Reliable rainfall estimates and forecast are essential for efficient water resources and flood risk management. The availability of new rainfall products from latest radar technology and international satellite missions adds to the growing databases of rain gauge measurements to provide water managers with a wealth of data. However, this enhances the problem of how to handle and make best use of these data to efficiently derive reliable estimates and forecasts of precipitation at the desired level of detail. Rain++ offers robust and customised solutions to address these challenges.
Based upon cutting-edge stochastic methods, geo-statistics and hydro-meteorological research and making use of advanced computing technologies (e.g. parallel/GPU programming), Rain++ offers four core techniques for handling and enhancing rainfall estimates and forecasts:
We use Bayesian methods to integrate the advantages of data from multiple sensors.
We use stochastic methods to generate rainfall estimates at the required scales.
We use advanced image processing theory to provide reliable rainfall nowcasts.
We use latest climate projections together with stochastic tools to shed light upon future rainfall.
These techniques can be deployed as stand-alone or web-based services both for offline as well as real-time applications. Alternatively, they can be customised and embedded within the client’s operational system to meet operational requirements. Beyond these techniques, at Rain++ we are happy to help you tackle other rainfall related challenges which require advanced data analytics, statistical, hydro-meteorological and computational skills.
Rain++ consists of experts in engineering, mathematics and computing from academia and beyond, coordinated by our core team:
Hydro-meteorologist and Software Developer
Engineering Mathematician
Hydrologist and Hydraulic Network Modeller
