Evaluating trends in time series of distributions: A spatial fingerprint of human effects on climate
| Autor: | Chang Sik Kim, Sungkeun Park, Robert K. Kaufmann, J. Isaac Miller, Joon Y. Park, Yoosoon Chang |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Economics and Econometrics
Global temperature Applied Mathematics Anomaly (natural sciences) 05 social sciences Global warming Northern Hemisphere Climate change 01 natural sciences 010104 statistics & probability Geography Climatology Greenhouse gas 0502 economics and business 0101 mathematics Mean radiant temperature Southern Hemisphere 050205 econometrics |
| Zdroj: | Journal of Econometrics. 214:274-294 |
| ISSN: | 0304-4076 |
| DOI: | 10.1016/j.jeconom.2019.05.014 |
| Popis: | We analyze a time series of global temperature anomaly distributions to identify and estimate persistent features in climate change. We employ a formal test for the existence of functional unit roots in the time series of these densities, and we develop a new test to distinguish functional unit roots from functional deterministic trends or explosive behavior. Results suggest that temperature anomalies contain stochastic trends (as opposed to deterministic trends or explosive roots), two trends are present in the Northern Hemisphere while one stochastic trend is present in the Southern Hemisphere, and the probabilities of observing moderately positive anomalies have increased. We postulate that differences in the pattern and number of unit roots in each hemisphere may be due to a natural experiment which causes human emissions of greenhouse gases and sulfur to be greater in the Northern Hemisphere, decreasing the mean temperature anomaly but increasing the spatial variance relative to the Southern Hemisphere. Together, these results are consistent with the theory of anthropogenic climate change. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect