Using weather radars to forecast more than just the weather
Insect species sometimes exhibit mass migratory movements across Australia. Most of us are familiar with locust swarms and the impressive movement of masses of bogong moths. It has been known for a long time that the flying movement of insects, birds and bats at high elevations can be seen on weather radars. However, their primary function is to provide us with information on rain, storms, and snow.
A new project led by CSIRO postdoctoral research, Mr Mubin Ul Haque, aims to extract insect movement information from this rich data stream and use it to help us predict and better manage pest outbreaks across Australia.
Locust swarms are a good example of insect mass movement.
The data that weather radars produce is complex and big they can scan multiple objects in airspace up to 3000m above the ground every 15 minutes. Analysing, interpreting, and classifying the different flying objects is a challenging task. Mr Haque will incorporate the capability of Machine Learning (ML) models to understand how those models can be utilised to analyse, interpret, and classify different flying animals in the airspace. Mr Haque will collaborate with scientists in the Agriculture and Food, Health & Biosecurity (Australian Centre for Disease Preparedness) and Data61.
Ultimately, we will create a platform that allows people to observe real-time insect movement activity across Australia (much like we can with weather information now). This will be of interest to both professional and amateur entomologists but also has the potential to inform farmers about potential risks from pest outbreaks.
An example of what we could observe from a weather radar image. The red circle and diamond shape indicates the location of Hillston weather radar2 and Hay Entomological Radar. The radar data has been obtained from the daily updated weather radar data Level 1 and the figure is developed by using Py-art.
Project Team: Mubin Ul Haque, Hazel Parry, Sarina Macfadyen, Joel Dabrowski
References
D. Lack and G. C. Varley, “Detection of Birds by Radar,” Nature, vol. 156, no. 3963, Art. no. 3963, Oct. 1945, doi: 10.1038/156446a0.
V. A. Drake, S. Hatty, C. Symons, and H. Wang, “Insect Monitoring Radar: Maximizing Performance and Utility,” Remote Sens., vol. 12, no. 4, Art. no. 4, Jan. 2020, doi: 10.3390/rs12040596.
J. Soderholm, A. Protat, and C. Jakob, “AURA – Operational Radar Network Level 1 Archive.” NCI Australia, 2022. doi: 10.25914/508X-9A12.
J. J. Helmus and S. M. Collis, “The Python ARM Radar Toolkit (Py-ART), a library for working with weather radar data in the Python programming language,” J. Open Res. Softw., vol. 4, Jul. 2016, doi: 10.5334/jors.119.