Multi‑week prediction of livestock chill conditions associated with the northwest Queensland floods of February 2019

The compound extreme weather event that impacted northern Queensland in February 2019 featured record-breaking rainfall, persistent high wind gusts and relatively cold day-time temperatures. This caused livestock losses numbering around 500,000 in the northwest Queensland Gulf region. In this study, we examine the livestock chill conditions associated with this week-long compound weather event and its potential for prediction from eleven world-leading sub-seasonal to seasonal (S2S) forecast systems. The livestock chill index combines daily rainfall, wind and surface temperature data. Averaged over the event week, the potential heat loss of livestock was in the moderate to high category, with severe conditions on the day of peak rainfall (5 February). Using calibrated forecasts from the Bureau of Meteorology's S2S forecast system, ACCESS-S1, a 1-week lead prediction showed a 20–30% probability of extreme livestock chill conditions over the northwest Queensland Gulf region, however the highest probabilities were located to the west of where the greatest livestock impacts were observed. Of the remaining ten S2S systems, around half predicted a more than 20% chance of extreme conditions, more than twice the climatological probability. It appears that the prediction accuracy arose from the skilful forecasts of extreme rainfall, as opposed to cold day-time temperature and strong wind forecasts. Despite a clear association between the observed extreme weather conditions and an active Madden–Julian Oscillation (MJO) event stalling in the western Pacific, the majority of 1-week lead S2S forecasts showed little indication of a slow-down in the MJO. As the livestock chill index was developed for southern Australian sheep, it may not be the best metric to represent the effects of exposure on tropical cattle breeds. Hence, this study draws attention to the need for tailored diagnostics that better represent the cold effects of summer tropical cyclones and tropical depressions on northern Australian livestock

Forecasting the extreme rainfall, low temperatures, and strong winds associated with the northern Queensland floods of February 2019

From late January to early February 2019, a quasi-stationary monsoon depression situated over northeast Australia caused devastating floods, killing an estimated 625,000 head of cattle in northwest Queensland, and inundating over 3 000 homes in the coastal city of Townsville. The monsoon depression lasted ~10 days, driving daily rainfall accumulations exceeding 200 mm/day, maximum temperatures 8–10 °C below normal, and wind gusts above 70 km/h. In this study, the atmospheric conditions during the event and its predictability on the weekly to subseasonal range are investigated. Results show that during the event, the tropical convective signal of the Madden-Julian Oscillation was over the western Pacific, and likely contributed to the heavy rainfall, however the El Niño-Southern Oscillation was not in the usual phase for increased rainfall over Queensland. Over the northern Tasman Sea, an anticyclone helped maintain a positive phase of the Southern Annular Mode and promote onshore easterly flow. Somewhat consistent with these climate drivers, the monthly rainfall outlook for February issued by the Australian Bureau of Meteorology on 31 January provided no indication of the event, yet forecasts, not available to the public, of weekly-averaged conditions by the Bureau's dynamical subseasonal-to-seasonal (S2S) prediction system were more successful. For the week of 31 January to 6 February the prediction system forecast a more than doubling of the probability of extreme (highest quintile) weekly rainfall a week prior to the event, along with increased probabilities of extremely low (lowest quintile) maximum temperatures and extreme (highest quintile) wind speeds. Ensemble-mean weekly rainfall amounts, however, were considerably underestimated by the prediction system, even in forecasts initialised at the start of the peak flooding week, consistent with other state-of-the-art dynamical S2S prediction systems. Despite this, one of the individual ensemble members of the Bureau's prediction system did manage to forecast close to 85% of the magnitude of the rainfall across the most heavily impacted region of northwest Queensland a week before the event. Predicting this exceptional event beyond two weeks appears beyond our current capability despite the dynamical system forecasts showing good skill in forecasting the broad-scale atmospheric conditions north of Australia a week prior

The morphology of star-forming gas and its alignment with galaxies and dark matter haloes in the EAGLE simulations

We present measurements of the morphology of star-forming gas in galaxies from the EAGLE simulations, and its alignment relative to stars and dark matter (DM). Imaging of such gas in the radio continuum enables weak lensing experiments that complement traditional optical approaches. Star-forming gas is typically more flattened than its associated stars and DM, particularly for present-day subhaloes of total mass $\sim$$10^{ 12-12.5} \mathrm{M_{ \odot}}$, which preferentially host star-forming galaxies with rotationally-supported stellar discs. Such systems have oblate, spheroidal star-forming gas distributions, but in both less- and more-massive subhaloes the distributions tend to be prolate, and its morphology correlates positively and significantly with that of its host galaxy's stars, both in terms of sphericity and triaxiality. The minor axis of star-forming gas most commonly aligns with the minor axis of its host subhalo's DM, but often aligns more closely with one of the other two principal axes of the DM distribution in prolate subhaloes. Star-forming gas aligns with DM less strongly than is the case for stars, but its morphological minor axis aligns closely with its kinematic axis, affording a route to observational identification of the unsheared morphological axis. The projected ellipticities of star-forming gas in EAGLE are consistent with shapes inferred from high-fidelity radio continuum images, and they exhibit greater shape noise than is the case for images of the stars, owing to the greater characteristic flattening of star-forming gas with respect to stars

