Yeah, very promising. Saw projections of 5 cents / kWhr. IF they can hit the numbers, this is a serious ‘game changer’.

2) Researchers at MIT recently discovered a polymer that very efficiently separates H and O from H2O with very low electrical power consumption.

Interesting. Had not heard about it. I presume it is this:

http://www.sciam.com/article.cfm?id=hydrogen-power-on-the-cheap

turned up in a google search. For a ‘downer man…’ point of view, see:

http://www.dailykos.com/story/2008/8/5/143320/8009

Now, the idea. Take #1 to collect electrical power and couple that to #2 to produce hydrogen that one could store almost indefinitely. Obtain an efficient hydrogen combustion electrical generator, and Viola! One could theoretically run their entire household off of the sun in a practical and affordable manner. Then, purchase an electric car, or plug-in hybrid, and you have essentially provided for all of your energy needs indefinitely.

The issues I see:

1) It’s all new. Often the road from idea to product dashes many hopes.
2) You don’t want hydrogen combustion, you want a hydrogen fuel cell. Much better though more expensive.
3) There is an engineering question of what’s more efficient: Plug in HEV or a direct H fuel cell vehicle. Implementation nit at most.

Generally, yes. IFF what they project is valid, you can do this. IF. Hydrogen is not an energy source, but it is an ‘ok’ battery. (Bit low on density and storage either takes BIG tanks, fancy hydrides, or one heck of a lot of pressure or cold. Better for stationary than for vehicles; but workable for both.)

No, I would read the source code to ‘get the full scoop’… Oh wait, I did that already! … see below…

However, what I assume he means is that, yes, there is a positive correlation between the temperature anomaly at one place and the temperature anomaly at another place within a distance of roughly 1000km. That doesn’t mean that stations separated by distances less than that agree perfectly but it does mean that, over such distances, the correlation in the temperature anomalies between two stations tends on average to be positive and statistically significant.

The problem I see in the code is that it doesn’t use ‘correlated’ it uses ‘linear’. That is, there is no scaling for non-linear correlation, a fixed slope is subtracted. This comes in one of two flavors. A single line, or two line segments with a ‘knee’. This, IMHO, is a lethal flaw in GISStemp and explains a lot of the ‘rewrite history by a degree or two in strange ways’ behaviour; especially as it relates to coastal urban areas moderated by the seas when compared to more volatile inland areas. “Damning” doesn’t even come close (IHMO, of course…)

Since most folks don’t really want to see the FORTRAN, I’ll include the comments in it (that do reflect what the code acutally does.) I’ve bolded a couple of interesting bits…

From STEP2 PApars.f file:

C**** The homogeneity adjustment parameters
C**** =====================================
C**** To minimize the impact of the natural local variability, only
C**** that part of the combined rural record is actually used that is
C**** supported by at least 3 stations, i.e. heads and tails of the
C**** record that are based on only 1 or 2 stations are dropped. The
C**** difference between that truncated combination and the non-rural
C**** record is found and the best linear fit and best fit by a broken
C**** line (with a variable “knee”) to that difference series are found.
C**** The parameters defining those 2 approximations are tabulated.
C****
C**** Note: No attempt is made to find the longterm trends for urban
C**** and rural combination separately; using the difference only
C**** minimizes the impact of short term regional events that
C**** affect both rural and urban stations, hence cancel out.

From Step2, PApars script:

if [[ $# -lt 1 ]]
then echo “Usage: $0 source (e.g. GHCN.CL) radius(km) overlap_cond(20)”
exit; fi

rad=1000 ; if [[ $# -gt 1 ]] ; then rad=$2 ; fi
lap=20 ; if [[ $# -gt 2 ]] ; then lap=$3 ; fi

i=”./ANN.dTs.$1″
echo “inputfiles: $i.1-6 rural neighborhood radius:$rad km overlap_cond:$lap”

Also, from the FORTRAN program PApars.f (one of the best commented and best written parts of the FORTRAN code) we have:

C*********************************************************************
C *** unit#
C *** Input files: 31-36 ANN.dTs.GHCN.CL.1 … ANN.dTs.GHCN.CL.6
C ***
C *** Output file: 78 list of ID’s of Urban stations with
C *** homogenization info (text file)
C *** Header line is added in subsequent step
C*********************************************************************
C****
C**** This program combines for each urban station the rural stations
C**** within R=1000km and writes out parameters for broken line
C**** approximations to the difference of urban and combined rural
C**** annual anomaly time series.

What does correlated mean in the sense used in that statement ?

As near as I can tell from the source code, it means that Hansen is quite happy to use the temperature ‘anomaly’ from 1000 km inland to ‘adjust’ the real data from San Francisco. So yes, Loreto Bay tells you everything you need to know about temperature changes in San Jose at the airport…

I’m only about 1/4 through the detailed source review, but the rough pass through the anomaly code looked like they were doing just that kind of thing.

