please explain this

Actually the 3 graphs@94 are very helpful. You get a like for posting (though not for whining about being appropriately scolded)

The bottom graph shows the sluggish increase in bottom troposphere humidity since 1948. I hope mojo sees it because he has posted spurious representations of humidity history in the past.

Such a small increase in humidity over time means that rainout must have increased. Because evaporation certainly has done. For me, there is some (possibly very low) limit to high humidity can go, and I wish that I had confidence this is being well handled in models.

Finally explore the units of first and third panels. Stratospheric humidity is 1/40 of troposphere, and that is g/kg. The stratosphere is much less dense. To put a rough number on it, 1/10th. So a square meter of stratosphere has 1/400 the water vapor of such in the troposphere below.

So, while it's good to question what's going on in the stratosphere, friendly-jacek's own graph argues that the troposphere (where water vapor does affect energy balance) is much more important.

Keep 'em coming.

 

NCEP/NCAR reanalysis@96. Excellent. Last time I read about that, they had put no results up. I hope this aspect of NOAA's research is not in funding jeopardy.

 

Bob, the NCEP/NCAR reanalysis take as much global meteorology data as they can find. In this posted example, since 1948. Then they do something akin to the BEST temperature 'proofing' (though I don't know the details). The output can be global composite as here. I recall there would also be gridded (regional) outputs.

I am truly pleased to see this. Somehow missed the memo they were open for business

 

ESRL : PSD : NCEP/NCAR Reanalysis at PSD


(happy happy happy)

 

Me too!

I had independently been puzzling over a long-wave, IR map and could not make sense of what I was seeing. But with your link, it looks like NOAA is making their historical and current data more accessible. In effect, a data portal. So this is one of my finds today:

Source: ESRL : PSD : GISTEMP Surface Temperature Analysis

You can clearly see the El Nino smear off the western coast of South America. Also, the high heat along the North American coast that has dried out California and led to Canadian and Alaskan fires.

It looks like there will be a lot of data mining.

Bob Wilson

 

THE HOCKEY SCHTICK: New paper finds no long-term trend in stratospheric water vapor, IPCC claims opposite

s

 

One of the problems with past postings has been a lack of source data. A pretty picture is flashed as if it means something. So I decided to find the source data for modern CO2, Keeling data, and the ice cores. When I combined them and plotted the graphs correctly, we get:

Driving home, I figured out a better approach (see above) and this is good news and bad news. The good news is showing the overlap of the Mauna Loa and the NOAA paleorecord, there is good agreement. The bad news is these two regional metrics are a little too close. More recent NASA metrics shows there is a distinct difference between Northern and Southern hemisphere CO{2} concentrations. But the NOAA paleorecords incude a mix and if the latter were Greenland, Northern hemisphere, they should match.

Bob Wilson

 

BTW, this same calibration issue needs to be investigates comparing modern temperature records and the proxy isotope records. We'll compare the overlap and determine what calibration is needed to make the modern and proxy data match.

Now I understand why those bogus charts have the time-scale wrong. You really want the most recent data on the left and the oldest on the right with the option to either use a date-range limited, linear x-axis scale or open date-range log scale.

Translation for our less technical folks,

"Lets stand him on his head!" - Firesign Theater, "I think we're all bozos on this bus!"

Bob Wilson

 

blogspot@106 a reference to the published study itself would be appreciated. Can't access the site

Actually there have been more studies of stratospheric water vapor that tropospheric, even though the latter is so much less as I mentioned above. I really don't know why that is. Guessing that the stratosphere is much better spatially mixed, so 'representative' measurements are more easily had.

The troposphere is bottom-bounded by a very heterogenous 'field'.

 

Also @94 I (or we?) were wished good luck predicting clouds (and their climate effects).

Aside from luck, folks do study these things. Here are a few recent ones:

Large contribution of natural aerosols to uncertainty in indirect forcing : Nature : Nature Publishing Group
A simple model of global aerosol indirect effects - Ghan - 2013 - Journal of Geophysical Research: Atmospheres - Wiley Online Library
Natural aerosols explain seasonal and spatial patterns of Southern Ocean cloud albedo | Science Advances

Actually I think clouds deserve a thread here, but hoping that someone else would step up to handle the task.

 

What i don't like about this log-display is it makes the nicely spaced glacial cycles look like noise. On the right in this case

 

It is an artifact of excel. The x-axis left edge is "1" and the bottom y-axis is "1" and both increase by the log values. This is how my slide rule works too but that is not a hard requirement. I've had a circular slide rule in my hands before . . . and loved it.

True enough but you lose the recent scale, the part I find interesting. But effort was to look at how the paleo-record of CO{2} looks compared to current data. Now if there were an independent source of glacial cycles, on the same scale we could see the association. But that is not really the interesting data:

So here we have a 40 year overlap between modern, Mauna Loa and NOAA provided paleo-record but there is a problem. The paleo-record data at the left is on the low side of Mauna and on the right, too often high on the right. Now credible claims can be made about how to deal with this anomaly. In one respect, it can be traced to pessimistic or optimistic values. So this is my opinion . . . someone who is used to dealing with noisy data.

• 1st - 367 ppm @14.5 years
• 1'st - 367 ppm @14.5 years
• 2nd - 330 ppm @43 years
• 2'nd - 325 ppm @43 years
• (325 - 330) / 330 ~= -5/330 = paleo-record is 1.515% too high after 28.5 years

Now there are several independent variables that have to examined. Back of the envelope, the most recent paleo-record, CO{2} reading are off by ~ 1.5% too high.