Direct shear mapping: the first technique to measure weak gravitational shear directly

© 2015 Dr. Catherine Odelia de Burgh-DayThis thesis develops and tests a new technique, called Direct Shear Mapping (DSM), to measure weak gravitational lensing shear, $\gamma$, directly from observations of a single background source. The technique assumes the velocity map of an un-lensed, stably-rotating galaxy will be rotationally symmetric. Lensing distorts the velocity map, making it asymmetric. The degree of lensing can be inferred by determining the transformation required to restore axisymmetry. This technique is in contrast to traditional weak lensing methods, which require averaging an ensemble of background galaxy ellipticity measurements, to obtain a single shear measurement. The accuracy of the fitting algorithm is tested in simulated data with a suite of systematic tests. It is demonstrated that in principle shears as small as $0.01$ can be measured. The shear is then fitted in very low redshift (and hence un-lensed) velocity maps, and a null result is obtained with an error of $\pm 0.01$. The high sensitivity achievable with DSM results from analysing spatially resolved spectroscopic images, including not just shape information (as in traditional weak lensing measurements) but velocity information as well. To investigate the prospects for making nonzero shear measurements with DSM in current and future surveys, a theoretical estimate is made of the frequency of galaxy-galaxy weak lensing at low redshift. The probability of weak lensing at low redshifts is found to be good (1 in 1,000 galaxies at $z\sim 0.2$). An algorithm is then presented to make an empirically driven estimate of the frequency of occurrence of weak lensing in existing low redshift galaxy survey data. This algorithm is applied to the Galaxy and Mass Assembly Phase 1 Survey Data Release 2 catalogue. It is estimated that to a redshift of $z\sim 0.6$, the probability of a galaxy being weakly lensed by at least $\gamma = 0.02$ is $\sim$0.01. A technique is then demonstrated to measure the scatter in the stellar mass-halo mass relation using a simulated sample of low redshift DSM shear measurements. It is estimated that for a shear measurement error of $\Delta\gamma = 0.02$, this measurement could be made with a sample of $\sim$50,000 spatially and spectrally resolved galaxies. Finally, the first step towards extending DSM to incorporate weak lensing flexion is made. Including flexion in a lensing analysis increases the sensitivity of weak lensing measurements, and facilitates measurement of the gradient of the gravitational potential. Weak lensing convergence, shear, and flexion field variables are derived for a generalised lensing mass, without assuming circular symmetry. It is shown that the equations reduce back to the correct expressions for simple lens mass distributions, and when solved numerically for circularly symmetric lenses reproduce the results obtained for analytical solutions. Finally, the equations are solved numerically for a simple non-circularly symmetric lens

Forecasting Northern Australian Summer Rainfall Bursts Using a Seasonal Prediction System

Rainfall bursts are relatively short-lived events that typically occur over consecutive days, up to a week. Northern Australian industries like sugar farming and beef are highly sensitive to burst activity, yet little is known about the multi-week prediction of bursts. This study evaluates summer (December to March) bursts over northern Australia in observations and multi-week hindcasts from the Bureau of Meteorology’s multi-week to seasonal system, ACCESS-S1 (Australian Community Climate and Earth-System Simulator, Seasonal version 1). The main objective is to test ACCESS-S1’s skill to confidently predict tropical burst activity, defined as rainfall accumulation exceeding a threshold amount over three days, for the purpose of producing a practical, user-friendly burst forecast product. The ensemble hindcasts, made up of 11 members for the period 1990–2012, display good predictive skill out to lead week 2 in the far northern regions, despite overestimating the total number of summer burst days and the proportion of total summer rainfall from bursts. Coinciding with a predicted strong Madden-Julian Oscillation (MJO), the skill in burst event prediction can be extended out to four weeks over the far northern coast in December, however this improvement is not apparent in other months or over the far northeast, which shows generally better forecast skill with a predicted weak MJO. The ability of ACCESS-S1 to skillfully forecast bursts out to 2-3 weeks suggests the Bureau's recent prototype development of a Burst Potential forecast product would be of great interest to northern Australia’s livestock and crop producers, who rely on accurate multi-week rainfall forecasts for managing business decisions

Direct shear mapping: Prospects for weak lensing studies of individual galaxy-galaxy lensing systems

Using both a theoretical and an empirical approach, we have investigated the frequency of low redshift galaxy-galaxy lensing systems in which the signature of 3D weak lensing might be directly detectable. We find good agreement between these two approaches. Using data from the Galaxy and Mass Assembly redshift survey we estimate the frequency of detectable weak lensing at low redshift. We find that below a redshift of z ~ 0.6, the probability of a galaxy being weakly lensed by γ ≥ 0.02 is ~ 0.01. We have also investigated the feasibility of measuring the scatter in the M* − Mh relation using shear statistics. We estimate that for a shear measurement error of Δγ = 0.02 (consistent with the sensitivity of the Direct Shear Mapping technique), with a sample of ~$50,000 spatially and spectrally resolved galaxies, the scatter in the M* − Mh relation could be measured. While there are currently no existing IFU surveys of this size, there are upcoming surveys that will provide this data (e.g The Hobby-Eberly Telescope Dark Energy Experiment (HETDEX), surveys with Hector, and the Square Kilometre Array (SKA))

