Wintertime SST and Chl a off NW Iberian shelf from satellite and in situ data

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1 Wintertime SST and Chl a off NW Iberian shelf from satellite and in situ data Paulo B. Oliveira+, Teresa Moita+, Rui Catarino+, António Jorge da Silva++ + INRB IPIMAR Instituto Nacional de Recursos Biológicos, Av. Brasilia, Lisboa, Portugal ++ IH Instituto Hidrográfico, Rua das Trinas 49, Lisboa, Portugal Abstract Data from AVHRR (Advanced Very High Resolution Radiometer), MODIS (MODerate Resolution Imaging Spectroradiometer) and MERIS (MEdium Resolution Imaging Spectrometer) are used together with field data from a survey carried out off NW Iberian Peninsula in February/March 2006 to study the effect of wind and river runoff on sea surface temperature (SST) and chlorophyll a (chl a) concentration, and assess the performance of algorithms to estimate chl a in the inner shelf region. The satellite images obtained during an event of northerly winds show the presence of patches of cold and pigment rich water in the mid shelf region (100m). These patches result from phytoplankton growth and accumulation in the edge of low salinity buoyant plumes of river origin that are advected offshore and overlay the warmer oceanic oligotrophic waters. The comparison between in situ, MODIS and MERIS chl a estimates, revealed that the spatial patterns on MODIS and MERIS (case 1 waters) images are very similar and the MERIS mask for invalid pixels is too restrictive in the outer shelf. Both algorithms overestimate chl a concentration at the inner shelf for water depths lower than 50m. At these depths, the best qualitative agreement with in situ surface chl a distribution is obtained with inverse radiative transfer model neural network algorithm (MERIS algal_2), which is able to reproduce the low chl a concentrations observed in the field data. INTRODUCTION The wintertime upper ocean circulation in the NW Iberian shelf region results from the interplay between the density driven poleward slope flow, the inshore currents associated to the low salinity buoyant plumes and the wind forcing (Relvas et al., 2007). The buoyant plumes originated from river runoff, respond rapidly to changes in wind conditions, being advected offshore under northerly winds and converging to the coast under southerlies (Otero et al., 2007). The stratification conditions associated with these plumes promote a vertical stability in the euphotic zone favouring the phytoplankton growth (Ribeiro et al., 2005). The riverine origin of these low salinity plumes, and their consequent sediment and yellow substance (YS) load, leads to the need of carefully identify the water type and correctly choose the algorithm used to estimate chl a concentrations from ocean colour sensors, thus avoiding the chl a overestimation in turbid waters (e.g. Le Fouest et. al, 2006).

2 Here, we use AVHRR, MODIS, MERIS and in situ data to describe the spatial patterns of sea surface temperature (SST) and chlorophyll a (chl a) concentration off the NW Iberian Peninsula in winter Synoptic satellite chl a images are compared with the in situ surface temperature, salinity and chl a distributions to qualitatively assess the performance of algorithms to estimate chl a in the inner shelf from ocean colour data. DATA AND METHODS The survey was carried out from 24 February to 7 March 2006 on board NRP Auriga, along 13 cross shelf sections extending from the coast the approximate position of the 150 m isobath (Fig. 1). Vertical profiles of temperature, salinity and turbidity were obtained with a Idronaut Ocean Seven 320 CTD (Conductivity, Temperature, Depth) equipped with a nephelometer. Water samples were collected using a General Oceanics rosette sampler equipped with six 5 L and five 1.7 L bottles. For the estimation of the in situ chl a, 250 ml water samples were filtered on board, and the filters kept frozen until chl a extraction with 90% acetone, and its concentration determined on a Perkin Elmer spectrofluorometer (Yentsch and Menzel, 1963). Satellite chl a estimates were obtained from MERIS and MODIS (Feldman & McClain, 2006) data provided by ESA and NASA, respectively. MODIS L2 and MERIS Fine Resolution data were re projected to a common geographical grid to allow direct visual comparison of the spatial chl a distributions. The satellite derived SST maps were extracted from EUMETSAT's Ocean and Sea Ice Satellite Application Facility Regional SST, available at 2 km resolution (Brisson et. al, 2001). Wind data was obtained from NCEP/NCAR reanalysis project (Kistler et al., 2001). Figure 1: Study region and satellite derived average SST from the AVHRR images of 27 and 28 February. The dots represent the position of the hydrographic stations occupied from 24 February to 7 March 2006 along 13 cross shelf sections.

