Preprints
https://doi.org/10.5194/egusphere-2024-729
https://doi.org/10.5194/egusphere-2024-729
25 Mar 2024
 | 25 Mar 2024
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

A comprehensive verification of the weather radar-based hail metrics POH and MESHS and a recalibration of POH using dense crowdsourced observations from Switzerland

Jérôme Kopp, Alessandro Hering, Urs Germann, and Olivia Martius

Abstract. Remote hail detection and hail size estimation using weather radar observations has the advantage of wide spatial coverage and high spatial and temporal resolution. Switzerland National Weather Service (MeteoSwiss) uses two radar-based hail metrics: the probability of hail at the ground (POH) to assess the presence of hail, and the maximum expected severe hailstone size (MESHS) to estimate the largest hailstone diameter. However, radar-based metrics are not direct measurements of hail and have to be calibrated with and verified against ground-based observations of hail, such as crowdsourced hail reports. Switzerland benefits from a particularly rich and dense dataset of crowdsourced hail reports from the MeteoSwiss app. We combine a new spatiotemporal clustering method (ST-DBSCAN) with radar reflectivity to filter the reports and use the filtered reports to verify POH and MESHS in terms of the Hit Rate, False Alarms Ratio (FAR), Critical Success Index (CSI), and Heidke Skill Score (HSS). Using a 4 km × 4 km maximum upscaling approach, we find FAR values between 0.3 and 0.7 for POH and FAR > 0.6 for MESHS. For POH, the highest CSI (0.37) and HSS (0.52) are obtained for a 60 % threshold, while for MESHS the highest CSI (0.25) and HSS (0.4) are obtained for a 2 cm threshold. We find that the current calibration of POH does not correspond to a probability and suggest a recalibration based on the filtered reports.

Jérôme Kopp, Alessandro Hering, Urs Germann, and Olivia Martius

Status: open (until 01 May 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Jérôme Kopp, Alessandro Hering, Urs Germann, and Olivia Martius

Model code and software

radar_metric_verifications Jérôme Kopp https://doi.org/10.5281/zenodo.10613380

Jérôme Kopp, Alessandro Hering, Urs Germann, and Olivia Martius

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Short summary
We present a verification of two products based on weather radars to detect the presence of hail and estimate its size.  Radar products are remote detection of hail, so they must be verified with ground-based observations. We use reports from users of the Swiss Weather Services phone app to do the verification. We found that the product estimating the presence of hail provides fair results but that it should be recalibrated, and that estimating the hail size with radar is more challenging.