This blog post was written by Howie Chan, Business Analyst at TechAlliance.
London has already had its fair share of wintery weather this season and I thought I’d take the time to highlight some of the technology that helps us track and predict weather.
Actual weather tracking is quite expensive. A sophisticated weather satellite can cost upwards of $650 million and ground weather stations can easily cost $1,000’s. Over the years, Environment Canada, in partnership with other international organizations (like the NOAA), have built a network of sensors and satellites in a coordinated effort to track environmental conditions.
Weather plays a large role in our daily lives. At the micro-level, individuals are most concerned with changes in weather conditions (from good to bad, and bad to worse). Weather can also be tied to headaches, anger and general unproductiveness. Although some psychologists and economists argue that rainy weather actually improves productivity.
Weather also has huge economic and environmental impacts. Hurricane Sandy ($75 billion), Typhoon Haiyan ($5.8 billion), and Canada’s own Quebec ice storm in 1998 ($5-7 billion) are all examples of just how costly extreme weather can be.
Weather also affects retail and commodity demand as well as supply chains (summarized in the “How Weather Influences the Economy” ISO report).
More recently and emerging from traditional sources of weather news (radio, television and print), are new weather apps. These apps take available data from sources like Environment Canada and display weather in an easily understood way. Essentially, these apps compete to provide an easy-to-use interface at the user’s fingertips. Apps at this level come from all sorts of companies (The Weather Network, Yahoo Weather, MacroPinch, etc…)
This leads us to ask whether there is room for disruptive innovation. I think we can definitely improve the weather industry and here are 3 of my suggestions:
1. Weather apps should tell me the actual weather where I stand. It will require the ability to provide real-time, granular updates for a particular location which is absolutely possible. Providing this level of information gives users a good idea of the immediate weather which is appropriate for short-term trips and activities.
2. Granular forecasting is key. Using established weather models you should be able to relay granular information of a specific location. Granular forecasting allows a user to plan activities in the 1 week horizon and could differ tremendously from the existing regional forecasts.
3. Weather forecasting models should be incorporated into traffic applications. Poor weather conditions create poor driving conditions – it’s a fact. Overlaying weather conditions will dramatically improve long-distance trips by optimizing both speed and safety.
As many of these technologies are possible, I think we will definitely see an emergence of some neat startups over the next few months – check out Cumulonimbus for a start.
