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Andréa S. Taschetto
,
Alex Sen Gupta
,
Harry H. Hendon
,
Caroline C. Ummenhofer
, and
Matthew H. England
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Andréa S. Taschetto
,
Alex Sen Gupta
,
Harry H. Hendon
,
Caroline C. Ummenhofer
, and
Matthew H. England

Abstract

This study investigates the impact of Indian Ocean sea surface temperature (SST) anomalies on the atmospheric circulation of the Southern Hemisphere during El Niño events, with a focus on Australian climate. During El Niño episodes, the tropical Indian Ocean exhibits two types of SST response: a uniform “basinwide warming” and a dipole mode—the Indian Ocean dipole (IOD). While the impacts of the IOD on climate have been extensively studied, the effects of the basinwide warming, particularly in the Southern Hemisphere, have received less attention. The interannual basinwide warming response has important implications for Southern Hemisphere atmospheric circulation because 1) it accounts for a greater portion of the Indian Ocean monthly SST variance than the IOD pattern and 2) its maximum amplitude occurs during austral summer to early autumn, when large parts of Australia, South America, and Africa experience their monsoon. Using observations and numerical experiments with an atmospheric general circulation model forced with historical SST from 1949 to 2005 over different tropical domains, the authors show that the basinwide warming leads to a Gill–Matsuno-type response that reinforces the anomalies caused by changes in the Pacific as part of El Niño. In particular, the basinwide warming drives strong subsidence over Australia, prolonging the dry conditions during January–March, when El Niño–related SST starts to decay. In addition to the anomalous circulation in the tropics, the basinwide warming excites a pair of barotropic anomalies in the Indian Ocean extratropics that induces an anomalous anticyclone in the Great Australian Bight.

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James S. Risbey
,
Michael J. Pook
,
Peter C. McIntosh
,
Matthew C. Wheeler
, and
Harry H. Hendon

Abstract

This work identifies and documents a suite of large-scale drivers of rainfall variability in the Australian region. The key driver in terms of broad influence and impact on rainfall is the El Niño–Southern Oscillation (ENSO). ENSO is related to rainfall over much of the continent at different times, particularly in the north and east, with the regions of influence shifting with the seasons. The Indian Ocean dipole (IOD) is particularly important in the June–October period, which spans much of the wet season in the southwest and southeast where IOD has an influence. ENSO interacts with the IOD in this period such that their separate regions of influence cover the entire continent. Atmospheric blocking also becomes most important during this period and has an influence on rainfall across the southern half of the continent. The Madden–Julian oscillation can influence rainfall in different parts of the continent in different seasons, but its impact is strongest on the monsoonal rains in the north. The influence of the southern annular mode is mostly confined to the southwest and southeast of the continent. The patterns of rainfall relationship to each of the drivers exhibit substantial decadal variability, though the characteristic regions described above do not change markedly. The relationships between large-scale drivers and rainfall are robust to the selection of typical indices used to represent the drivers. In most regions the individual drivers account for less than 20% of monthly rainfall variability, though the drivers relate to a predictable component of this variability. The amount of rainfall variance explained by individual drivers is highest in eastern Australia and in spring, where it approaches 50% in association with ENSO and blocking.

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Eun-Pa Lim
,
Harry H. Hendon
,
Debra Hudson
,
Guomin Wang
, and
Oscar Alves

Abstract

The relationship between variations of Indo-Pacific sea surface temperatures (SSTs) and Australian springtime rainfall over the last 30 years is investigated with a focus on predictability of inter–El Niño variations of SST and associated rainfall anomalies. Based on observed data, the leading empirical orthogonal function (EOF) of Indo-Pacific SST represents mature El Niño conditions, while the second and fourth modes depict major east–west shifts of individual El Niño events. These higher-order EOFs of SST explain more rainfall variance in Australia, especially in the southeast, than does the El Niño mode. Furthermore, intense springtime droughts tend to be associated with peak warming in the central Pacific, as captured by EOFs 2 and 4, together with warming in the eastern Pacific as depicted by EOF1.

