Discussion on common errors in analyzing sea level accelerations, solar trends and global warming
Nicola Scafetta

TL;DR
This paper identifies common analytical errors in climate signal analysis and demonstrates that correcting these errors significantly alters conclusions about sea level rise and solar influence on global warming.
Contribution
It highlights key methodological errors in analyzing geophysical signals and provides corrected estimates showing less alarming sea level rise and a greater solar contribution to 20th-century warming.
Findings
Sea level in NYC may rise about 350 mm from 2000 to 2100.
Solar activity contributed about 50% to 20th-century global warming.
Incorrect analysis methods can lead to misleading climate change interpretations.
Abstract
Errors in applying regression models and wavelet filters used to analyze geophysical signals are discussed: (1) multidecadal natural oscillations (e.g. the quasi 60-year Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO) and Pacific Decadal Oscillation (PDO)) need to be taken into account for properly quantifying anomalous accelerations in tide gauge records such as in New York City; (2) uncertainties and multicollinearity among climate forcing functions prevent a proper evaluation of the solar contribution to the 20th century global surface temperature warming using overloaded linear regression models during the 1900-2000 period alone; (3) when periodic wavelet filters, which require that a record is pre-processed with a reflection methodology, are improperly applied to decompose non-stationary solar and climatic time series, Gibbs boundary artifacts emerge…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
