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Arctic sea ice, a potential marker of global warming, experienced a shift in the late 1990s called the Arctic Shift. Initially, the 1980s and 1990s saw moderate declines in September Arctic sea-ice extent (SIE).
However, after the 1997 climate shift, a rapid decline set in, leading to "consensus" concerns about a potential ice-free Arctic.
Computer models predicted this outcome by 2040, triggering much public anxiety.
More recent research now suggests that 60% of the September SIE decline since 1979 may be due to atmospheric circulation changes. Additionally, persistent Arctic summer cloud cover has mitigated the ice-albedo feedback, slowing the decline since 2007 unexpectedly and contrary to predictions.
Thus, despite the approved consensus narrative, uncertainty persists among climate researchers regarding the natural climate shift influence versus the human influence on overall sea ice change and what direction Arctic sea ice will take in the future.
And then the unexpected recovery of sea ice in 2013 truly challenged the alarmist predictions. With the original 7-year pause now extending to 17 years that means there was only a 10% probability of that taking place.
This implies that past sea ice predictions were 90% inaccurate, in turn raising significant concerns about climate model reliability.
In June 2023, promoting more anxiety, global headlines warned of ice-free Arctic summers by the 2030s, irrespective of emission reduction efforts, based on a a new peer-reviewed study.
Unfortunately, this study relied on data only up to 2019, ignoring available 2020-22 data. Model projections for 2021 and 2022 significantly differed from observed data, prompting scrutiny and questions as to why the study was approved for publication in the first place.
Clearly, policymakers and the public grapple with challenges when relying on inaccurate computer model projections. Studies that are produced by flawed computer model predictions pose serious potential consequences that highlight the need for thorough evaluation and transparency in climate research. (source of information for above & video)