3 RESULTS The average satellite derived SST (Fig. 1, right) and the in situ temperature and salinity distributions at 3 dbar (Fig. 2) show that the observed upper ocean hydrological structure corresponded to a typical winter situation off NW Iberia: cold, low salinity water plumes of riverine origin are distributed over the shelf, overlying the warmer and saltier oceanic waters, with the lower salinity patches being found close to the mouth of the main rivers. Figure 2: Wind forcing (upper panel) and spatial distributions of surface (3 dbar) temperature, salinity and surface chl a (lower panel). Gray strips in the wind time series represent the days when in situ cross shelf sections were carried out from south to north S1: 24 Feb., S2 6: Feb., S7: 2 Mar., S8 9: 6 Mar., S11 13: 7 Mar Sections 2 6, contemporary with the satellite images, are labelled in red in the temperature and salinity distributions.

4 In contrast to the co location of the local temperature and salinity minima, the highest chl a concentrations are typically located at the offshore edge of the buoyant plumes, with the exception of the plume located at the mouth of the Douro river (41.2N), where a very strong cross shelf surface salinity gradient is found, and the vertical extent of the plume is small (< 10 m) (Fig. 3, bottom). Further north the low salinity buoyant plumes extend offshore, and stronger vertical mixing with the underlying waters leads to smaller vertical salinity gradients (Fig. 3, top). It is worth noting that the low surface chl a concentrations observed at 41.2N are associated with the inshore most penetration of the warm oceanic waters and found in the area where the vertical mixing is most intense (section 3 Fig. 3, bottom). Figure 3: Vertical sections of density anomaly, salinity and temperature sections, represented as a function of the distance to the coast in km (bottom scale). Station position and numbers are marked in the top axis. Section 3 (bottom) illustrates the Douro river plume overlying a warm and saline, vertically mixed oceanic water body occupying most of the shelf. Section 5 (top), shows two low salinity patches associated with lower vertical salinity gradients.

5 The MODIS and MERIS (algal_2) chl a images obtained on 28 February (Fig. 4) show pigment rich water patches in the shelf region, both images being similar to the in situ chl a distribution in water depths greater than 50 m. Over shallower depths the MODIS algorithm clearly overestimates the surface chl a, a feature not observed in the MERIS (algal_2) image, which reproduces the low chl a concentrations observed in the coastal stations. The chl a image derived from the MERIS data using the case 1 waters (Fig. 4, top middle and bottom) has most shelf pixels flagged as invalid, mainly due to the "anomalous scattering water" test (case2_anom flag, Aiken & Moore, 2000a), with most inner shelf also flagged as "sediment dominated case 2 water" (case2_s flag, Aiken & Moore, 2000b). When only the "water" flag is used to mask the land, the chl a patterns on MERIS algal_1 image (Fig. 4, bottom left) are very similar to the MODIS image. Figure 4: MODIS (~1km) chl a and MERIS (~300m) images for 28 February Operational products are presented in the top row: MODIS (left), MERIS algal_1 (middle) and MERIS algal_2 (right). Bottom row shows the MERIS algal_1 product with different masks applied: "water" flag only (left), "anomalous scattering water" (case2_anom, middle) and "sediment dominated case 2 water" (case2_s, right). Black dots in the images represent the hydrographic stations occupied on 27 and 28 February and the dashed lines represent the 200, 100 and 30 m bathymetric contours.

6 DISCUSSION The haline front delineating the region of fresh water influence shows strong cross shore undulations (Fig. 2). From the modelling study presented by Otero et al. (2007), the salinity distribution south of 42N may be interpreted as the result of interaction between the currents in the lower layers and the offshore Ekman transport of the buoyant plumes forced by the northerly winds observed at the beginning of the survey. North of 42N, a fast response of the buoyant plumes to the southerlies observed at the end of the survey may have been responsible for the inshore position of the haline front. The highest surface values of chl a are associated with the offshore spreading of the low salinity buoyant plumes. A similar result was obtained by Ribeiro et al. (2005) in a study using satellite and field data from the same region. Using a sequence of SeaWiFS images from February 2000, these authors estimated a net increase in chl a biomass during a northerly wind event and argued that retention of phytoplankton in the shallow stratified buoyant plumes was a key factor for this increase. The satellite derived chl a distribution that is most similar to the in situ surface distribution, derives from the inverse radiative transfer model neural network algorithm (Doerffer & Schiller, 2007). This algorithm is able to reproduce the low chl a concentrations observed at the inner shelf, where higher sediment loads and YS concentrations are found (Fig. 5), inhibiting phytoplankton growth through the decrease of photosynthetically active radiation. However, the chl a values obtained with this algorithm in shallow waters are lower than those for the oceanic waters, a feature not observed in the in situ data. Figure 5: Total suspended matter (left), yellow substance absorption (middle) and difference between MERIS algal_1 (no mask) and algal_2 algorithms. Dashed lines represent the 200, 100 and 30 m bathymetric contours The comparison between MERIS, MODIS and in situ (surface) chl a distributions (Fig. 4) shows that the MODIS chl a retrievals are very similar to the MERIS estimates for case 1 waters (algal_1, no mask; Morel & Antoine, 2007). Both algorithms overestimate chl a concentration at the inner shelf. While the MODIS product includes these erroneous values, the MERIS algal_1 product has almost all

