I'm sorry, but as far as I can see, the link to Delsole's study in your first article is not working
Your first article is a rehash of the unavailable study written by the science director of the Global Warming Policy Foundation, a UK charitable organization whose stated goal is to refute AGW. Hardly an objective source.
Your second article, which appears to have no study behind it, was published by the Hoover Institution, a conservative think tank associated with Stanford. It was authored by two fellows of the institution: a straight up economist and an economist whose spent his whole career in the pharmaceutical industry. This second fellow has some experience with econcomic modeling, apparently for Big Pharma. So, no climate science experience, at all, in either one.
David Richard Henderson (born November 21, 1950) is a Canadian-born American economist and author who moved to the United States in 1972 and became a U.S. citizen in 1986, serving on President Ronald Reagan's Council of Economic Advisers from 1982 to 1984. A research fellow at Stanford University's Hoover Institution since 1990, he took a teaching position with the Naval Postgraduate School in Monterey, California in 1984, and is now an emeritus professor of economics.
Charles L. Hooper is President and co-founder of Objective Insights, Inc. Prior to forming Objective Insights in 1994, Charley worked at Merck & Co., Syntex Labs, and NASA. Charley’s experience is in decision analysis, economics, product pricing, forecasting, and modeling. He is passionate about helping pharmaceutical companies think clearly about their business opportunities.
The central thrust of your first article seems to be as follows:
these things considered it’s important to investigate if climate models are doing well in accounting for variability in the region as the North Atlantic is often used as a test of a climate model’s capability.
Yet in AR6's Physical Science Basis, doing a search for "north atlantic" we find the following assorted comments which give a strong impression that the North Atlantic SSTs would be about the WORST test you might use to ascertain the accuracy of a climate model.:
There is medium confidence in a continued poleward shift of storms and their precipitation in the North Pacific, while there is low confidence in projected changes in the North Atlantic storm tracks.
There is high confidence that SST will increase in all oceanic regions except the North Atlantic.
The Southern Ocean, the eastern equatorial Pacific, and the North Atlantic Ocean have warmed more slowly than the global average or slightly cooled.
Global reconstructions of sea surface temperature were developed from material contained in deep-sea sediment cores (CLIMAP Project Members et al., 1976), providing the first quantitative constraints for model simulations of ice-age climates (e.g., Rind and Peteet, 1985). Paleoclimate data and modelling showed that the Atlantic Ocean circulation has not been stable over glacial–interglacial time periods, and that many changes in ocean circulation are associated with abrupt transitions in climate in the North Atlantic region (Ruddiman and McIntyre, 1981; Broecker et al., 1985; Boyle and Keigwin, 1987; Manabe and Stouffer, 1988).
Climatic changes since the pre-industrial era are a combination of long-term anthropogenic changes and natural variations on time scales from days to decades. The relative importance of these two factors depends on the climate variable or region of interest. Natural variations consist of both natural radiatively forced trends (e.g., due to volcanic eruptions or solar variations) and ‘internal’ fluctuations of the climate system which occur even in the absence of any radiative forcings. The internal ‘modes of variability’, such as the El Niño– Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO), are discussed further in Annex IV.
Natural variations in both weather and longer time scale phenomena can temporarily mask or enhance any anthropogenic trends (e.g., Deser et al., 2012; Kay et al., 2015). These effects are more important on small spatial and temporal scales but can also occur on the global scale.
Alternatively, transitions from one state to another can occur if a critical threshold is exceeded; this is called ‘bifurcation tipping’ (Figure 1.17c,d; Ashwin et al., 2012). The new state is defined as ‘irreversible’ on a given time scale if the recovery from this state takes substantially longer than the time scale of interest, which is decades to centuries for the projections presented in this report. A well-known example is the modelled irreversibility of the ocean’s thermohaline circulation in response to North Atlantic changes such as freshwater input from rainfall and ice-sheet melt (Rahmstorf et al., 2005; Alkhayuon et al., 2019), which is assessed in detail in Chapter 9
Most simulations show a reduction in the strength of the North Atlantic thermohaline circulation. Future unexpected, large and rapid climate system changes are difficult to predict. These arise from the nonlinear nature of the climate system. Examples include rapid circulation changes in the North Atlantic.
Numerous proxy records collectively imply that AMOC is currently at its weakest point in the past 1.6 ka (Rahmstorf et al., 2015; Caesar et al., 2018, 2021; Thibodeau et al., 2018; Thornalley et al., 2018). Caesar et al. (2021) analyse a compilation of various available indirect AMOC proxies from marine sediments, in situ-based reconstructions and terrestrial proxies, which show a decline beginning in the late 19th century and over the 20th century superimposed by large decadal variability in the second half of the 20th century. Indirect reconstructions of AMOC components based on coastal sea level records in the western North Atlantic (Ezer, 2013; McCarthy et al., 2015; Piecuch, 2020) show an AMOC decline since the late 1950s, with only a short period of recovery during the 1990s.
Inferred variability in the size and strength of the North Atlantic subpolar gyre was substantial, and included rapid changes on millennial time scales during both interglacial and glacial intervals over the last 150 kyr (Born and Levermann, 2010; Mokeddem et al., 2014; Irvalı et al., 2016; Mokeddem and McManus, 2016). North Atlantic – Arctic exchange has also varied in the past, with indications of an increasing inflow of Atlantic waters into the Arctic during the late Holocene (Ślubowska et al., 2005) with an acceleration to the recent inflow that is now the largest of the past 2 kyr (Spielhagen et al., 2011).
The AR5 conclusions about large uncertainties in AMV [Atlantic Multi-decadal Variation] paleo reconstructions (Hernández et al., 2020) have been reinforced by recent studies of tree rings (J. Wang et al., 2017b), Greenland ice (Chylek et al., 2012), and corals (Kilbourne et al., 2014; Svendsen et al., 2014b; J. Wang et al., 2017b).
Instrumental observations show that AMV is characterized by basin-wide warm and cool periods with an average variation in SST of about 0.4°C, but with larger variations in the North Atlantic subpolar gyre.
AND FINALLY, your second paper is based on an article by Patrick Frank, an accomplished scientist at SLAC who is also a contributor to the Heartland Insitute Journal. His paper goes over what he views to be relatively enormous errors in surface temperature data and model output. Here is the conclusion of a response by Roy W. Spencer. I strongly suggest you read the whole article, it is not long.
Again, I am not defending the current CMIP5 climate model projections of future global temperatures. I believe they produce about twice as much global warming of the atmosphere-ocean system as they should. Furthermore, I don’t believe that they can yet simulate known low-frequency oscillations in the climate system (natural climate change).
But in the context of global warming theory, I believe the largest model errors are the result of a lack of knowledge of the temperature dependent changes in clouds and precipitation efficiency (thus free-tropospheric vapor, thus water vapor “feedback”) that actually occur in response to a long-term forcing of the system from increasing carbon dioxide. I do not believe it is because the fundamental climate modeling framework is not applicable to the climate change issue. The existence of multiple modeling centers from around the world, and then performing multiple experiments with each climate model while making different assumptions, is still the best strategy to get a handle on how much future climate change there *could* be.
My main complaint is that modelers are either deceptive about, or unaware of, the uncertainties in the myriad assumptions — both explicit and implicit — that have gone into those models.
There are many ways that climate models can be faulted. I don’t believe that the current paper represents one of them.
I’d be glad to be proved wrong.
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