Startup ClimateAi is using machine learning to improve forecasts weeks to months in advance.
A tractor ploughs a field ready for the sowing of rye grass seeds on a farm, situated in an area declared a drought emergency due to lack of rain, in the Llado district of Girona, Spain, on Tuesday, Aug. 8, 2023. Spain's Catalonia region has declared a drought emergency in 24 municipalities following a prolonged lack of rain, and will begin to impose water restrictions next week. , Bloomberg
Forecasting extreme weather events like hurricanes and heat waves for hyper-specific geographies weeks to seasons ahead is difficult to do accurately. But having sufficient time to prepare for a natural disaster can be the difference between averting catastrophe and not. Those approaches include ingesting data from a variety of sources and using it to search for patterns and make predictions. ClimateAi pairs its deep learning models with both government-run forecast models like those from the US National Oceanic and Atmospheric Administration and numerical models like those used by the Intergovernmental Panel on Climate Change to achieve what it claims are higher accuracy and forecasting reliability.
Most of ClimateAi's approximately 40 global customers are in the food and agriculture industries, but Gupta is hoping to expand further into other sectors including manufacturing and energy.
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