Forecasting Cumulonimbus Clouds: Evaluation of New Operational Convective Index Using Lightning and Precipitation Data
Deep convective clouds, such as towering cumulus and Cumulonimbus, can endanger lives and property, also being a major hazard to aviation. This study presents the convective index (<i>IndexCON</i>) used operationally at the Portuguese Meteorological Watch Office. Moreover, <i>Index...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/9/1627 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Deep convective clouds, such as towering cumulus and Cumulonimbus, can endanger lives and property, also being a major hazard to aviation. This study presents the convective index (<i>IndexCON</i>) used operationally at the Portuguese Meteorological Watch Office. Moreover, <i>IndexCON</i> is evaluated against lightning and precipitation data for two years, between January 2022 and December 2023, over mainland Portugal and its surrounding areas. This index combines several European Center for Medium-Range Weather Forecasts (ECMWF) prognostic variables, such as stability indices, cloud water content, relative humidity and vertical velocity, using a fuzzy-logic approach. <i>IndexCON</i> performs well in the warm season (May–October), with a probability of detection (POD) of 70%, a false alarm ratio (FAR) of 30% and a probability of false detection (POFD) less than 5%, leading to a Critical Success Index (CSI) above 0.55. However, <i>IndexCON</i> performs worse in the cold season (November–April), when dynamical drivers are more relevant, mainly due to overestimating the convective activity, resulting in CSI and Heidke Skill Score (HSS) values below 0.3. Optimizing the membership functions partially reduces this overestimation. Finally, the added value of <i>IndexCON</i> was illustrated in detail for a thunderstorm episode, using satellite products, lightning and precipitation data. |
|---|---|
| ISSN: | 2072-4292 |