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Australia's large natural hydro-climatic variability has already seen many changes, such as declining rainfall in the southern part of the country. Understanding these shifts and associated impacts on water availability is an important issue for Australia, as water supply is dependent on the generation of surface water resources. Sustainable future urban and agriculture developments will depend on best available knowledge about the risks and vulnerabilities of future water availability.To understand those risks and vulnerabilities and to mitigate the impact of a changing climate, Australia's water policy, management and infrastructure decision making needs detailed high-resolution climate and water information. This includes information on multi-decadal timescales from future projections in the context of past climate variabilities. In Australia, currently, hydrologic change information exists in various forms, ranging from multiple regional downscaling efforts, bias-correction methods and different interpretation methods for hydrologic impact assessment – all limiting a national, consistent impact assessment across multiple spatial and temporal scales. These regional downscaling and hydrological impact data collections are either not application-ready or are tailored for specific purposes only, which poses additional barriers to their use across the water and other sectors.To overcome these barriers, the Bureau of Meteorology is soon to release a seamless national landscape water service known as the Australian Water Outlook (AWO), combining historical data on water availability with forecast products, as well as hydrological impact projections. This system's core is the Australian Landscape Water Balance model (AWRA-L) modelling hydrologic variables consistently across a large range of spatial and temporal scales. The AWRA-L model is underpinned by substantial scientific development including data assimilation approaches for model calibration as well as model evaluation approaches for past and present time scales. Additionally, consistent downscaling and bias-correction approaches are integrated for the hydrologic projections in the operational framework.This presentation will share an overview of the soon to be released Australian Water Outlook seamless service with an emphasis on the Hydrologic Projections part: the methodology, the user centred-design, as well as the development of guidance material containing confidence statements and uncertainty assessments to help decision makers in understanding the service. The presentation will also provide an overview of the tactics we applied to ensure the applicability of the new service including demonstration cases developed in partnership with users.

The aim of this study is to examine the statistics of convective storms and their concomitant changes with thermodynamic variability. The thermodynamic variability is analyzed by performing a cluster analysis on variables derived from radiosonde releases at Brisbane Airport in Australia. Three objectively defined regimes are found: a dry, stable regime with mainly westerly surface winds, a moist northerly regime, and a moist trade wind regime. S-band radar data are analyzed and storms are identified using objective tracking software [Thunderstorm Identification, Tracking, Analysis, and Nowcasting (TITAN)]. Storm statistics are then investigated, stratified by the regime subperiods. Convective storms are found to form and maintain along elevated topography. Probability distributions of convective storm size and rain rate are found to follow lognormal distributions with differing mean and variance among the regimes. There was some evidence of trimodal storm-top heights, located at the trade inversion (1.5–2 km), freezing level (3.6–4 km), and near 6 km, but it was dependent on the presence of the trade inversion. On average, storm volume and height are smallest in the trade regime and rain rate is largest in the westerly regime. However, westerly regime storms occur less frequently and have shorter lifetimes, which were attributed to the enhanced stability and decreased humidity profiles. Furthermore, time series of diurnal rain rate exhibited early morning and midafternoon maxima for the northerly and trade regimes but were absent for the westerly regime. The observations indicate that westerly regime storms are primarily driven by large-scale forcing, whereas northerly and trade wind regime storms are more responsive to surface characteristics.

The Australian Bureau of Meteorology’s operational weather radar network comprises a heterogeneous radar collection covering diverse geography and climate. A naïve Bayes classifier has been developed to identify a range of common echo types observed with these radars. The success of the classifier has been evaluated against its training dataset and by routine monitoring. The training data indicate that more than 90% of precipitation may be identified correctly. The echo types most difficult to distinguish from rainfall are smoke, chaff, and anomalous propagation ground and sea clutter. Their impact depends on their climatological frequency. Small quantities of frequently misclassified persistent echo (like permanent ground clutter or insects) can also cause quality control issues. The Bayes classifier is demonstrated to perform better than a simple threshold method, particularly for reducing misclassification of clutter as precipitation. However, the result depends on finding a balance between excluding precipitation and including erroneous echo. Unlike many single-polarization classifiers that are only intended to extract precipitation echo, the Bayes classifier also discriminates types of nonprecipitation echo. Therefore, the classifier provides the means to utilize clear air echo for applications like data assimilation, and the class information will permit separate data handling of different echo types.

