Carbon dioxide atmospheric concentration and hydrometeorological disasters

Abstract We study the long-run dynamic and predictive connection between atmospheric carbon dioxide (CO2) concentration and the probability of hydrometeorological disasters. For a panel of 193 countries over the period 1970-2016 we estimate the probabilities of hydrometeorological disasters at country levels by means of Bayesian sampling techniques. We then separate the effects of climatological and socio-demographic factors (used as proxies for exposure and vulnerability) and other country-specific factors, from a global probability of disasters (GPOD). Finally, we subject these global probability time paths to a cointegration analysis with CO2 concentration and run projections to year 2040 of the GPOD conditional on nine Shared Socioeconomic Pathways scenarios. We detect a stable long-term relation between CO2 accumulation and the GPOD that allows to determine projections of the latter process conditional on the former. This way, we demonstrate that generally and readily available statistical data on CO2 global atmospheric concentrations can be used as a conceptually meaningful, statistically valid and policy useful predictor of the probability of occurrence of (global) hydrometeorological disasters.