NowPrecip 2: Precipitation nowcasting in the complex terrain of Switzerland. Part II: Verification

Abstract NowPrecip is a real‐time nowcasting application, operational at MeteoSwiss since 2020. A new version has introduced a novel ensemble‐based approach designed to generate real‐time multi‐member precipitation forecasts and improve rainfall‐related severe weather warnings in Switzerland. This study provides a comprehensive verification of the NowPrecip ensemble by comparing its performance with precipitation observations from five C‐band dual‐polarization radars operated by MeteoSwiss. In addition, the Python‐based Short‐Term Ensemble Prediction System (PySTEPS), a widely used open‐source nowcasting framework, is employed to generate ensemble nowcasts, providing a valuable benchmark for NowPrecip performance. Both PySTEPS and NowPrecip nowcasting simulations are blended with members of the numerical weather prediction (NWP) ensemble derived from the Icosahedral Nonhydrostatic Model (ICON). To this end, we compute widely used deterministic and probabilistic verification metrics across a 3.5‐year dataset over the period 2020–2023. The results show that NowPrecip systems consistently outperform PySTEPS across skill scores, while deterministic verification demonstrates that NowPrecip methods exhibit superior performance compared with the current operational NWP ensemble for lead times up to four hours.

Authors

Institutions

Publication Details

Journal
Quarterly Journal of the Royal Meteorological Society
Published
2026-03-27
DOI
https://doi.org/10.1002/qj.70181
Primary Topic
Precipitation Measurement and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

NowPrecip 2: Precipitation nowcasting in the complex terrain of Switzerland. Part II: Verification

L. Clementi, Przemysław Juda, Marco Boscacci, Athanasios Ntoumos et al.
Quarterly Journal of the Royal Meteorological Society
Precipitation Measurement and Analysis
article

NowPrecip 2: Precipitation nowcasting in the complex terrain of Switzerland. Part II: Verification

L. Clementi, Przemysław Juda, Marco Boscacci, Athanasios Ntoumos, Alexis Berne, I. V. Sideris, M. Gabella, U. Germann, A. Hering
article en

Abstract

Abstract NowPrecip is a real‐time nowcasting application, operational at MeteoSwiss since 2020. A new version has introduced a novel ensemble‐based approach designed to generate real‐time multi‐member precipitation forecasts and improve rainfall‐related severe weather warnings in Switzerland. This study provides a comprehensive verification of the NowPrecip ensemble by comparing its performance with precipitation observations from five C‐band dual‐polarization radars operated by MeteoSwiss. In addition, the Python‐based Short‐Term Ensemble Prediction System (PySTEPS), a widely used open‐source nowcasting framework, is employed to generate ensemble nowcasts, providing a valuable benchmark for NowPrecip performance. Both PySTEPS and NowPrecip nowcasting simulations are blended with members of the numerical weather prediction (NWP) ensemble derived from the Icosahedral Nonhydrostatic Model (ICON). To this end, we compute widely used deterministic and probabilistic verification metrics across a 3.5‐year dataset over the period 2020–2023. The results show that NowPrecip systems consistently outperform PySTEPS across skill scores, while deterministic verification demonstrates that NowPrecip methods exhibit superior performance compared with the current operational NWP ensemble for lead times up to four hours.

Quarterly Journal of the Royal Meteorological Society
Federal Office of Meteorology and Climatology MeteoSwiss (CH), École Polytechnique Fédérale de Lausanne (CH)
Climate action
Openalex Percentile: Top 3%
Precipitation Measurement and Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.