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Topics - cesium62

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Arctic sea ice / Off Topic
« on: September 25, 2019, 06:23:51 AM »
This is the thread where one should discuss whether or not a posting to an Arctic Sea Ice thread is off topic.  Please remain on topic in this thread.  However, if you do go off topic, this is the thread to discuss that.

Arctic background / Bathymetry, Volcanoes and Upwellings
« on: August 14, 2017, 04:47:01 AM »
There appears to be a polyna in the Laptev at 120E 81N.  There is a large crater at the end of the Gakkel Ridge at those coordinates as well.  Is there a connection?

Does the Gakkel Ridge crater have a  name?  Do we have a good map that would show named features like that?

I can find reports of Volcanoes far to the northwest along the Gakkel Ridge; did the American research expeditions make it out to the end of the ridge?

In the Melting Season thread, Rathbone mentions that upwelling tends to occur over ridges.  Is the Gakkel Ridge Crater a known upwelling location?

[And is there a way to tag a forum thread to notify me when it gets updated?]

Arctic sea ice / Spelling
« on: April 12, 2016, 02:07:38 AM »
"A bit something on flawed data to not loose the bigger picture as to progress of melting this early in the season."

I hate it when the big pictures get loose.

[rebuttal to a rebuttal that was in the "melting season thread"]

Let's face it, coal is cheap

No it isn't.  Even if you ignore the externalities (deaths from particulate inhalation, CO2 emission, digging up and burning entire mountains), it still isn't all that cheap.
Geo, hydro, natural gas, and wind are all cheaper.  You can and should switch applications like pumping water to the tops of hills to pressurize city water systems to do most of the pumping when the wind is blowing instead of at night.
There exist regional areas where centralized PV is cheaper than coal.  PV and wind remain sufficiently unused that we can easily afford to rapidly build these out in the market niches where they are cheaper than coal and continue to drive down their costs.  Comparing the cost of electricity at the customer roof instead of at the factory gate produces a different set of more advantageous levelized costs for PV.  Google and Walmart can install PV using their advertising budgets.

Then add to that the exponential growth in vehicles, many of which are diesel and you realise that air quality is not going to be quite to easy to get.
The exponential growth in vehicles parallels the exponential growth in electric vehicles.  And electric vehicles can be powered from non-dispatchable technologies like wind and sun.  In the meantime, petroleum is "a very constrained resource which is hard to extract".  The US shale revolution can't fuel China and India.

Additionally, you now have to justify the assumption that "ease of life and comfort" requires exponential growth in vehicles.

Now let's look at the UK...
Obviously not representative of most of the world.  If I remember correctly, the latitude of the UK is somewhat further north than, say, China, India, the United States, Brazil, Australia, Africa...

So we shift the personal vehicle traffic to EV.
You left carbon fiber out of you analysis.  You've read Amory Lovins?  who includes commercial vehicle traffic in his analysis as well?

  Worse is that we will be closing down 7gwh of coal fired plants in the next 5 years
It's not entirely clear to me that we have to be completely off coal within 5 years.  Do you want to explain that?

Creating whole new businesses will require epic level government funding which will require epic level taxes.
Ah, so you have bought into that whole thing that any form of cooperation between people outside of a corporation is communism and inherently evil.  We must scale back "ease of life and comfort" for the masses because we can't possibly have cooperation on the large scale social level which would otherwise be required.

We have started too late and too little.  Far too few people even care about what is going on and even fewer of them want to make the sacrifices.  Trust me I talk to people about this a LOT.  The level of ignorance fostered by the FUD (Fear, Uncertainty and Doubt), pushed out by the right wing press and the denialoshpere is huge.

I don't need to produce surveys to prove my point, I just need to read the press, talk to people and, above all, watch how they vote.

Meanwhile the cryosphere shrinks and idiots like the Daily Mail and WUWT talk about "recovery"....

I'll accept this last argument.  I find it well-argued and convincing.  (I would say "perceived sacrifices".)

Over in the Melting thread, Siffy posts some graphs made by Wipneus of sea ice extent in various arctic seas.  The graphs display standard deviation bands assuming the distribution of data points for sea ice extent on a date are normally distributed.  However, the data is fairly clearly not normally distributed.

In hopes of getting at least a short detailed mathematical discussion out of this, I've created this new thread.

Siffy, your question has been mostly answered by others. The grey bands show the average cover with error bands of 1 and 2 standard deviations.
That is ignoring a geographical maximum cover in some region, but also the very skewed behavior of ice cover deviations: negative swings are much larger than positive ones even with no physical maximum's.
Note that just cutting the grey's off is not a sound solution. The possibilities that have been cutoff will have to appear somewhere else, that is in other regions. Before you know it you get into modelling so complicated that it cannot possibly be useful anymore. 

For the sake of simplicity and because such issues are commonly ignored in the field I did choose not to do anything about it. I am open to suggestions though.

The data distribution looks like a response time latency distribution.  An overly quick google search suggests that modeling this as an "Ex-Gaussian" distribution might work.  That still looks a bit complicated to implement.  It's not immediately obvious to me where you would draw the equivalent of the standard deviation bands.

The other approach is to simply draw in the bands given the data and avoid modeling a distribution for it.  (Well, we will still be modeling some sort of distribution, but...)  E.g. Sort the data points.  Find the median.  Find the points that are 1/3rd above and below the median (or choose whatever gradiant seems interesting to draw).  Find the points that are 3% from the top and 3% from the bottom or so.

Perhaps there are too few points (we have, what, 20 or 30?) for this exercise to be sufficiently meaningful, but it should be at least as meaningful as trying to force a normal distribution to the data.

[Edit: seaicesailor gives the same suggestion using simpler language some 8 hours before me, if I would bother to read ahead before responding...]

Arctic sea ice / Models and Math
« on: August 31, 2014, 08:48:20 AM »
The models are tuned over many runs to make them consistent with both science and history.
Much harder, in point of fact, than fitting a curve to some data.
Bruce, I nearly totally agree with you. But keep in mind that "tuning parameters in a model to make it consistent with history" and "fitting a curve to some data" is in every aspect the same thing...

That is reverse physics. Instead of testing the model (which should be a mathematical simplified describtion of some aspects of the nature) and rejecting a model if not fitting to observations you may tune the parameters every year again. There is no real value or deeper understanding of the world gained by doing the latter - that is only usefull for politics or convincing poeple for a very short time (and maybe that ugly standard model, which you could also fit to an elephant...).

The model informs the shape of the curve that you use.  F = m1*m2/d^2 is a model.  You still want to go out and measure m1, m2, and d for a particular application of the model.

That formula is the direct result of a theory. It is not a model. A moel would be to approximate the force and make it constant when distance is very small, to avoid too large errors near the d=0 singularity. That is THE model that can be used in computer simulations. The actual formula cannot be used for many calculations due to its singularity.
Guys please is this stuff for this thread?

Math is a model.  You want to show me where m1 and m2 and d exist in isolation?  When the distance is not very small, the formula is the formula that you would use for many calculations.  Is the distance usually not very small?  Are most pairs of objects in the universe nearly on top of each other?

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