Reconciling Model-Observation Reconciliations
Christy and Roy Spencer have frequently shown a graphic which purports to show a marked discrepancy between models and observations in tropical mid-troposphere, while, on the other hand, Zeke Hausfather, among others, have shown graphics which purport to show no
discrepancy whatever between models and observations. I’ve commented on this topic on a number of occasions over the years, including two posts discussing AR5 graphics (here, here) with an update comparison in 2016 (here) and in 2017 (tweet).
There are several moving parts in such comparisons: troposphere or surface, tropical or global. Choice of reference period affects the rhetorical impression of time series plots. Boxplot comparisons of trends avoids this problem. I’ve presented such boxplots in the past and update for today’s post.
I’ll also comment on another issue. Cowtan and Way argued several years ago that much of the apparent discrepancy in trends at surface arose because the most common temperature series (HadCRUT4,GISS etc) spliced air temperature over land with sea surface temperatures. This is only a problem because there is a divergence within CMIP5 models in trends for air temperature (TAS) over ocean and sea surface temperature (TOS). They proposed that the relevant comparandum for HadCRUT4 ought to be a splice as well: of TOS over ocean areas and TAS over land. When this was done, the discrepancy between HadCRUT4 and CMIP5 models was apparently resolved.
While their comparison was well worth doing, there was an equally logical approach which they either didn’t consider or didn’t report: splicing observations rather than models. There is an independent and long-standing dataset for night marine air temperatures (ICOADS). Combining this data with surface air temperature over land would avoid the problem identified by Cowtan and Way. Further, NMAT data is relied upon to correct/adjust inhomogeneity in SST series arising from changes in observation techniques, e.g. Karl et al 2015:
previous version of ERSST assumed that no ship corrections were necessary after this time, but recently improved metadata (18) reveal that some ships continued to take bucket observations even up to the present day. Therefore, one of the improvements to ERSST version 4 is extending the ship-bias correction to the present, based on information derived from comparisons with night marine air temperatures.Thus, there seems to be multiple reasons to look just as closely at a comparison resulting from this approach, as one from splicing model data, as proposed by Cowtan and Way. I’ll show the resulting comparisons without prejudging. Troposphere Spencer and Christy’s comparisons are for satellite data (lower troposphere.) They typically show tropical troposphere, for which the discrepancy is somewhat larger than for the GLB troposphere (shown below.) The median value from models is 0.28 deg C/decade, slightly more than double observed trends in UAH (0.13 deg C/decade) or RSS version 3.3 (0.14 deg C.) RSS recently adjusted their methodology resulting in a 37% increase in trend (now 0.19 deg C/decade.) The UAH and RSS3.3 trends are below all but one model-run combinations. Even the adjusted RSS4 trend is less than all but two (of 102) model-run combinations.





- According to models, tropospheric trends should be greater than surface trends. This is true over ocean, but not over land. Does this indicate that the surface series over land may have baked in non-climatic factors, as commonly argued by “skeptics”, such that the increase, while real, is exaggerated?
- According to models, marine air temperature trends should be greater than SST trends, but the opposite is the case. Does this indicate that SST series may have baked in some non-climatic factors, such that the increase, while real, is exaggerated?