Tag Archive: extreme rainfall

Research brief: Why Melbourne’s worst storms come in lines

September 3, 2021 8:51 am Published by Comments Off on Research brief: Why Melbourne’s worst storms come in lines

It has long been suggested in the literature, and discussed casually by meteorologists, that rainfall in Melbourne often occurs as lines of precipitation. However, this had yet to be quantified. CLEX researchers analysed 15 years of radar data from the Australian Radar Archive, using an objective method to identify and track these ‘linear systems’ based on radar reflectivity, size, and shape characteristics.

BOM02: Impacts of hydrological extremes using machine learning

August 23, 2021 8:36 am Published by Comments Off on BOM02: Impacts of hydrological extremes using machine learning

This project will explore the use of supervised and unsupervised statistical learning methods (such as neural networks, random forest, clustering) to understand the impact of climate change on hydrological extremes and/or to simulate downstream impacts on affected sectors, such as agriculture, energy, transport, water resources management.

UMELB03: Storm organisation and short duration extreme rainfall in Melbourne

August 18, 2021 12:06 pm Published by Comments Off on UMELB03: Storm organisation and short duration extreme rainfall in Melbourne

In Melbourne, 50% of rainfall and 75% of extreme daily rainfall occurs on days with at least one linearly organized convective system. However, thunderstorms are often localized events, and much of the rainfall in a region falls over a short period of time. Furthermore, not all thunderstorms necessarily occur in lines, and organized storms that lead to extreme sub-daily rainfall may be different from those that lead to extreme daily rainfall. This projects aims to identify and categorize organizational structures linked with the most intense rainfalls in the region.

UNSW05: Quantification of Continental-Scale shifts in Extreme Precipitation Intensity Across the Globe

August 18, 2021 9:15 am Published by Comments Off on UNSW05: Quantification of Continental-Scale shifts in Extreme Precipitation Intensity Across the Globe

Due to the lack of appropriate historical datasets, quantification of shifts in global extreme precipitation intensity has not been possible so far. This project will use a recently developed long-term global dataset of daily precipitation alongside a dataset of global temperature changes to calculate the CC scaling for broad climatic regions across the globe.

UNSW04: IF It Rains Does It Pour? Understanding Concomitancy of Mean and Extreme Changes in Global Daily Precipitation

August 18, 2021 9:14 am Published by Comments Off on UNSW04: IF It Rains Does It Pour? Understanding Concomitancy of Mean and Extreme Changes in Global Daily Precipitation

Recent research has shown that mean (raining) and extreme (pouring) changes can align in some regions. This project will use a recently developed long-term global dataset of daily precipitation to answer why, how and where changes in mean frequency and intensity align with changes in extreme frequency and intensity of precipitation.

UMELB02: Convection and extreme rainfall characteristics using radar

March 30, 2021 10:32 am Published by Comments Off on UMELB02: Convection and extreme rainfall characteristics using radar

The accumulation of rainfall over a given area depends on a range of things, including duration, intensity, and propagation speed. It is the characteristics of convection that ultimately determine these rainfall properties. The idea for this project is to use a simple method to characterise the properties of the most intense convective / rainfall bearing systems from radar data.

Research brief: The Sensitivity of Atmospheric River Identification

October 20, 2020 9:43 am Published by Comments Off on Research brief: The Sensitivity of Atmospheric River Identification

CLEX researchers explore the challenges of identifying atmospheric rivers and find that detecting these events is highly variable according to resolution, and choice of the integrated water vapour transport thresholds. The uncertainties in a single detection method and data parameters may be as large as uncertainties across AR detection methodologies.