"The project aims to prove commercial potential of innovative system for monitoring and prediction of usual and chemical weather and microclimate based on:
• New concept and models of atmospheric planetary boundary layer (PBL) as natural object responsible for local features of weather and climate
• Wireless sensor network technology to perform monitoring of environmental parameters with very high spatial and temporal resolution
• Machine learning technology for integrating weather-forecast data and sensor-network monitoring data into super-fine resolution weather forecast or microclimate evaluation
• Local GIS and decision-making support (DMS) technologies
The basic idea lies in retrieving extreme and local features of weather (or climate) from combination of inexact information from operational weather prediction (or climate) models with local monitoring of PBL-control and customer-specific parameters. Both information flows are digested through machine-learning technology accounting for new knowledge about PBL. The system starts operating with a period of tuning to local features of weather (or climate), which improves its performance and guaranties higher than operational quality of weather forecast (or microclimate evaluation).
Commercial potential of the idea will be implemented through establishing a business aimed at:
• Production and sales of monitoring/forecast correction systems: advanced versions – to municipalities, hospitals, agricultural, transport and energy companies; simple versions – to collective or individual customers, e.g., local communities, farmers, owners of summer houses
• Providing microclimate and land-use consulting, e.g., for construction or precision agriculture
• Delivering locally adjusted customer-specific weather forecasts for weather-dependent companies
The project implies global economic and societal benefits due to improved forecasting of extreme and dangerous weather events and advanced tools for land use."
Fields of science
Call for proposal
See other projects for this call