SST variability in the Azores region using AVHRR imagery: regional to local scale study Virginie Lafon *a, Ana Martins a, Igor Bashmachnikov a, Felix Jose a, Margarida Melo-Rodrigues a, Miguel Figueiredo a, Ana Mendonça a, Luis Macedo a
ABSTRACT Using 1.1 km resolution imagery from NOAA-12, -14, -16, and -17 recorded from April 2001 to May 2003 by “HAZO” HRTP mid-Atlantic satellite receiving station, 8-day average image are calculated to investigate AVHRR-derived SST distributions and associated dominant space and time scales around the Azores archipelago (34º to 42º N, 33º to 23º W). Eight-day average images together with zonal and meridional averages show a distinct seasonal cycle and typical gradients, which emphasise the dual influence of the Gulf Stream and the Azores Current in this region. In late spring, isotherms start moving to the north and retreat in early autumn. Low horizontal gradients are found during summertime, with warmer waters located to the south and west. Orientation of SST patterns changes with time from SW-NE (e.g. July 2001) to NNW-SSE (e.g. July 2002, August 2001 and 2002). The later orientation involves the sudden warming of the waters surrounding the northwestern group of islands of the Azores archipelago. This warming persists during 3 to 6 weeks with mean temperature differences of the order of 0.8 ºC. At a more local scale (2º x 2º in size) SST variability is also observed. In some cases, it is found that wind-driven coastal upwelling, a few km wide, occurs to the south of the islands during spring and summer months. Field data demonstrate that upwelling events increase local biomass. This result highlights the relevance of SST data to improve stock assessment and fishery management studies. Keywords SST, spatial variability, temporal variability, coastal upwelling, Azores
1. INTRODUCTION The Azores archipelago (Fig. 1) is situated in the inter-gyre region of the eastern North Atlantic, with the south edge of the subpolar gyre located at about 50º N, and the north edge of the subtropical gyre located at about 34º N1. The Gulf Stream current feeds the Azores area. Its southeastern branch crosses the Atlantic ridge at about 45º W and between 32º and 35º N generating the eastward-flowing Azores current (AzC)2,3. The AzC and its associated front, the Azores Front (AzF), are characterised by important thermohaline cross-gradients2,4. Measurements and models suggest that baroclinic instability of the AzC play an important role in meander and westward-propagating eddy formation in the AzC region 5,6,7,8,9. Eddies in the area have mean diameters on the order of 300-400 km and they travel at speed that can reach several kilometres per day10. In the area of investigation (Azores archipelago), the mean currents are very weak and mesoscale activity dominates the oceanic motion. This was previously noted by 11,12, while investigating large-scale sea-level and temperature variability in the subtropical north-east Atlantic. Large-scale sea-level variations in this wide oceanic region are characterised by a predominant
*
Occidental Group
Flores
Terceira
Faial
Central Group
São Miguel
Oriental Group
Figure 1: General NE Atlantic circulation and location of the Azores archipelago
[email protected]; phone +351 292 200 400; fax: +351 292 200 411; www.horta.uac.pt
seasonal fluctuation, whilst residual variations present time variations resembling that of the North Atlantic Oscillation (NAO)12. If sea-surface heights data provided by satellite altimeters have been largely investigated to document the large-scale variability of the Atlantic Ocean 7,9,11,12,13,14,15,16, concurrent sea surface temperature (SST) variability is more rarely addressed12,17, although large-scale sea-level and SST variability seem to be correlated12. Still, simple characteristics of the Azores waters, such as water temperature seasonal variability and mean anomaly fields, need to be precisely measured to better understand the climate in the North Atlantic. SST satellite imagery provides good support for the analysis of mesoscale variability of large oceanic regions. For instance, NOAA imagery has been extensively processed to produce weekly to monthly composites of oceanic basins. Among others, these have been exploited to analyse SST temporal and spatial variability18,19, to