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Harry H. Hendon

Abstract

The Bureau of Meteorology, Australia, routinely analyzes the tropospheric winds over the Australian Tropical Region (40°S–40°N, 70°–180°E). These wind data are assimilated without the use of a forecast model. While being free of any model bias, the optimum interpolation scheme imposes no dynamical constraints on the winds. To assess the realism of the Australian Tropical Region analyses, a qualitative comparison with gridded ECMWF wind data and OLR (as a proxy for tropical convection) is conducted.

In general, the depiction of the large-scale tropical circulation of the Australian Tropical Region analyses is quite reasonable. The gross features of the Australian and Asian Monsoons seem equally captured by both the ECMWF and Australian analyses. The seasonal development of the two monsoons and the relationship between the vertical structure of the divergence and zonal wind depicted in the Australian analyses agree well with previous theoretical and observational studies. Subtle differences (such as with the phase of the upper level anticyclones relative to the divergence) between the theory and the dynamics inferred from the Australian analyses are highlighted. However, we conclude that these objectively analyzed tropospheric winds are a valuable data resource for both the comparison with forecast model assimilated data and for deduction of physical processes.

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Sally Langford
and
Harry H. Hendon

Abstract

Seasonal rainfall predictions for Australia from the Predictive Ocean Atmosphere Model for Australia (POAMA), version P15b, coupled model seasonal forecast system, which has been run operationally at the Australian Bureau of Meteorology since 2002, are overconfident (too low spread) and only moderately reliable even when forecast accuracy is highest in the austral spring season. The lack of reliability is a major impediment to operational uptake of the coupled model forecasts. Considerable progress has been made to reduce reliability errors with the new version of POAMA2, which makes use of a larger ensemble from three different versions of the model. Although POAMA2 can be considered to be multimodel, its individual models and forecasts are similar as a result of using the same perturbed initial conditions and the same model lineage. Reliability of the POAMA2 forecasts, although improved, remains relatively low. Hence, the authors explore the additional benefit that can be attained using more independent models available in the European Union Ensemble-Based Predictions of Climate Changes and their Impacts (ENSEMBLES) project.

Although forecast skill and reliability of seasonal predictions of Australian rainfall are similar for POAMA2 and the ENSEMBLES models, forming a multimodel ensemble using POAMA2 and the ENSEMBLES models is shown to markedly improve reliability of Australian seasonal rainfall forecasts. The benefit of including POAMA2 into this multimodel ensemble is due to the additional information and skill of the independent model, and not just due to an increase in the number of ensemble members. The increased reliability, as well as improved accuracy, of regional rainfall forecasts from this multimodel ensemble system suggests it could be a useful operational prediction system.

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Matthew C. Wheeler
and
Harry H. Hendon

Abstract

A seasonally independent index for monitoring the Madden–Julian oscillation (MJO) is described. It is based on a pair of empirical orthogonal functions (EOFs) of the combined fields of near-equatorially averaged 850-hPa zonal wind, 200-hPa zonal wind, and satellite-observed outgoing longwave radiation (OLR) data. Projection of the daily observed data onto the multiple-variable EOFs, with the annual cycle and components of interannual variability removed, yields principal component (PC) time series that vary mostly on the intraseasonal time scale of the MJO only. This projection thus serves as an effective filter for the MJO without the need for conventional time filtering, making the PC time series an effective index for real-time use.

The pair of PC time series that form the index are called the Real-time Multivariate MJO series 1 (RMM1) and 2 (RMM2). The properties of the RMM series and the spatial patterns of atmospheric variability they capture are explored. Despite the fact that RMM1 and RMM2 describe evolution of the MJO along the equator that is independent of season, the coherent off-equatorial behavior exhibits strong seasonality. In particular, the northward, propagating behavior in the Indian monsoon and the southward extreme of convection into the Australian monsoon are captured by monitoring the seasonally independent eastward propagation in the equatorial belt. The previously described interannual modulation of the global variance of the MJO is also well captured.

Applications of the RMM series are investigated. One application is through their relationship with the onset dates of the monsoons in Australia and India; while the onsets can occur at any time during the convectively enhanced half of the MJO cycle, they rarely occur during the suppressed half. Another application is the modulation of the probability of extreme weekly rainfall; in the “Top End” region around Darwin, Australia, the swings in probability represent more than a tripling in the likelihood of an upper-quintile weekly rainfall event from the dry to wet MJO phase.

