Silo AI and Hurricane Unwinder predict tropical cyclones by applying computer vision on satellite images

Silo.AI and Hurricane Unwinder collaborate in building weather forecasts of extreme tropical cyclones. Rapid intensity changes and intense storms are increasing due to climate change, resulting in one fifth of the world’s population being exposed and at an annual cost of 30 billion euros. The computer vision algorithm that Silo.AI helped develop is able to forecast hurricane intensity at world-class accuracy, currently up to 24 hours with the goal of predicting up to 96 hours in advance. The solution built by Hurricane Unwinder and Silo.AI won the ESA’s Earth observation award Copernicus Masters in 2018.

Climate change is making intense storms more common and rapid intensity changes currently often come as a surprise. Hence inadequate warnings and preparations often lead to excessive damages. Hurricane Unwinder spun off from research at Finnish Meteorological Institute last year with the goal of replacing traditional numerical weather forecasts with a computer vision solution. In partnership with Silo.AI, they built an award-winning computer vision solution that predicts tropical cyclones in the coastal areas of the Atlantic, the Pacific and the Indian Ocean. The solution leverages high resolution satellite images and other parameters such as sea water temperature and weather forecasts.

– Traditional numerical weather forecasts are not able to forecast the intensity of the storm at the same level of detail as satellite images do. There is no existing computer-vision-based product to predict intensity changes, although scientific research supports the approach. With the help of Silo.AI, we’ve been able to create the world’s first forecasting solution with world-class accuracy, says Svante Henriksson, CEO of Hurricane Unwinder. 

Knowing the intensity of tropical cyclones is very important for both physical and financial preparation. A one-point change on the five-point Saffir-Simpson scale describing tropical cyclone intensity means a five-to-six-fold change in average damages. Tropical cyclones currently cause average annual damages of 30 billion euros with the disastrous 2017 Atlantic hurricane season alone having caused over 200 billion in damages.

– Hurricane Unwinder is a good example of a company with a strong basis in science and a clear vision for a field where they have over 15 years of experience. With 10 years of high-resolution satellite images of tropical storms, we were able to create a computer vision based AI solution for predicting these extreme conditions. We're proud to be part of such a high-impact project that has the potential to help governments and cities of some of the world’s most populous areas, comments Peter Sarlin, CEO of Silo.AI.

More information

Peter Sarlin
CEO, Silo.AI
+358 40 5727670

Svante Henriksson
CEO, Hurricane Unwinder
+358 50 4087900

Hurricane Unwinder does tropical cyclone forecasting and measurement. Spun off from research at Finnish Meteorological Institute by Svante Henriksson and Antti Pasila, the company uses cutting-edge computer vision to forecast tropical cyclones and IoT technology to measure them. Chief Technological Officer Kim Kaisti is responsible for developing the StreamSonde, a novel device weighing only 5 grams that floats around the natural winds of tropical cyclones and measuring them with world-class accuracy.  The company has a total of 8 employees and is currently based at the European Space Agency Business Incubation Centre on the Aalto University campus.

Silo.AI is the largest AI solution and service provider in the Nordics that offers scalable expertise in machine learning, computer vision and natural language processing. Silo.AI strongly believes in the future of human-centered AI solutions to provide strategic assets to the core business of its customers in a measurable, safe and explainable way. The company serves clients across several industries on four continents. Some Silo.AI solutions include a tool for the Finnish airline Finnair to improve situational awareness and a tool to improve water quality at water treatment facilities for the global leading engineering company Ramboll.


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