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10-22-07, 12:11 PM #21Registered Senior Member
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10-22-07, 12:26 PM #22
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10-22-07, 12:27 PM #23
Well, Atlanta has less than three months supply of water. We will see what happens within that time. Another option they have considered is piping the water from the Atlantic through desalination. By 2030, Atlanta is expected to have 8 million people. Something will have to be done by then.
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10-22-07, 12:35 PM #24Valued Senior Member
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That's true in some parts of the country (though falling levels are due to use) but NOT in the region where Atlanta is located. Snowfall in the Southeast US is something less than five or six inches a year - and zero in many years. That hardly qualifies as a source of water.
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10-22-07, 12:48 PM #25Valued Senior Member
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I live near Atlanta and I've NEVER heard that hare-brained option even suggested! There are plenty of lakes and rivers nearby that could be tapped at a MUCH lower cost. And as has already been pointed out, it's industry - not the general population - that uses the vast majority of water.
I also somewhat doubt that 8 million figure. The current population of the entire Metro area (which covers 26 counties) is only 5 million.
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10-22-07, 01:10 PM #26
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10-22-07, 07:23 PM #27Valued Senior Member
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A quick update: It's been raining for several hours today all across the watershed area that feeds Lake Lanier (where the city of Atlanta gets it's water). Even though it hasn't been a heavy rain, the temperature has been very mild ans the RH has been over 90% the entire time. That means very little was lost to evaporation.
Currently on the weather radar, there is even more headed into the area. And the forcast for tomorrow and the following day is for an even greater chance of rain thatn there was today. End result is that it's already bought a little additional time with more possible help on the way.
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10-23-07, 07:07 PM #28
Certain part of Utah use two types of water. Potable for house use and irrigation for yard and washing cars etc. My house there had that setup.
It is high time to split the water system this way, at least for new housing and retrofit. In case of emergency, water can be moved through gas pipelines or crude oil pipelines.
With global warming, and Icebergs melting down, we should get more rain and not less. Where the moisture is going, we need some research.
More rain means aquifers will get replenished. But with this global warming who know who gets water who does not. If we can find out where the new lakes will form, we can build pipelines - after all the way people are paying for the bottled water, we should be able to afford building those pumps.....
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10-23-07, 08:45 PM #29
Where is the moisture going? That's exactly what I'm thinking.
I know the Arkansas River is looking pretty sad here(oklahoma)lately and I think I know why. The river is very shallow and wide giving it a very wide surface area for the water to evaporate.
If we made the river deeper in the middle and give it a slope for the water to collect to the deep end. The river would be a lot more happy.
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10-23-07, 08:56 PM #30Registered Senior Member
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The Army Corps of Engineers is releasing 1.5 billion gallons of water each day from Lake Lanier. A lot of it is to protect an endangered species of mussel.
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10-23-07, 09:18 PM #31Valued Senior Member
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A good part of Atlanta did that a long time ago. There's a separate distribution system for the discharge water from several wastewater treatment plants. It's used primarily in commercial applications - office and other business buildings, golf courses, etc. In aparts of at least one county (Fulton) it also goes to many residences. But what isn't used in that way still isn't wasted - it goes back into the river and is pulled out by cities (MANY!) downstream.
But therein lies the BIG problem - no one knows where the rain is going to go. The major portion of it may well be in some unaccesible location - like the oceans, for example. And that's just one of the reasons why I dislike the term "global warming" and use the much prefered term "climate change."With global warming, and Icebergs melting down, we should get more rain and not less. Where the moisture is going, we need some research.
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10-23-07, 09:50 PM #32
Some time ago, I wanted to bid a sensor network that NASA is building covering the planet to gather information and do a neural model. I was told by friends that "don't bother" probably Lockheed Martin and Dyn Corp will win the contract and mess it up. No weather model.
Hope they do not mess up...then we will know what is going on. But if it is anything like FBI Sentinel project....it would be a white elephant.
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10-23-07, 09:59 PM #33Valued Senior Member
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It would be a VERY long time before they know, though - that's my whole point. Climate change is dynamic - thus the word "change" - it's in motion and no one can yet predict what the final pattern will look like. There are too many varibles in play and remember that we're talking about the ENTIRE Earth - not just a few regions here and there. It most likely will take several decades before any reasonable patterns stsrt to emerge and they could still change after that. So don't start start buying any pipelines and pumps for at least another 60 years - and even then you may put them in the wrong places.
