Toward a stochastic precipitation generator conditioned on ENSO phase for eastern Australia
Paper
Paper/Presentation Title | Toward a stochastic precipitation generator conditioned |
---|---|
Presentation Type | Paper |
Authors | An-Vo, Duc-Anh (Author), Stone, Roger (Author), Ngo-Cong, Duc (Author) and Marcussen, Torben (Author) |
Editors | Syme, G., Hatton MacDonald, D., Fulton, B. and Piantadosi, J. |
Journal or Proceedings Title | Proceedings of the 22nd International Congress on Modelling and Simulation (MODSIM2017) |
Journal Citation | pp. 1201-1207 |
Number of Pages | 7 |
Year | 2017 |
Publisher | Modelling and Simulation Society of Australia and New Zealand |
Place of Publication | Australia |
ISBN | 9780987214379 |
Digital Object Identifier (DOI) | https://doi.org/10.36334/modsim.2017.H11.anvo |
Web Address (URL) of Paper | https://www.mssanz.org.au/modsim2017/H11/anvo.pdf |
Web Address (URL) of Conference Proceedings | https://www.mssanz.org.au/modsim2017/papersbysession.html |
Conference/Event | 22nd International Congress on Modelling and Simulation (MODSIM2017) |
Event Details | Rank C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C C |
Event Details | 22nd International Congress on Modelling and Simulation (MODSIM2017) Parent International Congress on Modelling and Simulation Delivery In person Event Date 03 to end of 08 Dec 2017 Event Location Hobart, Australia Event Web Address (URL) |
Abstract | Stochastic generation of the required daily precipitation data offers an attractive alternative to the use of observed historical records. Stochastic precipitation generators are typically built on the statistical structure of historical data and thus can produce synthetic daily rainfall series with statistical characteristics similar to those of observed series. Parameters of precipitation generator have been typically estimated using all historical daily data for a given period. This approach, however, fails to capture signals in the precipitation process associated with an El Niño-Southern Oscillation (ENSO) phenomenon. ENSO signals have long been known to influence the precipitation in eastern Australia with high rainfall in a cold (La Niña) phase and low rainfall in a hot (El Niño) phase. Here, models for daily rainfall occurrence and intensity conditioned on each ENSO phase were developed to acknowledge ENSO signals in the precipitation process of eastern Australia. |
Keywords | precipitation models; climate variability; Australia; ENSO; weather generators; Markov chain |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 490510. Stochastic analysis and modelling |
Byline Affiliations | Computational Engineering and Science Research Centre |
International Centre for Applied Climate Science | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q483v/toward-a-stochastic-precipitation-generator-conditioned-on-enso-phase-for-eastern-australia
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