TY - JOUR
T1 - Revisiting ENSO and IOD Contributions to Australian Precipitation
AU - Liguori, Giovanni
AU - McGregor, Shayne
AU - Singh, Martin
AU - Arblaster, Julie
AU - Di Lorenzo, Emanuele
N1 - Funding Information:
G. Liguori, S. McGregor, J. Arblaster, and M. Singh acknowledge support from the Australian Research Council through the Centre of Excellence for Climate Extremes (CE170100023). Computational resources and services from the National Computational Infrastructure, which is supported by the Australian Government, are gratefully acknowledged. Portions of this study were supported by the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy's Office of Biological & Environmental Research (BER) Cooperative Agreement # DE-FC02-97ER62402 and by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation National Science Foundation under Cooperative Agreement No. 1852977. This research used resources from the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. E. D. Lorenzo and G. Liguori acknowledge the support of the National Science Foundation through the grants NSF-OCE 1634996, NSF-OCE 1419292, and NSF-OCE 1948627. G. Liguori also thanks Alex Sen Gupta and Harry Hendon for insightful discussions in the early stages of this work. All the authors thank the two anonymous reviewers for their constructive comments on the manuscript.
Funding Information:
G. Liguori, S. McGregor, J. Arblaster, and M. Singh acknowledge support from the Australian Research Council through the Centre of Excellence for Climate Extremes (CE170100023). Computational resources and services from the National Computational Infrastructure, which is supported by the Australian Government, are gratefully acknowledged. Portions of this study were supported by the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy's Office of Biological & Environmental Research (BER) Cooperative Agreement # DE‐FC02‐97ER62402 and by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation National Science Foundation under Cooperative Agreement No. 1852977. This research used resources from the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE‐AC02‐05CH11231. E. D. Lorenzo and G. Liguori acknowledge the support of the National Science Foundation through the grants NSF‐OCE 1634996, NSF‐OCE 1419292, and NSF‐OCE 1948627. G. Liguori also thanks Alex Sen Gupta and Harry Hendon for insightful discussions in the early stages of this work. All the authors thank the two anonymous reviewers for their constructive comments on the manuscript.
Publisher Copyright:
© 2021. American Geophysical Union. All Rights Reserved.
PY - 2022/1/16
Y1 - 2022/1/16
N2 - Tropical modes of variability, such as El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), exert a strong influence on the interannual variability of Australian precipitation. Nevertheless, commonly used indices of ENSO and IOD variability display significant co-variability that prevents a robust quantification of the independent contribution of each mode to precipitation anomalies. This co-variability issue is often addressed by statistically removing ENSO or IOD variability from the precipitation field before calculating teleconnection patterns. However, by performing a suite of coupled and uncoupled modeling experiments in which either ENSO or IOD variability is physically removed, we show that ENSO-only-driven precipitation patterns computed by statistically removing the IOD influence significantly underestimate the impact of ENSO on Australian precipitation variability. Inspired by this, we propose a conceptual model that allows one to effectively separate the contribution of each mode to Australian precipitation variability.
AB - Tropical modes of variability, such as El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), exert a strong influence on the interannual variability of Australian precipitation. Nevertheless, commonly used indices of ENSO and IOD variability display significant co-variability that prevents a robust quantification of the independent contribution of each mode to precipitation anomalies. This co-variability issue is often addressed by statistically removing ENSO or IOD variability from the precipitation field before calculating teleconnection patterns. However, by performing a suite of coupled and uncoupled modeling experiments in which either ENSO or IOD variability is physically removed, we show that ENSO-only-driven precipitation patterns computed by statistically removing the IOD influence significantly underestimate the impact of ENSO on Australian precipitation variability. Inspired by this, we propose a conceptual model that allows one to effectively separate the contribution of each mode to Australian precipitation variability.
KW - Australian precipitation
KW - CESM
KW - ENSO
KW - IOD
KW - partial regression analysis
KW - SST nudging
UR - http://www.scopus.com/inward/record.url?scp=85122737339&partnerID=8YFLogxK
U2 - 10.1029/2021GL094295
DO - 10.1029/2021GL094295
M3 - Article
AN - SCOPUS:85122737339
SN - 0094-8276
VL - 49
JO - Geophysical Research Letters
JF - Geophysical Research Letters
IS - 1
M1 - e2021GL094295
ER -