TY - JOUR
T1 - Core–shell clustering approach for detection and analysis of coastal upwelling
AU - Nascimento, Susana
AU - Martins, Alexandre
AU - Relvas, Paulo
AU - Luís, Joaquim F.
AU - Mirkin, Boris
N1 - Funding Information:
S.N. and A.M. acknowledge the support from NOVA LINCS, Portugal ( UIDB/04516/2020 ), P.R. acknowledges the support through projects UIDB/04326/2020 , UIDP/04326/2020 and LA/P/0101/2020 , J. L. acknowledges the support through project UIDB/50019/2020 , all funded by Portuguese national funds, Portugal from FCT- Foundation for Science and Technology, Portugal . B.M. acknowledges support from the Basic Research Program of the National Research University Higher School of Economics Moscow, UK . The authors are grateful to the anonymous reviewers for their insightful and constructive comments that allowed us to improve the presentation.
Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/10
Y1 - 2023/10
N2 - A comprehensive approach is presented to analyze season's coastal upwelling represented by weekly sea surface temperature (SST) image grids. The proposed model, core–shell clustering, assumes that the season's upwelling can be divided into shorter periods of stability, time ranges, consisting of constant core and variable shell parts. A one-by-one core–shell clustering algorithm is provided. The algorithm parameters are automatically derived from the least-squares clustering criterion. The approach applies to SST gridded data for sixteen successive years (2004–2019) of coastal upwelling in the western Iberian coast, the northernmost branch of the Canary Current Upwelling System. Our results show that at each season, there are 3 to 5 time intervals, the ranges, at which the upwelling presents stable core patterns of relatively cold water surrounded by somewhat larger shell areas of warmer waters. Based on other experimental computations performed by our team, we conclude that this pattern is not just a purely local phenomenon but has a more global meaning. Inter-annual time series analysis are consistent among themselves and with existing expert domain knowledge.
AB - A comprehensive approach is presented to analyze season's coastal upwelling represented by weekly sea surface temperature (SST) image grids. The proposed model, core–shell clustering, assumes that the season's upwelling can be divided into shorter periods of stability, time ranges, consisting of constant core and variable shell parts. A one-by-one core–shell clustering algorithm is provided. The algorithm parameters are automatically derived from the least-squares clustering criterion. The approach applies to SST gridded data for sixteen successive years (2004–2019) of coastal upwelling in the western Iberian coast, the northernmost branch of the Canary Current Upwelling System. Our results show that at each season, there are 3 to 5 time intervals, the ranges, at which the upwelling presents stable core patterns of relatively cold water surrounded by somewhat larger shell areas of warmer waters. Based on other experimental computations performed by our team, we conclude that this pattern is not just a purely local phenomenon but has a more global meaning. Inter-annual time series analysis are consistent among themselves and with existing expert domain knowledge.
KW - Coastal upwelling
KW - Core–shell cluster
KW - Spatio-temporal clustering
KW - SST images
KW - Time series segmentation
UR - http://www.scopus.com/inward/record.url?scp=85171611619&partnerID=8YFLogxK
U2 - 10.1016/j.cageo.2023.105421
DO - 10.1016/j.cageo.2023.105421
M3 - Article
AN - SCOPUS:85171611619
SN - 0098-3004
VL - 179
JO - Computers and Geosciences
JF - Computers and Geosciences
M1 - 105421
ER -