1989 |
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| 1. | T R Krishna Mohan, Subba Rao J; Ramaswamy, R Dimension analysis of climatic data Journal Article Journal of Climate, 2 (9), pp. 1047–1057, 1989. Abstract | Links | BibTeX | Tags: climate, fractal dimension @article{Mohan1989, title = {Dimension analysis of climatic data}, author = {T R Krishna Mohan, J Subba Rao and R Ramaswamy}, url = {https://doi.org/10.1175/1520-0442(1989)002%3C1047:DAOCD%3E2.0.CO;2}, doi = {10.1175/1520-0442}, year = {1989}, date = {1989-09-01}, journal = {Journal of Climate}, volume = {2}, number = {9}, pages = {1047–1057}, abstract = {It has been conjectured that the unpredictability of climatic systems is due to strange attractors (SAs) in the configuration space dynamics. One climatic record, the oxygen isotope ratio data from deep-sea cores that pertains to long periods on the order of one million years and provides direct correlation with the glaciation-deglaciation periods, seemed to indicate (under earlier analysis) a low dimensional attractor of correlation dimension D2 ≈ 3.1. Our present reanalysis of this data in light of recent methods suggested by Broomhead and King (BK) is at variance with that result. Two (model) four-variable systems that support chaotic strange attractors are examined using an analysis similar to BK to investigate the practical drawbacks of using a short time-series vis-a-vis the estimation of attractor dimension.}, keywords = {climate, fractal dimension}, pubstate = {published}, tppubtype = {article} } It has been conjectured that the unpredictability of climatic systems is due to strange attractors (SAs) in the configuration space dynamics. One climatic record, the oxygen isotope ratio data from deep-sea cores that pertains to long periods on the order of one million years and provides direct correlation with the glaciation-deglaciation periods, seemed to indicate (under earlier analysis) a low dimensional attractor of correlation dimension D2 ≈ 3.1. Our present reanalysis of this data in light of recent methods suggested by Broomhead and King (BK) is at variance with that result. Two (model) four-variable systems that support chaotic strange attractors are examined using an analysis similar to BK to investigate the practical drawbacks of using a short time-series vis-a-vis the estimation of attractor dimension. |