RAINVIS: rainfall visualization prototype

URL: http://hypewebapp-tst.smhi.se/skyfall/

Rainvis is a real-time high-resolution high-intensity rainfall visualization prototype from Sweden. It has been developed within the MUFFIN project in order to provide the user the best possible information and decision support both before a flood event (forecasts – for early warning), during the event (observation and forecast – for situation awareness) and after the event (observations – for post-event analysis). There are many visualization products today to assess the risk of high-intensity rainfall and subsequent pluvial flooding. However, there are hydrological limitations with these which Rainvis has attempted to overcome, for example the following. (1) The radar-based rainfall estimates are more closely adjusted towards gauge observations, represented by daily gridded fields, which ensures accurate long-term accumulations (Berg et al. 2016). (2) Concerning spatial resolution, the radar rainfall is averaged over hydrological basins (~40 000 sub-basins) covering Sweden with a median size of ~7 km². (3) Concerning temporal resolution, besides the highest available (1 hour), rainfall may be averaged over durations of 2, 3, 6 or 12 hours. (4) Observations from the recent hour(s) may be combined with forecasts for the coming hour(s). Works with Google Chrome.

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Name RAINVIS: rainfall visualization prototype
Description Rainvis is a real-time high-resolution high-intensity rainfall visualization prototype from Sweden. It has been developed within the MUFFIN project in order to provide the user the best possible information and decision support both before a flood event (forecasts – for early warning), during the event (observation and forecast – for situation awareness) and after the event (observations – for post-event analysis). There are many visualization products today to assess the risk of high-intensity rainfall and subsequent pluvial flooding. However, there are hydrological limitations with these which Rainvis has attempted to overcome, for example the following. (1) The radar-based rainfall estimates are more closely adjusted towards gauge observations, represented by daily gridded fields, which ensures accurate long-term accumulations (Berg et al. 2016). (2) Concerning spatial resolution, the radar rainfall is averaged over hydrological basins (~40 000 sub-basins) covering Sweden with a median size of ~7 km². (3) Concerning temporal resolution, besides the highest available (1 hour), rainfall may be averaged over durations of 2, 3, 6 or 12 hours. (4) Observations from the recent hour(s) may be combined with forecasts for the coming hour(s). Works with Google Chrome.
License License not specified
Publication year 2019