describe current flow and recirculation20, to determine temperature anomalies21, and to detect cyclonic and anticyclonic eddies22. Time-series of SST composites are also decisive for weather and climate monitoring and forecasting23. Thus, satellite-derive SST records may be valuable to investigate the region of the Azores. Within the framework of project DETRA (Implementação de técnicas de DETecção Remote nos Açores) that aims to study SST variability and help to manage fisheries activities in the Azores, an HRPT Satellite Receiving Station (HAZO) was installed in the island of Faial (cf. Fig. 1). Since 4th April 2001, the HAZO station daily receives images from SeaStar, NOAA-12, NOAA-14, and NOAA-16. NOAA-17 is recorded since 22nd July 2002. The objective of this contribution is to investigate a two-year time series satellite-derived SST (2001-2003) to analyse the space and time variability of the SST in the Azores region, both at a regional and a local scale. For this purpose, monthly and 8-day averages are performed. Since the average number of cloud free pixels is about 9% in the Azores region 24, the relevance of computing 8-day SST composites is estimated. Then, based on time series averages, the temperature seasonality is studied and the gradients are derived. A particular attempt is made to highlight intra- and inter-annual changes between the three groups of islands, and demonstrate the impact of changing SST patterns on chlorophyll a concentrations (chl a) derived from concurrent SeaWiFS measurements. Finally, local variation of SST (i.e. within groups) is searched for, and compared with field observations. The paper is structured as follows: second section presents the data bases, third section the methodology, fourth section the results and discussion, and the last section the conclusions.
2. DATA Twenty-five months of NOAA-AVHRR imagery have been used for this study. Records between 4th April 2001 and 31st May 2003 have been considered. Images have been processed at the Department of Oceanography and Fisheries at the University of the Azores (DOP/UAç), using an interactive satellite data analysis software package (TeraScan® 3.1, developed by Seaspace Corporation). With the exception of the navigation that is manual, all imagery processes have been automated25. SST values have been obtained implementing the MCSST algorithm26. Figure 2: HAZO Image processing The resultant SST images were remapped statistics to a cylindrical projection occupying a total area from 34º 39.15’ N to 42º 40.30’ N and from 33º 44.08’ W to 23º 30.32’ W. The pixel resolution obtained was 1.1132 km x 1.1132 km. As part of imagery post-processing, remnant cloudiness has been removed inputting threshold values to SST 8-day temperature histograms. Threshold values are defined using the mean of 8-day SST histograms plus or minus 3 times their standard deviation24. During the study period, 7083 images have been recorded among which 3410 have been processed up to obtainment of geophysical data (Fig.2). The remaining has been rejected mainly due to bad recording and/or coverage, and navigation problems. A total of 1056, 342, 1410, and 602 images from NOAA-12, -14, -16, and –17 have been analysed, respectively. SeaWiFS imagery recorded by HAZO station has been processed at DOP/UAç using SeaDAS, the SeaWiFS data analysis system. In that case, it was possible to automate all imagery processes 25. A total of 668 SeaWiFS images have been recorded during the study period and processed successfully (cf. Fig. 2).
CTD measurements, conducted by DOP/UAç, were carried out in the vicinity of São Miguel and Santa Maria islands during the annual demersal fisheries cruise survey onboard R/V “Arquipélago”. In the scope of this study, three measurement stations have been considered (Fig. 3): mpr1 (5 May 2003), on a fisheries bank to the southwest of São Miguel island, smi1 (10 May 2003) to the south of São Miguel and sma1 (8 May 2003). To understand local SST variability, zonal and meridional wind monthly averages output from the NOAA NCEP/NCAR Reanalysis Project27 have been used.
Figure 3: Location of in situ CTD stations (mpr1, sm1, and sma1). The two points (ref1 and ref2) represent SST and SeaWiFS chosen imagery locations. The bathymetry of the area (obtained from ETOPO 2) has been superimposed.
