment yourself!

 

Note, that they are estimating the standard error by taking the standard deviation. They are not using the actual error. But, let's go with this. Replacing the S in S/sqrt(N) with the standard deviation of the individual measurements instead of the actual error of the individual measurements yields an error of the mean of about 0.03C if you assume N is 500,000 which is common for a modern data assimilation system. Again, that's estimating the standard error with no foreknowledge of the actual RMS error of those 500,000 samples.

I've done it in Excel. I've done it with a computer program. By most importantly I used the errors estimated by real experts. Everything confirms the error of the mean is on the order of 0.01C.

I'm assuming an RMSE of 2C for each grid cell derived by a modern data assimilation system. Note, that's more than what this document says is "care needed".

I did the experiment and it confirms my original statement that the error of the mean is S/sqrt(N) where S is the RMSE of the individual samples and N is the number of samples. I encourage you do the same.

I can also add that experts also say the global mean temperature anomalies are accurate to within 0.01C. Do you really think you've figured something out that they haven't?

 

Thanks for demonstrating my point. I'm reminded of the flat earth....

 

...a flat earth theory that was largely a fabrication by Catholics to try and condescend protestants?

The earth is warming. Humans are overwhelmingly the reason.

 

The earth? Are you sure? I see you profess this. It seems dogmatic. Are you suggesting that you're Catholic now?

 

15" of snow in Algeria. This seems anomalous. I believe the last event was 40 or so years ago. Of course, they got a dusting last year, so does this point to a trend? Time will tell....

 

so does the AGW doomsday predictions..

 

When I say that RMSE is applicable for a multiple measurement of the same true value but it is not applicable for calculating a mean of multiple true values I think anybody who is interested can look up RMSE and see and understand that.

You can say whatever you want because you know nobody will look up or understand; what is simple and easy for you and me is extremely difficult for others because others have no education.

When I post a simple text book page telling basic step by step calculation of a mean of multiple true values you can say whatever you want, because you know, however the text may look simple and easy for you and me, it is extremely difficult for others who claim degrees in different fields, but in reality have no education.

So you say whatever you want and have your special fan stirring psychosis.

I don’t know how to deal with people blinded by their entrenched religious beliefs whether it is a belief in AWG, GW or in no GW or something in between.

They go on blogs and read all kind of rubbish and bring it here.

Who made up “climate sensitivity from CO2” – that denialist who “debunked” denialist’s Woods experiment?

Have fun throwing knives at easy targets, they hardy deserve a respect.

They come to express their feelings, but no to think, not to doubt, not to learn.

I leave our “disagreement’’ at this, just outlining a few points of it.

1. All physical theories, all physical laws, all inventions ever invented are based on observation of phenomena either in nature or laboratory experiment.

Since GW has no experiment demonstrating that CO2 absorbs more radiation energy from the sun during the day then it emits to the Cosmos during the night, it is no science, but a crazy religion, cult. That’s all what is needed be pointed to.

2. All other things, like absence of definitions, fake terms, fake statistics, fake everything are secondary. Of course, calculating exact mean temperature of world weather stations down to .01 degree is absolutely bogus and anyone who was just some education can see that. no reference is needed.
And if somebody doubts himself he can refer to this textbook page:


http://www.radford.edu/~biol-web/stats/standarderrorcalc.pdf


but then scientists and experts say that there is “climate sensitivity from CO2” and they are experts though nobody can define climate less climate sensitivity.

Have fan.