Ocean color response to wind forcing in the Alboran Sea: A new forecasting method

This work proposes a new method to reconstruct and forecast surface Chlorophyll (Chl) from remotely sensed (SeaWiFS) data in the Alboran Sea, based on the correlation between zonal wind velocities and satellite Chl concentrations. First, the spatial and temporal variability of Chl and zonal wind have been characterized using standard statistics. Second, the annual cycle and trends are removed from the original time series and the residuals submitted to an EOF computation scheme. Then, the correlations between the amplitudes of the first temporal modes of Chl-wind couple have been quantified. Using the most highly correlated pair (Chl-zonal wind, with r. =. 0.63), a simple linear relationship is proposed to reconstruct and forecast the Chl field. This forecasting method is more efficient than persistence for forecast horizons longer than 100. days, with a mean correlation between original and predicted field of 0.73 as compared to 0.5 for persistence for all the year round. In partic\ular, this new method gives a 0.95 mean correlation for periods from 100 to 290. days (while persistence gives 0.5). However, for a constant 8-days prediction horizon the persistence performs marginally better than the proposed method (0.79 vs. 0.68), giving some insight into the temporal scales of the features studied. These results may have significant implications for both short-term operational applications and seasonal forecasts. © 2012 Elsevier B.V.

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Main Authors: Solé, Jordi, Ruiz, Simón, Pascual, Ananda, Somot, Samuel, Tintoré, Joaquín
Format: artículo biblioteca
Language:English
Published: Elsevier 2012
Online Access:http://hdl.handle.net/10261/57139
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spelling dig-icm-es-10261-571392022-11-09T09:33:29Z Ocean color response to wind forcing in the Alboran Sea: A new forecasting method Solé, Jordi Ruiz, Simón Pascual, Ananda Somot, Samuel Tintoré, Joaquín This work proposes a new method to reconstruct and forecast surface Chlorophyll (Chl) from remotely sensed (SeaWiFS) data in the Alboran Sea, based on the correlation between zonal wind velocities and satellite Chl concentrations. First, the spatial and temporal variability of Chl and zonal wind have been characterized using standard statistics. Second, the annual cycle and trends are removed from the original time series and the residuals submitted to an EOF computation scheme. Then, the correlations between the amplitudes of the first temporal modes of Chl-wind couple have been quantified. Using the most highly correlated pair (Chl-zonal wind, with r. =. 0.63), a simple linear relationship is proposed to reconstruct and forecast the Chl field. This forecasting method is more efficient than persistence for forecast horizons longer than 100. days, with a mean correlation between original and predicted field of 0.73 as compared to 0.5 for persistence for all the year round. In partic\ular, this new method gives a 0.95 mean correlation for periods from 100 to 290. days (while persistence gives 0.5). However, for a constant 8-days prediction horizon the persistence performs marginally better than the proposed method (0.79 vs. 0.68), giving some insight into the temporal scales of the features studied. These results may have significant implications for both short-term operational applications and seasonal forecasts. © 2012 Elsevier B.V. We acknowledge the support of SESAME Integrated Project (Contract number 036949). Peer Reviewed 2012-10-03T06:51:47Z 2012-10-03T06:51:47Z 2012 2012-10-03T06:51:47Z artículo http://purl.org/coar/resource_type/c_6501 doi: 10.1016/j.jmarsys.2012.02.007 issn: 0924-7963 Journal of Marine Systems 98-99: 1- 8 (2012) http://hdl.handle.net/10261/57139 10.1016/j.jmarsys.2012.02.007 en open Elsevier
institution ICM ES
collection DSpace
country España
countrycode ES
component Bibliográfico
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databasecode dig-icm-es
tag biblioteca
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libraryname Biblioteca del ICM España
language English
description This work proposes a new method to reconstruct and forecast surface Chlorophyll (Chl) from remotely sensed (SeaWiFS) data in the Alboran Sea, based on the correlation between zonal wind velocities and satellite Chl concentrations. First, the spatial and temporal variability of Chl and zonal wind have been characterized using standard statistics. Second, the annual cycle and trends are removed from the original time series and the residuals submitted to an EOF computation scheme. Then, the correlations between the amplitudes of the first temporal modes of Chl-wind couple have been quantified. Using the most highly correlated pair (Chl-zonal wind, with r. =. 0.63), a simple linear relationship is proposed to reconstruct and forecast the Chl field. This forecasting method is more efficient than persistence for forecast horizons longer than 100. days, with a mean correlation between original and predicted field of 0.73 as compared to 0.5 for persistence for all the year round. In partic\ular, this new method gives a 0.95 mean correlation for periods from 100 to 290. days (while persistence gives 0.5). However, for a constant 8-days prediction horizon the persistence performs marginally better than the proposed method (0.79 vs. 0.68), giving some insight into the temporal scales of the features studied. These results may have significant implications for both short-term operational applications and seasonal forecasts. © 2012 Elsevier B.V.
format artículo
author Solé, Jordi
Ruiz, Simón
Pascual, Ananda
Somot, Samuel
Tintoré, Joaquín
spellingShingle Solé, Jordi
Ruiz, Simón
Pascual, Ananda
Somot, Samuel
Tintoré, Joaquín
Ocean color response to wind forcing in the Alboran Sea: A new forecasting method
author_facet Solé, Jordi
Ruiz, Simón
Pascual, Ananda
Somot, Samuel
Tintoré, Joaquín
author_sort Solé, Jordi
title Ocean color response to wind forcing in the Alboran Sea: A new forecasting method
title_short Ocean color response to wind forcing in the Alboran Sea: A new forecasting method
title_full Ocean color response to wind forcing in the Alboran Sea: A new forecasting method
title_fullStr Ocean color response to wind forcing in the Alboran Sea: A new forecasting method
title_full_unstemmed Ocean color response to wind forcing in the Alboran Sea: A new forecasting method
title_sort ocean color response to wind forcing in the alboran sea: a new forecasting method
publisher Elsevier
publishDate 2012
url http://hdl.handle.net/10261/57139
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AT ruizsimon oceancolorresponsetowindforcinginthealboranseaanewforecastingmethod
AT pascualananda oceancolorresponsetowindforcinginthealboranseaanewforecastingmethod
AT somotsamuel oceancolorresponsetowindforcinginthealboranseaanewforecastingmethod
AT tintorejoaquin oceancolorresponsetowindforcinginthealboranseaanewforecastingmethod
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