3. METHODOLOGY The percentage of cloud cover on weekly SST averages in the Azores was evaluated. Nighttime and daytime were processed separately. The same test was performed for SeaWiFS data. In this last case, the impact of cloud cover can be amplified due to the lower number of images used to compute the chl a composites. Then, 8day SST and chl a averages were performed. SST monthly averages were also calculated. Based on 8-day SST composites, meridional and zonal gradients were obtained. Main SST pattern orientations were extracted from monthly averages to allow improved visualization of SST gradients. Recent studies demonstrated that overlaying physical oceanographic and fishery data involves potential applications in fisheries monitoring28,29,30. Fig. 4 shows the location of surveys carried out onboard 24 Azorean tuna fisheries
Figure 4: Compilation of 24 tuna fisheries vessel positioning during 5 successive POPA fisheries campaigns from 1998 to 2002
vessels during fisheries campaigns realized from 1998 to 2002 (data obtained from the Program for the Observation of Tuna Fisheries of the Azores - POPA). Fishing areas are mainly concentrated around the islands and banks close to the islands. Therefore, it is important to carry out oceanographic research studies on the three groups of islands (cf. Fig. 1) simultaneously. For this purpose, mean values of SST and chl a were computed for each group (Occidental, Central, and Oriental) using 8-day composites and further compared. CTD observations were accomplished using an SBE 911plus CTD equipped with Beckman/YSI oxygen sensor and Chelsea Fluorometer. Temperature, salinity, oxygen and chl a concentration were profiled. All sensors were recently calibrated at Sea Bird Electronics, USA. The SEASOFT Software provided by Sea Bird Electronics was used to convert and analyse data. Only data pertained to downcasts were used. The data were screened for spikes and erroneous values (data quality control program) and were removed from further analysis. The filtered data were binned in 1m bins. When a measured value for a particular depth was missing, the gap was filled with linear trends. The trends were constructed as a linear least square fit approximation of the data for the depth segment with the size 3 times of that of the gap. The interpolated data were smoothed with a Savitzky-Golay second order filter with a window size twice of the maximum gap size. This is designed to filter the small spikes, which were not fished by the data quality control program and to smooth the raptures at the interpolated gap-region borders. The later result from the interpolation method used. The smoothed profiles were used for construction of the vertical profiles. CTD profiles obtained at the Oriental group (cf. Fig. 3) provide information on small scale SST variability. This was compared with concurrent SST and chl a satellite-derived measurements. Based on 8-day averages, mean temperature and chl a concentration were obtained from 3x3 pixel boxes centred on the CTD profile stations. Two far-field stations were chosen about 80 km and 40 km to the west of station smi1 (ref1) and sma1 (ref2) (cf. Fig. 3). SST anomalies were then calculated by subtracting each station (coastal and corresponding far-field) 3x3 pixel box average from the mean obtained by averaging the 3x3 pixel boxes from the two stations. The same method was applied to derive chl a anomalies. Both satellite-estimated anomalies were compared.
