Application of the method of artificial neural networks to the downscaling of precipitation forecasts in the coastal region of the Black Sea

Application of the method of artificial neural networks to the downscaling of precipitation... We correct the diurnal data on precipitation obtained from the output of the global system of reanalysis as applied to the observed daily amounts of precipitation at certain geographic points of the coastal region of the Black Sea. The estimations of the actual amounts of precipitation are taken from the ECAD (European Climate Assessment and Dataset) database. We analyze the amounts of precipitation for three winter months. As a working tool for the investigation of correlations between the regular meteorological variables (predictors) taken from the reanalysis and the local amounts of precipitation at certain geographic points (predictants), we use the method of artificial neural networks (ANN). A numerical criterion of adequacy of the estimates of the daily amounts of precipitation performed according to reanalysis and the ANN method is proposed. By using this criterion, we show that the efficiency of the ANN method in simulating precipitation is higher as compared with the procedure of reanalysis. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Physical Oceanography Springer Journals

Application of the method of artificial neural networks to the downscaling of precipitation forecasts in the coastal region of the Black Sea

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Publisher
Kluwer Academic Publishers-Consultants Bureau
Copyright
Copyright © 2006 by Springer Science+Business Media, Inc.
Subject
Earth Sciences; Oceanography; Remote Sensing/Photogrammetry; Atmospheric Sciences; Climate Change; Environmental Physics
ISSN
0928-5105
eISSN
0928-5105
D.O.I.
10.1007/s11110-006-0021-1
Publisher site
See Article on Publisher Site

Abstract

We correct the diurnal data on precipitation obtained from the output of the global system of reanalysis as applied to the observed daily amounts of precipitation at certain geographic points of the coastal region of the Black Sea. The estimations of the actual amounts of precipitation are taken from the ECAD (European Climate Assessment and Dataset) database. We analyze the amounts of precipitation for three winter months. As a working tool for the investigation of correlations between the regular meteorological variables (predictors) taken from the reanalysis and the local amounts of precipitation at certain geographic points (predictants), we use the method of artificial neural networks (ANN). A numerical criterion of adequacy of the estimates of the daily amounts of precipitation performed according to reanalysis and the ANN method is proposed. By using this criterion, we show that the efficiency of the ANN method in simulating precipitation is higher as compared with the procedure of reanalysis.

Journal

Physical OceanographySpringer Journals

Published: Sep 23, 2006

References

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