During the late afternoon on 16 November 2008 the Brisbane (Queensland, Australia) suburb of “The Gap” experienced extensive wind damage caused by an intense local thunderstorm. The CP2 research radar nearby detected near-surface radial velocities exceeding 43 m s−1 above The Gap while hail size reports did not exceed golf ball size, and no tornadoes were reported. The storm environment was characterized by a layer of very moist near-surface air and strong storm-relative low-level flow, whereas the storm-relative winds aloft were weak. While the thermodynamic storm environment contained a range of downdraft-promoting ingredients such as a ~4-km-high melting level above a ~2-km-deep layer with nearly dry-adiabatic lapse rates mostly collocated with dry ambient air, a ~1-km-deep stable layer near the ground would generally lower expectations of destructive surface winds based on the downburst mechanism. Once observed reflectivities exceed 70 dBZ, downdraft cooling due to hail melting and downdraft acceleration based on hail loading are found to likely become nonnegligible forcing mechanisms. The event featured the close proximity of a hydrostatically and dynamically driven mesohigh at the base of the downdraft to a dynamically driven mesolow associated with a low-level circulation. This proximity was instrumental in the anisotropic horizontal acceleration of the near-ground outflow and the ultimate strength of the Gap storm surface winds. Weak storm-relative midlevel winds are speculated to have allowed the downdraft to descend close to the low-level circulation, which set up this strong horizontal perturbation pressure gradient.

A naïve Bayes classifier (NBC) was developed to distinguish precipitation echoes from anomalous propagation (anaprop). The NBC is an application of Bayes's theorem, which makes its classification decision based on the class with the maximum a posteriori probability. Several feature fields were input to the Bayes classifier: texture of reflectivity (TDBZ), a measure of the reflectivity fluctuations (SPIN), and vertical profile of reflectivity (VPDBZ). Prior conditional probability distribution functions (PDFs) of the feature fields were constructed from training sets for several meteorological scenarios and for anaprop. A Box–Cox transform was applied to transform these PDFs to approximate Gaussian distributions, which enabled efficient numerical computation as they could be specified completely by their mean and standard deviation. Combinations of the feature fields were tested on the training datasets to evaluate the best combination for discriminating anaprop and precipitation, which was found to be TDBZ and VPDBZ. The NBC was applied to a case of convective rain embedded in anaprop and found to be effective at distinguishing the echoes. Furthermore, despite having been trained with data from a single radar, the NBC was successful at distinguishing precipitation and anaprop from two nearby radars with differing wavelength and beamwidth characteristics. The NBC was extended to implement a strength of classification index that provides a metric to quantify the confidence with which data have been classified as precipitation and, consequently, a method to censor data for assimilation or quantitative precipitation estimation.

As a response to extreme water shortages in southeast Queensland, Australia, brought about by reduced rainfall and increasing population, the Queensland government decided to explore the potential for cloud seeding to enhance rainfall. The Queensland Cloud Seeding Research Program (QCSRP) was conducted in the southeast Queensland region near Brisbane during the 2008/09 wet seasons. In addition to conducting an initial exploratory, randomized (statistical) cloud seeding study, multiparameter radar measurements and in situ aircraft microphysical data were collected. This comprehensive set of observational platforms was designed to improve the physical understanding of the effects of both ambient aerosols and seeding material on precipitation formation in southeast Queensland clouds. This focus on gaining physical understanding, along with the unique combination of modern observational platforms utilized in the program, set it apart from previous cloud seeding research programs. The overarching goals of the ...

