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Pregled bibliografske jedinice broj: 1089858

Estimation of hail using lightning vs radar data, Case study of 25 June 2017


Damjan Jelić, Barbara Malečić, Barbara Vodarić Šurija, Maja Telišman Prtenjak
Estimation of hail using lightning vs radar data, Case study of 25 June 2017 // Znanstveno-stručni skup s međunarodnim sudjelovanjem: Meteorološki izazovi 7: Meteorologija kao podrška tijelima javne uprave
Zagreb, Hrvatska, 2020. (predavanje, nije recenziran, neobjavljeni rad, znanstveni)


CROSBI ID: 1089858 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Estimation of hail using lightning vs radar data, Case study of 25 June 2017

Autori
Damjan Jelić, Barbara Malečić, Barbara Vodarić Šurija, Maja Telišman Prtenjak

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, neobjavljeni rad, znanstveni

Skup
Znanstveno-stručni skup s međunarodnim sudjelovanjem: Meteorološki izazovi 7: Meteorologija kao podrška tijelima javne uprave

Mjesto i datum
Zagreb, Hrvatska, 04.11.2020. - 05.11.2020

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Nije recenziran

Ključne riječi
hail, lightning

Sažetak
In the past decade new approach was developed based on lightning data to investigate hail, severe wind and tornadoes. It demonstrated good capabilities to nowcast severe effects and it has been used in Catalonia operationally for several years now. The method is based on a mathematical model which is detecting sudden increases in lightning activity known as a lightning jump. We expanded current use from nowcasting towards diagnostics and climatological assessments. Such approach uses fixed grid, which observes lightning activity as the storm is passing over. Lightning jump is computed independently in each of the grid points providing locations in space and time over which the storm was most active. Such method is well suited for archive data of lightning activity allowing us to examine potential hail activities in areas without direct measurements of hail. In our case we consider total lightning activity (cloud to cloud, cloud to ground, intra cloud and both positive and negative discharges) to ensure enough lightning strikes per grid point since the size of the point is 3x3km. Here we will present the case study where we inspect capabilities of such approach to represent hail measured on hail pads in continental parts of Croatia and compare it with radar estimates of hail. The goal is to find best suited parameters for both radar and lightning jump which will correspond well with measured hail. Such method can be a potential source of severe weather information with focus on hail, especially in areas lacking radar coverage and/or direct measurements.

Izvorni jezik
Engleski

Znanstvena područja
Geofizika



POVEZANOST RADA


Projekti:
HRZZ-IZHRZ0_180587 - Severe Weather over the Alpine-Adriatic region in a Changing Climate (SWALDRIC) (Telišman Prtenjak, Maja, HRZZ - Croatian-Swiss Research Programme 2017 - 2023) ( CroRIS)

Ustanove:
Prirodoslovno-matematički fakultet, Zagreb


Citiraj ovu publikaciju:

Damjan Jelić, Barbara Malečić, Barbara Vodarić Šurija, Maja Telišman Prtenjak
Estimation of hail using lightning vs radar data, Case study of 25 June 2017 // Znanstveno-stručni skup s međunarodnim sudjelovanjem: Meteorološki izazovi 7: Meteorologija kao podrška tijelima javne uprave
Zagreb, Hrvatska, 2020. (predavanje, nije recenziran, neobjavljeni rad, znanstveni)
Damjan Jelić, Barbara Malečić, Barbara Vodarić Šurija, Maja Telišman Prtenjak (2020) Estimation of hail using lightning vs radar data, Case study of 25 June 2017. U: Znanstveno-stručni skup s međunarodnim sudjelovanjem: Meteorološki izazovi 7: Meteorologija kao podrška tijelima javne uprave.
@article{article, year = {2020}, keywords = {hail, lightning}, title = {Estimation of hail using lightning vs radar data, Case study of 25 June 2017}, keyword = {hail, lightning}, publisherplace = {Zagreb, Hrvatska} }
@article{article, year = {2020}, keywords = {hail, lightning}, title = {Estimation of hail using lightning vs radar data, Case study of 25 June 2017}, keyword = {hail, lightning}, publisherplace = {Zagreb, Hrvatska} }




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