All model and observed data have same
spatial coverage as HadCRUT4.
Not exact matches
First impressions are that this has a number of artifacts in it likely due to inhomogeneities in the satellites (varying levels of
spatial coverage through time
as satellites drop in or out).
But the bias uncertainty is smaller than the errors which are not persistent in time (e.g. due to incomplete
spatial coverage), so I don't think accounting for this would make much difference,
as Victor suggests.
To make use of that potential we would need good estimates of sea ice thickness, such
as might be obtained from ICESat or CryoSat (i.e., complete
spatial coverage).
«Bias might be introduced in cases where the
spatial coverage is not uniform (e.g., of the 24 original chronologies with data back to 1500, half are concentrated in eastern Siberia) but this can be reduced by prior averaging of the chronologies into regional series (
as was done in the previous section)... Eight different methods have been used... They produce very similar results for the post-1700 period... They exhibit fairly dramatic differences, however, in the magnitude of multidecadal variability prior to 1700... highlighting the sensitivity of the reconstruction to the methodology used, once the number of regions with data, and the reliability of each regional reconstruction, begin to decrease.
«The addition of buoy data in recent decades has been particularly important
as the
spatial coverage from ship observations has decreased since the 1990's (cf. Fig. 1 (a) in (13)-RRB-.
The difference in the latter aspect is most likely due to improvement in the
spatial — temporal
coverage of the data used in this study,
as well
as the details of data processing procedures.
Going back further there are increasing uncertainties due to lower
spatial coverage, even more so
as you head into proxy data.
* In February, 2006 NCDC transitioned to the use of an improved Global Land and Ocean data set (Smith and Reynolds analysis (2005)-RRB- which incorporates new algorithms that better account for factors such
as changes in
spatial coverage and evolving observing methods.
There is no point is asking about Antarctic temperature change based on just one weather station, such
as South Pole, because that weather station has errors (that's inevitable) and because it isn't going to be very representative — one station gives you indadequate
spatial coverage.
VIIRS will also dramatically improve on MODIS and SeaWiFS
spatial resolution (via a patented OLS - like17 detector aggregation technique) and global
coverage (via a 40 percent wider imaging swath), while offering comparable absolute radiometry and sensitivity
as well
as the long - term stability required by the IORD to support CDRs.