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Fiona Lo
and
Harry H. Hendon

Abstract

An empirical model that predicts the evolution of the Madden–Julian oscillation (MJO) in outgoing longwave radiation (OLR) and 200-mb streamfunction is developed. The model is based on the assumption that the MJO can be well represented by a pair of empirical orthogonal functions (EOFs) of OLR and three EOFs of streamfunction. With an eye toward using this model in real time, these EOFs are determined with data only subjected to filtering that can be applied in near–real time. Stepwise lag regression is used to develop the model on 11 winters of dependent data. The predictands are the leading two principal components (PCs) of OLR and the leading three PCs of streamfunction. The model is validated with five winters of independent data and is also compared to dynamic extended range forecasts (DERFs) made with the National Centers for Environmental Prediction’s Medium Range Forecast (MRF) model.

Skillful forecasts of the MJO in OLR and streamfunction with the empirical model are achieved out to about 15 days. Initial skill arises from autocorrelation of the PCs. Subsequent skill beyond about 1 week arises primarily from the cross correlation with the other PCs that define the MJO. Inclusion of PCs not associated with the MJO as predictors appears not to reliably improve skill. Skill is found to be substantially better when the MJO is active at the initial condition than when it is inactive. The empirical forecasts are also found to be more skillful than DERF from the MRF for lead times longer than about 1 week. Furthermore, skill of DERF from the MRF is found to be better when the MJO is quiescent than when it is active at the initial condition. It is suggested that significant improvement of tropical DERF could be achieved by improvement of the representation of the MJO in the dynamic forecast model.

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Noel E. Davidson
and
Harry H. Hendon

Abstract

Evidence is presented of a downstream development mechanism operating across the entire longitudinal span of the 1978/79 Southern Hemisphere monsoon. Observationally it is seen as progressive cyclonic and anticyclonic vorticity increases that develop eastward in the monsoon trough at a speed of approximately 5 m s−1. The process results in many tropical cyclone and tropical depression formations over northern Australia and the South Pacific.

It is shown that the downstream development process is generally consistent with linearized barotropic dynamics, and that the Southern Hemisphere monsoon, because of an intrinsic westerly basic state, is a particularly suitable region for downstream events.

It is also shown that some apparent contradictions in previous observational studies can be rationalized by the theory. The interactions between the regional components of the monsoon (Indonesian, Australian and South Pacific sectors) can also he better understood. We further suggest that the process has implications for other features of the monsoon circulation, namely onset and 40–50 day events.

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Toshiaki Shinoda
,
Harry H. Hendon
, and
John Glick

Abstract

Reliability of the surface fluxes from National Centers for Environmental Prediction (NCEP) reanalyses is assessed across the warm pool of the western Pacific and Indian Oceans. Emphasis is given to the spatial distribution and coherence of the fluxes on intraseasonal (25–100 day) periods, as intraseasonal variability predominates the subseasonal variability across the warm pool. Comparison is made with surface fluxes estimated from data collected at a mooring during the Coupled Ocean–Atmosphere Response Experiment and with independent gridded estimates based on operational wind and surface pressure analyses and satellite observations of rainfall, shortwave radiation, and outgoing longwave radiation. In general, fluxes that depend primarily on surface wind variations (e.g., stress and latent heat flux) agree more favorably than fluxes that are largely dependent on fluctuations of convection (e.g., surface shortwave radiation and freshwater or precipitation). In particular, the intraseasonal variance of shortwave radiation and precipitation in the NCEP reanalyses is about half of that estimated from in situ observations and from satellite observations. Composite surface flux variations for the Madden–Julian oscillation, which is the dominant mode of intraseasonal variability in the warm pool, are also constructed. Again, the composite variations of wind stress and latent heat flux from the NCEP reanalyses agree reasonably well, both in magnitude and phasing, with the composite fluxes from the independent gridded data. However, the composite intraseasonal shortwave radiation and precipitation from the NCEP reanalyses, while agreeing in phase, exhibit less than half the amplitude of the satellite-based estimates.

