Progress in Oceanography 165 (2018) 123–144

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Progress in Oceanography

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Upper ocean hydrology of the Northern Humboldt Current System at T seasonal, interannual and interdecadal scales ⁎ Carmen Gradosa, , Alexis Chaigneaub, Vincent Echevinc, Noel Domingueza a Instituto del MAR de PErú (IMARPE), Callao, Peru b Laboratoire d'Études en Géophysique et Océanographie Spatiale (LEGOS), Université de Toulouse, CNES, CNRS, IRD, UPS, Toulouse, France c Laboratoire d'Océanographie et de Climatologie: Expérimentation et Analyse Numérique (LOCEAN), LOCEAN-IPSL, IRD/CNRS/Sorbonnes Universités (UPMC)/MNHN, UMR 7159, Paris, France

ARTICLE INFO ABSTRACT

Keywords: Since the 1960s, the Instituto del Mar del Perú (IMARPE) collected tens of thousands of in-situ temperature and North Humboldt Current System salinity profiles in the Northern Humboldt Current System (NHCS). In this study, we blend this unique database Hydrology with the historical in-situ profiles available from the World Ocean Database for the period 1960–2014 and apply Water masses a four-dimensional interpolation scheme to construct a seasonal climatology of temperature and salinity of the Seasonal variations NHCS. The resulting interpolated temperature and salinity fields are gridded at a high spatial resolution Geostrophic currents (0.1° × 0.1° in latitude/longitude) between the surface and 1000 m depth, providing a detailed view of the ENSO Interdecadal variability hydrology and geostrophic circulation of this region. In particular, the mean distribution and characteristics of the main water-masses in the upper ocean of the NHCS are described, as well as their seasonal variations be- tween austral summer and winter. The coastal upwelling region is well documented due to the increased data density along 3 highlighted cross-shore vertical sections off Paita (∼5°S), Chimbote (∼9°S) and San Juan (∼16.5°S). The large and long-term database also allowed us, through a composite analysis, to investigate the impact of the eastern Pacific El Niño and La Niña events on the NHCS hydrology. On average, during these periods, large temperature ( ± 3–4 °C) and salinity ( ± 0.1–0.2) anomalies are observed, impacting the water column of the coastal ocean off Peru down to 100–200 m depth. At 100 km from the coast, these anomalies are associated with a maximum deepening (shoaling, respectively) of the thermocline of 60 m (25 m) during com- posite El Niño (La Niña) events. At interdecadal scale, a similar approach reveals sea-surface temperature var- iations of ± 0.5°C, associated with a deepening (shoaling) of the thermocline of 5–10 m during warm (cold) periods.

1. Introduction Oceanic Current (POC) (e.g., Gunther, 1936; Wyrtki, 1965, 1966). The POC transports in the surface layers relatively cold (T < 13 °C) and The Northern Humboldt Current System (NHCS: 70–90°W; 0–20°S), fresh (S < 34.3) Eastern South Pacific Intermediate Water (ESPIW) mainly located off the Peruvian coast, corresponds to the northern part from Southern Chile towards the NHCS (Schneider et al., 2003). North of the Peru-Chile upwelling system and is the region where water ex- of ∼20°S the POC progressively veers westward feeding the South change between the equatorial and subtropical Eastern South Pacific Equatorial Current (SEC) (Chaigneau and Pizarro, 2005), and the occurs (Fig. 1). In the NHCS, the circulation is rather complex and ESPIW, which mixes with the warmer (T > 20 °C) and saltier transports water-masses (WM) of distinct origins with specific tem- (S > 35.1) Subtropical Surface Water (STSW), spreads northwestward perature (T) and salinity (S) ranges (Fig. 1). In the first ∼1000 m of the in the lower limit of the thermocline forming a lens of low-salinity water column the main WM characteristics and large-scale circulation water (Schneider et al., 2003). can be summarized as follows (e.g., Wyrtki, 1964, 1965, 1966, 1967; Second, persistent alongshore winds (Bakun and Nelson, 1991) Stevenson, 1970; Kessler, 2006; Fiedler and Talley, 2006; see Fig. 1). favor a year-round near-coastal upwelling of cold, nutrient-enriched First, the atmospheric South Pacific subtropical anticyclone drives subsurface waters (T < 19°C and S < 35.0) resulting in high rates of an upper layer subtropical gyre (e.g., Strub et al., 1998, 2013), of which productivity and the most productive eastern boundary upwelling the eastern branch in the NHCS is associated with the equatorward Peru ecosystem in terms of small pelagic fish (e.g., Chavez et al., 2008; Fréon

⁎ Corresponding author at: Instituto del Mar del Perú IMARPE, Esquina Gamarra y General Valle S/N, Chucuito, Callao, Peru. E-mail address: [email protected] (C. Grados). https://doi.org/10.1016/j.pocean.2018.05.005 Received 6 October 2016; Received in revised form 19 May 2018; Accepted 22 May 2018 Available online 24 May 2018 0079-6611/ © 2018 Published by Elsevier Ltd. C. Grados et al. Progress in Oceanography 165 (2018) 123–144

(Karstensen et al., 2008; Paulmier and Ruiz-Pino, 2008; Chavez and Messié, 2009; Llanillo et al., 2013). Below the ESSW, the relatively cold EPCC TSW (T ∼ 5 °C) and fresh (34.3 < S < 34.5) AAIW spreads northward at 0 SEC ESW intermediate depths (e.g., Tsuchiya and Talley, 1998). 200 PCC EUC The mean WM characteristics and large-scale circulation patterns 400 ESSW SEC vary seasonally according to atmospheric heat flux variations (e.g., 600 PCUC Takahashi, 2005) and wind forcing variations associated with the po- POC 35.5

Depth (m) 800 sition and strength of the large-scale atmospheric anticyclone (e.g., 35

STSW Salinity 1000 ESSW Strub et al., 1998, 2013). However, one of the key features of the NHCS ESPIW 34.5 0 AAIW is its connectivity to the basin-wide equatorial dynamics that strongly 34 impacts the hydrography, coastal currents and productivity of the −5 33.5 eastern South Pacific at intraseasonal (e.g., Belmadani et al., 2012; Illig Latitude (°S) AAIW −10 −70 et al., 2014; Echevin et al., 2014), seasonal (e.g., Echevin et al., 2011) −75 and interannual scales (e.g., Barber and Chavez, 1983; Chavez et al., −15 −80 2003; Colas et al., 2008; Montes et al., 2011, Espinoza-Morriberón −85 ff −20 −90 Longitude (°W) et al., 2017). Among these di erent timescales, the most important phenomenon is probably the well-known El Niño Southern Oscillation Fig. 1. Schematic of circulation and main water-masses of the NHCS. Color (ENSO), which is the strongest mode of natural climate fluctuation at shading corresponds to salinity (S) from the CSIRO Atlas of Regional Seas interannual scales (Philander, 1990; Wallace et al., 1998; Timmermann (CARS2009) and dashed thin line corresponds to S = 34.7. Nomenclature of the et al., 1999). Although ENSO can manifest as central Pacific or eastern water-masses : TSW: Tropical Surface Water; ESW: Equatorial Surface Water; Pacific events, the NHCS is mainly affected by “canonical” eastern Pa- STSW: Subtropical Surface Water; ESSW: Equatorial Subsurface Water; ESPIW: cific events (Ashok et al., 2007; Kao and Yu, 2009; Takahashi et al., Eastern South Pacific Intermediate Water; AAIW: Antarctic Intermediate Water. Nomenclature of the surface (thick solid lines) and subsurface (thick dashed 2011; Vimont et al., 2014). Indeed, during the warm (El Niño) and cold fi lines) currents: EPCC: Ecuador-Peru Coastal Current; PCC: Peru Coastal Current; (La Niña) phases of eastern Paci c ENSO events, the physical and SEC: South Equatorial Current; POC: Peru Oceanic Current; EUC: Equatorial biogeochemical characteristics of the NHCS as well as the large-scale Undercurrent; PCUC: Peru-Chile Undercurrent. circulation (Colas et al., 2008; Montes et al., 2011) and the whole ecosystem have been shown to be strongly impacted (Barber and et al., 2009). The upwelled Peruvian coastal water (pcw1) and the Chavez, 1983, 1986; Chavez et al., 2003; Jahncke et al., 2004). At in- fi offshore STSW form a strong cross-shore density gradient that forces, terdecadal scales, the Paci c Decadal Oscillation (PDO) (Mantua et al., fi through geostrophic adjustment, the equatorward Peru Coastal Current 1997), often described as a long-lived El Niño-like pattern of Paci c (PCC) (e.g., Strub et al., 1998). climate variability (Zhang et al., 1997; Mantua and Hare, 2002), seems Third, in the Northern region of the NHCS the upwelled pcw is to also impact the NHCS as shown from multidecadal variations in the advected northwestward by the PCC and SEC, and mixes with the water productivity and main ecosystem components (Chavez et al., 2003; upwelled from the Equatorial Undercurrent (EUC) along the equator. It Thomas et al., 2009; Bertrand et al., 2011; Gosselin et al., 2013; Guinez results in a cold tongue extending from Northern Peru to the west of et al., 2014). Galapagos Islands associated with Equatorial Surface Water (ESW) and Due to these peculiar characteristics, the NHCS has spurred in- characterized by relatively low temperature (T < 21°C) and high tensive multidisciplinary studies through national and international salinity (S > 34.5) (Wyrtki, 1966; Fiedler and Talley, 2006). cooperative programs, mainly initiated in the 1960s with the beginning Fourth, North of ∼2–3°S and nearshore is found the relatively warm of a long-term oceanographic monitoring program conducted by the – (T > 23°C) and fresh (S < 33.5) Tropical Surface Water (TSW) that IMARPE. It consists of repeated ship surveys (4 5 per year) that occupy results from an excess of precipitation beneath the Inter Tropical several hydrographic cross-shore sections between the Peruvian coast ff fi Convergence Zone and the Gulf of Panama, and freshwater input from and as far as 200 nm o shore, covering the main upwelling and shery large Colombian and Ecuadorian rivers (Enfield, 1976; Strub et al., areas of the NHCS. This program, which has been improved regularly 1998; Fiedler and Talley, 2006; Poveda and Mesa, 2000). This TSW can throughout the years, aims to provide to the Peruvian government the fi be transported poleward along the north Peruvian coast by the surface scienti c basis for the rational exploitation and sustainability of the fi Ecuador-Peru Coastal Current (Chaigneau et al., 2013), or north- Peruvian shery resources. Although the in-situ temperature and sali- westward by the surface Ecuador Coastal Current close to the Ecua- nity data acquired during these surveys have been used to depict some dorian coast (not shown in Fig. 1)(Collins et al., 2013). The strong physical characteristics of the near-coastal WM in the NHCS, the results temperature and salinity gradients separating TSW from ESW are ob- were mainly published in national journals (e.g., IMARPE, 1965; Zuta served in the first ∼100 m of the water column form the Equatorial and Guillén, 1970; Zuta and Urquizo, 1972; Urquizo et al., 1987; Front (Pak and Zaneveld, 1974; Fiedler and Talley, 2006). Morón, 2011) and an integrated and comprehensive study based on all In the subsurface layers (∼100–1000 m depth), the NHCS en- available information is still lacking. Besides, existing global climatol- compasses two main water masses, namely the Equatorial Subsurface ogies, such as the World Ocean Atlas (Locarnini et al., 2010; Antonov Water (ESSW) and the Antarctic Intermediate Water (AAIW). ESSW et al., 2010) and the CSIRO Atlas of Regional Seas (CARS2009) (T < 17 °C and S > 35), which is transported poleward along the (Ridgway et al., 2002; Dunn and Ridgway, 2002) have not incorporated continental slope by the Peru Chile Undercurrent (PCUC) (Silva and the nearshore in-situ data collected during IMARPE cruises after the Neshyba, 1979; Chaigneau et al., 2013) is the main source of the up- 1980s; in addition, the coarser resolution (e.g., 0.5° × 0.5°) of these welled pcw driving the high productivity of this ecosystem (Brockmann products does not fully resolve coastal features, particularly in upwel- et al., 1980; Huyer et al., 1987; Toggweiler et al., 1991; Albert et al., ling regions as the NHCS. 2010). Furthermore, the offshore spreading of the ESSW between Thus, the main goal of this study is to obtain a high-resolution ∼100 m and ∼600 m depth forms the core of the most intense and (0.1° × 0.1°) seasonal climatology of the hydrology and WM char- shallower subsurface oxygen minimum zone of the World Ocean acteristics in the NHCS by merging the IMARPE original dataset with other in-situ observations from available international cruises or au- tonomous floats (see Section 2). The resulting NHCS regional clima- 1 Note that pcw is noted as lower-case letters because it is not sensu stricto a WM tology provides a detailed description of the mean and seasonal varia- (Tomczak, 1999) since it results from the mixing of ESSW and STSW (Morón, 2011). tions of the physical properties (temperature, salinity and density) and

