DocumentCode :
512923
Title :
Relationship between sea regions with high thermal variability and wildfires from 1981 TO 2008
Author :
Nunez-Casillas, L. ; Arbelo, M. ; Moreno-Ruiz, J.A. ; Hernandez-Leal, P.A. ; Barreto, A. ; Alonso-Benito, A.
Author_Institution :
Dept. de Fis., Univ. de La Laguna, La Laguna, Spain
Volume :
1
fYear :
2009
fDate :
12-17 July 2009
Abstract :
Daily OISST version 2 data from 1981 to 2008 are used to detect high SST variability regions in order to explore their relationship with wildfires in some particular regions. A burned area (BA) dataset is obtained for Canada for the period 1982-2006, from LTDR dataset version 2 and LAC burned area record. A selection of high variability cells encountered within the Nino 3.4 region is analyzed with standardized seasonal BA, where a significant correlation at year lag in spring and three year lag in summer and autumn was found. Yet, results showed that SST and Oceanic Nino Index did not cause BA with a three-year lag time in Wiener-Granger sense, whereas annual SST did cause BA in spring, at the 0.95 confidence level. The proportion of fires occurred from 1982 to 2006 after an El Nino event increased at one- and two-year lag.
Keywords :
Bayes methods; El Nino Southern Oscillation; fires; ocean temperature; oceanographic regions; vegetation; AD 1981 to 2008; Canada; El Nino event; LAC burned area record; LTDR dataset version 2; Oceanic Nino Index; Wiener-Granger sense; burned area dataset; daily OISST version 2 data; high SST variability region; wildfires; Error correction; Ice surface; Interpolation; Los Angeles Council; Ocean temperature; Radiometry; Satellite broadcasting; Sea surface; Smoothing methods; Spatial resolution; Burned Area; El Niño; SST; causality; lag correlation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009
Conference_Location :
Cape Town
Print_ISBN :
978-1-4244-3394-0
Type :
conf
DOI :
10.1109/IGARSS.2009.5416897
Filename :
5416897
Link To Document :
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