Delft Measures: Assessment of citizen science rainfall observations
Arjan Droste1, Marchien Boonstra1, Marit Bogert1, Sandra de Vries2
1Water Management Department, Delft University of Technology, Delft, The Netherlands
2 PULSAQUA, Rotterdam, The Netherlands
The Citizen-Science programme ‘Delft Measures’ has been running for several years in the city of Delft, the Netherlands. Interested citizens can apply to receive a low-cost Alecto WS5500 weather station, to measure local meteorological parameters in their own garden. Regular meetings and workshops with the citizen scientists provide a unique measurement setup that typical studies of Private Weather Stations do not have: information about the conditions of the private space that the stations are installed in. To make full use of the interactions with the citizen scientists, and test the scientific quality of these Alecto stations, at the Green Village (TU Delft’s outdoor urban climate field lab), 8 test stations have been explicitly installed in ways that a citizen might do: not perfectly! Such a two-way process with a long-term group of dedicated Citizen Scientists has shown great potential to improve the usability of crowdsourced data for urban hydrometeorological applications.
Towards a toolbox for real time data acquisition of personal weather station rainfall data
Georges Schutz1, Jochen Seidel2, Nathalie Rombeek3
1RTC4Water s.à.r.l., Roeser, Luxembourg
2 Institute for Modelling Hydraulic and Environmental Systems, University of Stuttgart, Germany
3 Department of Water Management, Delft University of Technology, The Netherlands
Personal weather stations (PWSs) provide valuable rainfall estimates in (near) real-time at a high temporal resolution (~5 min) and have a high network density, which often exceeds that of dedicated weather stations from national meteorological agencies. PWS rainfall data can potentially be used for nowcasting, flood forecasting or early warning systems. The latency and quality of the PWS data are important aspects to consider.
We explored the real-time potential of rainfall data from PWSs from the private company Netatmo, which can be accessed via an application programming interface (API). We analyzed the real-time accessibility and latency of the data, explored how to optimally use the API, and evaluated existing quality control algorithms in terms of real-time applicability. First results of these analyses and a roadmap for implementing this as a software package are presented.