The impact of the underestimation of these surface flux variations in the NCEP reanalyses on the intraseasonal evolution of sea surface temperature (SST) in the warm pool is investigated in the context of a one-dimensional mixed layer model. When forced with the intraseasonal surface fluxes from the NCEP reanalyses, the amplitude of the intraseasonal SST variation is some 30%–40% smaller than observed or than that from forcing with the independent gridded fluxes. This reduced amplitude is primarily caused by the underestimation of the intraseasonal shortwave radiation variations in the NCEP reanalyses.

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Mei Zhao
,
Harry H. Hendon
,
Oscar Alves
,
Yonghong Yin
, and
David Anderson

Abstract

The authors assess the sensitivity of the simulated mean state and coupled variability to systematic initial state salinity errors in seasonal forecasts using the Australian Bureau of Meteorology Predictive Ocean Atmosphere Model for Australia (POAMA) coupled model. This analysis is based on two sets of hindcasts that were initialized from old and new ocean initial conditions, respectively. The new ocean initial conditions are provided by an ensemble multivariate analysis system that assimilates subsurface temperatures and salinity and is a clear improvement over the previous system, which was based on univariate optimal interpolation, using static error covariances and assimilating only temperature without updating salinity.

Large systematic errors in the salinity field around the thermocline region of the tropical western and central Pacific produced by the old assimilation scheme are shown to have strong impacts on the predicted mean state and variability in the tropical Pacific for the entire 9 months of the forecast. Forecasts initialized from the old scheme undergo a rapid and systematic adjustment of density that causes large persistent changes in temperature both locally in the western and central Pacific thermocline, but also remotely in the eastern Pacific via excitation of equatorial waves. The initial subsurface salinity errors in the western and central Pacific ultimately result in an altered surface climate because of induced temperature changes in the thermocline that trigger a coupled feedback in the eastern Pacific. These results highlight the importance of accurately representing salinity in initial conditions for climate prediction on seasonal and potentially multiyear time scales.

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Harry H. Hendon
,
Noel E. Davidson
, and
Bruce Gunn

Abstract

Onset of the Australian summer monsoon during 1986/87 is examined using the gridded tropospheric winds and surface pressure data from the Australian Bureau of Meteorology Tropical Region Analyses. Dramatic and sudden circulation changes on the synoptic and larger scale are known to occur at onset of the ,monsoon. The enhanced observing network during AMEX 1987 afforded an excellent opportunity to study these changes as the onset occurred during the experiment.

During November 1986 through early January 1987 anomalous convection and low-level westerly winds persisted in the central equatorial Pacific associated with an El Niño/Southern Oscillation event. This anomalous convection forced a large-scale sinking, dry southeasterly flow over the Australian tropics, inhibiting the onset of the monsoon. In early January the anomalous ENSO convection in the central Pacific diminished rapidly, apparently due to the passage of the downward branch or a 40–50 day oscillation event. Thus the attendant dry sinking motion over the Australian tropics diminished, and monsoon onset subsequently occurred in the second week of January.

Onset in the Australian region appears to have been triggered by the arrival of a westward moving equatorial wave disturbance. This synoptic scale disturbance appears to have originated in the ENSO Westerlies in the central Pacific just before their temporary demise in early January. It propagated at least 5000 km across the Pacific into the Australian region. Synoptic-scale low-level moist northerlies due to the wave drastically increased the low level humidity while the wave's convergence appears to have initiated organized convection over the Australian region. Subsequently, in a matter of one to two days, monsoon convection and low-level westerlies developed over a longitudinal span of ∼40°. The synoptic-scale wave disturbances also appear to be associated with formation of tropical cyclones in the region soon after onset. The subsequent expansion of the monsoon westerlies after onset results from a combination of an amplification of the synoptic-scale wave disturbance in the Doppler-shifted group velocity direction (eastward) and by the passage of a 40-50 day oscillation event

From a thermodynamic viewpoint, substantial but unrealizable conditional instability existed over the Australian tropics prior to the monsoon onset. Because of the lack of low-level saturation (due to the dry sinking circulation produced by the ENSO anomaly) substantial lifting was required to achieve buoyancy prior to onset. The onset process appears to be one where initial development of convection induced by synoptic convergence and moisture advection cools and further moistens the lower troposphere and thereby reduces the degree of lifting required to achieve buoyancy. Onset occurs as a dramatic blowup of convection over a large longitudinal span (∼40°) when the lifting required for buoyancy achieves a minimum but prior to the loss of deep conditional instability due to the vertical transport of heat and moisture by the monsoon convection.

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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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