4. RESULTS AND DISCUSSION 4.1 Cloud cover On average, 55.4, 70.6, and 66.3 % of the pixels should represent the water surface in nighttime AVHRR, daytime AVHRR, and SeaWiFS 8-day composites, respectively. These average values integrate large temporal variations (Fig. 5). Results of this test show that the percentage of NOAAAVHRR cloud-free pixels is higher during daytime. HowFigure 5: Percentage of cloud-free pixels in SeaWiFS and ever, nighttime data seems to nighttime/daytime AVHRR 8-day composites be more adapted to study SST variability in the Azores. In fact, and as demonstrated in a previous study31, the mean SST difference between daytime and nighttime imagery changes along the year, with biases lower than 0.2 ºC during wintertime and higher than 1 ºC during summer. Two processes explain day and nighttime differences: the skin effect 32 and the diurnal warming33. Thermal sensors measure the temperature of the skin of the ocean. This molecular boundary layer, less than 1 mm thick, is responsible for heat flux between the ocean and the atmosphere. Because the net flux is generally towards the atmosphere the skin is generally cooler than the bulk temperature. The second process expresses the warming of the sea surface due to solar insulation. The skin effect influences the SST at both night and day and the diurnal warming at day only, which explains the differences observed between nighttime and daytime SST values. Therefore, it appears more relevant to use nighttime data to study SST variability along the year. Furthermore, the effect of diurnal warming is maximum in low wind conditions. With increasing wind, surface cooling is observed33,34,35. Long term wind observations in the Azores region show that the winds are on average stronger to the west of the archipelago36, and therefore, daytime SST values are certainly influenced by wind patterns. Thus, although SST nighttime data are continuously negatively biased in comparison with
bulk SST values34, they are certainly more constant throughout time and space. Therefore nighttime imagery will be used in this study. 4.2 Temperature gradients Meridional and zonal averages (Fig. 6) show a distinct seasonal cycle and gradients typical of mid latitudes. On average, meridional gradients are more pronounced than zonal gradients. Seasonal warming of the waters is clearly evidenced on zonal averages. Isotherms start moving to the north in April-May. Maximum temperatures (24 ºC) are found to the south of the study area in August and September. During summer 2001, the warmest temperatures are found up to about 40 ºN. This upper layer warming was attributed to barring of the internal water structure by formation of the seasonal thermocline2,37. Then, isotherms start retreating in November. The coolest waters are found to the north. More intense cooling is observed in 2002. Waters with temperature as low as 12 ºC persist during several months, whilst they appear only in February in 2001. Also, isotherm 12 ºC reaches 41 ºN during the winter of 2002/2003. It remains in the vicinity of 42 ºN in 2001/2002. However, the isotherm 14 ºC is limited at 36 ºN during both years. As a direct influence of the Gulf Stream, the warmest waters are found to the west, as seen on the meridional SST averages. Waters with temperature higher than 24 ºC extend to 29 ºW. Increased warming is observed to the east in 2001 and to the west in 2002. In 2002, an intensification of the cooling is observed to the west coincident with the northern cooling observed on the meridional gradients. The existence of NS and EW gradients with intensity varying with space and time implies that the three groups of islands display characteristic behaviours.
Figure 6: Meridional and zonal averages obtained from 8-day SST composites.
4.3 SST patterns orientation SST general pattern orientation was deduced from SST monthly averages. Four principal orientations were defined (Fig. 7). Orientation 1 (NW-SE) is the most represented (Table 1). It is regularly observed in spring and autumn. In this configuration, most part of the time, a pool of cooler water surrounds the archipelago. The Central and Oriental groups appear to be the most affected by this cooling. Orientation 2 is relatively close to orientation 1, except to the extremities where the gradient displacement shows that waters are warmed to the north and to the south. This warming, observed only during summer months, affects strongly the Occidental group and is of short duration. It can be attributed to the Gulf Stream which propagates into this region being limited to the east by the Mid Atlantic Ridge. Orientation 3 (WNW-ESE) is also regularly observed (cf Table 1), mainly in winter and autumn and once
Figure 7: Orientation of main SST patterns displayed on the bathymetric chart of the Azores
