1-26-17 How to use Global Climate Measurements to see causes of Climate Change
Wednesday, April 18, 2007 (14:31:49)

Posted by admin

Record I have been watching these links for over ten years. One thing I have noticed is that the Gulf Stream is at last 50% stronger than it was 6-8 years ago. Much of the Arctic ice melt in the North Atlantic can be explained by the stronger than normal Gulf Stream. Skip forward a week at a time and watch the eddies and loops form as the GS weakens and then disappear when the GS strengthens. Coupled with the speed code(white is fastest) gives a good eyeball estimate of GS strength.

Links will be added as useful ones are suggested. They must be based on a reliable series of consistent measurements over time. The start date can be recent, but the further back we can go is best.

How to combine and and compare these chains of measurements "OVER TIME" to show causation, i.e. which one(s) move first and in what sequences, is explained below these links.

7-09-2008 edit: Here are links to time sequence scientific measurements of some relevant Earth Climate variables. So far no one has compared the amplitude of these many available measurements along the same time line. Comparing where each measured variable sits at the same time on its Extremes to Mean Line will reveal causal links between changes in variables like CO2 levels, solar output, volcanic eruptions, ocean currents, cloud cover, Earth's aggregate mean surface temperature, upper level sea temperatures, etc, etc.

How many of you will volunteer or help pay for constructing this measuring tool. All it takes is an agreement by the various govt and private groups who now collect and report these component measurements to input their daily or weekly results into this 3-D array Box.

Your Radiation This Week
There appears to be a discrepancy between these two radiation reports. The 'radiation network' below has decreased both in its number of over 40 cpm sites over the last year and its number of reporting sites. Given its sites are supposed to be provided by volunteers and radiation levels are increasing???
USA/Can real time radiation network

Latest Mean Global Temperature From 1979 by Satellite.

Why CO2 can NOT cause global warming.
Deplorable Science Blog which tracks the massive official temperature measurement frauds, etc, by the warmists. For example, the record increase in Greenland ice mass in the 2016/17 winter. Since they used taxpayer dollars to lie to us that makes them criminals. They must be prosecuted.

Ice Age Now.info
The Hockey Stick vs Ice Core Data
Average Daily Sunspot Area

National Snow & Ice Data Center
Danish Meteorological Institute Arctic Ice Record
By USA Cryosphere Today World Ice Cover Maps US usually lower than others for Arctic Ice.
Canadian arctic ice extent
Canadian measures and news about Northern ice cover .

DEOS Gulf Steam Velocities
Article Effects & Mechanism of Slowing

Sea Surface Temp Anomalies
North GS Sea Surface Temp Outline showing Sargasso Sea warming
World Sea Surface Temperature Maps
Global Sea Surface Temp Map
Ocean Weather

Current worldwide active volcano data
Current Worldwide Earthquake Events
Center for Earthquake Research & Information
Earthquake and Volcano links

Near Earth Asteroid Tracking
IAU Minor Planet Center
Royal Observatory, Edinborough

Sunspots & Geomagnetic Storm Warnings
NOAA Space Weather Prediction Center

CO2 levels rise 3 times faster than expected
Real Climate site for Climatologists on GS
Climate Patrol
How to measure Earth's heat balance with Joules.

Energy Bulletin on Peak Oil

Nitrogens massive bad effects

How To determine the causes of "Global Climate Change": thru time using split 3-D.". Directions below.

Create an +/- extreme bar graph of each variable, make the length of the bar be the range of values through time with max +/- min values at ends of bar; The bar will be the same length for each variable. e.g From the front, you would see a rectangular box with a series of vertical lines going from left to right: |||||| and so on.

Each line represents some variable like "Mean tropospheric temperature or 'total ice cover', etc.

Next, compute the mean of each variable through time so we can indicate its position on its Extreme)/Mean Line;

Next, show your start dates for each E/M line.

Next, show which variables have a common start date, e.g What is first date we have measurements common to any group of variables variables.

Next go forward in time and see how the means move with respect to each other.

Put these equal length E/ML lines vertically side by side with one another setting them an equal amount apart on the horizontal axis, varying where a line is within this array will give interesting results; especially by noticing which ones change first, and then organizing by which precedes which, from left to right(or right to left); i.e. a cause always precedes an effect.

Move this rectangular array box, with the proportions of .62 vertical to 1.62 horizontal(not golden mean, but I think better because it compares E/ML using Phi/phi, away from you through time and watch the relative changes between the locations of each measured variable. You can also look at this rectangular box from any side except top and bottom and observe the pattern of changes. The boxed array proportions are the Golden Ratio which reflects our universes geometry;

From the starting rectangle in front you would see the dots representing the variable's means position vary with respect to each other through time on each measurement's vertical E/MLine. From the side you would see the changes in lines that progress through time. Thus you can compare causal relationships in two ways side by side; i,e, using the front vertical E/M lines to compare with the side that shows the changes through time lines.

Then deduce which moves in what direction first. As we look from the right or left side of our front 2-D box we can see see how time line of these changes variables change with respect to one another and watch for crossing points, or extremes before changes.

From the front, we will also see distinct patterns that precede meaningful changes in long term variables that matter to mankind.

Computer Graph how they change with respect to each other over time;
which means you can see causal sequence between any two or more E/MLs you select, especially useful identifying 'negative feedback start points' between variables.

Conclusion: We have constructed a split 3-D Time Array Measurement Box that incorporates our scientific and geometric unit of logical integrity Phi*phi = 1.

Time is always measured by c, the speed of light in Planck units = minimum time it takes to see a change in an atomic state.

Figure out which +/- changes in variables precede which, so we can deduce which might cause what, and then try to predict the future consequences of present inputs. Remember, a cause always precedes an effect, by definition; but a preceding change in a variable does not always prove causation, sometimes only correlation, as its absence in some instances can demonstrate.

The hard part comes in figuring out the actual causal link(s) and then demonstrating it.

Use how your predictions are wrong to construct a theory that makes accurate predictions.

Task: Build this measuring tool. I do not have the time. Who will Volunteer?

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