124 C. Grados et al. Progress in Oceanography 165 (2018) 123–144 geostrophic circulation along the Peruvian coast. This product may and CTD. Originally, the total number of T and S profiles is of serve as a reference for multidisciplinary studies or to validate regional ∼233,000 and ∼130,000 respectively, with around 30–35% of the model simulations. Furthermore, given the good spatio-temporal cov- profiles acquired by IMARPE (Table 1) during more than 370 oceano- erage of the blended database, the mean impact of the interannual graphic surveys along the Peruvian coast (Fig. 2a and e). Quality con- ENSO events and interdecadal warm and cold phases on the WM trol reduced the final number of stations by ∼15–20% (see Section 2.2 characteristics of the NHCS are also investigated. While the obtained and Table 1). results are of interest for the oceanographic community they can also be The Peruvian near-coastal region has been extensively sampled due relevant for regional climate studies, since the surface WM encountered to the IMARPE long-term observational program that continues to in the near-coastal regions of the NHCS tend to stabilize the marine permanently occupy cross-shore sections to sample the main upwelling boundary layer leading to the largest and most persistent stratocumulus cells and major fishery areas (Fig. 2a–b and e–f). While the nearshore deck in the world (Klein and Hartmann, 1993; Wood et al., 2010; Zheng region has been mainly sampled with CTD and OSD, the eastern tropical et al., 2011). Pacific has also been considerably sampled with XBT and MBT probes from international surveys and commercial ships (Fig. 2d). PFL data are rather homogeneously distributed in the offshore ocean, whereas 2. Data and methods moorings’ data were mainly acquired in speci fic sites of the equatorial Pacific as part of the Tropical Atmosphere Ocean (TAO) project (Fig. 2c 2.1. Data sources and g). The regions with fewer observations are the southwestern part of the NHCS and the Ecuadorian and Colombian near-coastal ocean. The vertical T and S profiles used to compute the climatology were The temporal distribution of the number of T/S data is shown in gathered from (i) the World Ocean Database (WOD, http://www.nodc. Fig. 3. Between 1960 and 2014 the number of yearly T profiles varied noaa.gov/OC5/WOD/pr_wod.html) of the National Oceanographic typically between 1000 and 3000 (Fig. 3a). However, in 1996 and early Data Center (NODC) and (ii) the IMARPE. T and S profiles collected 2000s, the number of observations strongly increased in the region, between January of 1960 and December of 2014 in the region ex- with more than 6000 temperature casts realized during 2001–2002. tending from 30°S to 10°N and from 70°W to 100°W were used (Fig. 2). This relatively high number of profiles at the beginning of the 2000s is Vertical profiles from the WOD were acquired by several types of in- due to an increase of IMARPE coastal cruises and associated OSD during struments (Johnson et al., 2006): high-resolution Conductivity-Tem- this period. One may wonder whether this increased number of data perature Depth (CTD), Ocean Station Data (OSD) collected using re- may distort or not the interpolated temperature fields of the clima- versing thermometers as well as bottles and low-resolution CTD, tology. However, a climatology built after artificially removing 2/3 of Moored Buoys (MRB), Profiling Floats (PFL) mainly associated with the the vertical profiles acquired during 2000–2002 shows very small international Argo program (http://www.argo.net), Expendable Bath- temperature differences with the climatology constructed from the ythermograph (XBT) and Mechanical Bathythermograph (MBT). In whole dataset (not shown). The strongest differences of ± 0.1°C were contrast, IMARPE hydrographic profiles were acquired only from OSD

(a) (b) (c) (d)

(e) (f) (g) (h)

Fig. 2. Spatial distribution of the vertical temperature (upper panel) and salinity (lower panel) profiles by sensors and databases. a) Temperature profiles from the IMARPE database, acquired by Conductivity-Temperature-Depth (CTD, in red) probes and Ocean Station Data (OSD, in black). b) Same as (a) but for the WOD. c) Same as (b) but from Moored Buoys (MRB, in red) and Profiling floats (PFL, in black). d) Same as (c) but for mechanical and expendable bathythermographs (MBT in red and XBT in black, respectively). e–g) Same as (a–c) but for salinity profiles. h) The blue line shows the alongshore section located at 100 km from the coast and along which the seawater properties are depicted in Figs. 6, 12 and 14, whereas red lines correspond to the 3 cross-shore sections off Paita, Chimbote and San-Juan (SJ) presented in Figs. 7–9. Dashed black lines in (a–h) delimit the region where the regional climatology of the NHCS is computed. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

125 C. Grados et al. Progress in Oceanography 165 (2018) 123–144

Table 1 Number of temperature and salinity profiles (NP) available after each processing step.

Instrument Original NP NP after elimination of bad NP after elimination of NP after quality NP after vertical NP after removing profiles duplicates control interpolation outliers

Temperature OSD_WOD 36,083 34,613 24,355 24,355 24,192 22,931 PFL_WOD 29,200 29,045 28,966 28,963 28,917 28,885 CTD_WOD 7633 7392 7203 7203 7201 7169 XBT_WOD 27,664 27,237 27,083 27,083 27,082 27,064 MBT_WOD 18,867 18,286 17,152 17,141 17,135 17,120 MRB_WOD 43,878 43,878 43,855 43,855 43,855 43,817 OSD_IMARPE 57,606 54,279 46,553 46,549 44,433 42,992 CTD_IMARPE 12,394 12,134 4712 4710 4635 4565 TOTAL 233,325 226,864 199,879 199,859 197,450 194,543

Salinity OSD_WOD 25,016 24,109 17,102 17,102 16,935 16,161 PFL_WOD 27,270 27,114 27,039 27,039 26,999 26,932 CTD_WOD 7871 7622 7440 7440 7438 7412 MRB_WOD 24,108 24,108 24,106 24,106 24,106 23,379 OSD_IMARPE 33,536 31,016 27,610 27,606 26,357 24,859 CTD_IMARPE 12,375 12,116 4695 4694 4622 4441 TOTAL 130,176 126,085 107,992 107,987 106,457 103,184

0

Temperature Number of Data 6000 (a) (b) 4000 200 3000 4000 400 2000 600

2000 Depth (m) 800 1000 Number of Data 0 1000 0 0 2500 (c) Salinity (d) Number of Data 3000 200 2000

400 1500 2000 600 1000

1000 Depth (m) 800 500 Number of Data 0 1000 0 1960 1970 1980 1990 2000 2010 JFMAMJJASOND Year Month

Fig. 3. Temporal distribution of the temperature and salinity profiles shown in Fig. 2. a, c) Yearly evolution of the number of temperature (a) and salinity (c) profiles. b, d) Seasonal evolution of the number of temperature (b) and salinity (d) profiles as a function of depth.

