GRANGER CAUSALITY
; STATISTICAL-ANALYSIS
; TEMPERATURE
; TIME
; SERIES
; ATTRIBUTION
; BREAKS
; COINTEGRATION
; OSCILLATION
; MODELS
WOS学科分类:
Multidisciplinary Sciences
WOS研究方向:
Science & Technology - Other Topics
英文摘要:
In our study, we present a purely statistical observations-based model-free analysis that provides evidence about Granger causality (GC) from long-lived radiative forcings (LLRFs) to the climate trend (CT). This relies on having locally ordered breaks in the slopes of the trend functions of LLRF and the CT, with the break for LLRF occurring before that of the CT and with the slope changes being of the same sign. The empirical evidence indicates that these conditions are satisfied empirically using standard global surface temperature series and an aggregate measure of LLRF (carbon dioxide, nitrous oxide, and chlorofluorocarbons). We also discuss why the presence of broken trends can lead one to conclude in favor of GC when using standard methods even if the noise function in LLRF is negligible.
1.Univ Nacl Autonoma Mexico, Ctr Ciencias Atmosfera, Ciudad Univ, Mexico City 04510, DF, Mexico 2.Vrije Univ Amsterdam, Inst Environm Studies, Amsterdam, Netherlands 3.Boston Univ, Dept Econ, Boston, MA 02215 USA
Recommended Citation:
Estrada, Francisco,Perron, Pierre. Causality from long-lived radiative forcings to the climate trend[J]. ANNALS OF THE NEW YORK ACADEMY OF SCIENCES,2019-01-01,1436(1):195-205