Atmo, an AI weather forecast system, has set its sights on the Asia-Pacific region to help improve the lives of citizens, said CEO Alexander Levy in an interview during the COP27 climate summit in Egypt last November.
Levy said during the interview that the Asia-Pacific region is “a vulnerable place” due to the massive population and vulnerability to extreme weather conditions.
The remarks come at a time when the World Meteorological Organization estimated that Asia suffered nearly USD 36 billion in economic losses due to extreme weather events in 2021 alone, with nearly 50 million people affected, Nikkei reports.
The CEO also stated his belief that AI forecasting is the way of the future, as machines are able to continuously learn, helping them make more precise predictions about weather patterns that deviate from the norm.
According to the United Nations, half the world’s countries lack an early warning system to help communities prepare for hazardous climate-related events, with small-island developing states in the Pacific often having weak coverage.
The Netherlands-based Global Commission on Adaptation estimates that spending USD 800 million on such systems could help avoid up to USD 16 billion in losses annually, as well as protect human lives.
Levy continued by saying that most rich countries implement cutting-edge traditional forms of forecasting, which poorer countries who are vulnerable to extreme weather conditions cannot afford. AI and deep learning help to combat this as it is a lot more efficient, making it that much more affordable.
The start-up has recently signed an agreement with Indonesia, to focus on storm forecasting, extreme flash flooding prediction, and rain forecasting, to start operating next year.
Furthermore, the company has also been “in discussion” with other Southeast Asian countries and is in the planning process with partners in Japan to go online this year.
Founded in 2020, Atmo develops AI-based weather forecasting systems, early warning systems, and weather models, mainly partnering with national meteorological agencies to integrate into their existing infrastructure for tasks such as disaster response.
The start-up informed that their founding AI research showed that the rate of meteorology improvement could rise 10X, and operating costs drop 90%, retaining results that show first-of-a-kind systems that will put beyond-state-of-the-art weather forecasting in the hands of every community worldwide.