during spring. In this configuration the gradients are almost orientated N-S, with cold waters to the north and warm waters to the south. Finally, in June and July 2001, SW-NE gradients were found. They imply an important warming of the Oriental group, whilst the effect of the Gulf Stream is little perceptible and does not affect the SST gradients. This configuration probably originates from a northward displacement of the Subtropical Gyre and/or Azores current. This may be explained by a strong negative NAO index found during winter and spring 2001 (Table 2). Table 1: Temporal distribution of main SST pattern orientations
Orientation 1 (NW-SE) Feb 03 Mar 03 Apr 01, 02, 03 May 01, 02 Sep 01, 02 Nov 01, 02 Dec 01, 02
Orientation 2 (N-S/NW-SE) Jul 02 Aug 01, 02
Orientation 3 (E-W) Jan 02, 03 Feb 02 Mar 02 Jun 02 Oct 02, 03
4.4 SST and chl a variability for the three groups The three groups of islands show a distinct seasonal cycle and gradients typical of mid latitude (Fig. 8). However, due to changing gradient orientations, they display specificities that regularly happened with time, or that are, in the contrary, singular. For instance, the warming of the Occidental group is evidenced during the 2 summers covered by the study. This warming persists during 3 and 6 weeks in 2001 and 2002, respectively. During this warm episode, the mean temperature difference between the Occidental and Oriental group is of the order of 0.8 ºC. Contrarily, the warming of the Oriental group, corresponding to pattern orientation 4 (cf. Fig. 7), was observed only in spring 2001. It involves mean temperature differences with the other groups of the order of 1.5 ºC and this warming event persisted during almost 7 weeks. In winter 2001/2002, the coolest waters are encountered in the Central group (corresponding to pattern orientation 3). In 2002/2003, both the Central and the Oriental group display temperatures of about 14.5 ºC, whilst temperatures of the Occidental group are about 1 ºC higher. In the last case, patterns were orientated NW-SE in February and March showing wide influence of the Gulf Stream during this period. The strong positive NAO index observed during spring and summer 2002 (versus negative in spring 2001 and slightly positive in summer 2001) (cf. Table 2) may ex-
Orientation 4 (SW-NE) June 01 July 01
Table 2: Seasonal average of NAO index (adapted from NOAA, http://www.cpc.ncep.noaa.gov/products/pr ecip/CWlink/pna/nao_index.html)
Year Winter
Spring Summer Autumn
2000
0.201
0.3147
0.2433
2001 -0.6877 -0.9937
0.0303
0.2117
2002 -0.3407
0.485
0.135
-0.948
2003 -0.7033
0.206
Figure 8: SST value seasonality for the three groups of islands
Figure 9: Variation of SST and chl a with time.
plain the difference between SST in winter 2001/2002 and 2002/2003, respectively. The influence of the SST on chl a distribution has already been widely discussed in the literature. In the case of the Azores, SST and chl a display a high correlation (Fig. 9). Two peaks of chl a are observed. The principal appears during the spring and a secondary peak, less visible, is perceptible in autumn, this distribution being typical of mid latitudes38. In the Occidental group the spring bloom is less intensive during 2003 than during the first two years. Comparison of chl a time series based on 8-day SeaWiFS composites show that the three groups are characterised by very different biomass concentration during the spring bloom (Fig. 10). The Occidental group presents the highest chlorophyll concentrations in 2001 and 2002. In 2002, the bloom appears early in the beginning of April and affects the Occidental group first. Then the biomass starts to increase in the two other groups (about 2-3 weeks later). In 2002, the lowest concentrations are found in the Oriental group. In 2003, and following a warm winter to the west (cf. Fig. 8), the bloom starts early April in both Central and Oriental group, and about 4 weeks later in the Occidental group. 4.5 Local scale variability: example of the Oriental group Among the 3 groups of islands, results clearly show varying trends of both chl a concentration and SST values. Within each group, small scale variability also appears. CTD measurements carried out in the Oriental groups reveal that stations located at a few tens of kilometres from each other present different physical and biological characteristics (Fig. 11). The station mpr1 located near Mar da Prata Bank shows a pronounced seasonal thermo-, halo-, and picnocline at 50 m depth. The southern near-island stations smi1 and sma1 have very shallow thermocline at 10-15 m. This uplifted thermocline may be linked to local upwelling. Wind data for the Oriental group27 show that during the second part of April and beginning of May there are WNW winds persisting in the region with a mean speed of 5-7 m s-1. Those can give rise to upwelling on the southern parts of São Miguel and Santa Maria islands. In fact, the vertical profiles of chl a (cf. Fig. 11, B) show chlorophyll maximums closer to the surface on São Miguel and Santa Maria islands, than Mar da Prata bank. This supports the idea of upwelling with surface nutrient
