A new book by a Japanese climate scientist explains why the predictions of climate models are useful but insufficiently reliable for large scale public policy action. None of this is new information. None of it is widely known.
Excerpts from Confessions of a climate scientist (2019)
By Mototaka Nakamura.
He wrote an introduction and summary in English for a Kindle version of his Japanese book. This excerpt show some of his findings and explanations.
Read the e-book to see his detailed and technical analysis, and his references.
Climate simulation models are fine tools to study the climate system, so long as the users are aware of the limitations of the models and exercise caution in designing experiments and interpreting their output. In this sense, experiments to study the response of simplified climate systems, such as those generated by the “state-of-the-art” climate simulation models, to major increases in atmospheric carbon dioxide or other greenhouse gases are also interesting and meaningful academic projects that are certainly worth pursuing. So long as the results of such projects are presented with disclaimers that unambiguously state the extent to which the results can be compared with the real world, I would not have any problem with such projects. The models just become useless pieces of junk or worse (worse, in a sense that they can produce gravely misleading output) only when they are used for climate forecasting.
All climate simulation models have many details that become fatal flaws when they are used as climate forecasting tools, especially for mid- to long-term (several years and longer) climate variations and changes. These models completely lack some of critically important climate processes and feedbacks, and represent some other critically important climate processes and feedbacks in grossly distorted manners to the extent that makes these models totally useless for any meaningful climate predictions. …
Measuring global temperature.
A quasi-global observation system has been operating only for 50 years or so, since the advent of artificial satellite observation. Temperature data before then were collected over extremely small (with respect to the earth’s entire surface area) areas and, thus, have severe spatial bias. We have an inadequate amount of data to calculate the global mean surface temperature trend for the pre-satellite period. …