Estimation of convective precipitation mass from lightning data using a temporal sliding‐window for a series of thunderstorms in Southeastern Brazil

Garcia, João Victor Cal; Stephany, Stephan; D’Oliveira, A.

doi:10.1002/asl2.453

Cited by 6 publications

(1 citation statement)

References 20 publications

(16 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some studies suggest that lightning data may improve rainfall retrievals (Biron et al, 2012;Garcia et al, 2013;Grecu et al, 2000). For instance, Grecu et al (2000) assessed the use of lightning information in convective rainfall estimation.…”

Section: Ii) Indirect Techniquementioning

confidence: 99%

Near-real-time rainfall detection and estimation from commercial microwave links and meteosat second generation data

Kumah¹

View full text Add to dashboard Cite

Many operational applications, including agriculture and water resources management, local climate studies, flash flood prediction and forecasting that directly affect human livelihoods, need accurate high-resolution rainfall information. High-resolution rainfall is also vital in research applications such as evaluating satellite rainfall products to inform new satellite rainfall observation missions. However, despite its great value, rainfall's intricate characteristics, such as intermittency and spatial variation, make accurate rainfall estimation challenging.

show abstract

Section: Ii) Indirect Techniquementioning

confidence: 99%

Near-real-time rainfall detection and estimation from commercial microwave links and meteosat second generation data

Kumah¹

View full text Add to dashboard Cite

show abstract

Data Mining Approaches to the Real-Time Monitoring and Early Warning of Convective Weather Using Lightning Data

Stephany

Strauss

Calheiros

et al. 2019

Towards Mathematics, Computers and Environment: A Disasters Perspective

View full text Add to dashboard Cite

Horizontal grid spacing comparison among Random Forest algorithms to nowcast Cloud-to-Ground lightning occurrence

Fata

Amato

Bernardi

et al. 2022

Stoch Environ Res Risk Assess

View full text Add to dashboard Cite

The relation between the increase in the frequency and the effects of extreme events with climate change has been widely demonstrated and the related consequences are a global concern. In this framework, the strong correlation between significant lightning occurrence and intense precipitation events has been also documented. Consequently, the possibility of having a short-term forecasting tool of the lightning activity may help in identifying and monitoring the evolution of severe weather events on very short time ranges. The present paper proposes an application of Random Forest (RF), a popular Machine Learning (ML) algorithm, to perform a nowcasting of Cloud-to-Ground (CG) lightning occurrence over the Italian territory and the surrounding seas during the months of August, September, and October from 2017 to 2019. Results obtained with three different spatial resolutions have been compared, suggesting that, to enhance the skills of the model in identifying the presence or absence of strokes, all the data selected as input should be commonly gridded on the finest available spatial resolution. Moreover, the features’ importance analysis performed confirms that meteorological features describing the state of the atmosphere, especially at higher altitudes, have a stronger impact on the final result than topology data, such as Latitude or Digital Elevation Model (DEM).

show abstract

Estimation of convective precipitation mass from lightning data using a temporal sliding‐window for a series of thunderstorms in Southeastern Brazil

Cited by 6 publications

References 20 publications

Near-real-time rainfall detection and estimation from commercial microwave links and meteosat second generation data

Near-real-time rainfall detection and estimation from commercial microwave links and meteosat second generation data

Data Mining Approaches to the Real-Time Monitoring and Early Warning of Convective Weather Using Lightning Data

Horizontal grid spacing comparison among Random Forest algorithms to nowcast Cloud-to-Ground lightning occurrence

Contact Info

Product

Resources

About