Numerical Weather Prediction models have been adopted by most of
the meteorological services to issue weather forecasts. Despite the
improvement in the models, there are various limitations,
specifically Sub-Grid scale weather phenomenon that cannot be
explicitly resolved with present models and are derived through
statistical relationship, which is not a theoretically stable
process and there is a strong need for searching alternative tools.
This book provides practical applications of data mining for
interpretation of weather patterns. Pre-processing of
multidimensional weather data using hyper cubes has been
demonstrated to speed up storage and retrieval of weather
variables. Association of rainfall with movement of LPS has also
been done along with rainfall forecasting using Artificial Neural
Networks. k-means clustering technique has been applied on the
clusters of ensemble of derived weather variables for real life
cases of tornado and cloudburst to locate patterns conducive to
formation of these events. This approach should help the
researchers, meteorologists and practitioners who may be looking
forward to understand this unique blend of meteorology and computer
science.
General
Imprint: |
Scholars Press
|
Country of origin: |
United States |
Release date: |
December 2012 |
First published: |
December 2012 |
Authors: |
Kavita Pabreja
|
Dimensions: |
229 x 152 x 11mm (L x W x T) |
Format: |
Paperback - Trade
|
Pages: |
196 |
ISBN-13: |
978-3-639-51010-2 |
Categories: |
Books >
Computing & IT >
General theory of computing >
General
|
LSN: |
3-639-51010-0 |
Barcode: |
9783639510102 |
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