That was an educational link. Thanks. I might turn from nuclear engineer to statistician yet (give or take a decade).

More of those educationa statistical links, please.

John

The uncertainty in 1°x1° regional LW clear-sky TOA flux is determined from calibration
uncertainty, error in narrow-to-broadband conversion, ADM error, time-space averaging, and
scene identification. For CERES, calibration uncertainty is 0.5% (1σ), which for a typical global
mean clear-sky LW flux corresponds to ≈1 Wm-2. Figs. 2a and 2b show the regional distribution
of the correction used to correct for regional narrow-to-broadband error. This is derived by
applying narrow-to-broadband regressions to MODIS infrared radiances for completely cloud3
free CERES footprints and then comparing the estimated broadband flux with CERES. The
overall bias is -0.5 Wm-2 and the regional RMS difference is 2.5 Wm-2. Assuming a 50% error in
the correction, the narrowband-to-broadband contribution to regional uncertainty becomes 1.74
Wm-2. For clear-sky LW TOA flux, ADM error contributes 0.7 Wm-2 to regional RMS error
(Loeb et al., 2007), and time-space averaging adds 1 Wm-2 uncertainty. The latter assumes zero
error over ocean (i.e., no diurnal appreciable diurnal cycle in clear-sky LW) and a 3 Wm-2 error
in the half-sine fit over land and desert (Young et al., 1998). In EBAF, “clear-sky” is defined as
cloud-free at the MODIS pixel scale (1 km). A pixel is identified as clear using spectral MODIS
channel information and a cloud mask algorithm (Minnis et al., 2011). Based upon a comparison
of LW TOA fluxes for CERES footprints identified as clear according to MODIS but cloudy
according to CALIPSO, and TOA fluxes from footprints identified as clear according to both
MODIS and CALIPSO, Sun et al. (2011) found that footprints with undetected subvisible clouds
emit 5.5 Wm-2 less LW radiation compared to completely cloud-free footprints, and occur in
approximately 50% of footprints identified as clear by MODIS. This implies an error of 2.75
Wm-2 due to misclassification of clear scenes. The total error in TOA outgoing clear-sky LW
radiation in a region is sqrt(12+1.742+0.72+12+2.752) or approximately 3.6 Wm-2.

http://ceres.larc.nasa.gov/cmip5-data/Tech-Note_rlutcs_CERES-EBAF_L4_Ed2-6_20110809.pdf

So at least part of the figure is assumed, through choice of one of several ADM errors (Angular Distribution Model). Will be interesting to see this reference Loeb, N.G., S. Kato, W. Su, T. Wong, F.G. Rose, D.R. Doelling, and J. Norris, 2011: Advances
in understanding top-of-atmosphere radiation variability from satellite observations. Surveys
Geophys. (submitted).

http://climateaudit.org/2011/09/13/some-simple-questions/#comment-303183

Arthur Dent tore up the bit of paper with the answer to “the fundamental question of life the universe and everything” on it. When they patched it back together, they apparently failed to notice the decimal point.

The white mice presumably were well aware of all this but continue to observe the human race running round in circles trying to work out for themselves.

If they read the peer-review literature, they must be pissing themselves laughing.

http://tinypic.com/r/fth5vk/7

+ve lag shows radiation leading temperature and the oscillatory nature is what would be produced by -lambda.dT negative feedback.

zero lag corresponds to the in phase (plank) response of radiation to temperature. Don’t be fooled by the regression “slope” being 1.5 . The error in doing that is incorrectly calling the ols regression estimate “slope”. OLS estimator will be attenuated by the non linear signal, in this case roughly equal to it in amplitude and contaminated by non-zero correlation of the oscillatory component.

The negative side shows rad lagging temp , the zero crossing probably answers Qu2.

There could be some discussion about lags between SST and the UAH measured temps seen here. There seems to be too much crud affecting surface temperature records to get this kind of clear result.

So Steve, does that tie in with what you have found?