eCite Digital Repository
Climate-informed stochastic hydrological modeling: Incorporating decadal-scale variability using paleo data
Citation
Henley, BJ and Thyer, M and Kuczera, G and Franks, SW, Climate-informed stochastic hydrological modeling: Incorporating decadal-scale variability using paleo data, Water Resources Research, 47 pp. 1-14. ISSN 1944-7973 (2011) [Refereed Article]
 | PDF Not available 2Mb |
Copyright Statement
Copyright 2011 by the American Geophysical Union.
Abstract
A hierarchical framework for incorporating modes of climate variability into stochastic
simulations of hydrological data is developed, termed the climate-informed multi-time scale
stochastic (CIMSS) framework. A case study on two catchments in eastern Australia
illustrates this framework. To develop an identifiable model characterizing long-term
variability for the first level of the hierarchy, paleoclimate proxies, and instrumental indices
describing the Interdecadal Pacific Oscillation (IPO) and the Pacific Decadal Oscillation
(PDO) are analyzed. A new paleo IPO-PDO time series dating back 440 yr is produced,
combining seven IPO-PDO paleo sources using an objective smoothing procedure to fit
low-pass filters to individual records. The paleo data analysis indicates that wet/dry IPO-PDO
states have a broad range of run lengths, with 90% between 3 and 33 yr and a mean of 15 yr.
The Markov chain model, previously used to simulate oscillating wet/dry climate states, is
found to underestimate the probability of wet/dry periods >5 yr, and is rejected in favor of a
gamma distribution for simulating the run lengths of the wet/dry IPO-PDO states. For the
second level of the hierarchy, a seasonal rainfall model is conditioned on the simulated
IPO-PDO state. The model is able to replicate observed statistics such as seasonal and
multiyear accumulated rainfall distributions and interannual autocorrelations. Mean seasonal
rainfall in the IPO-PDO dry states is found to be 15%–28% lower than the wet state at the
case study sites. In comparison, an annual lag-one autoregressive model is unable to
adequately capture the observed rainfall distribution within separate IPO-PDO states.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | climate variability change risk rainfall model |
| Research Division: | Engineering |
| Research Group: | Environmental engineering |
| Research Field: | Air pollution modelling and control |
| Objective Division: | Environmental Management |
| Objective Group: | Other environmental management |
| Objective Field: | Other environmental management not elsewhere classified |
| UTAS Author: | Franks, SW (Professor Stewart Franks) |
| ID Code: | 86418 |
| Year Published: | 2011 |
| Web of Science® Times Cited: | 34 |
| Deposited By: | Engineering |
| Deposited On: | 2013-09-14 |
| Last Modified: | 2013-10-28 |
| Downloads: | 0 |
Repository Staff Only: item control page