observed in the surface layer. (ΔZlim = 0.5 × ZBATHY for ZBATHY <50m; ΔZlim = 0.4 × ZBATHY for The number of monthly temperature data decreases with depth, 50 m < ZBATHY < 200 m; ΔZlim = 0.3 × ZBATHY for 200 m < from ∼4000–5000 in the upper layers, to less than 500 below ZBATHY < 500 m; ΔZlim = 0.2 × ZBATHY for 500 m < 600–800 m depth (Fig. 3b). Seasonally, the number of vertical profiles ZBATHY < 1000 m; ΔZlim = 0.1 × ZBATHY for ZBATHY > 1000 m). is slightly bimodal with less observations collected during January, Around 2–3% of the original dataset was thus discarded due to erro- June and July (Fig. 3b). During these months, less international and neous positions (Table 1). Peruvian coastal cruises were realized reducing the number of CTD and OSD casts. The temporal and vertical distributions of the number of S 2.2.2. Duplicate detection data show similar patterns than those obtained for T, but the number of Many duplicate profiles have been identified and removed. Because S observations is typically reduced by a factor of ∼2(Fig. 3c and d). of diverse data sources and inconsistency in format, our definition of duplicate profiles extended to any profile acquired at the same time 2.2. Data preprocessing (year, month and day, as more precise information was not always available) and within a 1 km radial distance of another profile. When 2.2.1. Selection of profiles identical casts (two or more casts from the same location and date) Profiles erroneously located inland (on continent or islands) were were identified but had a different number of values, we only retained identified and systematically discarded. Casts were also rejected when the profile containing the higher number of observations. Duplicates their indicated bottom depths (ZCAST) were clearly greater than the were found between the individual data sources (WOD and IMARPE) local bathymetry (ZBATHY) estimated from ETOPO01 (Amante and but also within them due to the presence of some casts realized si- Eakins, 2009). When ZCAST was deeper than ZBATHY, we only retained multaneously using distinct instruments (e.g. CTD and Niskin bottles). profiles for which the depth difference (ΔZ=ZCAST − ZBATHY > 0) did The percentages of profiles removed by this procedure is relatively high not exceed a given limit (ΔZlim) that depends on the local bathymetry (12–14%, see Table 1) and mainly concerned OSD stations, due to the

126 C. Grados et al. Progress in Oceanography 165 (2018) 123–144 fact that the WOD includes most of the data acquired by IMARPE before procedure. the 1980s. 2.3. Four-dimensional interpolation method 2.2.3. Quality control fi The rst quality control consisted in eliminating obvious erroneous T and S profiles were horizontally and vertically interpolated using data that fell outside the large temperature and salinity ranges given by the four-dimensional interpolation algorithm developed by Ridgway fi Johnson et al. (2006) for the equatorial and coastal-equatorial Paci c et al. (2002). At each grid point of the given three-dimensional grid, the extending from 10°S to 10°N. We assumed that the broad temperature analysis consists of: (i) weight the irregularly distributed observations and salinity ranges given by Johnson et al. (2006) also hold between and (ii) interpolate these weighted data by projecting them onto 10°S and 30°S (see values in their Appendices 9.1 and 9.2). Secondly, quadratic functions of spatial coordinates while simultaneously fitting fi depth inversions or depth duplications were detected in some pro les, annual and semiannual harmonics. These spatio-temporal functions are fi fl particularly for casts acquired by pro ling oats. In such casts, data fitted to the data using weighted least squares giving more weight to responsible of the depth inversions were removed and when depth observations near the considered grid point and less weight to data fi duplications occurred, only the rst value was retained. This procedure further away. The weighting of the data points also allows for the in- removed between 10,000 and 15,000 individual observations at spe- fluence of both bathymetry and land barriers. As mentioned by fi ci c depths, which represent less than 0.1% of the total available T/S Ridgway et al. (2002) and Dunn and Ridgway (2002), including the data. impact of the local bathymetry in the weighting function of the ob- servations allows, in particular, obtaining more realistic near-coastal 2.2.4. Vertical interpolation properties and cross-shore gradients (e.g., Fig. 4). Finally, in order to All vertical profiles were interpolated onto a set of 55 standard reduce the effects of discontinuities in data distributions between ad- depth levels between the surface and 1000 m depth, with an increased jacent vertical levels, observations on adjacent vertical levels are also resolution in the mixed-layer and seasonal thermocline (Table 2). We considered in the interpolation scheme. These adjacent observations used the vertical interpolation scheme described in Boyer et al. (2002), have a reduced weight in the interpolation than the observations lo- which is mainly based on the weighted parabolic algorithm developed cated at the vertical level of the considered grid point. Readers inter- by Reiniger and Ross (1968). The latter is widely used by the scientific ested in more detail regarding the interpolation algorithm are invited to community (e.g. Fichaut et al., 2003; Locarnini et al., 2006; Ridgway refer to Ridgway et al. (2002) and Dunn and Ridgway (2002). Similar et al., 2002; Troupin et al., 2010) following the recommendation of interpolation schemes were used to reconstruct mean ocean fields at UNESCO (1991). Note that this interpolation algorithm does not ex- regional (Fiedler and Talley, 2006; Lourey et al., 2006) and global trapolate the profiles below their maximum depth. As some hydro- scales (e.g., Roemmich and Gilson, 2009). graphic stations have a low number of discrete data on the vertical, they The interpolation grid used to map the T/S fields extends from 20°S could not be vertically interpolated at standard levels. This resulted in to the equator and from the coast to 90°W (region delimited by the an additional discard of ∼1% of the original profiles (Table 1). black dashed lines in Fig. 2) with a uniform spatial resolution of 0.1° × 0.1° in longitude-latitude and 55 standard levels between the 2.2.5. Outlier detection surface and 1000 m depth (Table 2). At each grid point, we selected all

Outliers and extreme values may have substantial influence on in- observations within a minimum search radius (Rmin = 200 km). If the terpolated gridded fields, leading to distortion and possibly inaccurate number of observations was less than Nmin = 400, the search radius was mean values. In order to detect outliers in the T and S vertically-in- expanded until reaching Nmin observations. The maximum radius ex- terpolated profiles, a uniform spatial grid of 1°×1° was considered. For pansion was of ∼450 km both in temperature and salinity. It was found each grid point and each of the 55 standard levels, all T or S observa- below 500 m depth and in the northeast of the study area off Ecuador tions located within a search radius of ∼200 km from the grid point where density data is relatively low. In contrast, the number of ob-

(see Section 2.3) were gathered and outliers were detected as any value servations within Rmin largely exceeded Nmin in near-coastal regions off that falls outside ± 3 standard deviations around the mean. This out- Peru were data density is high (Fig. 2). As described above, locally liers detection method is based on the characteristics of a normal dis- weighted least squares fitting was applied on the selected observations tribution for which 99.87% of the data fall within ± 3 standard de- at each grid point. viations around the mean. Therefore, under the assumption that T and S Although it is available for each month, the T/S and density (ρ) are normally distributed, removing the values that occur only in 0.13% regional climatology of the NHCS is here presented at seasonal scales of all cases does not appear too conservative. Identified outliers were for two contrasted seasons, namely austral summer (i.e. January to removed from the datasets and the process was repeated, providing a March average) and winter (i.e. July to September average). tighter statistics. About 1.5% (3%, respectively) of the temperature Geostrophic currents were computed from both alongshore and cross- (salinity) observations were discarded by this outlier detection shore sections of the density field using the thermal wind equation and

Table 2 The 55 standard level depths of the regional climatology.

Standard level Standard depth Standard level Standard depth Standard level Standard depth Standard level Standard depth Standard level Standard depth (m) (m) (m) (m) (m)

1 0 12 90 23 180 34 275 45 500 2 5 13 100 24 190 35 280 46 550 3 10 14 110 25 200 36 290 47 600 4 20 15 120 26 210 37 300 48 650 5 30 16 125 27 220 38 325 49 700 6 40 17 130 28 225 39 350 50 750 7 50 18 140 29 230 40 375 51 800 8 60 19 150 30 240 41 400 52 850 9 70 20 160 31 250 42 425 53 900 10 75 21 170 32 260 43 450 54 950 11 80 22 175 33 270 44 475 55 1000

127 C. Grados et al. Progress in Oceanography 165 (2018) 123–144

0 22.6 Temperature (a) 34.4 Salinity (b) Density (c) Summer 34.5 Summer 34.6 Summer 34.7 34.8 22.8 4°S Paita Paita Paita

34.9

8°S 35.1 35 23 23.2 26 Chimbote Chimbote Chimbote 35.2 23.4 LIMA LIMA LIMA 12°S 25 35.3 23.6 21 35.5 24.6 Pisco Pisco Pisco 22 24.2 24 23.8 35.4 35.1 San Juan San Juan 24 San Juan 16°S 35.2 24.2 23 35 23 24 24 23.8 22 24.4 20°S

0 24 23 (d) (e) (f) Temperature Salinity 24.2 Density 22 34.7 34.8 Winter Winter Winter 24.4 34.9 35 24.6 4°S Paita Paita Paita 21 22

8°S 35.1 24.4 25 Chimbote 35.2 Chimbote 24.8 Chimbote

25.2 LIMA LIMA LIMA 12°S 35.5 20 35.3 25.4 Pisco Pisco Pisco 19 San Juan 35.4 San Juan San Juan 16°S 18 17 25.6 35 35.1

20°S 90°W 86°W 82°W 78°W 74°W 70°W 86°W 82°W 78°W 74°W 70°W 86°W 82°W 78°W 74°W 70°W

15 16 17 18 19 20 21 22 23 24 25 26 33.5 34 34.5 35 35.5 36 25.325.2222 625.52525.42423 Temperature (°C) Salinity Density (kg m-3)

