The KNMI has two networks acquiring ground-based measurements of precipitation. For example, we can assess how extreme this precipitation event was compared to previous ones, or to carry out attribution studies in which we estimate the probability of this event being triggered by climate change. Observations also help to put this event in a climatological context. This information is essential for forecast verification and to improve future forecasts of extreme precipitation. Observations are fundamental to know the rainfall intensity and amount during the event. Extreme precipitation is strongly linked to increasing global temperatures, thus in future we can expect more extreme precipitation with subsequent impact for communities. Precipitation varies a lot in space and time, so even in a large-scale event like this, there are small regions where very extreme precipitation occurs, like the south-eastern edge of Limburg province. This was a large-scale event that straddled several countries and led to the observation of large precipitation amounts. Finally, because of the expected strong impact on society a code red was issued on the afternoon of the 14th. A code orange was issued in the evening of the 13th for precipitation exceeding 75 mm in 24 hours. KNMI issued a code yellow for extreme precipitation (> 50 mm in 24 hours) in the morning of the 12th. The heavy rainfall was well forecast from a meteorological perspective. The extreme precipitation and flooding caused devastating impacts in the region, impacting lives, livelihoods, and damaging infrastructure. Heavy rainfall was recorded in the south-east of the Netherlands (Limburg), leading to a serious flooding event. On July 13th and 14th 2021, a stationary low-pressure system delivered record precipitation to the region covering parts of Germany, Belgium, Luxemburg and the Netherlands. We examine precipitation on July 13th and 14th measured by the WOW-NL network to show how the acquisition of crowdsourced measurements can help KNMI to better understand extreme events. Crowdsourced data can complement the existing official KNMI network by providing observations with both a high spatial and temporal resolution. Weather observations are the cornerstone of climatological and meteorological services.
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