Transformation-cost time-series method for analyzing irregularly sampled data

ACKNOWLEDGEMENTS We thank K.-H. Wyrwoll and F. McRobie from the School of Earth and Environment (UWA) for fruitful discussions. Moreover, we acknowledge for financial supports from TUBITAK under the 2214/A program (I.O.), from the Leibniz Association (WGL) under Grant No. SAW-2013-IZW-2542 (D.E.), as well as from the BMBF within the Potsdam Research Cluster for Georisk Analysis, Environmental Change and Sustainability (PROGRESS) Support Code No. 03IS2191B (N.M.).Peer reviewedPublisher PD

See-saw relationship of the Holocene East Asian-Australian summer monsoon

D.E. and N.M. acknowledge support by the Leibniz Association (WGL) under Grant No. SAW-2013-IZW-2. F.H.M.’s research is funded through an Australian Postgraduate Award. I.O. is financially supported from TUBITAK under 2214/A program and by Ege University under the Research Project number 2015FEN028. This study received funding from the European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska-Curie grant agreement No 691037. The publication of this article was funded by the Open Access Fund of the Leibniz Association. K.H.W. thank Rhawn F. Denniston for his wider involvement in the northwest Australian monsoon project and the Kimberley Foundation Australia for financial support for this project and Paul Wyrwoll for helpful comments. We are also grateful to Yanjun Cai for providing the Lake Qinghai record.Peer reviewedPublisher PD

See–saw relationship of the Holocene East Asian–Australian summer monsoon

The East Asian–Indonesian–Australian summer monsoon (EAIASM) links the Earth’s hemispheres and provides a heat source that drives global circulation. At seasonal and inter-seasonal timescales, the summer monsoon of one hemisphere is linked via outflows from the winter monsoon of the opposing hemisphere. Long-term phase relationships between the East Asian summer monsoon (EASM) and the Indonesian–Australian summer monsoon (IASM) are poorly understood, raising questions of long-term adjustments to future greenhouse-triggered climate change and whether these changes could ‘lock in’ possible IASM and EASM phase relationships in a region dependent on monsoonal rainfall. Here we show that a newly developed nonlinear time series analysis technique allows confident identification of strong versus weak monsoon phases at millennial to sub-centennial timescales. We find a see–saw relationship over the last 9,000 years—with strong and weak monsoons opposingly phased and triggered by solar variations. Our results provide insights into centennial- to millennial-scale relationships within the wider EAIASM regime

A survey of natural radiation levels in soils and rocks from Aliaga-Foca region in Izmir, Turkey

WOS: 000321056600006PubMed ID: 23222553The gamma spectroscopic analysis of Ra-226, Th-232 and K-40 has been carried out in surface soil samples collected from Aliaga-Foa industrial region. The rock samples as parent materials of the soils are also collected and analysed for relevant radionuclides in order to evaluate the natural radiation levels. In the present study, the mean activity concentrations and ranges of the related radionuclides in the soil samples from 60 sites distributed all over the region are as follows: Ra-226 is 38 (14123) Bq kg(1); Th-232, 63 (27132) Bq kg(1) and K-40, 633 (1411666) Bq kg(1). Meanwhile, the ranges of natural radionuclide activities in the rock samples characterising the region are 4195 Bq kg(1) for Ra-226, 10122 Bq kg(1) for Th-232 and 2641470 Bq kg(1) for K-40, respectively. Based on the available data, the radiation hazard parameters associated with the surveyed soils/rocks are calculated and the results do not exceed the permissible recommended values except for soils originated from Foa rhyolites and tuffs. Furthermore, the collected data allowed for the mapping of the measured activities and corresponding gamma dose rates

Recurrence plot analysis of irregularly sampled data

Irregularly sampled time series usually require data preprocessing before a desired time-series analysis can be applied. We propose an approach for distance measuring of pairs of data points which is directly applicable to irregularly sampled time series. In order to apply recurrence plot analysis to irregularly sampled time series, we use this approach and detect regime transitions in prototypical models and for an application from palaeoclimatatology. This approach might be useful for any method that is based on distance measuring, e.g., correlation sum or Lyapunov exponent estimation