− Fig. 4. Mean sea surface temperature (SST in °C, left panel), salinity (SSS, middle panel) and density anomaly (σ in kg m 3, right panel) for austral summer (January- − March, upper panel) and winter (July-September, lower panel) conditions. Contour intervals are of 1°C in temperature, 0.1 in salinity and 0.2 kg m 3 in density. a reference level of no-motion at 1000 m depth. The reference level is austral summer and winter (Fig. 4). Close to the coast, SST displays a generally chosen as deep as possible in order to capture the whole well-marked nearshore front, stronger in summer (∼4 °C over baroclinic contribution to the motion field. As the regional climatology ∼100–200 km, Fig. 4a) than in winter (∼2 °C over ∼100–200 km, computed here only extended to 1000 m depth, this depth was con- Fig. 4d). This near-coastal thermal front separates the cold upwelled sidered as the level of no-motion. Indeed, at this depth, the large-scale pcw, that have a quite homogeneous salinity of 34.9–35.1, from the circulation inferred from Argo floats shows that the average speeds of warmer and saltier offshore STSW, that have a maximum SST of − the currents are less than 2 cm s 1 (Ollitrault and Colin de Verdière, 23–25°C and SSS of 35.5 in the NHCS (Fig. 4a–b and d–e). The hor- 2014). Over the continental slope and shelf, where the bathymetry is izontal SST gradient between the offshore STSW and the pcw is stronger shallower than 1000 m, dynamic height was first computed relative to in summer (Fig. 4a and d) due to the stronger solar flux and reduced the seafloor. Then, the contribution of the missing part of the water latent heat flux in this season (e.g. Takahashi, 2005). Also during column, between the seafloor and 1000 m depth, was added by opti- winter, the cross-shore salinity front is less marked (∼0.2 over mally interpolating the nearby climatological profiles that extend to ∼300 km) than during summer (∼0.3 over ∼300 km), and waters with 1000 m depth (Rubio et al., 2009). Three different interpolation salinity less than 35.2 have a much larger extent, likely due to the methods were tested (e.g. (bi-) linear interpolation, nearest neighbor, enhanced horizontal and vertical mixing due to stronger winds in optimal interpolation). Although the results were not drastically dif- winter. The coolest pcw (17°C in winter and 16°C in summer) is ob- ferent between the 3 methods, we preferred to retain the optimal in- served close to the coast in the intense upwelling cell located between terpolation that gave a slightly better agreement with the current Pisco (14°S) and San Juan (16°S), driven by intensified alongshore structures observed along the coast from Acoustic Doppler Current winds in this region (Bakun and Mendelssohn, 1989; Strub et al, 1998). Profiler (ADCP) data (Chaigneau et al., 2013). Note that, before the This upwelling cell is somewhat geographically separated from the computation of the geostrophic currents, the density field has been upwelling that occurs north of 12°S. filtered spatially to remove residual spatial scales smaller than 100 km, North of 4–5°S, the equatorial front separates relatively cold and the typical Rossby radius in the study region (Chelton et al., 1998). saline ESW from the relatively warm and fresh TSW (Wyrtki, 1966, 1981; Fiedler and Talley, 2006). This front extends from ∼4°S at the coast to Galapagos Islands at 90°W (Fig. 4a–b and d–e) and has a clearer 3. Results signature in SSS than in SST. South of this front, the relatively cold ESW results from the mixing of near-coastal water advected by the PCC and 3.1. Surface temperature, salinity and density fields SEC with water from the equatorial upwelling (Wyrtki, 1966, 1981; Fiedler and Talley, 2006). This ESW forms the equatorial cold tongue General hydrographic features of the NHCS are illustrated by the which contrasts with the warmer and low salinity TSW found North of mean seasonal patterns of SST, SSS and sea-surface density (SSρ)in

128 C. Grados et al. Progress in Oceanography 165 (2018) 123–144 the Equatorial Front (Fig. 4a–b and d–e). In summer, the equatorial that has temperatures of 4–7 °C and salinity of 34.5–34.6. The local front does not have a clear signature in SST although the cold tongue salinity minimum associated with the AAIW is progressively eroded as can still be discerned between Paita and the Galapagos (Fig. 4a). The this WM moves northward due to the weak but continuous mixing with equatorial front is also more marked in SSS during winter, likely due to surrounding saltier WMs. the enhanced northward and cross-shore advection by the PCC and SEC The WM T/S ranges given above correspond to the WM character- of relatively saline coastal waters during this season, associated with istics in the NHCS and can differ from those found in previous published the reinforcement and northward displacement of the large-scale at- regional studies (Table 3). Not surprisingly, the TSW described in this mospheric subtropical anticyclone (Strub et al., 1998). Considering the analysis is relatively saltier and cooler than in other studies dealing 34.6 isohaline as the southern edge of the equatorial front (Fig. 4b and with larger scales (Wyrtki, 1966; Enfield, 1976; Fiedler and Talley, e), this front exhibits a meridional displacement of 2–3° in latitude 2006; Strub et al., 1998). This is expected, because TSW is mainly between summer and winter. The low salinity TSW are formed in re- formed by an excess of precipitation in the Panama-Colombia region gions of intense precipitations northward of the NHCS (e.g., Poveda and further North and is advected towards the NHCS progressively mixing Mesa, 2000), and eventual riverine inflow in summer may also con- with saltier and colder underlying and surrounding water. ESW and tribute to the freshening of coastal water as observed near the Gulf of STSW are also saltier off Peru than in the definitions provided by pre- Guayaquil (∼4°S) where the Guayas River flows into the Pacific ocean. vious studies (Wyrtki, 1966; Enfield, 1976; Fiedler and Talley, 2006; In southern Peru near 18°–20°S, the presence of a coastal dome of Strub et al., 1998). ESSW exhibits large T/S ranges and is saltier and maximum SST (T ∼ 24 °C) centered at 73°W and 19°S is mainly ob- warmer off Peru than previously described off Northern Chile by Strub served during summer (Fig. 4a). This SST structure, that has been also et al. (1998). South of the NHCS, lower salinity values are expected due identified in model simulations (Takahashi, 2005; Toniazzo et al., to mixing of ESSW with fresher waters (ESPIW and AAIW), as it is 2010) and in-situ data from the Northern Chile region (Blanco et al., transported poleward by the PCUC. In contrast, the salinity of ESPIW is 2001), is associated with an anticyclonic circulation reaching ∼200 m higher (S ∼ 34.8) than values encountered off Chile (S < 34.3) by depth during summer (Blanco et al., 2001). The separation of this near- Schneider et al. (2003). The increased salinity of ESPIW off Peru is due coastal dome from the warm STSW located offshore and north of 15°S to its progressive mixing along its path with the saltier STSW and ESSW may be due to the offshore advection of relatively cold upwelled waters found immediately above and below, respectively. Subpycnocline originating from the intense Pisco-San Juan coastal upwelling near AAIW is also saltier (S ∼ 34.5) off Peru than west of the HCS 14°S–16°S (Takahashi, 2005). (S < 34.5) near 88°W (Fiedler and Talley, 2006). It is worth men- The large-scale structure and seasonal changes of the surface density tioning that the WM characteristics presented in Table 3 were sampled field (Fig. 4c–f) are very close to those of surface temperature, which during different time periods, depending on the study considered. Thus, clearly dominates over the effect of salinity. In contrast, at small scale in the observed discrepancies can also be partly attributable to the large- the northern NHCS (0–4°S), density gradients are controlled by the scale, low frequency variability. strong surface salinity gradient associated with the equatorial front. The surface geostrophic current in the coastal band of ∼100–200 km is 3.3. Alongshore thermohaline distribution likely to be more intense in summer than in winter due to the increased cross-shore density gradient during summer. However, this may not be Variations of temperature, salinity and cross-shore geostrophic ve- true offshore due to the strong baroclinic contribution of subsurface locity along a section located at 100 km from the coast (blue solid line density gradients in the thermal wind relationship, as it was verified in in Fig. 2h) for summer and winter are presented in Fig. 6. The ap- a regional model simulation (fi gures not shown, Echevin et al., 2014). proximate location of the main WMs is also indicated. In this figure, the grey shading between 7°S and 11°S indicates the presence of the Peru shelf which is shallower than 1000 m at 100 km from the coast. The 3.2. T/S diagram and main water-masses characteristics vertical structure of temperature displays a well-marked thermocline near ∼30–50 m depth (Fig. 6a and d), more marked in summer In order to provide a description of the main water-masses found in (Fig. 6a) due to an increased surface heating by higher surface heat the NHCS, mean T/S diagrams obtained averaging all climatological fluxes and weaker alongshore winds (Bakun and Mendelssohn, 1989; fi pro les located within 5 distinct subregions are shown in Fig. 5. In the Bakun and Nelson, 1991). North of 4°S, the stratification is dominated surface layer, 4 main water masses are found: in the Northern part of by the fresh TSW (Fig. 6b and e). At the base of the permanent ther- fi the NHCS (green pro le in Fig. 5), TSW exhibits typical mean salinities mocline, the 15 °C isotherm rises from 100 m depth near the equator to – – of 33.5 34.4 and temperatures of 23.5 24.5 °C; South of the Equatorial 40 m at 20°S, due to the mixing of the warm and saline ESSW, trans- fi Front (purple pro le in Fig. 5), the ESW is cooler (20 °C < T < 24 °C) ported poleward by the PCUC, with cold and fresher waters of Antarctic ff and saltier (34.6 < S < 35) than the TSW. Further south and o shore origin (AAIW and ESPIW), flowing equatorward. The wind-driven up- 2 fi – (red pro le in Fig. 5), STSW has salinities of 35.4 35.5 and tempera- welling may partly drive the poleward shoaling of the 15 °C isotherm as – tures of 19 23.5 °C. The pcw, that occupies the upper layer of the near- it begins near 4°S where the upwelling-favorable wind intensifies (see fi coastal region (blue pro le in Fig. 5) but is not considered sensu-stricto Fig. 1 in Dewitte et al., 2011). However the alongshore wind reaches its as a WM, exhibits the coldest temperatures (15 °C < T < 18.5 °C) and maximum south of Pisco (14°S–15°S) and decreases south of this lati- ∼ an almost constant salinity of 35. tude (Dewitte et al., 2011), whereas the 15 °C isotherm continues to In a greater density range corresponding to the subsurface layers, shoal (Fig. 6a and d). It is thus unlikely that the coastal upwelling ESSW is found below the ESW and TSW, and is transported towards the would be responsible for the shoaling south of 14°S. Peruvian coast by the eastward Tsushiya jets and Equatorial The salinity structure (Fig. 6b and e) remains largely unchanged Undercurrent (e.g., Montes et al., 2010; see Fig. 1). In the NHCS, ESSW seasonally off the Central coast, with maximum values larger than 35.1 – – has typical temperatures of 8 14 °C and salinities of 34.6 35 (Fig. 5). In between ∼8°S and 12°S in the first 25 m, associated with the nearshore the southern part of the NHCS, the ESSW is surmounted by the warmer proximity of STSW (see also Fig. 4). The presence of fresh waters from ∼ fi (12 °C < T < 14 °C) and fresher (S 34.8) ESPIW (cyan pro le in equatorial origin and its mixing with STSW is evidenced as far south as Fig. 5) that enters the NHCS from the southern boundary (Schneider 7°S. North of this latitude, ESW and fresh TSW are slightly displaced to et al., 2003; see Fig. 1). At depths below the ESSW is found the AAIW the south during summer (Fig. 6b) likely due to advection from the EPCC during this season, although the reinforcement of the EPCC 2 For interpretation of color in Fig. 5, the reader is referred to the web version of this during summer was not clearly evidenced by Chaigneau et al. (2013). article. In subsurface layers, a core of maximum salinity (S > 35) deepens

