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- Piece‐wise constant cluster modelling of dynamics of upwelling patternsPublication . Nascimento, Susana; Martins, Alexandre; Relvas, Paulo; Luis, Joaquim; Mirkin, BorisA comprehensive approach is presented to analyse season's coastal upwelling represented by weekly sea surface temperature (SST) image grids. Our three-stage data recovery clustering method assumes that the season's upwelling can be divided into shorter periods of stability, ranges, each to be represented by a constant core and variable shell parts. Corresponding clustering algorithms parameters are automatically derived by using the least-squares clustering criterion. The approach has been successfully applied to real-world SST data covering two distinct regions: Portuguese coast and Morocco coast, for 16 years each.
- Connections between upwelling patterns and phytoplankton variability under different coastal regimes in SW Iberia PeninsulaPublication . Krug, Lilian; Silvano, Kathleen M.; Barbosa, Ana B.; Domingues, Rita B.; Galvão, Helena M.; Luis, Joaquim; Platt, Trevor; Relvas, Paulo; Sathyendranath, ShubhaThe region off southwestern Iberia (NE Atlantic) encompasses a wide variety of oceanographic regimes, including differently (geographic) oriented coastal areas impacted by upwelling, riverine inputs and submarine groundwater discharge, submarine canyons and seamounts, and open ocean waters, thereby potentially promoting zone-specific phytoplankton dynamics. Overall, this heterogeneous region is classified as being very sensitive to climate change, and climate-driven alterations (e.g., sea surface warming, changes in upwelling patterns and intensity) have been recently reported for the area. The present study aims to understand the contribution of upwelling to seasonal and interannual variability of coastal phytoplankton, using a remote sensing-based approach. Phytoplankton variability was evaluated using satellite-derived chlorophyll-a (Chl-a), as a proxy for phytoplankton biomass, and primary productivity (PP). Chl-a were obtained from merged SeaWiFS (Seaviewing Wide Field-of-view Sensor), MeRIS (Medium Resolution Imaging Spectrometer) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer) sensors at Globcolour portal. PP data at 9.25 km resolution were derived from Eppley’s Vertically Generalized Production Model, based on SeaWiFS and MODIS-Aqua and available at the Ocean Productivity site. Upwelling intensity was estimated using the difference in sea surface temperature (SST) between off and nearshore zones. Advanced Very-High Resolution Radiometer (AVHRR) 4 km SST were obtained from Pathfinder database. Other phytoplankton environmental drivers, such as local (e.g., river flow) and global (e.g., North Atlantic Oscillation - NAO) climate variables, were also analysed. The study area was divided into subareas differently impacted by upwelling and riverine flow, and satellitederived data was averaged for each zone. Seasonal and interannual variability covering a 14-year time series (1998- 2011) for each variable/region were explored. Chl-a at offshelf locations was significantly lower than coastal areas, and exhibited a fairly stable unimodal annual cycle, with maximum during March. Coastal locations displayed more variable annual patterns, with spring and summer Chl-a maxima, reflecting the impact of upwelling events and freshwater inputs. In respect to interannual variability, NAO index and coastal Chl-a were negative and significantly correlated, with 1-month lag. Chl-a interannual trends were also correlated to local climate variables, namely riverine flow for the easternmost coastal zone. The correlation between upwelling intensity and phytoplankton off SW Iberia is region-dependent being less strong within regions dominated by riverine influence.
- Importance of the mesoscale in the decadal changes observed in the northern Canary upwelling systemPublication . Relvas, Paulo; Luis, Joaquim; Santos, A. Miguel P.Analysis of sea surface temperature (SST) time series since 1960 from existing data bases shows a generalized warming trend in the northern Canary upwelling system. The field of the satellite-derived SST trends off Western Iberia was built at the pixel scale (4 x 4 km) for the period 1985-2008, revealing significant spatial differences in the warming rates. Weaker warming trends fit to the known upwelling pattern off the southern part of the Western Iberia, pointing out the intensification of this feature since 1985, particularly during the peak summer months. A more regular behavior is found further north suggesting significant decadal changes in the mesoscale patterns of the northern Canary upwelling system. Citation: Relvas, P., J. Luis, and A. M. P. Santos (2009), Importance of the mesoscale in the decadal changes observed in the northern Canary upwelling system, Geophys. Res. Lett., 36, L22601, doi:10.1029/2009GL040504.
- Novel cluster modeling for the spatiotemporal analysis of coastal upwellingPublication . Nascimento, Susana; Martins, Alexandre; Relvas, Paulo; Luis, Joaquim; Mirkin, BorisThis work proposes a spatiotemporal clustering approach for the analysis of coastal upwelling from Sea Surface Temperature (SST) grid maps derived from satellite images. The algorithm, Core-Shell clustering, models the upwelling as an evolving cluster whose core points are constant during a certain time window while the shell points move through an in-and-out binary sequence. The least squares minimization of clustering criterion allows to derive key parameters in an automated way. The algorithm is initialized with an extension of Seeded Region Growing offering self-tuning thresholding, the STSEC algorithm, that is able to precisely delineate the upwelling region at each SST instant map. Yet, the application of STSEC to the SST grid maps as temporal data puts the business of finding relatively stable "time windows", here called "time ranges", for obtaining the core clusters onto an automated footing. The experiments conducted with three yearly collections of SST data of the Portuguese coast shown that the core-shell clusters precisely recognize the upwelling regions taking as ground-truth the STSEC segmentations with Kulczynski similarity score values higher than 98%. Also, the extracted time series of upwelling features presented consistent regularities among the three independent upwelling seasons.