The ability to predict these inter–El Niño variations of SST and Australian rainfall is assessed with the Australian Bureau of Meteorology dynamical coupled model seasonal forecast system, the Predictive Ocean and Atmospheric Model for Australia (POAMA). A 10-member ensemble of 9-month hindcasts was generated for the period 1980–2006. For the September–November season, the leading 2 EOFs of SST are predictable with lead times of 3–6 months, while SST EOF4 is predictable out to a lead time of 1 month. The teleconnection between the leading EOFs of SST and Australian rainfall is also well depicted in the model. Based on this ability to predict major east–west variations of El Niño and the teleconnection to Australian rainfall, springtime rainfall over eastern Australia, and major drought events are predictable up to a season in advance.

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Eun-Pa Lim
,
Harry H. Hendon
,
David L. T. Anderson
,
Andrew Charles
, and
Oscar Alves

Abstract

The prediction skill of the Australian Bureau of Meteorology dynamical seasonal forecast model Predictive Ocean Atmosphere Model for Australia (POAMA) is assessed for probabilistic forecasts of spring season rainfall in Australia and the feasibility of increasing forecast skill through statistical postprocessing is examined. Two statistical postprocessing techniques are explored: calibrating POAMA prediction of rainfall anomaly against observations and using dynamically predicted mean sea level pressure to infer regional rainfall anomaly over Australia (referred to as “bridging”). A “homogeneous” multimodel ensemble prediction method (HMME) is also introduced that consists of the combination of POAMA’s direct prediction of rainfall anomaly together with the two statistically postprocessed predictions.

Using hindcasts for the period 1981–2006, the direct forecasts from POAMA exhibit skill relative to a climatological forecast over broad areas of eastern and southern Australia, where El Niño and the Indian Ocean dipole (whose behavior POAMA can skillfully predict at short lead times) are known to exert a strong influence in austral spring. The calibrated and bridged forecasts, while potentially offering improvement over the direct forecasts because of POAMA’s ability to predict the main drivers of springtime rainfall (e.g., El Niño and the Southern Oscillation), show only limited areas of improvement, mainly because strict cross-validation limits the ability to capitalize on relatively modest predictive signals with short record lengths. However, when POAMA and the two statistical–dynamical rainfall forecasts are combined in the HMME, higher deterministic and probabilistic skill is achieved over any of the single models, which suggests the HMME is another useful method to calibrate dynamical model forecasts.

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Awolou Sossa
,
Brant Liebmann
,
Ileana Bladé
,
Dave Allured
,
Harry H. Hendon
,
Pete Peterson
, and
Andrew Hoell

Abstract

This study focuses on the impact of the Madden–Julian oscillation (MJO)—as monitored by a well-known multivariate index—on large daily precipitation events in West Africa for the period 1981–2014. Two seasons are considered: the near-equatorial wet season in March–May (MAM) and the peak of the West African monsoon during July–September (JAS), when the intertropical convergence zone (ITCZ) is at its most northerly position. Although the MJO-related interannual variation of seasonal mean rainfall is large, the focus here is on the impacts of the MJO on daily time scales because variations in the frequency of intense, short-term, flood-causing, rainfall events are more important for West African agriculture than variations in seasonal precipitation, particularly near the Guinean coast, where precipitation is abundant. Using composites based on thresholds of daily precipitation amounts, changes in mean precipitation and frequency of the heaviest daily events associated with the phase of the MJO are investigated. The expected modulation of mean rainfall by the MJO is much stronger during MAM than during JAS; yet the modulation of the largest events (i.e., daily rainfall rates above the 90th percentile) is comparable in both seasons. Conservative statistical tests of local and field significance indicate unambiguous impacts of the MJO of the expected sign during certain phases, but the nature of the impact depends on the local seasonal precipitation regime. For instance, in JAS, the early stages of the MJO increase the risk of flooding in the Sahel monsoon region while providing relief to the dry southern coast.