129 C. Grados et al. Progress in Oceanography 165 (2018) 123–144

22.5 Fig. 5. Mean T/S diagrams in the areas 24 marked in colors in the inset. These diagrams TSW illustrates the T/S characteristics of the main 23 water-masses found in the NHCS. For each 22 ESW STSW area, filled dots represent the mean properties 23.5 at the 55 vertical levels of the climatology 20 24 whereas vertical and horizontal lines indicate the temperature and salinity standard devia- tions, respectively. Nomenclature of the 24.5 18 water-masses: TSW: Tropical Surface Water; ESW: Equatorial Surface Water; STSW: 25 Subtropical Surface Water; ESSW: Equatorial 16 Subsurface Water; ESPIW: Eastern South 25.5 Pacific Intermediate Water; AAIW: Antarctic 14 Intermediate Water. 26ESPIW 12 Temperature (°C) 26.5

10 ESSW 27 8 27.5 6 AAIW 28 4 33.5 34 34.5 35 35.5 Salinity

Table 3 Temperature (T, in °C) and salinity (S) ranges of the main water-masses found in the NHCS between the surface and 1000 m depth. Nomenclature of the water- masses: TSW: Tropical Surface Water; ESW: Equatorial Surface Water; STSW: Subtropical Surface Water; ESSW: Equatorial Subsurface Water; ESPIW: Eastern South Pacific Intermediate Water; AAIW: Antarctic Intermediate Water. The published works considered here are: FT2006: Fiedler and Talley (2006); STR1998: Strub et al. (1998); SCH2003: Schneider et al. (2003); BLA2001: Blanco et al. (2001); ZUT1970: Zuta and Guillén (1970); MOR2011: Morón (2011).

Water mass This study FT2006 STR1998a SCH2003 BLA2001a ZUT1970a MOR2011

TSW T 23.5–24.5 > 25 > 25 ––– – S 33.5–34.4 < 34 < 33.5 –– < 33.8 < 34

ESW T 20–24 < 25 20–24 ––– – S 34.6–35.0 > 34 33.5–35.0 –– < 34.8 –

STSW T 19–23.5 – 20–28 – 17–25 > 17 – S > 35.4 > 35 > 35 – 34.9–35.7 > 35.1 35.1–35.6

ESSW T 8–14 13–20 8.5–10.5 – 11–13 13–15 – S 34.6–35.0 34.3–35.5 34.4–34.8 – 34.7–34.9 34.9–35.1 –

ESPIW T 12–14 – 11.5–14.5 11–13 11–14 13–15 – S 34.8 – 34.1–34.8 34.1–34.3 34.3–34.8 34.6–34.8 –

AAIW T 4–74–10 5.5 – 6–84–7 – S 34.5–34.6 < 34.5 34.3–34.5 – > 34.5 34.45–34.6 –

a Note that these authors referred to ESPIW as Subantarctic Water. equatorward and connects the STSW to the deeper layers 14°S. Most are present during summer and winter, but generally in- (∼100–200 m) of the equatorial region. This subsurface maximum tensify and extend deeper in winter (∼800 m, Fig. 6f) than in summer salinity layer is probably a mixing between the ESSW transported by the (∼600 m, Fig. 6c). The strongest onshore jet, which has a velocity of − EUC and the STSW that subducts below the lighter ESW and TSW as ∼10 cm s 1 between the surface and 300 m depth, is located near − also shown in Fig. 1 at 90°W. Below 200 m depth, the ESSW is trans- 2–3°S, north of an intense (> 10 cm s 1 between the surface and 600 m ported southward by the PCUC and is progressively mixed with the depth) westward jet located near 3–4°S. Although these near-equatorial fresher ESPIW, of which the low salinity core (S < 34.9) is centered latitudes are close to the validity limit for the geostrophic computation, near 70–100 m depth between 20°S and 16°S. Between 600 m and the nearshore eastward jets are likely related to the eastward flowing 1000 m depth, a thick layer of AAIW is evidenced, of which the upper Southern Subsurface Countercurrents previously observed near 4°S and − limit deepens northward. As already mentioned, the salinity minimum 6°S with similar velocities of 5–10 cm s 1 (e.g., Tsuchiya, 1975; Montes − (S < 34.5) observed in the southern NHCS in the AAIW core is also et al., 2010). Alternating eastward and westward jets of 5–10 cm 1 progressively eroded during its northward spreading. have also been revealed near the NHCS from model simulations, alti- The alongshore section of cross-shore geostrophic flow displays al- metry data and Argo floats trajectories (e.g. Maximenko et al., 2005, ternating onshore (eastward) and offshore (westward) jets (Fig. 6c and 2008; Cravatte et al., 2012; Belmadani et al., 2017). f). Onshore jets are located near 2–3°S, between 4°S and 12°S, and near A portion of the water transported eastward by the jets is likely to be

130 C. Grados et al. Progress in Oceanography 165 (2018) 123–144

STSW ESW TSW 0 35.1 17 25.8 16 ESPIW 35 26

15 Jan. - Feb. March 100 14 26.2 13 34.9 200 12 26.4 Summer 34.8 300 11 ESSW 26.6 10 400 34.7 26.8 9

Depth (m) 8 34.6 27 600 7 34.5 6 27.2 800 AAIW 5 (a) (b) (c) 1000 0 18 17 18 18 17 35.1 25.8 25.6 25.4 15 16 35 26 14 26.2 100 July - Aug. - Sep. 13 34.9 26.4 200 12

34.8 Winter 300 11 26.6 10 34.7 400 9 26.8 8

Depth (m) 34.6 27 600 7 6 34.5 27.2 800 5 (d) (e) (f) 1000 20°S 16°S 12°S 8°S 4°S 0 16°S 12°S 8°S 4°S 0 16°S 12°S 8°S 4°S 0 Latitude Latitude Latitude

4681012141618202224 33.8 34 34.2 34.4 34.6 34.8 35 35.2 -10 -8 -6-4 -2 0 2 4 6 8 10 Temperature (°C) Salinity Geostrophic Velocity (cm s-1)

