Calculating power and technology's advancement like artificial intelligence has enabled researchers to not just examine data faster and simpler, but learn from historical data, as well for better situational consciousness and decision-making.
A Forbes report specified that within the weather community, AI is being used to many different challenges. One concentration is to develop a better weather forecast.
There is much argument about AI and the benefits of its employment from dating, marketing, and social media to exploration of space and medical advancements. Relatively, there is no industry that has been impacted by this dynamic tool which includes the weather.
The Internet of Things
Meteorology has constantly struggled with the issue of big data. Those in the field would even suggest that science was the epitome of large data before the word turned mainstream.
Because of the weather's multivariate and chaotic nature for over 500 years that meteorologists have addressed using terabytes of data, as well as modeling variables to generate an accurate forecast.
Currently, the data is still being processed on the scale of petabytes because of the Internet of Things, ensemble modeling, and more sensors.
According to Tel Alcorn, a writer, he approximates that the weather models today integrate roughly "100 million pieces of data every day, degree of complexity similar to simulations of the brain of humans or the universe's birth.
95-Percent Preciseness
Forecasting is progressively turning more precise. At present, a five-day forecast has 90-percent preciseness, similar to a three-day prediction 25 years ago.
Additionally, short-term forecasts, or presently casting in hourly spans of time, are more problematic specifically because of micro-changes in the surface. In connection to this, DeepMind and the University of Exeter scientists have partnered with the United Kingdom.
Met Office to develop a "nowcasting system" through the use of AI would surpass such challenges to make more precise short-term forecasts which include critical storms and floods.
Another study is investigating the efficiency of modeling and the manner AI can examine previous weather patterns to forecast future occurrences not just more efficient but more precisely, as well.
Application of AI
For instance, use of AI in the utility sector to forecast potential outages, a similar Daily US Post report specified. Past outage data is gathered on a particular utility site or region and enables a computer to produce forecasts for future needs according to predicted weather conditions.
Essentially, such outage data understands the manner infrastructure has responded to previous storms which include learning differences in the hardening of networks, realizing individual infrastructure components' age and maintenance practices.
Additionally, these datasets will produce a baseline of potential outages from future storms. The same approach can be applied with municipalities, according to a similar Paper Tribune report.
Understanding variables like the topography, infrastructure, and evacuation routes of the city, along with historical weather information, such data can help cities achieve a better understanding into potential sites of effect and danger of public or safety of infrastructure.
And while advanced technology and understandings are being talked about, experts in the field think it is essential to note that the human element remains critical to the process.
Related information about AI predicting weather forecast is shown on What's AI's YouTube video below:
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