Welcome back to Industry Shifters.

Today we are exploring the magical world of meteorology.

Could crowdsourced weather data improve weather forecasting in Australia’s rural regions?

Let’s find out!

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Crowdsourced Weather Data

Crowdsourced weather data in Australia leverages a network of individual contributions from smartphones and personal weather stations to provide real-time, hyper-local weather insights. 

Unlike traditional meteorological data, which comes from established weather stations, crowdsourcing pulls information directly from public sources, offering granular data that can improve localised forecasts and assist with rapid weather assessments. 

This approach has gained traction through platforms and apps where users voluntarily report local conditions such as temperature, rainfall, or wind speed, which is then aggregated and analysed by weather services. 

In Australia, where weather conditions can be highly variable due to its diverse geography, this technology enhances data coverage in underserved regions, helps track severe weather events in real time, and contributes to more accurate, community-driven forecasting models.

Potential Impact

While a precise figure for the entire meteorology industry's value in Australia is difficult to pinpoint, as of 2021 the industry employed approximately 710 meteorologists across Australia, and the industry as a whole is estimated to be worth around $200 million AUD. 

Therefore, apps and products that incorporate crowdsourced weather data could be very profitable endeavours and could come to account for tens of millions of dollars within this industry - provided this technology continues to develop and offer accurate weather insights to its users.

Why this WILL be disruptive:

• Enhanced Coverage and Localised Accuracy: Crowdsourced data can fill gaps in traditional weather station networks, especially in remote and underserved areas like rural Australia or the outback. This can improve the spatial resolution of weather observations, leading to more accurate and localised forecasts, particularly for severe weather events like hail, tornadoes, and flash floods.

• Real-Time Reporting for Quicker Response: Citizens can provide real-time weather observations, enabling faster detection and response to severe weather conditions. This can enhance early warning systems and improve public safety, potentially saving lives during extreme weather events.

• Cost Efficiency and Financial Benefits: Crowdsourcing weather data is cost-effective compared to traditional meteorological services, which require expensive infrastructure and expert staff. By leveraging devices like smartphones, crowdsourcing reduces operational costs while still providing valuable data.

Why this WON’T be disruptive:

• Data Quality and Reliability Issues: Crowdsourced data can be less reliable than professional observations, as it may come from non-expert contributors using uncalibrated or non-standardized devices. This inconsistency can undermine forecasting accuracy and reliability unless rigorous quality control and validation processes are in place.

• Geographical and Technological Limitations: Crowdsourced data may be unevenly distributed, particularly in areas with poor infrastructure or low technological penetration, limiting its impact on forecasting accuracy. Reliance on mobile devices and internet connectivity can further hinder data collection in rural or remote regions.

• Regulatory and Legal Issues: The use of non-official data sources in weather forecasting could raise questions about liability, regulatory compliance, and adherence to official standards. In Australia, for example, government agencies like the Bureau of Meteorology set strict regulations for weather reporting, which may not accommodate crowdsourced data.