Airborne measurements of condensation nuclei (CN), aerosol particles (APs) and sulphur dioxide (SO2) were made near a cold front to examine new particle formation and the effects of the front on CN and SO2 concentrations and the AP size distribution and concentration. Measurements were made in the boundary layer (BL) and free troposphere (FT) both preceding and following the passage of the front. Statistical analyses of CN and AP concentrations in the air masses around the front show that new particle formation was prevalent in the pre-frontal and post-frontal FT, however the post-frontal FT contained higher concentrations of ultrafine condensation nuclei (UCN). Mixing diagrams of conserved thermodynamic quantities, total water content and wet equivalent potential temperature were constructed for horizontal aircraft transects in the pre-frontal and post-frontal FT regions; they show that many of the fluctuations in UCN concentrations can be explained by mixing of air masses with differing initial concentrations of UCN. However, regions of enhanced UCN were found to be associated with mixing between air masses of distinct thermodynamic properties, suggesting that mixing between air masses with large gradients in temperature and relative humidity may have promoted new particle formation. Furthermore, analysis of fluctuations in UCN concentrations during vertical soundings show that low pre-existing AP surface area was not a necessary requirement for the production of new particles but, rather, turbulent mixing was a major mechanism for new particle production. Observations also suggest that species other than SO2 were required for new particle production to occur. Copyright © 2010 Royal Meteorological Society

Observations of aerosol-particle (AP) composition obtained via volatility measurements during the ‘Rain In Cumulus over the Ocean’ (RICO) experiment are presented. The measurements show that sub-cloud APs with a radius rp ≤ 0.2 µm are composed mainly of ammonium sulphate, while APs with a radius rp ≥ 0.2 µm are composed mainly of sea salt. The AP distribution also contains an indeterminate non-volatile component (rp ≤ 0.4 µm), which could be either elemental carbon or mineral dust. Copyright © 2008 Royal Meteorological Society

Airborne measurements, obtained during the Asian Aerosol Characterisation Experiment (ACE-Asia), of SO2 and condensation nuclei (CN) concentrations were made in the local environment of a cumulus cloud band. Conserved quantities, wet equivalent potential temperature θq, and total water content Q, were used to identify the sources of air detrained on the downwind side of the cumulus band. It was found that ~65% of the detrained air originated from below cloud base and the remainder was air that had been entrained from the free troposphere upwind of the cloud and subsequently been detrained. Calculation of the sources of the detrained air parcels enabled a prediction of the concentration of SO2 and CN, assuming that SO2 and CN experienced no processing within cloud. A comparison of the predicted concentration of SO2 and CN was made with those observed. The concentration of SO2 observed was less than predicted and the amount of SO2 scavenged within cloud was calculated. The CN concentration observed was also less than predicted and, moreover, inclusion of the loss of CN to cloud droplets due to Brownian scavenging resulted in an enhanced decrease of the number concentration of CN predicted. Clear air regions around the cloud exhibited no indication of being a major source of new particles. It was concluded that new particles were formed within cloud.

Airborne observations of aerosol processing by a cumulus cloud, obtained during the ACE-Asia experiment, are presented. Mixing diagrams of conserved variables, wet equivalent potential temperature and total water mixing ratio are used to identify the fraction of cloud-base air that has combined with environmental air entrained into the cloud. We extend this analysis to deduce the origins of detrained air. Using observations of aerosol spectra obtained from below cloud base, and upwind and downwind of the cumulus band, we predict the shape of the aerosol spectrum in the detrained air and compare it with observations. The results show evidence of size-dependent scavenging of the aerosol, with up to 20% loss of ultra-fine (particle radius, rp ≤ 0.003 µm) and fine mode particles 0.006 µm ≤ rp ≤ 0.066 µm) and up to a 40% loss of aerosol in the accumulation mode 0.066 µm ≤ rp ≤ 0.7 µm). We conclude that coalescence of cloud droplets, even in a mildly precipitating cumulus, can result in a substantial depletion of larger accumulation mode aerosol. The cloud not only caused a general reduction in aerosol concentration, but also substantially modified the aerosol size distribution in the lower free troposphere. This effect may significantly influence the properties of clouds subsequently formed on the detrained aerosol. Copyright © 2006 Royal Meteorological Society.