− Fig. 6. Mean alongshore vertical section of temperature (in °C, left panel), salinity (middle panel) and cross-shore geostrophic velocity (in cm s 1, right panel) for austral summer (January-March, upper panel) and winter (July-September, lower panel) conditions. In Figures (c) and (f), isocontours of σ (σ = ρ − 1000 where ρ is − the density) are superimposed (in kg m 3). This alongshore section is located at 100 km from the coast (see Fig. 2h). Contour intervals are of 1 °C in temperature, 0.05 − in salinity and 0.2 kg m 3 in density. Nomenclature of the water-masses indicated in b) TSW: Tropical Surface Water; ESW: Equatorial Surface Water; STSW: Subtropical Surface Water; ESSW: Equatorial Subsurface Water; ESPIW : Eastern South Pacific Intermediate Water; AAIW: Antarctic Intermediate Water. upwelled and subsequently transported offshore in the surface Ekman variability and the southward displacements of the equatorial front; (ii) layer by the Ekman current. At 100 km from the coast, the maximum off Chimbote (9°S), a region characterized by an intense primary pro- source water depth (Hupw) of the upwelled coastal water can be roughly ductivity and enriched fisheries (Rojas de Mendiola, 1981) and a large estimated as follows. Assuming that the total cross-shore transport continental shelf; (iii) off San Juan (16°S), where the shelf narrows and through the alongshore section should be close to zero (under the as- the most intense coastal upwelling takes place. sumption that the transport between the alongshore section and the adjacent coast does not change), Hupw corresponds to the depth above ff which the vertically integrated cross-shore geostrophic transport com- 3.4.1. O Paita (5°S) pensates the westward Ekman transport. The Ekman transport, esti- The temperature section in front of Paita displays large seasonal mated from the SCOW wind stress climatology (Risien and Chelton, variations in the upper 100 m, where the thermocline and halocline are 2008) through the entire alongshore section, is of ∼1.5 Sv and 2.7 Sv in found (Fig. 7). During summer in the surface layer, temperatures vary summer and winter, respectively. Integrating the cross-shore geos- from 21 °C close to the coast to 24 °C at 300 km from the coast, with a – trophic current vertically and horizontally over the extent of the strong seasonal thermocline centered at 30 40 m depth (Fig. 7a). alongshore section, we obtain a cross-shore geostrophic transport that During this season, a weak near-coastal upwelling occurs (as indicated by the shoaling of the isotherms towards the coast) but the coastal re- equals the Ekman transport for Hupw ∼ 50 m and 110 m in summer and fl winter, respectively (not shown). These estimates are consistent with gion is mostly under the in uence of fresh ESW with salinities lower ∼ ff results from high resolution model simulations: they are close to the than 34.8 between the coast and 170 km o shore (Fig. 7b). This WM source water depth of 30–100 m obtained using virtual Lagrangian overlies the saltier STSW and ESSW forming a strong halocline at ∼ – floats (e.g. Fig. 10 in Espinoza-Morriberón et al., 2017) and to the 30 50 m depth (Fig. 7b). In contrast in winter, the wind-forced maximum depth (∼150 m) of simulated nearshore upward velocity (see coastal upwelling is more active as evidenced by the stronger shoaling of the isotherms towards the coast (Fig. 7d) and the vertical tempera- Fig. 4e in Colas et al., 2012). Note that our estimates of Hupw would slightly differ using other wind products to compute the Ekman trans- ture gradients within the seasonal thermocline are weaker. Waters with temperature of 17–18 °C upwell at the coast and the depth of the source port, but our aim here was to give an order of magnitude of Hupw. waters 300 km from the coast is ∼70 m depth, assuming a constant temperature of the source water parcels during their transit towards the 3.4. Cross-shore hydrographic properties coast. During winter, the surface salinity increases, varying from ∼35 at the coast to 35.1 farther than 200 km from the coast, and the seasonal Three cross-shore sections, from the coast to 300 km offshore, were halocline is much less marked (Fig. 7e). This salinity increase is related selected to contrast the main hydrographic features and alongshore to the reinforcement and northward displacement of the subtropical geostrophic flow in the near-coastal NHCS. As shown in Fig. 2h, these 3 anticyclone during winter that enhances the northward advection of sections were performed (i) off Paita (5°S), near the northern boundary saline coastal waters during this season and displaces northward the of the coastal upwelling system which is influenced by the equatorial equatorial front by 2–3° (see Section 3.1).

131 C. Grados et al. Progress in Oceanography 165 (2018) 123–144

0 17 16 35 25.8 100 15 26 Jan. - Feb. March 35 14 26.2 200 Summer 13 34.9 26.4 300 12 11 34.8 26.6 400 10 9 34.7 26.8 Depth (m) 8 27 600 7 34.6 6 27.2 800 5 (a) (b) (c) 1000 0 19 18 17 35 25 25.2 16 25.8 100 15 26 July - Aug. - Sep. 35 14 26.2 200

13 Winter 34.9 26.4 300 12 11 34.8 26.6 10 400 9 34.7 26.8 Depth (m) 8 27 600 7 34.6 6 27.2 800 5 (d) (e) (f) 1000 300 250 200 150 100 50 0 300 250 200 150 1000 5 0 300 250 200 150 1000 5 0 Distance from coast (km) Distance from coast (km) Distance from coast (km)

5 10 15 20 25 34.4 34.6 34.8 35 35.2 -10 -6 -2 2 6 10 Temperature (°C) Salinity Geostrophic Velocity (cm s-1)

− Fig. 7. Mean cross-shore vertical section of temperature (in °C, left panel), salinity (middle panel) and along-shore geostrophic velocity (in cm s 1, right panel) for austral summer (January-March, upper panel) and winter (July-September, lower panel) conditions front off Paita (5°S, see Fig. 2 h). In Figures (c) and (f), iso- − − contours of σ (σ = ρ − 1000 where ρ is the density) are superimposed (in kg m 3). Contour intervals are of 1 °C in temperature, 0.05 in salinity and 0.2 kg m 3 in density.

Between 50 m and 100 m depth, we note the presence of a salinity water at the coast and the warming of surface offshore STSW by en- maximum (S > 35), more clearly observed in winter (Fig. 7b and e). In hanced solar heat flux (see also Fig. 4). this season, the stronger alongshore winds enhance the surface current Highly saline waters (S > 35.1) are found in the upper 75 m farther that advects north-westward the relatively fresh ESW. This more in- than 75 km from the coast in summer (Fig. 8b) but reach the coast in tense coastal upwelling could be associated with an enhanced subsur- winter (Fig. 8c). As for the Paita section at 5°S, the presence of these face (∼30–50 m depth) compensating flow of saltier water towards the saline waters near the coast might be due to the onshore subsurface coast. In contrast during summer, the wind intensity decreases, hence current which is reinforced during winter by the stronger winds the surface offshore and subsurface onshore compensating flow are (Fig. 6f). Near the surface during summer, the tilt of the isohalines likely to be less intense. Furthermore, ESW is advected cross-shore by likely indicates the offshore advection of relatively fresher water over Ekman transport with little change of properties due to the reduced the layer of saline waters by the Ekman current (Fig. 8b). Below 300 m vertical mixing in summer. This may explain the erosion of the sub- depth, the variability of the hydrological structure is weak. surface salinity maximum observed during this season (Fig. 7b). How- The signature of the PCUC, which can be traced by the deepening of ever, this erosion is at odds with the geostrophic onshore current the 12–14 °C isotherms between 100 km and the continental shelf, is computed at 5°S, which is slightly stronger in summer (Fig. 6c) than in well evidenced in the cross-shore sections of alongshore geostrophic winter (Fig. 6f). We will discuss this point in Section 4. velocity (Fig. 8c and f). The geostrophic part of the PCUC is located off The alongshore geostrophic flow is equatorward between the sur- the slope, and its vertical extent reaches ∼600 m depth in this latitude − − face and ∼40 m depth and poleward below within 200 km from the range. The maximum poleward velocity (∼3–4cms 1 and 4–5cms 1 coast during summer (Fig. 7c). The poleward current, which corre- in summer and winter, respectively) is encountered between 100 and sponds to the shoaling Peru-Chile Undercurrent, is more intense in 200 m depth. Furthermore, equatorward flow is found on the shelf summer than in winter as it nearly disappears. The offshore equator- (Fig. 8c and f). It intensifies during winter due to the stronger surface ward flow between 150 m and 800 m depth corresponds to the Peru thermal front associated with the enhanced upwelling (Fig. 4a). This Oceanic Current (Chaigneau et al., 2013). Overall, the summer along- contrasts with the results of Chaigneau et al. (2013) who found that shore circulation is quite similar with the annual-mean, alongshore- near 9°S the PCUC exhibits a maximum southward velocity of − averaged (3–6°S) circulation computed from ADCP data (see Fig. 5a in ∼8cms 1 at the shelf edge with a core extending down to ∼350 m Chaigneau et al., 2013). depth.

3.4.2. Off Chimbote (9°S) 3.4.3. Off San Juan (16.5°S) Off the central region of Peru, large cross-shore changes in tem- San Juan is located into the most intense Peruvian upwelling cell perature and salinity are found in the upper 75 m (Fig. 8). The onshore associated with a wind intensification near 15°S–16°S (e.g., Dewitte shoaling of the isotherms and isohalines takes place above ∼100 m et al., 2011). In this region, 15 °C water reaches the surface during depth within ∼50–75 km of the coast (Fig. 8a–d). The cross-shore winter (Fig. 9d), while further North at Chimbote and Paita the up- thermal gradient is stronger in summer due to the upwelling of cold welled water has typical temperature of 16–17 °C (Figs. 7d and 8d). The

132 C. Grados et al. Progress in Oceanography 165 (2018) 123–144

0 35.2 35.1 16 25.8

15 Jan. - Feb. March 26 100 14 26.2 35 13 200 26.4 Summer

300 12 34.9 26.6 400 11 34.8 10 26.8

Depth (m) 9 34.7 8 27 600 7 27.2 800 6 34.6 5 (a) (b) (c) 1000 0 25.2 18 17 16 35.2 25.4 35.1 25.8 15 26

100 July - Aug. - Sep. 14 26.2 35 200 13 26.4 Winter 300 12 34.9 26.6 10 34.8 400 9 26.8 34.7 Depth (m) 8 27 600 7 6 27.2 800 34.6 5 (d) (e) (f) 1000 300 250 200 150 100 50 0 300 250 200 150 1000 5 0 300 250 200 150 1000 5 0 Distance from coast (km) Distance from coast (km) Distance from coast (km)

5 10 15 20 25 34.4 34.6 34.8 35 35.2 -10 -6 -2 2 6 10 Temperature (°C) Salinity Geostrophic Velocity (cm s-1)

Fig. 8. Same as Fig. 7 but front off Chimbote (9°S, see Fig. 2h). shape of the isotherms suggests that upwelling is slightly deeper at this Guillén (1970) also mentioned that the upwelling takes place above latitude than further North, and occurs above ∼80 m depth (Fig. 9a and 70 m within 40–80 km from the coast. d), which is consistent with the alongshore-mean upwelling depth At the coast, the reduced salinity (S < 35) probably results from

(Hupw ∼ 50–110 m) estimated in Section 3.3. Note that Zuta and the upwelling and mixing of (i) the relatively salty ESSW (S > 34.9)

0 35 15 14 34.9 26

26.2 Jan. - Feb. March 100 13 34.9 26.4 200 12 Summer

11 34.8 26.6 300 10 26.8 400 9 34.7

Depth (m) 8 34.6 27 600 7 6 27.2 800 5 (a) (b) (c) 1000 0 35.1 35 17 16 25.6 25.8 15 14 26 100 26.2 13 July - Aug. - Sep. 34.9 26.4 200 12 Winter 11 34.8 26.6 300 10 400 9 34.7 26.8

Depth (m) 8 34.6 27 600 7 6 27.2 800 5 (d) (e) (f) 1000 300 250 200 150 100 50 0 300 250 200 150 1000 5 0 300 250 200 150 1000 5 0 Distance from coast (km) Distance from coast (km) Distance from coast (km)

5 10 15 20 25 34.4 34.6 34.8 35 35.2 -10 -6 -2 2 6 10 Temperature (°C) Salinity Geostrophic Velocity (cm s-1)

Fig. 9. Same as Fig. 5 but front off San-Juan (16.5°S).

