Nowcasting the precipitation phase combining weather radar data, surface observations, and NWP model forecasts

Heavy snowfall events can cause substantial transport disruption and exert a negative socioeconomic impact, particularly in low-altitude and midlatitude regions, where it seldom snows. Such problems may be exacerbated if there are rapid transitions between different precipitation phases within the s...

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Autores: Casellas, Enric, Bech, Joan, Veciana, Roger, Pineda, Nicolau, Miró, Josep Ramon, Moré, Jordi, Rigo, Tomeu, Sairouni, Abdel
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/194999
Acceso en línea:https://hdl.handle.net/2445/194999
Access Level:acceso abierto
Palabra clave:Observacions meteorològiques
Radar
Temps (Meteorologia)
Meteorological observations
Weather
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spelling Nowcasting the precipitation phase combining weather radar data, surface observations, and NWP model forecastsCasellas, EnricBech, JoanVeciana, RogerPineda, NicolauMiró, Josep RamonMoré, JordiRigo, TomeuSairouni, AbdelObservacions meteorològiquesRadarTemps (Meteorologia)Meteorological observationsRadarWeatherHeavy snowfall events can cause substantial transport disruption and exert a negative socioeconomic impact, particularly in low-altitude and midlatitude regions, where it seldom snows. Such problems may be exacerbated if there are rapid transitions between different precipitation phases within the same event. Previous studies have addressed this issue using precipitation-phase nowcasting techniques, often focusing on critical infrastructures such as airports. Very short-range forecasts are usually based on trends of observations and numerical weather prediction models. Nowcasting schemes considering the precipitation phase generally merge extrapolated surface observations, modelled vertical temperature profiles, and extrapolated weather radar precipitation fields. In this study, a precipitation-phase nowcasting scheme was developed and evaluated, initially using eight different algorithms to classify precipitation into rain, sleet or snow, together with a probabilistic weather radar data extrapolation technique. In addition, three combinations of the previous algorithms were also evaluated. The nowcasting scheme was applied to a midlatitude region in the Northwestern Mediterranean to assess its performance during eight snowfall events. Single and combined algorithms were compared to determine their suitability in conditions close to freezing point, when there is increased uncertainty about the precipitation phase. The results indicate that, although single and combined algorithms perform similarly, the latter can provide valuable information during event monitoring. Precipitation phase transitions were also analysed, finding that on average they can be forecast correctly with a lead time of 120 min. The proposed methodology can be readily applied to other regions where ground-based observations, weather radar data, and model forecasts are availableWiley2021info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/2445/194999Articles publicats en revistes (Física Aplicada)reponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaInglésReproducció del document publicat a: https://doi.org/10.1002/qj.4121Quarterly Journal of the Royal Meteorological Society, 2021, vol. 147, num. 739, p. 3135-3153https://doi.org/10.1002/qj.4121cc by-nc (c) Casellas, Enric et al., 2021http://creativecommons.org/licenses/by-nc/3.0/es/info:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/1949992025-07-25T16:43:42Z
dc.title.none.fl_str_mv Nowcasting the precipitation phase combining weather radar data, surface observations, and NWP model forecasts
title Nowcasting the precipitation phase combining weather radar data, surface observations, and NWP model forecasts
spellingShingle Nowcasting the precipitation phase combining weather radar data, surface observations, and NWP model forecasts
Casellas, Enric
Observacions meteorològiques
Radar
Temps (Meteorologia)
Meteorological observations
Radar
Weather
title_short Nowcasting the precipitation phase combining weather radar data, surface observations, and NWP model forecasts
title_full Nowcasting the precipitation phase combining weather radar data, surface observations, and NWP model forecasts
title_fullStr Nowcasting the precipitation phase combining weather radar data, surface observations, and NWP model forecasts
title_full_unstemmed Nowcasting the precipitation phase combining weather radar data, surface observations, and NWP model forecasts
title_sort Nowcasting the precipitation phase combining weather radar data, surface observations, and NWP model forecasts
dc.creator.none.fl_str_mv Casellas, Enric
Bech, Joan
Veciana, Roger
Pineda, Nicolau
Miró, Josep Ramon
Moré, Jordi
Rigo, Tomeu
Sairouni, Abdel
author Casellas, Enric
author_facet Casellas, Enric
Bech, Joan
Veciana, Roger
Pineda, Nicolau
Miró, Josep Ramon
Moré, Jordi
Rigo, Tomeu
Sairouni, Abdel
author_role author
author2 Bech, Joan
Veciana, Roger
Pineda, Nicolau
Miró, Josep Ramon
Moré, Jordi
Rigo, Tomeu
Sairouni, Abdel
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Observacions meteorològiques
Radar
Temps (Meteorologia)
Meteorological observations
Radar
Weather
topic Observacions meteorològiques
Radar
Temps (Meteorologia)
Meteorological observations
Radar
Weather
description Heavy snowfall events can cause substantial transport disruption and exert a negative socioeconomic impact, particularly in low-altitude and midlatitude regions, where it seldom snows. Such problems may be exacerbated if there are rapid transitions between different precipitation phases within the same event. Previous studies have addressed this issue using precipitation-phase nowcasting techniques, often focusing on critical infrastructures such as airports. Very short-range forecasts are usually based on trends of observations and numerical weather prediction models. Nowcasting schemes considering the precipitation phase generally merge extrapolated surface observations, modelled vertical temperature profiles, and extrapolated weather radar precipitation fields. In this study, a precipitation-phase nowcasting scheme was developed and evaluated, initially using eight different algorithms to classify precipitation into rain, sleet or snow, together with a probabilistic weather radar data extrapolation technique. In addition, three combinations of the previous algorithms were also evaluated. The nowcasting scheme was applied to a midlatitude region in the Northwestern Mediterranean to assess its performance during eight snowfall events. Single and combined algorithms were compared to determine their suitability in conditions close to freezing point, when there is increased uncertainty about the precipitation phase. The results indicate that, although single and combined algorithms perform similarly, the latter can provide valuable information during event monitoring. Precipitation phase transitions were also analysed, finding that on average they can be forecast correctly with a lead time of 120 min. The proposed methodology can be readily applied to other regions where ground-based observations, weather radar data, and model forecasts are available
publishDate 2021
dc.date.none.fl_str_mv 2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/194999
url https://hdl.handle.net/2445/194999
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.1002/qj.4121
Quarterly Journal of the Royal Meteorological Society, 2021, vol. 147, num. 739, p. 3135-3153
https://doi.org/10.1002/qj.4121
dc.rights.none.fl_str_mv cc by-nc (c) Casellas, Enric et al., 2021
http://creativecommons.org/licenses/by-nc/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc by-nc (c) Casellas, Enric et al., 2021
http://creativecommons.org/licenses/by-nc/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv Articles publicats en revistes (Física Aplicada)
reponame:Dipòsit Digital de la UB
instname:Universidad de Barcelona
instname_str Universidad de Barcelona
reponame_str Dipòsit Digital de la UB
collection Dipòsit Digital de la UB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,638193

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