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Use of radar data for characterizing extreme precipitation at fine scales and short durations
Extreme precipitation is one of the most devastating forms of atmospheric phenomenon, causing severe damage worldwide, and is likely to intensify in strength and occurrence in a warming climate. This contribution gives an overview of the potential and challenges associated with using weather radar data to investigate extreme precipitation. We illustrate this by presenting radar data sets for Germany, the U.S. and the UK that resolve small-scale heavy rainfall events of just a few km ^2 with return periods of 5 years or more. Current challenges such as relatively short radar records and radar-based QPE uncertainty are discussed. An example from a precipitation climatology derived from the German weather radar network with spatial resolution of 1 km reveals the necessity of radars for observing short-term (1–6 h) extreme precipitation. Only 17.3% of hourly heavy precipitation events that occurred in Germany from 2001 to 2018 were captured by the rain gauge station network, while 81.8% of daily events were observed. This is underlined by a similar study using data from the UK radar network for 2014. Only 36.6% (52%) of heavy hourly (daily) rain events detected by the radar network were also captured by precipitation gauging stations. Implications for the monitoring of hydrologic extremes are demonstrated over the U.S. with a continental-scale radar-based reanalysis. Hydrologic extremes are documented over ∼1000 times more locations than stream gauges, including in the majority of ungauged basins. This underlines the importance of high-resolution weather radar observations for resolving small-scale rainfall events, and the necessity of radar-based climatological data sets for understanding the small-scale and high-temporal resolution characteristics of extreme precipitation.
Use of radar data for characterizing extreme precipitation at fine scales and short durations
Extreme precipitation is one of the most devastating forms of atmospheric phenomenon, causing severe damage worldwide, and is likely to intensify in strength and occurrence in a warming climate. This contribution gives an overview of the potential and challenges associated with using weather radar data to investigate extreme precipitation. We illustrate this by presenting radar data sets for Germany, the U.S. and the UK that resolve small-scale heavy rainfall events of just a few km ^2 with return periods of 5 years or more. Current challenges such as relatively short radar records and radar-based QPE uncertainty are discussed. An example from a precipitation climatology derived from the German weather radar network with spatial resolution of 1 km reveals the necessity of radars for observing short-term (1–6 h) extreme precipitation. Only 17.3% of hourly heavy precipitation events that occurred in Germany from 2001 to 2018 were captured by the rain gauge station network, while 81.8% of daily events were observed. This is underlined by a similar study using data from the UK radar network for 2014. Only 36.6% (52%) of heavy hourly (daily) rain events detected by the radar network were also captured by precipitation gauging stations. Implications for the monitoring of hydrologic extremes are demonstrated over the U.S. with a continental-scale radar-based reanalysis. Hydrologic extremes are documented over ∼1000 times more locations than stream gauges, including in the majority of ungauged basins. This underlines the importance of high-resolution weather radar observations for resolving small-scale rainfall events, and the necessity of radar-based climatological data sets for understanding the small-scale and high-temporal resolution characteristics of extreme precipitation.
Use of radar data for characterizing extreme precipitation at fine scales and short durations
Katharina Lengfeld (author) / Pierre-Emmanuel Kirstetter (author) / Hayley J Fowler (author) / Jingjing Yu (author) / Andreas Becker (author) / Zachary Flamig (author) / Jonathan Gourley (author)
2020
Article (Journal)
Electronic Resource
Unknown
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