This is likely caused, in part, by GISS masking sea surface temperature data in the polar oceans and replacing it with
land surface air temperature data, which is naturally more volatile.
They then infill the Arctic and Southern Oceans with
land surface air temperature data.
Not exact matches
For their paper, published in Applied Geography, researchers at the Earth Institute at Columbia University and Battelle Memorial Institute studied
air temperature data from weather stations,
land surface temperatures measured by satellites and socioeconomic
data.
So the infilled GISS
data, which extends out over the Arctic, would show the greater warming since the 1970s... until the warming stops for Northern Hemisphere sea
surface temperatures and for the low - to - mid latitude
land surface air temperatures.
The hybrid method used by Cowtan and Way (2013) fills in missing
data (both
land air and sea
surface temperature) using lower troposphere
temperature data from UAH.
It's hard to imagine how Cowtan and Way could determine with any degree of certainty how «the hybrid method works best over
land and most importantly sea ice» when there is so little
surface air temperature data over sea ice.
These issues, which are either not recognized at all in the assessments or are understated, include: - the identification of a warm bias in nighttime minimum
temperatures - poor siting of the instrumentation to measure
temperatures - the influence of trends in
surface air water vapor content on
temperature trends - the quantification of uncertainties in the homogenization of
surface temperature data, and the influence of
land use /
land cover change on
surface temperature trends.
HadSST3, HADISST and ERSST.v3b, all include bucket model adjusted ICOADS
data, and HADCRUT4 is «a blend of the CRUTEM4
land -
surface air temperature dataset and the HadSST3 sea -
surface temperature (SST) dataset.»
The
surface data (left panel) are comprised of
surface air temperature over
land and the
temperature of water at the ocean's
surface, and have been subjected to a slight additional smoothing to simplify the pattern (Jones et al., 1999).
To clarify,
land temperature anomalies are recorded as
surface air temperature, but ocean
temperature records are a more complex function that I believe also incorporates
data from the water
surface itself.
«Causes of differences in model and satellite tropospheric warming rates» «Comparing tropospheric warming in climate models and satellite
data» «Robust comparison of climate models with observations using blended
land air and ocean sea
surface temperatures» «Coverage bias in the HadCRUT4
temperature series and its impact on recent
temperature trends» «Reconciling warming trends» «Natural variability, radiative forcing and climate response in the recent hiatus reconciled» «Reconciling controversies about the «global warming hiatus»»
Figure 2.4 (Folland et al., 2001) shows simulations of global
land -
surface air temperature anomalies in model runs forced with SST, with and without bias adjustments to the SST
data before 1942.
aaron, all three datasets start with the same source
data:
land surface air temperatures and sea
surface temperatures.
NASA Earth Observatory images by Jesse Allen, using
AIRS Land Surface Temperature data provided courtesy of the
AIRS team.
Combining this
data with
surface air temperature over
land would avoid the problem identified by Cowtan and Way.
Therefore, in contrast to the Jones et al. (2001) global
land -
surface air temperature data, the global
land and sea
surface temperature data are not a simple average of the hemispheres.