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10-23-07, 10:11 PM #34
Any dynamic system can be measured and expressed in mathematical terms. The hope is with enough data points and time series, it is not that difficult as long as one covers the whole system and not one location. Using fuzzy logic and neural net we could get 85% closer than what we have - the weatherman based on 100 points in hundred years with localized input.
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10-24-07, 04:56 PM #35Registered Senior Member
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10-24-07, 05:18 PM #36Valued Senior Member
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I'm afraid that's nothing more than wishful thinking, knguru. My point is that the climate is dynamic and changing. Wind patterns and ocean currents are going to change and eventually change again - no one know how MANY times. Even if you had totally valid data today (which, of course, is impossible) it would be worthless in five year's time. And the changes are likely to take a century before ever settling down - if indeed they EVER do.
Case in point: we already have a system that collects data from thousands and thousands of points across the globe and current 5-day forecasts are generally no better than 50% accurate. It also requires a tremendous amount of computing time and effort just to predict the rainfall pattern for a specific area 24 hours in advance and again, the accuracy of that prediction is pretty low. Just imagine trying to do THAT on a global scale!!! It will not happen within your lifetime.
Technology is great but it isn't THAT great.
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10-24-07, 05:50 PM #37
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10-24-07, 06:36 PM #38Valued Senior Member
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10-24-07, 07:00 PM #39
Types of Forecasting
Meteorologists actually use a combination of several different methods to come up with their daily weather forecasts. Here are the different types:
1. Persistence Forecasting: This assumes that what the weather is doing now is what it will continue to do. To find out what the weather is doing, meteorologists make weather observations.
A thermometer measures temperature.
A barometer measures air pressure.
A rain gauge measures precipitation.
An anemometer measures wind speed.
A radiosonde attached to a weather balloon measures weather high in the atmosphere.
A satellite orbiting Earth takes pictures of clouds from space to help us see where and how fast clouds are moving.
A radar shoots a radio signal into a cloud to shows where precipitation is falling and how much. It can also spot severe storms and how fast they are moving.
Eyes and ears are probably the most accurate tools. Meteorologists all over the world observe clouds and precipitation, and relay that information and their measurements to other meteorologists throughout the world so we can know how the weather is changing from place to place.
Meteorologists plot their observations on a weather map every hour to see how fast the weather is changing, then forecast where those changes will occur next.
2. Synoptic Forecasting: This method uses basic rules that the atmosphere follows. Meteorologists take their observations, and apply those rules to make a short-term forecast.
3. Statistical Forecasting: Meteorologists ask themselves, what does it usually do this time of year? Records of average temperatures, average rainfall and average snowfall over the years give forecasters an idea of what the weather is "supposed to be like" at a certain time of year.
4. Computer forecasting: Forecasters take their observations and plug the numbers into complicated equations. Several ultra-high-speed computers run these various equations to make computer "models" which give a forecast for the next several days. Often, different equations produce different results, so meteorologists must always use the other forecasting methods along with this one. That's why when it comes to forecasting, machines can't do it alone; you always need humans involved.
Using all the above methods, forecasters come up with their "best guess" as to what weather conditions will be over the next few days.
Most of the time, people use statistical forecasting plus guess work
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10-24-07, 07:08 PM #40
An ensemble of neural networks for weather forecasting
The weather is a continuous, data-intensive, multi-dimensional, dynamic and chaotic process, and these properties make weather forecasting a formidable challenge. Generally, two methods are used to forecast weather: (a) the empirical approach and (b) the dynamical approach. The first approach is based upon the occurrence of analogues and is often referred to by meteorologists as analogue forecasting. This approach is useful for predicting local-scale weather if recorded cases are plentiful. The second approach is
based upon equations and forward simulations of the atmosphere, and is often referred to as computer modelling. Because of the grid coarseness, the dynamical approach is only useful for modelling large-scale weather phenomena and may not predict short-term weather efficiently. Most weather prediction systems use a combination of empirical and dynamical techniques.
However, little attention has been paid to the use of artificial neural networks (ANNs) in weather forecasting. (2004)
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