EGU22-7879
https://doi.org/10.5194/egusphere-egu22-7879
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Selecting Good Quality Official and Citizen Science Rain Gauge Data and Blending with Radar for More Accurate Rainfall Representation 

Tess O'Hara, Elizabeth Lewis, Fergus McClean, Hayley Fowler, and Geoff Parkin
Tess O'Hara et al.
  • School of Engineering, Newcastle University, United Kingdom of Great Britain – England, Scotland, Wales (t.ohara@ncl.ac.uk)

Rainfall data collected by citizen scientists is typically regarded as low quality and therefore remains underused in hydrological applications. Conversely, official data collected by professional organisations is often treated as more reliable than it really is. Here we demonstrate that value can be extracted from citizen science rainfall data by applying automated statistical quality control combined with manual checks. We also consider the pros and cons of citizen science rain observations.

Carefully selected rain data from official and citizen science gauges have been blended with radar.  Examples of how rainfall depths vary depending on the data inputs are presented, highlighting the benefit of incorporating all available data sources. This approach is particularly important when determining rainfall during spatially and temporally variable convective storms. The research is concerned with convective storms that resulted in pluvial flooding in urban areas of the UK between 2014 – 2018, however, the methodology could be implemented in any location where hourly (or shorter interval) rain gauge data and radar are available.  

How to cite: O'Hara, T., Lewis, E., McClean, F., Fowler, H., and Parkin, G.: Selecting Good Quality Official and Citizen Science Rain Gauge Data and Blending with Radar for More Accurate Rainfall Representation , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7879, https://doi.org/10.5194/egusphere-egu22-7879, 2022.

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