ORCID Profile
0000-0002-0129-0922
Current Organisation
Australian Bureau of Meteorology
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Publisher: Springer Science and Business Media LLC
Date: 02-02-2018
DOI: 10.1038/S41598-018-20628-2
Abstract: Expected increases in food demand and the need to limit the incorporation of new lands into agriculture to curtail emissions, highlight the urgency to bridge productivity gaps, increase farmers profits and manage risks in dryland cropping. A way to bridge those gaps is to identify optimum combination of genetics (G), and agronomic managements (M) i.e. crop designs (GxM), for the prevailing and expected growing environment (E). Our understanding of crop stress physiology indicates that in hindsight, those optimum crop designs should be known, while the main problem is to predict relevant attributes of the E, at the time of sowing, so that optimum GxM combinations could be informed. Here we test our capacity to inform that “hindsight”, by linking a tested crop model (APSIM) with a skillful seasonal climate forecasting system, to answer “What is the value of the skill in seasonal climate forecasting, to inform crop designs?” Results showed that the GCM POAMA-2 was reliable and skillful, and that when linked with APSIM, optimum crop designs could be informed. We conclude that reliable and skillful GCMs that are easily interfaced with crop simulation models, can be used to inform optimum crop designs, increase farmers profits and reduce risks.
Publisher: Springer Netherlands
Date: 2011
Publisher: Elsevier BV
Date: 10-2015
Publisher: Wiley
Date: 22-10-2023
DOI: 10.1002/QJ.4585
Publisher: American Meteorological Society
Date: 02-2011
Abstract: Mass coral bleaching, associated with anomalously warm ocean temperatures over large regions, poses a serious threat to the future health of the world coral reef systems. Seasonal forecasts from coupled ocean–atmosphere models can be a valuable resource for reef management, providing early warning of potential bleaching conditions, allowing for a proactive management response. Here, the ability of a dynamical seasonal forecast model (Predictive Ocean Atmosphere Model for Australia, POAMA) to forecast degree heating months (DHMs) in the tropical oceans is assessed, with particular focus on the 1997/98 El Niño–Southern Oscillation (ENSO) and associated global bleaching events. The model exhibits useful skill in forecasting sea surface temperatures (SSTs) across the tropical oceans for 1982–2006 and reproduced both the magnitude and distribution of DHM values observed during the 1997/98 ENSO event. In general, observed teleconnections between ENSO indices and tropical SST at various lags are well captured by the model. In particular, strong observed correlations between peak ENSO indices and SST in the Caribbean in the following summer were reproduced. The model also shows skill in predicting ocean conditions conducive to bleaching in non-ENSO years, capturing the anomalously warm conditions in the Caribbean region in 2005. Probabilistic forecasts of DHM values above certain thresholds for the Caribbean show useful skill and could be valuable in the assessment of the likelihood of bleaching for the region.
Publisher: Springer Science and Business Media LLC
Date: 26-10-2013
Publisher: Inter-Research Science Center
Date: 2001
DOI: 10.3354/CR016079
Publisher: American Geophysical Union (AGU)
Date: 07-08-2008
DOI: 10.1029/2007JD009250
Publisher: Springer Science and Business Media LLC
Date: 20-02-2021
Publisher: American Meteorological Society
Date: 11-2009
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 in idual 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.
Publisher: Springer Science and Business Media LLC
Date: 10-12-2010
Publisher: Springer Science and Business Media LLC
Date: 10-12-2013
Publisher: Wiley
Date: 04-04-2013
DOI: 10.1002/JOC.3486
Publisher: American Meteorological Society
Date: 25-11-2013
Abstract: The Australian Bureau of Meteorology has recently enhanced its capability to make coupled model forecasts of intraseasonal climate variations. The Predictive Ocean Atmosphere Model for Australia (POAMA, version 2) seasonal prediction forecast system in operations prior to March 2013, designated P2-S, was not designed for intraseasonal forecasting and has deficiencies in this regard. Most notably, the forecasts were only initialized on the 1st and 15th of each month, and the growth of the ensemble spread in the first 30 days of the forecasts was too slow to be useful on intraseasonal time scales. These deficiencies have been addressed in a system upgrade by initializing more often and through enhancements to the ensemble generation. The new ensemble generation scheme is based on a coupled-breeding approach and produces an ensemble of perturbed atmosphere and ocean states for initializing the forecasts. This scheme impacts favorably on the forecast skill of Australian rainfall and temperature compared to P2-S and its predecessor (version 1.5). In POAMA-1.5 the ensemble was produced using time-lagged atmospheric initial conditions but with unperturbed ocean initial conditions. P2-S used an ensemble of perturbed ocean initial conditions but only a single atmospheric initial condition. The improvement in forecast performance using the coupled-breeding approach is primarily reflected in improved reliability in the first month of the forecasts, but there is also higher skill in predicting important drivers of intraseasonal climate variability, namely the Madden–Julian oscillation and southern annular mode. The results illustrate the importance of having an optimal ensemble generation strategy.