133 C. Grados et al. Progress in Oceanography 165 (2018) 123–144 that flows southward within the PCUC and (ii) the ESPIW characterized the Peruvian coastal region (ENFEN, 2012; Takahashi et al., 2014; by a minimum salinity (S < 34.9) at ∼70–130 m depth (Fig. 9b and e). Table 4). Depending on the maximum SST anomalies reached for at These results are consistent with Zuta and Guillén (1970) who men- least 3 consecutive months during these events, El Niño and La Niña tioned that the source water are mostly ESSW coming from the North in periods can be further classified into several intensity categories winter, and ESPIW (also called Subantarctic Water at that time) coming (Takahashi et al., 2014; see Table 4). from the South during the weaker summer upwelling. The surface Fig. 10 depicts the ICEN time series (black solid line) where El Niño stratification (vertical gradient of temperature and salinity) is much events of moderate, strong and extraordinary intensity (red shaded − stronger in summer (e.g., vertical T gradient of ∼−0.04 °C m 1 in the areas) and La Niña events of moderate and strong intensity (blue − seasonal thermocline) than in winter (T gradient of ∼−0.02 °C m 1). shaded areas) are highlighted. The occurring years of these events are The subsurface (100–200 m depth) lens of high salinity (S ∼ 34.9) lo- indicated in Table 4 as well as the peak months when the maximum SST cated ∼150 km from the coast and separated from the coastal vein of anomalies were observed. A similar filtered SST anomaly time series ESSW during summer could be the signature of coastal ESSW trapped was computed from our in-situ temperature database averaging all within offshore propagating subsurface anticyclonic eddies (e.g. profiles located within the Peruvian near-coastal region, between 4°S Chaigneau et al., 2011; Colas et al., 2012; Stramma et al., 2013; and 18°S and from the coast to 100 km offshore. Although the spatio- Thomsen et al., 2016). Such mesoscale features could be formed by temporal distribution of the in-situ temperature profiles does not allows instabilities of the nearshore current system, as the San Juan section is us for a robust comparison, this SST time series (gray solid line in embedded in a region of high mesoscale activity (Chaigneau et al., Fig. 10a) is well correlated with the ICEN (r2 = 0.80) indicating that 2008). At greater depths, seasonal variations are weak and the AAIW any El Niño or La Niña event identified from the ICEN did effectively found below ∼500 m depth is slightly fresher than further North as also impact the SST in the Peruvian coast with a similar or even stronger noted in Fig. 6. amplitude. Between ∼100 and 250 m depth, the splitting of isotherms towards the coast, indicative of the PCUC, is very weak and mainly observed in 3.5.2. Impact of El Niño and La Niña events on the thermohaline structure summer (Fig. 9a, d). This is confirmed by the subsurface geostrophic In order to depict the mean impacts of ENSO events in the NHCS, flow which is very weak within 100 km from the coast (Fig. 9c and f) composite climatologies were thus computed for neutral, El Niño-like and only present during summer, between 100 and 300 km from the (from moderate to extreme) and La Niña-like (from moderate to strong) coast and between 50 and 600 m depth. This poleward flow which periods identified from the ICEN. Although each ENSO event differs in − corresponds to the PCUC is weaker (∼4cms 1) and located further terms of SST/SSS and exhibits a unique geographic extent, strength and from the coast (with a core at 150 km) than the mean flow between peak season (see Table 4), we focus here on the mean composite ther- − 15°S and 18°S evidenced from the ADCP measurements (∼8cms 1 at mohaline structure associated with the concurrent presence of 9 El Niño approximately 70 km from the coast, see Fig. 5 in Chaigneau et al., and 13 La Niña events. Note that several authors have used similar 2013). composite analyses to study the mean impact of ENSO events on oceanographic and atmospheric parameters (e.g., Schwing et al., 2002; 3.5. Mean signature of El Niño and La Niña events on the NHCS hydrology Larkin and Harrison, 2005; Kug et al., 2009). It is important to note that the number of available data used to construct these composite fields is This Section aims to investigate how the relatively cold La Niña and strongly reduced (Fig. 10b–d) compared to the seasonal climatology warm El Niño events modify, in average, the mean thermohaline including the whole database (e.g., Fig. 2). The results discussed below, structure of the NHCS. To do so, in-situ profiles used to construct the in particular for El Niño and La Niña conditions, are only reliable South climatology were classified among 3 categories depending whether the of ∼2–3°S and between the coast and 200–300 km offshore. casts were acquired during El Niño, La Niña or neutral periods. For each The monthly mean SST/SSS distributions obtained from neutral of these categories a T/S climatology is computed using the four-di- periods are very similar to the ones obtained from the regional clima- mensional interpolation described in Section 2.3 and these gridded tology that includes all the available historical profiles (not shown). fields are compared with the seasonal climatology presented above. Differences between these fields are almost null everywhere except in very small mesoscale features particularly observed in SSS in the 3.5.1. Coastal El Niño Index (ICEN) Northern part of the NHCS. These weak SSS differences are probably The ENSO phenomenon, which originates in the western pacific, is induced by both the reduced number of salinity data in this region commonly identified using the Oceanic Niño Index (ONI) which cor- (Fig. 10b) and any weak meandering of the equatorial front that can responds to a 3-month running mean of SST anomalies in the Niño3.4 induce large salinity anomalies. Similarly, the two climatologies do not region located in the central equatorial Pacific (170°W–120°W; show significant differences at depth (not shown). The strongest dif- 5°S–5°N). Periods associated with an ONI exceeding ± 0.5 °C for more ferences are observed in the surface layer where on average ∘ ∘ than five consecutive months are considered by the NOAA as El Niño or ΔSST±=± σΔSST 0.03 0. 15 C and ΔSSS±= σΔSSS 0.001 ± 0. 041 C be- La Niña episodes, respectively (https://www.ncdc.noaa.gov/ tween the two climatologies. This suggests that our regional monthly teleconnections/enso/indicators/sst.php). However, several El Niño climatology of the NHCS, obtained from all historical available in-situ events known as El Niño Modoki or Central Pacific El Niño have a data, is not significantly biased by the interannual ENSO events and is signature in the Central Pacific but do not significantly impact the representative of normal conditions observed during neutral periods. Eastern Equatorial Pacific (e.g., Ashok et al., 2007). In order to take into In contrast, the mean thermohaline structure of the NHCS is account only the events that more likely impact the NHCS, we used the strongly affected by the interannual El Niño/La Niña events (Figs. 11 Coastal El Niño Index (ICEN) defined by the Peruvian Multisectoral and 12). On average, during El Niño events, relatively warm waters Commission of the National Study of El Niño Phenomenon (ENFEN). (T > 20 °C) are present along the coast, except in a ∼30 km-wide ICEN corresponds to a 3-month running mean of SST anomalies in narrow strip south of Pisco (14°S), where temperatures are of the Niño1+2 region located in the NHCS (90°W–80°W; 10°S-0) ∼18–19 °C (Fig. 11b). The presence of this relatively cool coastal water (ENFEN, 2012; Takahashi et al., 2014; see Fig. 10a). Monthly SST band (with respect to offshore waters) indicates that coastal upwelling anomalies are computed from the version 3b of the Extended Re- remains active during El Niño as also suggested by previous studies constructed SST (ERSST-v3b) dataset (Smith et al., 2008) relative to the (e.g., Wyrtki, 1965; Kessler, 2006; Colas et al., 2008). However during 1981–2010 period. Periods associated with an ICEN higher (lower, re- El Niño periods, the annual mean SST is considerably warmer than spectively) than +0.4 °C (−1.0 °C) for more than three consecutive during normal conditions with anomalies of up to 3–4 °C in the near- months are considered by the ENFEN as an El Niño (La Niña) event in shore region (Fig. 11c). This intense warming can be associated with