Sidebar: The guy who wrote the only section in Python (STEP1) seems to have a clue how to write production code. IMHO, he ought to have been given a contract to re-write all of it. He even had ‘pride of authorship’ enough to put his name in the comments in the code that GISS publishes.

The name was found in the “C” extension (also well written) for Python in that section. Assuming he’s the guy who wrote all of it:

Kudos to: Jay Glascoe, SSAI, NASA/GISS

Professional job.

(That does not mean I endorse the ideas that the code embodied. It does mean that he writes good, clean, tight code and I’d hire him in a heartbeat.)

Now if only the FORTRAN were as well done… and the ideas behind it…

Sounds like a cheech and chong movie! lol

Hehe, Sorry just a silly joke. :)

Off topic, here’s one to ponder,

It’s said that the moon controls the tides and gets it’s reflection from the earth and is always facing the one side to earth, it’s just the angle you look at it that makes it a full moon/new moon on it’s cycle.

That doesn’t make sense to me, and like Venus, I belive the moon bright side always points toward the sun. You can see it just with impact craters from dark to bright side. Tons of deep impacts holes on the dark side and smoothed out craters on the bright side. The sun controls the moon and pulls it away at 1/2 inch(or so, or was it 1cm?lol) a year.

Ever wonder why there is two tides in a day, one small and one large?

A smaller lunar and a larger solar tide, extreme tides happen on the full moon/new moon.

That pesky sun trying to control us again. ; )

Oh and yes, I’m a fountain of useless knowledge . lol

“… the danger that we face is the Venus syndrome. There is no escape from the Venus Syndrome. Venus will never have oceans again. … If the planet gets too warm, the water vapor feedback can cause a runaway greenhouse effect. The ocean boils into the atmosphere and life is extinguished.” “””

Mmmm, now let’s compare Earth’s situation to that of Venus:

1. Avg distance from the Sun for Earth = 93,000,000 miles, for Venus = 67,000,000 miles; so Venus is around about 26,000,000 miles closer to the Sun than we are…now that’s going to give you one hell of a sun tan.

2. Earth’s rotation about its own axis (an Earth day) approx 24 hours, or 1/365th of it’s year. Keeps things nice and fresh. Venus’ rotation about its own axis (a Venutian day) approx 240 (earth) days or approx one Venutian year. What does this mean? Effectively Venus presents the same side to the sun all year (almost), now that’s going to cause some interesting weather effects with one half baking and one half not…

Cheers

Mark.

Again – that is his opinion. I think he would have a tough time proving his statements in a court of law. So the context doesn’t change my opinion. Others can decide for themselves as the link is there to the letter.

Anyway, the heat is on – see the latest post. No statement here as I will have to see the context. :]

Want to get rid of a lot of “excess human heat sources”? Get rid of the pollution standards and all the excess government red tape that produces nothing useful. Only 11% of employed Americans produce the rest shuffle paper or sell Chinese goods. Sounds like a good place to start making humans more efficient doesn’t it.

Steve Hempell says:

This is a quote from Hansen’s PDF document :
Global Warming Twenty Years Later: Tipping Points Near James Hansen

“In my opinion, these CEOs should be tried for high crimes against humanity and nature.”

http://www.columbia.edu/~jeh1/2008/TwentyYearsLater_20080623.pdf

I understand this as – It is his opinion, that if these CEOs disagree with the science he presumes to be correct, then they should be incarcerated.

I interpret it differently in the context of the full quotation, which is this:

Special interests have blocked transition to our renewable energy future. Instead of moving heavily into renewable energies, fossil companies choose to spread doubt about global warming, as tobacco companies discredited the smoking-cancer link. Methods are sophisticated, including funding to help shape school textbook discussions of global warming.

CEOs of fossil energy companies know what they are doing and are aware of long-term consequences of continued business as usual. In my opinion, these CEOs should be tried for high crimes against humanity and nature.

The keys to me are the comparison to the tobacco companies and the statement that the “CEOs of fossil energy companies know what they are doing and are aware of long-term consequences of continued business as usual”. The presumption Hansen is making, presumably, is that this knowledge on their part and willful deceit can be proven in court as it could for the tobacco companies. So, what I think he is trying to say is that they don’t really disagree with him on the science but, just as with the tobacco companies, they know what the science really says but are actively distorting it anyway.

At any rate, we don’t disagree that much because I have said that I don’t like this statement by Hansen either. But, I do think it is important to interpret it in the full context of what he actually wrote so that one doesn’t claim he said things that I don’t think he really said.

This is a quote from Hansen’s PDF document :
Global Warming Twenty Years Later: Tipping Points Near James Hansen

“In my opinion, these CEOs should be tried for high crimes against humanity and nature.”

http://www.columbia.edu/~jeh1/2008/TwentyYearsLater_20080623.pdf

I understand this as – It is his opinion, that if these CEOs disagree with the science he presumes to be correct, then they should be incarcerated.