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Seok-Woo Son
,
Yuna Lim
,
Changhyun Yoo
,
Harry H. Hendon
, and
Joowan Kim

Abstract

Interannual variation of seasonal-mean tropical convection over the Indo-Pacific region is primarily controlled by El Niño–Southern Oscillation (ENSO). For example, during El Niño winters, seasonal-mean convection around the Maritime Continent becomes weaker than normal, while that over the central to eastern Pacific is strengthened. Similarly, subseasonal convective activity, which is associated with the Madden–Julian oscillation (MJO), is influenced by ENSO. The MJO activity tends to extend farther eastward to the date line during El Niño winters and contract toward the western Pacific during La Niña winters. However, the overall level of MJO activity across the Maritime Continent does not change much in response to the ENSO. It is shown that the boreal winter MJO amplitude is closely linked with the stratospheric quasi-biennial oscillation (QBO) rather than with ENSO. The MJO activity around the Maritime Continent becomes stronger and more organized during the easterly QBO winters. The QBO-related MJO change explains up to 40% of interannual variation of the boreal winter MJO amplitude. This result suggests that variability of the MJO and the related tropical–extratropical teleconnections can be better understood and predicted by taking not only the tropospheric circulation but also the stratospheric mean state into account. The seasonality of the QBO–MJO link and the possible mechanism are also discussed.

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Guomin Wang
,
Pandora Hope
,
Eun-Pa Lim
,
Harry H. Hendon
, and
Julie M Arblaster

Abstract

When record-breaking climate and weather extremes occur, decision-makers and planners want to know whether they are random natural events with historical levels of reoccurrence or are reflective of an altered frequency or intensity as a result of climate change. This paper describes a method to attribute extreme weather and climate events to observed increases in atmospheric CO2 using an initialized subseasonal to seasonal coupled global climate prediction system. Application of this method provides quantitative estimates of the contribution arising from increases in the level of atmospheric CO2 to individual weather and climate extreme events. Using a coupled subseasonal to seasonal forecast system differs from other methods because it has the merit of being initialized with the observed conditions and subsequently reproducing the observed events and their mechanisms. This can aid understanding when the reforecasts with and without enhanced CO2 are compared and communicated to a general audience. Atmosphere–ocean interactions are accounted for. To illustrate the method, we attribute the record Australian heat event of October 2015. We find that about half of the October 2015 Australia-wide temperature anomaly is due to the increase in atmospheric CO2 since 1960. This method has the potential to provide attribution statements for forecast events within an outlook period (i.e., before they occur). This will allow for informed messaging to be available as required when an extreme event occurs, which is of particular use to weather and climate services.

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Matthew C. Wheeler
,
Harry H. Hendon
,
Sam Cleland
,
Holger Meinke
, and
Alexis Donald

Abstract

Impacts of the Madden–Julian oscillation (MJO) on Australian rainfall and circulation are examined during all four seasons. The authors examine circulation anomalies and a number of different rainfall metrics, each composited contemporaneously for eight MJO phases derived from the real-time multivariate MJO index. Multiple rainfall metrics are examined to allow for greater relevance of the information for applications. The greatest rainfall impact of the MJO occurs in northern Australia in (austral) summer, although in every season rainfall impacts of various magnitude are found in most locations, associated with corresponding circulation anomalies. In northern Australia in all seasons except winter, the rainfall impact is explained by the direct influence of the MJO’s tropical convective anomalies, while in winter a weaker and more localized signal in northern Australia appears to result from the modulation of the trade winds as they impinge upon the eastern coasts, especially in the northeast. In extratropical Australia, on the other hand, the occurrence of enhanced (suppressed) rainfall appears to result from induced upward (downward) motion within remotely forced extratropical lows (highs), and from anomalous low-level northerly (southerly) winds that transport moisture from the tropics. Induction of extratropical rainfall anomalies by remotely forced lows and highs appears to operate mostly in winter, whereas anomalous meridional moisture transport appears to operate mainly in the summer, autumn, and to some extent in the spring.

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Pandora Hope
,
Guomin Wang
,
Eun-Pa Lim
,
Harry H. Hendon
, and
Julie M. Arblaster
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