Assessment of WRF numerical model forecasts using different lead time initializations during extreme precipitation events over Macaé city, Rio de Janeiro (Brazil)

Fabricio Polifke Silva (), Alfredo Silveira Silva (), Maria Gertrudes Alvarez Justi Silva () and Gisele Dornelles Pires ()
Additional contact information
Fabricio Polifke Silva: Institute of Geosciences, Universidade Federal do Rio de Janeiro - UFRJ, CCMN ‑ Cidade Universitária - Ilha do Fundão
Alfredo Silveira Silva: Institute of Geosciences, Universidade Federal do Rio de Janeiro - UFRJ, CCMN ‑ Cidade Universitária - Ilha do Fundão
Maria Gertrudes Alvarez Justi Silva: Universidade Estadual do Norte Fluminense Darcy Ribeiro - UENF
Gisele Dornelles Pires: Universidade Iguaçu - UNIG

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2022, vol. 110, issue 1, No 31, 695-718

Abstract: Abstract The ability to forecast extreme precipitation events has become increasingly important over the last decades due to their significant impacts on society and properties. In this context, the reliability degree related to the warnings issues and a possible natural hazard is relevant. Thus, research aimed to evaluate the strengths and weaknesses of numerical forecasts can also be addressed as prevention measures. In this context, first, this study endeavored to identify the extreme precipitation events in Macaé city, Brazil. Secondly, evaluate the precipitation forecast using the Weather Research and Forecasting (WRF) model using different lead time initialization and three grids domain (27, 09, and 03 km); and investigate the thermodynamic and dynamic physical processes related to the extreme events found. From the qualitative and quantitative evaluation of the precipitation forecast, it was possible to verify that the 24 h lead time initialization presented the best performance compared to the other ones. The third domain also presented the statistical results of the precipitation forecasts, suggesting that the increased horizontal resolution enabled the model to represent mesoscale physical processes and better use high-resolution input data, such as the mountainous region of Macaé city. It was possible to verify the importance of conditional atmospheric instability, moisture offer at lower atmospheric levels, and dynamic trigger mechanisms to originate the extreme rainfall events from the thermodynamic and dynamic parameters. Lastly, we sought to show the challenges of forecasting the extreme rainfall and natural hazards imminence warnings and exploring the daily operational challenges verified in the monitoring centers and civil defenses.

Keywords: Precipitation; Forecasting; Extreme rainfall events; Numerical weather prediction (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11069-021-04964-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:110:y:2022:i:1:d:10.1007_s11069-021-04964-7

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-021-04964-7

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().