These up-and-coming technologies can help us ‘weather’ changing climatic conditions.
One of the things that can ruin a good day is bad weather that you’re completely unprepared for. While not carrying an umbrella on a rainy day is an inconvenience for the average Joe, a lack of information about weather conditions can have drastically damaging effects on crops and buildings.
This is precisely why we have weather prediction technologies—to help people and nations at large prepare for bad weather so that they face the least possible risk of damage. As we deal with one weather crisis after another, from heat waves to floods, particularly given the impact of climate change, it is more important than ever to predict weather conditions accurately. Let’s take a look at the brand-new technologies being created to improve the precision of weather forecasting.
Using artificial intelligence to predict severe weather
Much like other industries, artificial intelligence (AI) has entered the weather forecasting space as well. Within weather forecasting, AI is being used for detecting storms. Researchers from Pennsylvania State University have created ClimateAI which analyzes cloud formations to detect the possibility of severe weather events. To do so, they sought the help of meteorologists to study clouds. They found that comma-shaped cloud formations often lead to hail, blizzards, high winds and thunderstorms. The resulting data was used to train ClimateAI, which can now catch the cloud patterns with almost 100% accuracy.
Similarly, Microsoft India and Sustainable Environment and Ecological Development Society (SEEDS) have developed an AI called Sunny Lives which can predict cyclones, floods as well as heatwaves in India.
Analyzing data to give hourly temperature updates
Knowing about adverse weather conditions is great but finding out what the weather of a particular area would look like throughout the day is equally invaluable. This tells you when to carry that umbrella, when to dry your clothes and when to water your plants. Again, Microsoft is making its name in this space with its AI model— DeepMC. This AI uses machine learning and deep learning to go through historical weather data and mainstream forecasts to find hourly temperature patterns with up to 90% accuracy. Other companies, such as the Indian startup Frizzle, are also using historical data to predict hyperlocal weather patterns with 95% accuracy.
Satellites for weather data collection
While Satellites have been used in weather forecasting since the 1960s, attempts are being made to improve data accuracy. One such attempt is the special prism invented by aeronautical engineer Frédérick Pasternak. The prism would be used in a pre-existing weather forecasting instrument called Infrared Atmospheric Sounding Interferometer (IASI) to help deal with the distortion issues that were previously present in IASI. The special prism developed by Pasternak would give meteorologists precise information about temperature and humidity, identifying atmospheric gases and air concentration above the ground. This will, in turn, help accurately predict weather conditions.
Deep learning to predict rain
U.K.-based startup DeepMind collaborated with the U.K.’s national weather service called Met Office to create a deep learning tool called DGMR (deep generative model of rainfall), which accurately predicts the possibility of rain in the next 90 minutes. This tool is much more on the mark than any other prediction tool present in the weather forecasting space today.
Using data visualization tools to understand weather conditions
While all the previous developments were related to collecting data and predicting the weather, for people to understand weather conditions, they need to be able to see what is happening without going through heavy data sets. Consequently, companies are working to simplify the visualization of weather data. One such company is the U.S.-based environmental intelligence firm Earth Networks which provides web-based visualization of environmental conditions thereby helping businesses prevent any weather-related issues they might otherwise end up facing.
In 2021, the weather forecasting market was worth US$2.14 billion, projected to reach US$3.78 billion by 2030. One of the factors contributing to this growth is the rapid rise in the available technological implements. The arrival of innovative technologies will be a great asset to human forecasters working in this sector. These forecasters previously focused on generating accurate weather predictions based on their knowledge and academic training. However now, with the advent of the implements we mentioned in this article, they will be able to direct their efforts to communicate the implications of forecasts to the public. And thus, they will be able to help people and businesses navigate their day-to-day lives more effectively based on weather conditions.
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