Figure 10: Chl a concentration seasonality for the three groups of islands
A
mpr1 sma1 smi1
B
mpr1 sma1 smi1
Figure 11: In situ temperature (A) and Chl a (B) profiles
enrichment on the southern coasts of these islands. Similar events were searched for in AVHRR and SeaWiFS imagery. SST and chl a 8-day anomalies between, on one hand, smi1 and ref1 and, on the other hand, sma1 and ref2, have been plotted on Figs. 12, 13, 14 and 15, respectively. An SST negative anomaly appears at smi1 location in May 2003 (julian day 846) (cf. Fig. 12), i.e. at the time of the CTD measurements. An SST anomaly at smi1 also persists from end of June 2002 (julian day 534) to beginning of August 2002 (julian day 582). During this period, NW winds with wind speeds between 3 and 4 m s-1 have been reported. Both upwelling events are clearly associated to a positive biomass anomaly (cf Fig. 13). However, a positive biomass anomaly starts mid May 2002 (julian day 478), earlier than the SST negative anomaly. Winds in May 2002 were from NE. Figs. 14 and 15 show SST and chl a anomalies between sma1 and ref2. Negative SST anomalies are found in three occasions at station sma1 (cf. Fig. 14). The first one happened between the end of June 2001 (julian day 174) and mid August (julian day 230) 2001. July 2001 was characterized by strong NW winds. This cooling was not observed to the south of São Miguel. It is accompanied by a slight positive anomaly of the biomass starting beginning of August (julian day 214) (cf. Fig. 15). The second negative anomaly at sma1 persists from beginning of April to mid June 2002 (julian days 454 to 526). This event happens before the cooling event observed in 2002 to the south of São Miguel island. About two weeks after a negative SST anomaly appeared on the imagery, a slight positive biomass can be seen to the south of Santa Maria island. Finally, the cooling event observed in May 2003 (julian day 782) to the south of São Miguel was observed as early as April to the south of Santa Maria. The later shows a positive biomass anomaly in May 2003 (julian day 851).
Fig. 12: SST anomaly between stations smi1 and ref1. Boxes highlight negative anomalies close to São Miguel island.
Fig. 13: Chl a anomaly between stations smi1 and ref1. Boxes highlight negative anomalies close to São Miguel island.
Fig. 14: SST anomaly between stations sma1 and ref2. Boxes highlight negative anomalies close to Santa Maria island.
5. CONCLUSIONS Using 1.1 km resolution imagery from NOAA-12, -14, -16, and -17 recorded from April 2001 to May 2003 by HAZO station, 8-day and monthly images were calculated to investigate AVHRRderived SST distributions and associated dominant space and time scales around the Azores archipelago. Despite the large and frequent cloud cover found over the Azores region, HAZO
Fig. 15: Chl a anomaly between stations sma1 and ref2. Boxes highlight negative anomalies close to Santa Maria island.
satellite images clearly demonstrated their capability to study mesoscale variability in this region of the ocean. Results from the eight-day average images together with zonal and meridional averages show a distinct seasonal cycle with higher and lower surface temperature values found during the summer and winter months, respectively. Four typical SST gradient patterns were identified. The most general NW-SE and E-W are typically found during spring/autumn and winter months, respectively. On the Occidental group a tilt of the NW-SE pattern towards N-S is observed during summertime that is attributed to seasonal northward propagation of the Gulf Stream. A less common pattern (SW-NE) was found during June and July 2001. This was attributed to a northward displacement of the Subtropical Gyre and/or Azores current, probably linked to NAO inter-annual variability. On a local scale, wind-induced upwelling events are suggested on the imagery. These were confirmed using coincident CTD data. Upwelling on the southern side of São Miguel and Santa Maria islands (Oriental group) is observed near the coast, during W-NW and NW winds. Upwelled waters bring nutrients to the surface as shown by increased chlorophyll a concentrations observed on SeaWiFS imagery. Chl a concentration vary inversely with temperature although some time lag exists between cooling of surface waters and increase in phytoplankton biomass. Upwellings events are short lived, although their impact should necessarily be important for fisheries in the Azores. This study provides an important insight towards ocean mesoscale variability in the Azores region using ocean color and SST data.
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