Publisher: American Meteorological Society
Date: 27-03-2014
Abstract: The skill with which a coupled ocean–atmosphere model is able to predict precipitation over a range of time scales (days to months) is analyzed. For a fair comparison across the seamless range of scales, the verification is performed using data averaged over time windows equal in length to the lead time. At a lead time of 1 day, skill is greatest in the extratropics around 40°–60° latitude and lowest around 20°, and has a secondary local maximum close to the equator. The extratropical skill at this short range is highest in the winter hemisphere, presumably due to the higher predictability of winter baroclinic systems. The local equatorial maximum comes mostly from the Pacific Ocean, and thus appears to be mostly from El Niño–Southern Oscillation (ENSO). As both the lead time and averaging window are simultaneously increased, the extratropical skill drops rapidly with lead time, while the equatorial maximum remains approximately constant, causing the equatorial skill to exceed the extratropical at leads of greater than 4 days in austral summer and 1 week in boreal summer. At leads longer than 2 weeks, the extratropical skill flattens out or increases, but remains below the equatorial values. Comparisons with persistence confirm that the model beats persistence for most leads and latitudes, including for the equatorial Pacific where persistence is high. The results are consistent with the view that extratropical predictability is mostly derived from synoptic-scale atmospheric dynamics, while tropical predictability is primarily derived from the response of moist convection to slowly varying forcing such as from ENSO.
Publisher: American Geophysical Union (AGU)
Date: 10-2009
DOI: 10.1029/2009GL040100
Publisher: Springer Science and Business Media LLC
Date: 09-07-2011
Publisher: Springer Science and Business Media LLC
Date: 07-10-2019
Publisher: Wiley
Date: 13-04-2020
DOI: 10.1002/QJ.3789
Publisher: American Meteorological Society
Date: 05-2022
Abstract: Studies of atmospheric rivers (ARs) over Australia have, so far, only focused on northwest cloudband–type weather systems. Here we perform a comprehensive analysis of AR climatology and impacts over Australia that includes not only northwesterly systems, but easterly and extratropical ARs also. We quantify the impact of ARs on mean and extreme rainfall including assessing how the origin location of ARs can alter their precipitation outcomes. We found a strong relationship between ARs and extreme rainfall in the agriculturally significant Murray–Daring basin region. We test the hypothesis that the tropical and subtropical originating ARs we observe in Australasia differ from canonical extratropical ARs by examining the vertical structure of ARs grouped by origin location. We found that in the moisture abundant tropics and subtropics, wind speed drives the intensity of ARs, while in the extratropics, the strength of an AR is largely determined by moisture availability. Finally, we examine the modulation of AR frequency by different climate modes. We find weak (but occasionally significant) correlations between ARs frequency and El Niño–Southern Oscillation, the Indian Ocean dipole, and the southern annular mode. However, there is a stronger relationship between the phases of the Madden–Julian oscillation and tropical AR frequency, which is an avenue for potential skill in forecasting ARs on subseasonal time scales.
Publisher: Wiley
Date: 04-1997
DOI: 10.1002/(SICI)1097-0088(199704)17:5<459::AID-JOC147>3.0.CO;2-R
Publisher: The Royal Society
Date: 24-05-2002
Abstract: Two aspects of global climate change are particularly relevant to river and coastal flooding: changes in extreme precipitation and changes in sea level. In this paper we summarize the relevant findings of the IPCC Third Assessment Report and illustrate some of the common results found by the current generation of coupled atmosphere-ocean general circulation models (AOGCMs), using the Hadley Centre models. Projections of changes in extreme precipitation, sea-level rise and storm surges affecting the UK will be shown from the Hadley Centre regional models and the Proudman Oceanographic Laboratory storm-surge model. A common finding from AOGCMs is that in a warmer climate the intensity of precipitation will increase due to a more intense hydrological cycle. This leads to reduced return periods (i.e. more frequent occurrences) of extreme precipitation in many locations. The Hadley Centre regional model simulates reduced return periods of extreme precipitation in a number of flood-sensitive areas of the UK. In addition, simulated changes in storminess and a rise in average sea level around the UK lead to reduced return periods of extreme high coastal water events. The confidence in all these results is limited by poor spatial resolution in global coupled models and by uncertainties in the physical processes in both global and regional models, and is specific to the climate change scenario used.
Publisher: Elsevier
Date: 2019
Publisher: American Meteorological Society
Date: 06-2016
Abstract: There has been increasing demand in Australia for extended-range forecasts of extreme heat events. An assessment is made of the subseasonal experimental guidance provided by the Bureau of Meteorology’s seasonal prediction system, Predictive Ocean Atmosphere Model for Australia (POAMA, version 2), for the three most extreme heat events over Australia in 2013, which occurred in January, March, and September. The impacts of these events included devastating bushfires and damage to crops. The outlooks performed well for January and September, with forecasts indicating increased odds of top-decile maximum temperature over most affected areas at least one week in advance for the fortnightly averaged periods at the start of the heat waves and for forecasts of the months of January and September. The March event was more localized, affecting southern Australia. Although the anomalously high sea surface temperature around southern Australia in March (a potential source of predictability) was correctly forecast, the forecast of high temperatures over the mainland was restricted to the coastline. September was associated with strong forcing from some large-scale atmospheric climate drivers known to increase the chance of having more extreme temperatures over parts of Australia. POAMA-2 was able to forecast the sense of these drivers at least one week in advance, but their magnitude was weaker than observed. The reasonably good temperature forecasts for September are likely due to the model being able to forecast the important climate drivers and their teleconnection to Australian climate. This study adds to the growing evidence that there is significant potential to extend and augment traditional weather forecast guidance for extreme events to include longer-lead probabilistic information.
Publisher: Wiley
Date: 21-03-2011
DOI: 10.1002/QJ.769
Publisher: Wiley
Date: 11-11-2016
DOI: 10.1002/QJ.2928
Publisher: Springer Science and Business Media LLC
Date: 11-12-2013
Publisher: American Geophysical Union (AGU)
Date: 14-12-2016
DOI: 10.1002/2016GL071423
Publisher: Springer Science and Business Media LLC
Date: 25-02-2010
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Debra Hudson.