Can we predict seasonal changes in high impact weather in the United States
Bibliographic Data
| ID | 15549264 |
|---|---|
| Authors | Eunsil Jung (0000-0003-0970-2730, University of Miami, corresponding author), Ben P Kirtman (0000-0001-7423-2734, University of Miami) |
| Year | 2016 |
| Volume | 11 |
| Issue | 7 |
| Pages | 074018-074018 |
| Publication date | 2016-07-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environmental Research Letters (JOURNAL) |
| Journal identifiers | ISSN: 1748-9326 • E-ISSN: 1748-9326 |
| Publisher | IOP Publishing (PUBLISHER • GB) |
| DOI | 10.1088/1748-9326/11/7/074018 |
| OpenAlex | W2461860820 |
| Language | EN |
| References cited | 26 |
Severe convective storms cause catastrophic losses each year in the United States, suggesting that any predictive capability is of great societal benefit. While it is known that El Niño and the Southern Oscillation (ENSO) influence high impact weather events, such as a tornado activity and severe storms, in the US during early spring, this study highlights that the influence of ENSO on US severe storm characteristics is weak during May–July. Instead, warm water in the Gulf of Mexico is a potential predictor for moist instability, which is an important factor in influencing the storm characteristics in the US during May–July
Atmospheric sciences · Climatology · Convective storm detection · El Niño Southern Oscillation · Geography · Meteorology · Severe weather · Southern oscillation · Storm · Tornado · Climate variability and models · Environmental Science · Meteorological Phenomena and Simulations · Tropical and Extratropical Cyclones Research · Geology
| Highly cited | No |
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