Projects per year
Abstract
Proximity soundings have long been used to explore how the vertical structure of temperature, humidity, and winds influence convective storms and their associated hazards. In severe thunderstorm research and forecasting, convective parameters are often used to summarize certain characteristics of the sounding. While extremely useful, these parameters are unable to describe the rich complexity that is readily apparent in hodographs and skew T-logp diagrams. Motivated by a desire to retain more of these details, the present study uses self-organizing maps (SOMs) to group soundings based on their full vertical structure. The analysis makes use of a sample of more than 10 000 model proximity soundings for right-moving supercells associated with tornadoes and significant severe hail and straight-line winds in the contiguous United States (CONUS). Separate SOMs are developed for the wind and thermodynamic profiles, each with 3×3 nodes, resulting in a set of nine hodographs and nine skew T-logp diagrams that broadly represent the spectrum of near-storm environments for significant severe right-moving supercells in the CONUS. Both SOMs are shown to provide a good representation of the variability in key convective parameters, although, for the thermodynamic SOM, variations in LCL heights and midlevel lapse rates are somewhat limited. Based on the soundings assigned to them, the SOM nodes are characterized in terms of their associated hazards, their relationship with storm mode and mesocyclone strength, and their spatial and temporal variability. Potential applications of the SOMs in severe weather forecasting and idealized numerical simulations are also highlighted.
Original language | English |
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Pages (from-to) | 3299-3323 |
Number of pages | 25 |
Journal | Monthly Weather Review |
Volume | 149 |
Issue number | 10 |
DOIs | |
Publication status | Published - 1 Oct 2021 |
Keywords
- Clustering
- Severe storms
- Soundings
- Storm environments
- Supercells
Projects
- 1 Finished
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ARC Centre of Excellence for Climate Extremes
Pitman, A. J., Jakob, C., Alexander, L., Reeder, M., Roderick, M., England, M. H., Abramowitz, G., Abram, N., Arblaster, J., Bindoff, N. L., Dommenget, D., Evans, J. P., Hogg, A. M., Holbrook, N. J., Karoly, D. J., Lane, T. P., Sherwood, S. C., Strutton, P., Ebert, E., Hendon, H., Hirst, A. C., Marsland, S., Matear, R., Protat, A., Wang, Y., Wheeler, M. C., Best, M. J., Brody, S., Grabowski, W., Griffies, S., Gruber, N., Gupta, H., Hallberg, R., Hohenegger, C., Knutti, R., Meehl, G. A., Milton, S., de Noblet-Ducoudre, N., Or, D., Petch, J., Peters-Lidard, C., Overpeck, J., Russell, J., Santanello, J., Seneviratne, S. I., Stephens, G., Stevens, B., Stott, P. A. & Saunders, K.
Monash University – Internal University Contribution, Monash University – Internal School Contribution, Monash University – Internal Faculty Contribution, University of New South Wales (UNSW), Australian National University (ANU), University of Melbourne, University of Tasmania, Bureau of Meteorology (BOM) (Australia), Department of Climate change, Energy, the Environment and Water (DCCEEW) (New South Wales)
1/01/17 → 31/12/24
Project: Research