Description:

“Best practices” for precedence (cause-effect) analysis of climate change begins with using verified, validated, and real-time records of our biosphere. It recognizes that cause cannot come after an effect. But beyond that, what is the best practice to derive the best estimate of a potential causal relationship between an independent variable and climate change? Topics will include: testing records for compatibility with base assumptions, the hypothesis correctly stated, the physics of the theory correctly matched to the methodology (linear, non-linear, univariate, multiple, etc.), removing co-effects (trend, seasonality, cyclicity, diurnal, etc.) and tests thereof, the testing of lags, an unbiased estimate of the coefficient of determination for each independent variable (univariate and multiple), stating conclusions, and the importance of an association willing to publish papers that follow best practice.

Once a best practice is defined, then evidence that meets best practice can be assimilated to support or dismiss climate theories, minimize conflict, and focus further research.