Bob Wilson

 

Wait, what? Contemporaneous ice-core data more accurate than Keeling's CO2 in the early years? By possibly more than 1 ppm? That is going to be a tough sell. Keeling was a chemstry beast.

Anyway, make your x axis years before 2014. You can't go after one of my demigods and fumble the ball in the same post. I'll not have it.

 

The x-axis scale does not need to be the same everywhere. It only needs to be explicit everywhere.

Paleothermometer - Wikipedia, the free encyclopedia

Also the scale changes can impart some information about uncertainties associated with data (proxies) in different time periods.

 

just to pick the same nit, carbon dioxide concentration should correctly be on a log scale, while time should be on a linear scale to understand, and time should progress left to right. How to lie with statistics 101 points out how to use the wrong scale, but I really don't understand what the chart is trying to lie about, so whoever made it did a bad job if they were trying to lie about something, which I doubt, and doubly wrong if they wanted some connection to be easy to visualize.

I believe the relationship is supposed to be temperature, solar radiation energy, log of carbon dioxide equivalent concentration, versus time. That is difficult so you can adjust temperature for radiation, or .... show it, that way we can see the glacial and interglacial periods clearly and how they relate to green house gasses in the past and today. Alley has made some excellent charts as have others.

SOme have show local charts this way, and its easy to see how local or regional areas can look more or less sensitive to ghg. The climate change theory is global not local. The antarctic temperatures react quite differently than aortic to short term effects, which leaves region charts of say greenland looking like it can prove things about ghg warming that it can not.

For example if I wanted to show that ghg wasn't releated to temperature change, I would show a 20 year plot of temperature and co2 concentration. Or a 20,000 year plot of greenland or antartica. If I wanted to show it was I would do what mann did a 1000 year plot ending in 1998, with yearly temperature grafted onto smoothed paleo data.

If I wanted to actually visualize it though and get a correct answer, I would probably try to get a 500 year record, smooth the last 180 years of temperature and co2 data to a weighted average 30 year (climate and fits the paleo), and plot the co2 on a log scale, and try to show solar radiation estimates as well.

 

Indeed, physics points us to log CO2. But in scientific communication, we ought to 'impedance match' the intended audience as much as possible.

I am much less than certain that general audiences know what mathematical logs are. Teach that here, now, and your message bounces off. And you get scolded later as elitist.

Yet I take the point, and replotting Royer et al. 2004 paleo CO2 as logs is on my to-do list.

The arrow of time: ecologists (being sensible ) always shoot from left to right. Geologists often oppositely for reasons undisclosed. The other common geology approach is 'newest on top', which flips the axes. This can be justified because newest deposition is on the top. However once again, we hope the audience will apprehend some message, so the graphing style had better not require much explanation.

 

There is overlap with the Berkeley Earth, temperature record so we can see the more recent end of the scale and to what extent it overlaps the ice core data.

Geologists have some curious practices when dating the ice core record. We'll leave that as an academic exercise. Hint: January 1, 1950 is special.

BTW, there is a technique I used in the Dashboard report that can solve this problem:

The term is split-scale which is how I plot both the ZVW30 and everyone else in the same chart while letting the fine detail show up for both. The left Y-axis is one scale, the right Y-axis another, but I use a constant offset to the ZVW30 that is plotted on the right axis so both sets show up in the same chart with the fine detail showing the historical changes. A similar technique can be used with the X-axis, time.

I could do a simple split so the left half covers say year 1-150 years and then switch scale for the 150-10,000 year data. Both would be linear yet the split scale would meet my interest, the recent data, versus those fascinated by the paleo-record. However, there is no limit on how to segment the split, linear scales. A semi-log, segmented linear scale would work too:

• 1-10 years - left 1/4
• 10-100 years - next 2/4
• 100-1000 years - next 3/4
• 1000-10000 years - last 4/4

All of this is possible because unlike the OP, I looked for and found the source data used to generate the first, crappy graph. It means we'll each be able to see the parts of the elephant we wish to see along with the transitions between each.

As I've pointed out before, "I see numbers" but in grade school realized not everyone does. However, I can use excel to stitch the data together so others can see a glimpse of my mind's eye:

(Note: this version won't cause our moderators to 'set their hair on fire.')

Bob Wilson

 

Well here is where that little nuance is critical to understanding the physics of green house gasses. I don't think I have ever been called an elitist on a log chart, but ... I have been asked questions. Here the questions should hopefully inform the curious memeber of the general audience. The climate doesn't react to the concentration linearly but to a doubling. We have already experienced a doubling from 200 ppm durning the ice age to 400 ppm today. We don't expect the same temperature rise from 400ppm-600ppm, but need to double it to 800 ppm. We think there has been around 2.8 degrees C of warming in that doubling, so we expect around 3 in going from 400 ppm - 800 ppm. etc. Add in scary bits that man has never been on the planet where it has been 3 degrees warmer, and caveat that we don't really know sensitivity, but think we will get between 1.5 degrees (man lived in this) to 4.5 degrees. 4.5 is even scarier than 3, so we should take some insurance and not double again. etc.
+1

It does make it easier to visualize.

Normally these things are historical, and it makes perfect sence for a geologist 50 years ago to go from newest to oldest as a convention. You could leave some extra room on the right side of your graph, and then add it as we discovered older information. We were adding the past much faster than the future. With the viewing on computer screens instead of paper or projections the overall reason for these conventions goes away and we can focus on understanding, and intuitive charts, not ones that are easy to compare and add to on paper.