Making clouds reflect more light

I know, I sorry, just inherent laziness. AND, a suspicion that Science and Scientist really know nothing, but do like to talk about it. When it comes to weather prognostication on a grand scale, we humans are quite inept.
Incidentally I do very much enjoy ALL of your comments!

 

Yes and no:

• yes - math is precise and absolutely knowable
• no - observations are subject to refinement
  • less so for those that destroy the original sample

Our discussions are often sharing understanding and refining what we know and that is not a problem.

Bob Wilson

 

Sharing is definitely productive. So long as radical predictions are not involved. I am referring to Climate change in particular. Our meteorologist can look out to the Pacific and predict a High or a Low pressure area coming in, but they are also wrong sometimes and the weather pattern moves up toward Canada. We cannot predict the Jet stream, a large influencer of weather patterns, it is often radical in its swings, going from Canada to Mexico and back up close to Canada. Weather can be observed, studied but no predictions or forecast can be made on a large scale. This whole Global warming is mist and just fodder for Al Gores notoriety.

 

No problem as we use "logical" predictions from direct observations and solid math. For example, sea level:

The 'red' line comes from the Berkeley Earth data and the blue line from satellite observations of sea level. I've use a Gaussian filter to find the embedded minimum and maximums in the data. A Gaussian filter is a type of weight average compared to a straight-line average.

An ordinary or straight-line average is calculated by adding all of the data observations and dividing by the number of samples. For example:

	data	avg(3)	Gauss(3)
1	8
2	9	9.0	9.0
3	10	9.3	9.5
4	9	9.7	9.5
5	10	8.3	8.8
6	6	6.7	6.5
7	4	5.7	5.3
8	7	6.3	6.5
9	8	8.0	8.0
10	9	9.0	9.0
11	10

Notice what happens when there is a dip in the data, the "4". The average of three points, 5.7, suppresses the dip whereas the Gaussian filter shows 5.3, a significant difference. The straight line average 'hides' the dip in the middle of the data:

• avg = (n1 + n2 + n3) / 3
• Gaussian = ( (.25*n1) + (.5*n2) + (.25*n3) )

This keeps the neighbors on either side from suppressing the interesting dips and peaks in the data.

Generating the coefficients for a Gaussian filter is a little more involved. As the number of elements under the Gaussian curve increases, the coefficients become harder to calculate. We can go over that if you are interested.

Bob Wilson

 

Climate is not weather though.
Weather is day to day prediction, and climate is the trends over years. Weather will predict the next week will be hot, humid, with a chance for a thunderstorm. Climate says summers will tend to be warmer, but drier than springs.

 

They are two sides of the same coin:

• Climate - a probability
• Weather - current observations

Weather forecasting is something in between. As weather forecasting gets better, it uses similar data to what climate scientists are using.

Bob Wilson

 

Bob you are delusional.The climate models have been wrong for the past 18 years.

 

It would be perfect if everything finally boiled down to mathematical averages. Certain areas are highly non-predictive: weather, stock market, agricultural production in particular and almost any human endeavor. Only a few parameters are constant, an ounce of gold, probably most other elements on Earth, sub atomic particles are probably pretty consistent in mass and weight but even here are variations caused by outside influences: Air pressure, temperature, velocity of surrounding electrons. How much influence does the Sun have, the Moon? What is Ether? Does it really exist. I see Scientist are reevaluating and using the term Ether again, after many years of Poopah. Scientist still do not understand all the properties of water! But I still prefer Wilson over Gore.