Backradiation - fixing the effect of 2 variables plotting the third

Up to now I've plotted the effect of cloud coverage, humidity and temperature on the difference between DLWIR and ULWIR.

However these plots are not a simple xy since there may be a correlation between temperature/humidity and clouds.

To improve the plots it would be best to plot for example humidity vs dlwir/ulwir at a fixed temperature and cloud cover. The problem is there are too few corresponding points to get a meaningful result.

The following plots were made by inspecting plots and choosing a range of values for each parameter where the dlwir/ulwir change is minimal (about 10% or less)

As a trial cloud coverage was replotted at a much closer variation in the other 2 parameters - this shows a good correspondance with the wider variation but with increased variability.

It should be pointed out that the dlwir as a % of ulwir is a combination of at least all the 3 parameters considered. All that can be gleaned from these plots is the effect of variation of  one parameter whilst holding the others static.

It should be noted that cloud cover is only measured during daylight. All the plots below are therefore only relevant for daylight.

From the above it can be seen that the:

temperature effect is inconsistent and small

relative humidity is the largest effect - more humidity more DLWIR

Cloud cover is significant - more clouds more DLWIR



More on Bart, FFTs and Cloud vs temperature

To me it seems that the plot has been lost on CA were discussions revolve around FFTs iFFT convolutions etc.

Is there a relation ship between cloud (Net_tot-SW_clr) and temperature or temperature and cloud?

How about a few simple plots:

The first uses data filtered with a Hodrick-Prescott filter of 1 and plots temperature anomaly against (Net_tot-SW_clr) sorted .

The second removes any filtering:

As can be seen the is a slight rising trend.

So now reverse the axis and plot cloud cover vs temperature anomaly (sorted) These are Duff!!

So there does seem to be a temperature and  (Net_tot-SW_clr) relationship. But which is the forcing????

WUWT - A science blog of note

In entry:
Rebuttal to the Skeptical Science “Crux of a Core”

Posted on March 1, 2011 by Anthony Watts
Guest post by Dr. J Storrs Hall

http://wattsupwiththat.com/2011/03/01/rebuttal-to-the-skeptical-science-crux-of-a-core/

There is this gem of a scientific annotation to this graph:

(This is GISP2 in green, NGRIP, another Greenland core, in cyan, and the Vostok Antarctic core in blue. The Vostok has been scaled and shifted for a best match with the others; the temperature in Antarctica is colder, with smaller variations, than in Greenland. Furthermore, there are some time-scaling issues — note the temporal divergence of the two Greenland records before about 40 kya. It’s possible that NH/SH actually match better than this plot indicates.  Look here for data.)
 
Consider the supposed desecration of science of hide the decline - see earlier post
 
Storrs Hall
has invisibly shifted a whole data set in time.
has changed the data scaling of a data set
Has used 2 locations on the globe only to prove that AGW is a fraud.
 
Not one post points this out!!!!!!

Scafetta on 60 year climate oscillations

From the paper comes this plot:

Compare this to the HADCRUT 3V plot:

By filtering the temperature all the low frequency uplift since the 60s has been lost.
What therefore, has caused the recent warming?
According to the plot the last 10 years should have been cooling and the next 10 should see a 1C warming.
If I remember correctly the last 10 years have been stable and not reduced by 1C. If Scafetta is correct the world should be 2C hotter by 2025. Is this not a bit worrying?
and
WHY is the Scafetta plot so different to the HADCRU3V?????

OK so now add a 15 to 25 year filter and whats the comparison like?

Certainly a better fit but the trace obtained by filtering (red) is not what Scafetta gets (black). Also looking at the extreme s the temperature is loosing sync with SCMSS.

Correlation between LOD and SSN???????

WUWT posts that there is a correlation between length of day and Sun Spot Number

My response:

Not sure were all the data in the header comes from but this is the plot I get for LOD and SSN

There seems to be no correlation worthy of note.

This is their take on it:

LOD here

http://hpiers.obspm.fr/eop-pc/

SSN here

ftp://ftp.ngdc.noaa.gov/STP/SOLAR_DATA/SUNSPOT_NUMBERS/MONTHLY