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Sunday, July 19, 2020

(B) A study that 'proves' the obvious

Geophysical Research Letters
Volume 47, Issue 12

Climate Model Projections 
of 21st Century Global Warming 
Constrained Using the 
Observed Warming Trend
by Yongxiao Liang
E-mail address: yongxiao@uvic.ca
https://orcid.org/0000-0003-3162-1494

School of Earth and Ocean Sciences, 
University of Victoria, Victoria, 
British Columbia, Canada



SUMMARY:
This study is not 
a wild guess about 
the future ...
( the usual
nonsense. )

But it states
the obvious.

The obvious 
does not require
any study.

Who pays for this ?

The Obvious Conclusion:
  If you examine a large
batch of climate models,
and then toss aside
those that had been 
making the worst 
predictions
(predicting far too 
much global warming ), 
then the remaining 
models will seem 
more "accurate".

I didn't need to read
a study to know that.

How about eliminating
every climate model,
except the Russian
model, that predicts 
mild global warming
and "seems" to be 
quite accurate ?

I call it the Russian
"no thinking model"
 -- it seems to assume
past mild global warming
will continue indefinitely.

It's already been happening
for about 325 years, so that
seems like a safe bet !


DETAILS:
Observed (measured) 
warming trends 
for the post‐1970s period 
may be a good metric 
to better projected 
future warming. 

The Coupled Model 
Inter-comparison Project 
Phase 6 (CMIP6) archive 
includes larger ensembles, 
longer historical simulations, 
and models with a broader 
range of climate sensitivity 
than CMIP5.

Different climate models 
dict different amounts 
of future warming 
over the 21st century. 

Most previous studies 
have weighted models 
equally to derive 
a range of projected 
future warming. 

That sums 
of the "wild guesses" 
of climate change 
when no one knows 
which mode is best.

That makes sense, 
because every model 
is a different guess 
about the effect of
(mainly) carbon dioxide 
on the future global 
average temperature.

This study gives more weight 
to models that were better able 
to match the observed 
1970–2014 warming trend. 

This approach substantially 
reduces the upper bound 
of projected warming 
over the 21st century.

The Fifth Assessment Report 
                  (AR5) 
of the Intergovernmental 
Panel on Climate Change 
                  (IPCC) 
included a range of model 
projections of long‐term warming 
without any performance‐based 
weighting (Collins et al., 2014). 

Projections in the IPCC's 
Sixth Assessment Report  
                (AR6) 
will be based largely on 
CMIP6 (Eyring et al., 2016)

Compared to CMIP5, 
the number of different models,
model variants, and ensemble 
sizes of individual models 
have all increased in CMIP6. 

Future scenario simulations
in CMIP6 were coordinated 
by the ScenarioMIP project 
(O'Neill et al., 2016) 
and are driven by a 
new set of emissions 
and land use scenarios, 
known as Shared 
Socioeconomic Pathways 
(SSPs) (Riahi et al., 2017)

Some new CMIP6 models 
show higher transient 
climate response
           (TCR) 
and equilibrium 
climate sensitivity 
           (ECS)
compared with previous
versions of these models 
in CMIP5,
(Gettelman et al., 2019; 
Sellar et al., 2019; S
wart et al., 2019; 
Voldoire et al., 2019; 
Zelinka et al., 2020)

An unweighted ensemble 
of climate models 
to make projections, 
as not all models
 are equally skillful 
in reproducing 
observations 
(Brunner et al., 2019; 
Gillett, 2015; 
Knutti et al., 2017; 
Lorenz et al., 2018)

Historical model simulations
(1850–2014) and projections 
(2015–2100) of climate change 
under each of the Tier 1 
SSP scenarios are used 
in this study 
(O'Neill et al., 2016; 
Riahi et al., 2017). 

Thirty models with up to 
50 ensemble members each 
are included in the analysis. 

The study focuses on 
changes in monthly‐mean 
global‐mean near‐surface
 air temperature (GSAT)
in historical and 
future periods. 

The HadCRUT4 data set 
consists of monthly 
historical instrumental
temperature records, 
combining sea surface 
temperature data 
from the UK Met Office 
Hadley Centre with 
land surface air 
temperature records 
from the University of 
East Anglia Climatic 
Research Unit (CRU).