Forecasting monthly precipitation in Central Chile: a self-organizing map approach using filtered sea surface temperature
Rivera, Diego ; Lillo, Mario ; Bertacchi Uvo, Cintia LU
; Billib, Max
and Luis Arumi, Jose
(2012)
In Theoretical and Applied Climatology
107(1-2).
p.1-13
- Abstract
- Western South America is subject to considerable inter-annual variability due to El Nio-Southern Oscillation (ENSO) so forecasting inter-annual variations associated with ENSO would provide an opportunity to tailor management decisions more appropriately to the season. On one hand, the self-organizing maps (SOM) method is a suitable technique to explore the association between sea surface temperature and precipitation fields. On the other hand, Wavelet transform is a filtering technique, which allows the identification of relevant frequencies in signals, and also allows localization on time. Taking advantage of both methods, we present a method to forecast monthly precipitation using the SOM trained with filtered SST anomalies. The use of... (More)
- Western South America is subject to considerable inter-annual variability due to El Nio-Southern Oscillation (ENSO) so forecasting inter-annual variations associated with ENSO would provide an opportunity to tailor management decisions more appropriately to the season. On one hand, the self-organizing maps (SOM) method is a suitable technique to explore the association between sea surface temperature and precipitation fields. On the other hand, Wavelet transform is a filtering technique, which allows the identification of relevant frequencies in signals, and also allows localization on time. Taking advantage of both methods, we present a method to forecast monthly precipitation using the SOM trained with filtered SST anomalies. The use of the SOM to forecast precipitation for Chillan showed good agreement between forecasted and measured values, with correlation coefficients (r (2)) ranging from 0.72 to 0.91, making the combined use filtered SST fields and SOM a suitable tool to assist water management, for example in agricultural water management. The method can be easily tailored to be applied in other stations or to other variables. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2358494
- author
- Rivera, Diego
; Lillo, Mario
; Bertacchi Uvo, Cintia
LU
; Billib, Max
and Luis Arumi, Jose
- organization
- publishing date
- 2012
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Theoretical and Applied Climatology
- volume
- 107
- issue
- 1-2
- pages
- 1 - 13
- publisher
- Springer
- external identifiers
-
- wos:000298999300001
- scopus:84855528144
- ISSN
- 1434-4483
- DOI
- 10.1007/s00704-011-0453-5
- language
- English
- LU publication?
- yes
- id
- 8107c9e1-515b-411d-a6d0-681f05bd70ff (old id 2358494)
- date added to LUP
- 2016-04-01 14:27:55
- date last changed
- 2022-01-28 00:46:23
@article{8107c9e1-515b-411d-a6d0-681f05bd70ff,
abstract = {{Western South America is subject to considerable inter-annual variability due to El Nio-Southern Oscillation (ENSO) so forecasting inter-annual variations associated with ENSO would provide an opportunity to tailor management decisions more appropriately to the season. On one hand, the self-organizing maps (SOM) method is a suitable technique to explore the association between sea surface temperature and precipitation fields. On the other hand, Wavelet transform is a filtering technique, which allows the identification of relevant frequencies in signals, and also allows localization on time. Taking advantage of both methods, we present a method to forecast monthly precipitation using the SOM trained with filtered SST anomalies. The use of the SOM to forecast precipitation for Chillan showed good agreement between forecasted and measured values, with correlation coefficients (r (2)) ranging from 0.72 to 0.91, making the combined use filtered SST fields and SOM a suitable tool to assist water management, for example in agricultural water management. The method can be easily tailored to be applied in other stations or to other variables.}},
author = {{Rivera, Diego and Lillo, Mario and Bertacchi Uvo, Cintia and Billib, Max and Luis Arumi, Jose}},
issn = {{1434-4483}},
language = {{eng}},
number = {{1-2}},
pages = {{1--13}},
publisher = {{Springer}},
series = {{Theoretical and Applied Climatology}},
title = {{Forecasting monthly precipitation in Central Chile: a self-organizing map approach using filtered sea surface temperature}},
url = {{http://dx.doi.org/10.1007/s00704-011-0453-5}},
doi = {{10.1007/s00704-011-0453-5}},
volume = {{107}},
year = {{2012}},
}