Scientists and schools join forces to understand urban climate

A new citizen science project will place meteorological and air quality sensors in Sydney schools to gather valuable research data and increase awareness of the changing local urban environment.

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The Schools Weather and Air Quality (SWAQ) project is the brain-child of Melissa Hart, Angela Maharaj and Giovanni Di Virgilio of UNSW’s Climate Change Research Centre. With funding from the Department of Industry, Innovation and Science, SWAQ will improve urban weather and air quality measurements around Sydney by placing meteorological and air quality sensors in its schools. Students will collect and analyse research quality data for use in science and geography curriculum-aligned classroom activities. The data will also be freely available online to the public and researchers via this website, enabling everyone to visualize the data and the current weather and air quality of each school’s location.

SWAQ investigator Angela Maharaj will discuss the SWAQ project and citizen science at a public lecture at the Bureau of Meteorology in Sydney on December 14 2018 as part of the upcoming Frontiers in Fluid Dynamics workshop. All are welcome to attend this event.

Speaker: Dr Angela Maharaj (UNSW).

Title: Schools weather and air quality (SWAQ): where citizen science meets urban climate research.

When: 6:00 pm, 14 December 2018.

Where: Bureau of Meteorology, 16/300 Elizabeth St, Sydney




Last chance to register for Frontiers of Fluid Dynamics workshop

Friday 7 December is the last day to register for this interdisciplinary workshop sponsored by the Bureau of Meterology, the Australian Meteorological and Oceanographic Society, and UNSW School of Mathematics and Statistics.

Find out more:

When: 8:30am-5:30pm, 14 December 2018 (lunch provided).

Where: Bureau of Meteorology, 16/300 Elizabeth St, Sydney

Registration: (Deadline 7 December)

Upcoming seminar by Sarah Perkins-Kirkpatrick on Stats and Heatwaves

Monday November 5th, 4pm
RC-4082, The Red Centre, UNSW 

Heatwaves are changing. What role does statistics have in understanding these changes?

Heatwaves are increasing in their frequency, intensity and duration. Loosely described as prolonged periods of excessive heat, statistical techniques underpin their measurement, understanding their changes, the physical mechanisms behind these changes, the role anthropogenic climate change plays, and estimates of uncertainty (or certainty)  surrounding these factors.  This talk will explore the vital role statistics has behind heatwaves, making our understanding of these high-impact events possible.

Dr Sarah Perkins-Kirkpatrick is an ARC Future Fellow at the Climate Change Research Centre, UNSW Sydney. Her background focuses on measuring heatwaves, what drives them, the role climate change plays and future projections in a warmer world. Sarah’s Future Fellowship is working towards improving the attribution methods of extreme events (such as heatwaves) to human influence, as well as determining whether the health impacts of heatwaves can be attributed to human influence on the climate. Since gaining her PhD in 2010, Sarah has published 60 peer reviewed scientific papers on climate extremes. She co-leads an expert team for the World Meteorological Organisation’s Commission for Climatology, and is a frequent voice in local and international media on all things climate change in heatwaves. Sarah has won numerous awards for her research, and was named one UNSW’s 20 rising stars who will change our world in 2016.

This seminar is part of the ‘Mathematics for Planet Earth’ initiative ( and is co-hosted by the Department of Statistic at the School of Mathematics and Statistics at UNSW, Sydney. Light refreshments will follow the seminar. 

Call for abstracts: Big data in oceanography and meteorology at AMOS-ICTMO 2019

Abstracts are invited for a special session on Big Data in Oceanography and Meteorology at the annual meeting of the Australian Meteorological & Oceanographic Society (AMOS) and the International Conference on Tropical Meteorology and Oceanography (ICTMO), held in Darwin, NT, from 11-15 June 2019.

AMOS-ICTMO 2019 will bring together experts in meteorology, oceanography, climate, and other related sciences from Australia and around the world as well as government representatives, NGOs, businesses and the media to focus on the latest research.

The following special session on big data will be convened by Moninya Roughan, Shane Keating, and Steefan Contractor. Abstracts for oral and poster presentations are to be submitted via the AMOS-ICTMO 2019 submission site. The deadline for submission is Sunday 18 November 2018.

Big Data in Oceanography and Meteorology: Challenges, Applications, and Data Products

Oceanographers and meteorologists are drowning in a tide of data. Data availability has increased steadily in recent years due to the move towards higher resolution modelling and the increase in observations. Observational density has increased because of an increase in frequency of measurements, introduction of new single and multi-instrument datasets and new remote-sensing platforms. As a result, studies of geophysical fluid dynamics are becoming increasingly data driven. In order to derive valuable insights and knowledge from large volumes of data, new methods and techniques are emerging in the field of big data for visualization, analysis, and data dispensation. Vast numbers of datasets are being published and released freely for analysis and sharing.

We invite talks that are broadly related to the field of big data and data products. We encourage presentations on analysis of data from the syntheses of programmes such as IMOS and CMIP5 analyses, projects that deliver products and insights to end users, or that focus on pattern analysis and identification of complex relationships, predictive modelling using supervised and unsupervised algorithms, tools for handling large datasets and for increasing computational efficiency, novel applications of statistical learning and high volume time series analysis, blending of diverse datasets, reproducibility of analysis, inherent structural uncertainties in data, best practices in big datasets and guidance on recommended use for new and existing datasets.