A General Linear Model to Describe Observed Global Warming as a Function of the Atmospheric Surface Concentrations of Greenhouse Gases and Greenhouse Constants

Author:

Friberg RasmusORCID

Abstract

Abstract

This is the first paper in a series of papers with the overall aim of analyzing and deriving theoretical models to indirectly measure and test the root cause of observed global warming (GW) and the greenhouse effect (GHE) at the earth’s surface due to the atmospheric concentration of greenhouse gases (GHGs) in general and the mass of anthropogenic CO2 emissions (MACE) in particular. The objective of this specific paper is to present a new theoretical model, which is the framework theory and the starting point for explaining the relationship between observed global warming (GW) and the atmospheric concentrations of greenhouse gases (GHGs). It is derived from the theory of Lambert–Beer–Bouger’s law, Planck’s law and the heat balance over the atmospheric surface layer, where the GW is measured. The result is called the general linear model of GW (GLMGW). Consequently, the GLMGW indicates that there is a linear relationship between the observed GW (or GAST-global atmospheric surface temperature) and the GHG atmospheric surface concentrations. The characteristic constants of the GLMGW are the greenhouse constants for each GHG, which is a measure of how much the temperature rises per atmospheric concentration of a given greenhouse gas. The claims originating from the GLMGW were tested directly or indirectly in subsequent papers (Evidences I-V) based on the global data series of temperature and atmospheric GHG concentrations obtained from NOAA, ECMWF and GCP. Several new practical validated measurement models are available for calculating and forecasting GW as a function of the dominant GHGs. The different models can be used with high measurement certainty and forecasting capability to estimate several different quantities in the context of the GW; for example, the global atmospheric surface temperature anomaly (GASTA) can be used as a function of the atmospheric CO2 concentration, and the remaining time and remaining MACE can be used to breach the 1.5K and 2.0K limits.

Publisher

Springer Science and Business Media LLC

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