Not 2 Green

 

 January 2nd, 2021 by Roy W. Spencer, Ph. D.

The Version 6.0 global average lower tropospheric temperature ( LT ) anomaly for December, 2020 was + 0.27 deg. C, down substantially from the November, 2020 value of + 0.53 deg. C .

2020 ended as the 2nd warmest year in the 42-year satellite tropospheric temperature record at + 0.49 deg. C, behind the 2016 value of + 0.53 deg. C.

Cooling in December was largest over land, with 1-month drop of 0.60 deg. C, which is the 6th largest drop out of 504 months. This is likely the result of the La Nina now in progress.

The linear warming trend since January, 1979 remains at + 0.14 C / decade ( + 0.12 C / decade over the global-averaged oceans, and + 0.18 C / decade over global-averaged land ).

Not 2 Green  |  Busted !

The ecos ( Leftists, enviros, greens, fascists ) always fail to provide concrete empirical evidence of “misinformation of opposing views” or data to support their insane positions because none exist …

Solar, wind and biofuels are insanely expensive, intermittent, unreliable, diffuse and have laughable energy densities, such sources will never replace conventional ( hydro, nuclear or hydrocarbon ) energy sources. 

Hard empirical evidence, simple physics, logic and common sense overwhelming show solar, wind and biofuels are completely incapable of replacing fossil fuels and nuclear power.

Because of the Left’s Cancel Culture, any opposing views they don’t like ( not that they’re false or unsupported ) are censored and the people espousing opposing views are personally attacked and often ruined for no good reason.

Those ecos believe the mere repetition of lies somehow magically make their absurd lies true ...

Not 2 Green  |  CLIMATE MODEL REVIEW

Since we don’t know future atmospheric CO2, volcanic eruptions, and whatever “ other climate drivers ” should be put into the IPCC models,  why are we using these models to set policy ?

1992  IPCC Supplement, Policymaker Summary of Working Group I
          (First Scientific Assessment of Climate Change)
Section 5.2, page 75

Although  scientists  are  reluctant  to give a single best estimate in this range,  it is necessary  for  the  presentation  of climate predictions  for  a choice of best estimate to  be  made. Taking into account  the model  results,  together with  observational  evidence  over  the  last  century  which is suggestive  of  the  climate  sensitivity being  in the  lower half of  the  range,   (see   section: " Has  man  already  begun  to change global climate ? ")  a value of climate sensitivity of 2.5°C  has  been  chosen  as  the  best  estimate ( for a doubling of CO2 ).
In   this  Assessment,   we  have  also  used  much  simpler  models,  which  simulate  the  behaviour  of  GCMs,   to  make  predictions  of  the  evolution  with  time  of global temperature  from  a  number  of emission  scenarios.   These  so-called  box-diffusion  models  contain  highly simplified  physics  but  give similar results  to GCMs  when  globally  averaged. 

1996  IPCC Second Assessment Full Report, The Science of Climate Change,
          Section 6, page 24

In particular, to reduce uncertainties further work is needed on the following priority topics:
Representation of climate processes in models, especially feedbacks associated  with  clouds,  oceans,  sea  ice  and  vegetation,  in  order  to improve projections of rates and regional patterns of climate change.

2001  IPCC Third Assessment Report, The Scientific Basis
          14 - Advancing Our Understanding
Page 774, 2nd column, top :  14.2.2.2 Balancing the need for finer scales and the need for ensembles

In sum, a strategy must recognize what is possible. In climate research and modelling, we should recognize that we are dealing with a coupled non-linear chaotic system, and therefore that the long-term prediction of future climate states is not possible. The most we can expect to achieve is the prediction of the probability distribution of the system’s future possible states by the generation  of  ensembles  of  model  solutions.

2007  IPCC Fourth  Assessment Report, The Physical Science Basis
          8  Climate Models and their Evaluation
Frequently Asked Questions  8.1,   Page  601  bottom of 1st column

Nevertheless, models still show significant errors. Although these  are  generally  greater  at  smaller  scales,  important  large-scale  problems  also  remain.  For  example,  deficiencies  remain  in  the  simulation  of  tropical  precipitation,  the  El  Niño-Southern  Oscillation  and  the  Madden-Julian  Oscillation  (an  observed  variation  in  tropical  winds  and  rainfall  with  a  time  scale  of  30  to  90  days).  The  ultimate  source  of  most  such  errors is that many important small-scale processes cannot be represented  explicitly  in  models,  and  so  must  be  included  in  approximate  form  as  they  interact  with  larger-scale  features.  This is partly due to limitations in computing power, but also results  from  limitations  in  scientific  understanding  or  in  the  availability of detailed observations of some physical processes. Significant uncertainties, in particular, are associated with the representation of clouds, and in the resulting cloud responses to climate change. Consequently, models continue to display a substantial range of global temperature change in response to specified greenhouse gas forcing  (see Chapter 10). Despite such uncertainties, however, models are unanimous in their prediction of substantial climate warming under greenhouse gas increases,  and  this  warming  is  of  a  magnitude  consistent  with  independent estimates derived from other sources, such as from observed climate changes and past climate reconstructions.

2013  IPCC Fifth Assessment Report, The Physical Science Basis
          9 Evaluation of Climate Models
Frequently Asked Questions  9.1,  Page 824, 3rd paragraph

Are Climate Models Getting Better, and How Would We Know ?
Climate models of today are, in principle, better than their predecessors. However, every bit of added complexity, while intended to improve some aspect of simulated climate, also introduces new sources of possible error ( e.g., via uncertain parameters ) and new interactions between model components that may, if only temporarily, degrade a model’s simulation of other aspects of the climate system. Furthermore, despite the progress that has been made, scientific uncertainty regarding the details of many processes remains.