Impact of the assimilation of lightning data on the precipitation forecast at different forecast ranges
This study investigates the impact of the assimilation of total lightning data on the precipitation forecast of a numerical weather prediction (NWP) model. The impact of the lightning data assimilation, which uses water vapour substitution, is investigated at different forecast time ranges, name...
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doaj-4576cab3d2284c9b96ce1d617c3d1cd72020-11-25T00:10:43ZengCopernicus PublicationsAdvances in Science and Research1992-06281992-06362017-06-011418719410.5194/asr-14-187-2017Impact of the assimilation of lightning data on the precipitation forecast at different forecast rangesS. Federico0M. Petracca1G. Panegrossi2C. Transerici3S. Dietrich4ISAC-CNR, UOS of Rome, via del Fosso del Cavaliere 100, 00133-Rome, ItalyISAC-CNR, UOS of Rome, via del Fosso del Cavaliere 100, 00133-Rome, ItalyISAC-CNR, UOS of Rome, via del Fosso del Cavaliere 100, 00133-Rome, ItalyISAC-CNR, UOS of Rome, via del Fosso del Cavaliere 100, 00133-Rome, ItalyISAC-CNR, UOS of Rome, via del Fosso del Cavaliere 100, 00133-Rome, ItalyThis study investigates the impact of the assimilation of total lightning data on the precipitation forecast of a numerical weather prediction (NWP) model. The impact of the lightning data assimilation, which uses water vapour substitution, is investigated at different forecast time ranges, namely 3, 6, 12, and 24 h, to determine how long and to what extent the assimilation affects the precipitation forecast of long lasting rainfall events (> 24 h). The methodology developed in a previous study is slightly modified here, and is applied to twenty case studies occurred over Italy by a mesoscale model run at convection-permitting horizontal resolution (4 km). The performance is quantified by dichotomous statistical scores computed using a dense raingauge network over Italy. <br><br> Results show the important impact of the lightning assimilation on the precipitation forecast, especially for the 3 and 6 h forecast. The probability of detection (POD), for example, increases by 10 % for the 3 h forecast using the assimilation of lightning data compared to the simulation without lightning assimilation for all precipitation thresholds considered. The Equitable Threat Score (ETS) is also improved by the lightning assimilation, especially for thresholds below 40 mm day<sup>−1</sup>. <br><br> Results show that the forecast time range is very important because the performance decreases steadily and substantially with the forecast time. The POD, for example, is improved by 1–2 % for the 24 h forecast using lightning data assimilation compared to 10 % of the 3 h forecast. The impact of the false alarms on the model performance is also evidenced by this study.https://www.adv-sci-res.net/14/187/2017/asr-14-187-2017.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
S. Federico M. Petracca G. Panegrossi C. Transerici S. Dietrich |
spellingShingle |
S. Federico M. Petracca G. Panegrossi C. Transerici S. Dietrich Impact of the assimilation of lightning data on the precipitation forecast at different forecast ranges Advances in Science and Research |
author_facet |
S. Federico M. Petracca G. Panegrossi C. Transerici S. Dietrich |
author_sort |
S. Federico |
title |
Impact of the assimilation of lightning data on the precipitation forecast at different forecast ranges |
title_short |
Impact of the assimilation of lightning data on the precipitation forecast at different forecast ranges |
title_full |
Impact of the assimilation of lightning data on the precipitation forecast at different forecast ranges |
title_fullStr |
Impact of the assimilation of lightning data on the precipitation forecast at different forecast ranges |
title_full_unstemmed |
Impact of the assimilation of lightning data on the precipitation forecast at different forecast ranges |
title_sort |
impact of the assimilation of lightning data on the precipitation forecast at different forecast ranges |
publisher |
Copernicus Publications |
series |
Advances in Science and Research |
issn |
1992-0628 1992-0636 |
publishDate |
2017-06-01 |
description |
This study investigates the impact of the assimilation of total
lightning data on the precipitation forecast of a numerical weather
prediction (NWP) model. The impact of the lightning data assimilation, which
uses water vapour substitution, is investigated at different forecast time
ranges, namely 3, 6, 12, and 24 h, to determine how long and to what extent
the assimilation affects the precipitation forecast of long lasting rainfall
events (> 24 h). The methodology developed in a previous study is
slightly modified here, and is applied to twenty case studies occurred over
Italy by a mesoscale model run at convection-permitting horizontal resolution
(4 km). The performance is quantified by dichotomous statistical scores
computed using a dense raingauge network over Italy.
<br><br>
Results show the important impact of the lightning assimilation on the
precipitation forecast, especially for the 3 and 6 h forecast. The
probability of detection (POD), for example, increases by 10 % for the 3 h
forecast using the assimilation of lightning data compared to the simulation
without lightning assimilation for all precipitation thresholds considered.
The Equitable Threat Score (ETS) is also improved by the lightning
assimilation, especially for thresholds below 40 mm day<sup>−1</sup>.
<br><br>
Results show that the forecast time range is very important because the
performance decreases steadily and substantially with the forecast time. The
POD, for example, is improved by 1–2 % for the 24 h forecast using
lightning data assimilation compared to 10 % of the 3 h forecast. The
impact of the false alarms on the model performance is also evidenced by this
study. |
url |
https://www.adv-sci-res.net/14/187/2017/asr-14-187-2017.pdf |
work_keys_str_mv |
AT sfederico impactoftheassimilationoflightningdataontheprecipitationforecastatdifferentforecastranges AT mpetracca impactoftheassimilationoflightningdataontheprecipitationforecastatdifferentforecastranges AT gpanegrossi impactoftheassimilationoflightningdataontheprecipitationforecastatdifferentforecastranges AT ctranserici impactoftheassimilationoflightningdataontheprecipitationforecastatdifferentforecastranges AT sdietrich impactoftheassimilationoflightningdataontheprecipitationforecastatdifferentforecastranges |
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1725407501194625024 |