## Abstract Avalanches in the Western Himalaya cause loss of life and damage property every year. To reduce such losses avalanche forecasting is practiced. This technique requires information about various surface weather parameters at least a couple of days in advance. In view of the above require
Identification of significant parameters for the prediction of pre-monsoon thunderstorms at Calcutta, India
โ Scribed by Ghosh, S.; Sen, P.K.; De, U.K.
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 77 KB
- Volume
- 19
- Category
- Article
- ISSN
- 0899-8418
No coin nor oath required. For personal study only.
โฆ Synopsis
In the present work, the well-known principal component analysis (PCA) technique has been applied to study the thunderstorm phenomenon (which evidently has a multivariate structure) at Calcutta (India) during the pre-monsoon season (i.e. March-May). Various parameters (both thermodynamic and dynamic) already identified by different scientists as responsible for thunderstorm occurrence have been considered here for different atmospheric layers. The purpose of the study is to reduce the number of parameters and hence identify the significant parameters linked up with various layers of the atmosphere for thunderstorm as well as for fair-weather days of Calcutta so that these may be used for parameterization.
As the analysis reveals that there is a structural difference between the morning and the afternoon atmosphere at Calcutta, so the analysis has been performed separately for morning and afternoon on thunderstorm as well as fair-weather days. Originally, 20 parameters were included in the analysis. The final result shows that in the morning only four parameters out of the 20 and in the afternoon only five parameters out of the 20 are found to be significant (i.e. they are expected to be jointly responsible) for occurrence or non-occurrence of thunderstorms at Calcutta during the pre-monsoon season. The study has however been confined up to the 500 hPa level.
๐ SIMILAR VOLUMES