I think if you read the full q

And thanks for the clarification on the reason for anomalies. I can’t say I agree with the concept though.

If the mean global surface temperature (if you could measure it) were plotted on a graph with a temperature scale that goes from -90C to +60 C as does the local instantaneous surface temperature on even one day in the real world; perhaps we wouldn’t have all this ruckus of people trying to make us believe that something untoward is actually happening.

But I’m also concerned that since radiative cooling of the planet’s surface follows along a generally 4th power of temperature relationship, and that the relative importance of any single GHG particularly CO2, relates more to the peak of the spectral emittance curve rather than the integral of it; which goes as the 5th power of the temperature, and invokes the Wien displacement of that peak from the GHG absorption line as well; then I can’t look on it as a quantitative science to fall back on changes in small differences; which is a differential process, well known for increasing noise in signal.

Thanks for the references.

George

There are many scientists with credentials more pertaining to the study of Climate than he is (He is a astrophysicist) who disagree with the science of CO2 causing catastrophic climate change. Who is he to make such a asinine statement!!

This is what gets me about people complaining that Steve McIntyre isn’t a climatologist, or that Anthony is “Only a TV meteorologist”, and therefore their opinions don’t matter.

Joel Shore (08:54:16) :

You are missing the whole point of that page which is that the reason to study anomalies rather than absolute surface air temperatures is exactly all of these problems that exist if you try to look at absolute surface air temperatures. This is well-explained on the main GISTEMP page from which the link to the discussion of the problems with absolute SATs that you quoted from originates ( http://data.giss.nasa.gov/gistemp/ ):

No, I understood the point of the page. My point is that the underlying methodology for obtaining the anomalies (via absolute temp measurements) can’t even be quantified by Hansen. So the anomaly starting point is flawed in the first place.

“And, Hansen did not say people should be incarcerated if they disagree with him. He made a particular comment about fossil fuel company executives and his point was, as I understand it, was analogous again to the cigarette case: If it can be shown that they knew the scientific evidence was saying one thing but continued to claim otherwise and thus delayed action and caused harm then they should be held liable.”

This is a quote from Hansen’s PDF document :
Global Warming Twenty Years Later: Tipping Points Near James Hansen

“In my opinion, these CEOs should be tried for high crimes against humanity and nature.”

http://www.columbia.edu/~jeh1/2008/TwentyYearsLater_20080623.pdf

I understand this as – It is his opinion, that if these CEOs disagree with the science he presumes to be correct, then they should be incarcerated.

There are many scientists with credentials more pertaining to the study of Climate than he is (He is a astrophysicist) who disagree with the science of CO2 causing catastrophic climate change. Who is he to make such a asinine statement!!

I guess we should agree to disagree. Believe it or not, I am agnostic on this and I am tying to be patient enough to see where the data takes us. However, that may not be until after I’m pushing up daisies.

Regarding particle physics. Ya, string theory seems a little flaky to me too. However, the Standard Model (as Pollack says should be Standard Theory) seems pretty solid to me being that the mathematics seems capable of making predictions and gives accurate results.

The first paragraph (i.e. the unindented one) is my words and the second paragraph (i.e. the indented one) is Hansen’s.

The bottomline as I see it is this: If you plot absolute surface temperatures as a function of location, this 2-dimensional field will not have very “nice” characteristics. For example, if you are in a mountainous region, the surface temperature will vary wildly with location. Think of such a plot near Mt. Washington: the weather station at the top of the mountain will have a vastly different temperature than one located in a valley only a few miles away. Even if surface topography is not strongly varying, you can still get other effects, e.g. due to a nearby body of water or river.

However, the temperature anomaly, i.e., the surface temperature minus the average surface temperature (over some, say, 30 year period) will have much nicer characteristics. Hence, this is the variable that one should focus on.

And just what is meant by correlated out to distances of 1000 km. Does that mean that what happens here in down town San Jose, a quarter mile from the international airport, is representative of what is going on in the Sea of Cortez off Santa Rosalia, or meybe even Loreto Bay ?

What does correlated mean in the sense used in that statement ?

Well, I would recommend reading the reference that Hansen cites if you want to get the full scoop. However, what I assume he means is that, yes, there is a positive correlation between the temperature anomaly at one place and the temperature anomaly at another place within a distance of roughly 1000km. That doesn’t mean that stations separated by distances less than that agree perfectly but it does mean that, over such distances, the correlation in the temperature anomalies between two stations tends on average to be positive and statistically significant.

See, for example, here for a general tutorial on measuring such correlations: http://en.wikipedia.org/wiki/Correlation Tamino had a couple of posts about these correlations in temperature anomalies, the latter of which is here (with a link to the earlier one): http://tamino.wordpress.com/2007/04/15/temperature-records-of-the-week-shelby-county-tennessee/ I seem to also recall a very nice correlation map presented somewhere…I thought it was at Tamino’s blog but I can’t seem to find it.