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

Anthropogenic intensification of short-duration rainfall extremes

Short- duration (1-3 h) rainfall extremes can cause serious damage to societies through rapidly developing (flash) flooding and are determined by complex, multifaceted processes that are altering as Earth's climate warms. In this Review, we examine evidence from observational, theoretical and modelling studies for the intensification of these rainfall extremes, the drivers and the impact on flash flooding. Both short- duration and long- duration (\textgreater1 day) rainfall extremes are intensifying with warming at a rate consistent with the increase in atmospheric moisture (~7% K-1), while in some regions, increases in short- duration extreme rainfall intensities are stronger than expected from moisture increases alone. These stronger local increases are related to feedbacks in convective clouds, but their exact role is uncertain because of the very small scales involved. Future extreme rainfall intensification is also modulated by changes to temperature stratification and large- scale atmospheric circulation. The latter remains a major source of uncertainty. Intensification of short- duration extremes has likely increased the incidence of flash flooding at local scales and this can further compound with an increase in storm spatial footprint to considerably increase total event rainfall. These findings call for urgent climate change adaptation measures to manage increasing flood risks

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

Convective precipitation efficiency observed in the Tropics

Precipitation efficiency refers to the fraction of condensate in the atmosphere that reaches the surface as precipitation. A high-quality data set of radar-estimated precipitation rates and convective scale vertical velocity near Darwin, Australia, is used to construct the first estimate of precipitation efficiency at convective scales for a long record of observations in the tropics. It is found that precipitation efficiency increases with precipitation rate and midtropospheric humidity and decreases with increasing convective available potential energy and surface temperature. Precipitation efficiency is largest under moist monsoonal conditions and smallest during monsoon break periods, which are characterized by a drier free troposphere. However, these differences in efficiency do not translate to differences in the instantaneous precipitation rate across the synoptic regimes because of a compensating change in the net condensation rate. This is driven by variations in cloud updraft velocity, which is larger in drier environments than in moist environments

Climate change projections for the Australian monsoon from CMIP6 Models

Climate change projections for the Australian monsoon have been highly uncertain in previous generations of coupled climate models. The new Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble provides an opportunity to address the uncertainty in future projections for northern Australia. We find that the range in Australian monsoon projections from the available CMIP6 ensemble is substantially reduced compared to CMIP5, although models continue to disagree on the magnitude and direction of change. While previous CMIP5 studies identified warming in the western equatorial Pacific as important for Australian monsoon projections, here we show that the western Pacific is not strongly connected to northern Australian precipitation changes in the CMIP6 models. By comparing groups of models based on their future projections, we note that the model-to-model differences in Australian monsoon projections are congruent with the zonally averaged precipitation response in the Southern Hemisphere tropics within each model

Exploring the capability approach to conceptualize gender inequality and poverty in Fiji

This article highlights the gaps in Fiji's poverty literature, notably the persistent insensitivity to gender within mainstream approaches to poverty measurement. To address the androcentric biases in household analyses, the author suggests the capability approach as more suited to conceptualize and assess gender inequality and women's poverty within the household. This article uses the capability framework to indicate a space within which intrahousehold comparisons are made using empirical evidence from Fiji. The article explores the ways in which one could operationalize the methodologies for gender-sensitive measures of poverty, which are capable of reflecting the experiences of women and men