7 shelf pixels flagged as invalid". The similarity between all chl a estimates in the outer shelf suggests that the mask is too restrictive, eliminating valid chl a (algal_1) estimates. The distributions of the total suspended sediment (Fig. 5, left) and YS absorption (Fig. 5, middle) show that the highest sediment and YS loads are confined to water depths roughly less than 30 m, the area where the difference 3 between the chl a estimates from the two MERIS algorithms exceeds 3 mg/m. The chl a overestimation has been reported in many coastal and shelf areas, particularly when using SeaWiFS data (see Le Fouest et al., 2006 and references therein) and constitutes an important factor to be taken into account when using satellite derived chl a databases to study the seasonal and interannual variability. The results obtained here confirm that the very high winter chl a concentrations in the inner shelf off NW Iberian Peninsula arrived at by Peliz & Fiúza (1999) are a result of a predominance of waters whose optical properties are dominated by suspended sediment and YS. As this effect is also present in actual MODIS products, it still needs to be taken into account when using MODIS data to study chl a variability off NW Iberian Peninsula. ACKNOWLEDGEMENTS This work was done in the frame of the ESA projects AMAZING (AOPT 2423) and ProFit (AOPT 2313), and the respective Portuguese Science Foundation (FCT) Projects: PDCTE/CTA/49953/2003 and PDCTE/CTA/50386/2003. The in situ measurements were obtained in the frame of the NICC (POCTI/CTA/49563) and ECOIS (POCTI/CTA/48461) Projects. NCEP Reanalysis wind data were provided by the NOAA CIRES Climate Diagnostics Center, Boulder, Colorado, USA, from their Web site at MODIS L2 data were obtained from NASA's Goddard Space Flight Center ( Satellite derived SST data were obtained from EUMETSAT Ocean and Sea Ice Satellite Application Facility ( saf.org). REFERENCES Aiken, J. and G. Moore (2000a). ATBD 2.8: Case 2 Anomalous Scattering and Gelbstoff Waters Flags. ESA Doc. No. PO TN MEL GS 0005, Aiken, J. and G. Moore (2000b). ATBD 2.5: Case 2 Turbid Waters Flag. ESA Doc. No. PO TN MEL GS 0005, Brisson A., S. Eastwood, P. LeBorgne and A. Marsouin (2001) O&SI SAF sea surface temperatures: pre operational results. Proceedings of the 2001 EUMETSAT Meteorological Data Users' Conference, Antalaya, Turkey, 1 5 October. Doerffer, R. and Schiller, H., (2007) The MERIS Case 2 water algorithm. International Journal of Remote Sensing, 28, pp Feldman, G. C., C. R. McClain, (2006) Ocean Color Web, MODIS Reprocessing 1.1, NASA Goddard Space Flight Center. Eds. Kuring, N., Bailey, S. W.,11 Dec Kistler, R., E. Kalnay, W. Collins, S. Saha, G. White, J. Woollen, M. Chelliah, W. Ebisuzaki, M. Kanamitsu, V. Kousky, H. van den Dool, R. Jenne and M. Fiorino (2001) The NCEP/NCAR 50 year reanalysis: Monthly means CD ROM and documentation. Bulletin of the American Meteorological Society, 82, pp

8 Le Fouest, V., B. Zakardjian, F.J. Saucier, and S.A. Çizmeli, (2006) Application of SeaWIFS and AVHRR derived data for mesoscale and regional validation of a 3 D high resolution physical biological model of the Gulf of St. Lawrence (Canada). Journal of Marine Systems, 60, pp Morel, A. & D. Antoine (2007). ATBD 2.9: Pigment Index Retrieval in Case 1 Waters. ESA Doc. No. PO TN MEL GS 0005, Otero, P., Ruiz Vilarreal, M. A. Peliz. (2007) Variability of river plumes off Northwest Iberia in response to wind events. Journal of Marine Systems, in press. Peliz, A.J. and A.F.G. Fiúza, (1999) Temporal and spatial variability of CZCS derived phytoplankton pigment concentrations off western Iberian Peninsula. International Journal of Remote Sensing, 20, pp Ribeiro, A.C., A. Peliz and A.M.P. Santos, (2005) A study of the response of chlorophyll a biomass to a winter upwelling event off Western Iberia using SeaWiFS and in situ data. Journal of Marine Systems, 53, pp Yentsch, C.S., Menzel, D.W., (1963) A method for the determination of phytoplankton chlorophyll and phaeophytin by fluorescence. Deep Sea Research, 10, pp