Skill of ACCESS-S2 in predicting rainfall bursts over Australia

Precipitation falling in multi-day bursts is an important water source for the northern Australian tropics in summer and southern Australia in the cool autumn and winter months. Primary producers of crops and livestock need to plan for these events beyond the 7-day deterministic timeframe during the northern wet season (October – April) and southern wet season (April – November), to aid in their business operations. To coincide with the operational release of a multi-week burst potential forecast product in mid-2022, this report examines the skill of the Bureau's latest sub-seasonal-to-seasonal forecast system, the Australian Community Climate Earth-System Simulator – Seasonal version 2 (ACCESS-S2), released in October 2021, in predicting burst events 1 to 4 weeks in advance, predominantly focusing on northern Australia. We use the Symmetric Extremal Dependence Index (SEDI) as a metric to evaluate the skill of ACCESS-S2 in predicting rainfall bursts, given these are often rare events, particularly throughout the rangelands and sub-arid regions of northern Australia. As well as evaluating the hindcast skill of ACCESS-S2, we also apply the SEDI score to ACCESS-S1, to assess if there has been an appreciable improvement in burst prediction skill between forecast system versions. As expected, the skill of ACCESS-S2 in predicting rainfall bursts across northern Australia (north of 30°S) is highest in the first week of the forecast and decreases with lead time. Skill is generally stronger and more significant over Queensland than the Northern Territory and northern Western Australia in the second week of the forecast between October to December. The peak skill months, in terms of magnitude and area of significance, occur from January to March, with the highest skill scores in March across all lead times (weeks 1 to 4). The ACCESS-S2 forecast system is also more skilful at predicting lower threshold bursts (e.g., 20 or 30 mm in 3-day events) than the more extreme, rarer burst events (e.g., 50 or 70 mm in 3-day events). This is likely as a result of sampling rather than real skill. Given that ACCESS-S2 shows good skill out to four weeks in February and March over the southern Top End, the Victoria River District, the Kimberley and Cape York, even for 50 mm in 3-day events, the burst potential forecast product has the potential to be useful to producers in these regions. This four-week prediction skill is in line with ACCESS-S2's prediction skill of the Madden Julian Oscillation (MJO). For southern Australia, model skill is only seen in lower thresholds, and there is good model skill out to two weeks in March to July over the Murray-Darling Basin. Likewise for southwest Western Australia, southern Victoria and Tasmania, there is prediction skill out to two weeks from June through to November. Beyond two weeks, there is very little accuracy. This two-week timescale is in line with current limits of skill for predicting atmospheric blocking and the Southern Annular Mode on the daily/sub-weekly timescale; they are two key drivers of rainfall variability over southern Australia. Based on regional averages of the SEDI scores for '30 mm in 3-day' burst events over northwest and northeast Australia, ACCESS-S2 is generally more skilful than ACCESS-S1 across all lead weeks in the peak monsoon months of December to March. Armed with skill maps, examples of which are provided in the Appendix, and observed burst climatology maps, primary producers will be able to judge whether a burst event forecast is: (1) likely to be accurate; and (2) the outcome is more or less likely than they would expect for that time of year

Tropical forcing of Australian extreme low minimum temperatures in September 2019

We explore the causes and predictability of extreme low minimum temperatures (T ) that occurred across northern and eastern Australia in September 2019. Historically, reduced T is related to the occurrence of a positive Indian Ocean Dipole (IOD) and central Pacific El Niño. Positive IOD events tend to locate an anomalous anticyclone over the Great Australian Bight, therefore inducing cold advection across eastern Australia. Positive IOD and central Pacific El Niño also reduce cloud cover over northern and eastern Australia, thus enhancing radiative cooling at night-time. During September 2019, the IOD and central Pacific El Niño were strongly positive, and so the observed T anomalies are well reconstructed based on their historical relationships with the IOD and central Pacific El Niño. This implies that September 2019 T anomalies should have been predictable at least 1–2 months in advance. However, even at zero lead time the Bureau of Metereorolgy ACCESS-S1 seasonal prediction model failed to predict the anomalous anticyclone in the Bight and the cold anomalies in the east. Analysis of hindcasts for 1990–2012 indicates that the model's teleconnections from the IOD are systematically weaker than the observed, which likely stems from mean state biases in sea surface temperature and rainfall in the tropical Indian and western Pacific Oceans. Together with this weak IOD teleconnection, forecasts for earlier-than-observed onset of the negative Southern Annular Mode following the strong polar stratospheric warming that occurred in late August 2019 may have contributed to the T forecast bust over Australia for September 2019. min min min min mi