134 C. Grados et al. Progress in Oceanography 165 (2018) 123–144

(a) 4

2

0 SSTA (°C) −2

Niño 1+2 −4 Coastal Region

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 Year

0 200 (b) (c) (d) 180 Neutral El Niño La Niña 4°S 160

140 Number of Data 8°S 120 100 12°S 80 60 16°S 40 20

20°S 0 90°W 86°W 82°W 78°W 74°W 70°W 86°W 82°W 78°W 74°W 70°W 86°W 82°W 78°W 74°W 70°W

Fig. 10. Time series of sea-surface temperature anomalies (SSTA) in the NHCS and spatial distribution of the number of available in-situ profiles for the composite analysis during neutral, El Niño and La Niña conditions. a) Coastal El Niño Index (ICEN) computed from ERSST-v3b (see text) in the Niño1+2 region (90°W–80°W; 10°S-0; black solid line) and SSTA computed from in-situ profiles available in a near-coastal region extending from the coast to 100 km offshore and from 4°S to 18°S (grey solid line). Based on the ICEN, El Niño events of moderate, strong and extraordinary intensity are identified in red whereas La Niña events of moderate and strong intensity are marked in blue. b–d) Number of in-situ salinity profiles (in 1°×1° boxes) used to construct composite climatologies for neutral (b), El Niño (c) and La Niña (d) periods. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) various processes. First, the deepening of the thermocline induced by g). This increased salinity is probably due the onshore geostrophic the passage of downwelling coastal-trapped waves (e.g., Clarke and Van advection of STSW (Colas et al., 2008) and to the wind-driven coastal Gorder, 1994) allows local surface heat fluxes to warm the surface layer upwelling and offshore spreading of saltier, shallower than normal, (Kessler and McPhaden, 1995; Vialard et al., 2001; Cronin and Kessler, subsurface waters. Along the Peruvian coast, the strongest nearshore 2002). Second, as wind-driven coastal upwelling is active during El SSS anomalies are observed to the South of 12°S. In the equatorial re- Niño (Kessler, 2006; Colas et al., 2008; Chamorro et al., 2018) and the gion to the North of 4°S, the strong positive and negative SSS anomalies warm surface layer is thicker due to the thermocline deepening at the are likely due to the meandering of the equatorial front in the inter- coast, warmer water than during normal conditions is upwelled to the polated fields as large errors can arise from the lack of salinity data in surface. Third, as commented by Kessler (2006), “a positive feedback this region (e.g., Fig. 10c). However the freshening of the surface water occurs because warmer SST tends to inhibit the formation of the usual between 86°W and 82°W might be due to the expected poleward east Pacific stratus decks, thereby allowing further warming”. Fourth, transport of relatively fresh ESW and TSW by El Niño coastal currents. the alongshore southward advection of warmer ESW and TSW by the Between 8°S and 14°S, the relatively large area of weak SSS anomalies shoaling and strengthening of the PCUC during El Niño and the passage suggests that the STSW advected nearshore may counterbalance the of downwelling coastal trapped waves (e.g. Montes et al., 2011; freshening due to the southeastward advection of ESW and TSW. Al- Chaigneau et al., 2013; Pietri et al., 2014) may produce positive SST though they may not be robust due to the reduced number of ob- anomalies. Fifth, the onshore advection of STSW (e.g., Colas et al. servations (Fig. 10c), the strong offshore salinity anomalies north of 8°S (2008) for the 1997–1998 El Niño event) can participate to the ob- and west of ∼83°W may be indicative of anomalous south-eastward served warming. SST anomalies are maximum on the Peruvian shelf, advection of offshore, saltier, STSW towards the Peru central region and decrease South of 16°S, from 3 °C to ∼1–1.5 °C (Fig. 11c). Warming (see for example Fig. 13 in Colas et al., 2008). also occurs offshore with decreasing amplitude towards the west. The In the near-coastal region, El Niño events strongly modify the mean extent of the zonal band of anomalous warming (with SST anomalies thermohaline structure between the surface and ∼200 m depth large than +1 °C) decreases southward from ∼400 km North of 12°S to (Fig. 12a and c). On average at 100 km from the coast, the strongest less than 100 km South of 16°S. temperature anomalies (up to 4 °C) are observed at 50 m depth between During El Niño, the nearshore region between 7°S and 20°S also 2°S and 14°S (Fig. 12a) due to a strong deepening of the thermocline by shows the presence of more saline waters (∼35.1) producing positive 30–60 m (not shown). The anomalously warm layer is getting thinner SSS anomalies of 0.1–0.2 compared to normal conditions (Fig. 11e and southward, from 200 m near the equator to 100 m near 20°S (Fig. 12a).

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Table 4 Classification of El Niño and La Niña periods (1960–2014) based on the Costal El Niño Index (ICEN). Periods for weak coastal El Niño and La Niña events are not indicated. Peak months correspond to the months when the largest sea-surface temperature anomalies (SSTA) are observed.

Category ICEN Monthly Value Period Peak Month

Coastal El Niño Extraordinary SSTA > 3 °C 1982/07– > 1983/11 1983/06 1997/03– > 1998/09 1997/12 Strong 3.0 °C ≥ SSTA > 1.7 °C 1972/03– > 1973/02 1972/07 Moderate 1.7 °C ≥ SSTA > 1.0 °C 1965/03– > 1965/10 1965/05 1969/04– > 1969/07 1969/05 1986/12– > 1987/12 1987/04 1991/10– > 1992/06 1992/04 2006/08– > 2007/02 2006/11 2014/05– > 2014/10 2014/07 Weak 1.0 °C ≥ SSTA > 0.4 °C ––

Neutral 0.4 °C ≥ SSTA ≥−1°C ––

Coastal La Niña Weak −1.0 °C < SSTA ≤−1.2 °C –– Moderate −1.2 °C < SSTA ≤−1.4 °C 1966/04– > 1966/07 1966/05 1973/05– > 1974/02 1973/09 1974/10– > 1975/01 1974/11 1985/02– > 1985/09 1985/05 2010/08– > 2010/12 2010/09 Strong SSTA < −1.4 °C 1962/02– > 1962/08 1962/04 1964/03– > 1964/11 1964/06 1967/07– > 1968/06 1967/10 1970/04– > 1971/11 1970/07 1975/07– > 1976/01 1975/11 1988/05– > 1988/11 1988/08 2007/05– > 2007/12 2007/11 2013/04– > 2013/08 2013/07

Alongshore salinity anomalies have a more complex structure and fresher (see haline stratification in Figs. 7– 9) than during normal (Fig. 12c). North of 5°S, the expected freshening associated with the conditions. Indeed, the averaged alongshore section shows that the cold southeastward intrusion of the ESW at the coast (see Fig. 11g) is not and fresh anomalies typically extend down to 50–100 m depth in the clearly observed. The pool of anomalously saline surface waters water column (Fig. 12b–d). On the vertical, temperature (salinity, re- (0.2–0.3) observed near 0–2°S in the upper ∼30 m (Fig. 12c) is due to spectively) anomalies are stronger in northern (southern) Peru where the meandering of the equatorial front in the interpolated fields and less the vertical temperature (salinity) gradients are much marked (e.g., available data in this region. Weak positive salinity anomalies Fig. 6). The observed anomalies at depth are thus consistent with an (∼0.05–0.1) are observed at depth (∼50–150 m) between 4°S and 8°S enhanced near-coastal upwelling during la Niña events, associated with whereas the strongest anomalies of ∼0.1–0.15 are found to the South of a shoaling of the halocline/thermocline of 5–25 m at 100 km from the 12°S between the surface and ∼50–100 m depth. These strongest SSS coast (not shown). anomalies are likely the result of the onshore transport of STSW (Fig. 11e and g) that deepens the halocline. During La Niña conditions, the near-coastal region exhibits rela- 3.6. Interdecadal variations of the NHCS hydrology tively cold (15–16 °C) and fresh (34.9–35) waters that spread far off- shore in the southern NHCS (Fig. 11b and f). The equatorial cold tongue As an attempt to estimate the interdecadal variations in the NHCS, extending from northern Peru to Galapagos (SST < 21 °C and SSS < the near-coastal SST anomaly time series shown in Fig. 10 (0–100 km; 35) and the equatorial front are much more marked than during 4°S–18°S) was low-pass filtered with a cutoff period of 8 years. Based on normal conditions. Negative SST (SSS, respectively) anomalies are ob- this low-passed time series, 3 interdecadal periods clearly emerged served in the whole (Southern) NHCS during La Niña conditions, de- since the 1960s (Fig. 13a and b): a cold phase from 1960 to 1978, a creasing the temperature and salinity ranges of STSW up to ∼1–2°C warm phase from 1979 to 1998 and a cold phase from 1999 to 2014. and 0.1–0.15 respectively (Fig. 11b, d, f, h). The strongest SST and SSS These observed low-frequency SST anomalies are mainly in phase with anomalies are found offshore in the transition region between pcw and the Pacific Decadal Oscillation (PDO), a climate index defined as the STSW as well as in the equatorial cold tongue, which slightly contrasts principal component of monthly SST anomalies in the North Pacific with the anomaly patterns observed during El Niño conditions. This Ocean, poleward of 20°N (Mantua et al., 1997; Zhang et al., 1997). The suggests that the anomalously cold waters originate from the coastal correlation between the PDO and our time series is of 44% (54% if data upwelling and are advected offshore by Ekman currents. The observed after 1999 are not taken into account). However, note that the last cold negative anomalies could also be reinforced by the enhanced equator- phase in the PDO (1999–2015) includes 2 warmer periods in ward advection of fresher and colder water of southern origin by the 2004–2006 and 2014 not observed in our low-passed time series POC and PCC as part of the large-scale wind-driven gyre circulation. (Fig. 13). Multidecadal fluctuations associated with the PDO impact the Indeed, during La Niña, surface winds associated with the South Pacific equatorial Pacific SST and thermocline slope with a spatial structure Anticyclone tend to be enhanced with respect to normal conditions that bear similarities with ENSO patterns albeit on longer, decadal time (Schwing et al., 2002). The near-coastal impact of La Niña, associated scales. During the cool PDO regime, the basin-scale sea level slope (and with eastward-propagating upwelling equatorial Kelvin waves thermocline) is accentuated: lower in the eastern equatorial Pacific and (McPhaden, 1999) which trigger poleward-propagating upwelling higher in the western Pacific. The opposite occurs during the warm coastal trapped waves at the American coast (e.g., Pizarro et al., 2001), regimes. This decadal variability is driven by the variability of equa- is mainly to strengthen the upward shoaling of the thermocline/halo- torial winds (Clarke and Lebedev, 1999; McPhaden and Zhang, 2002; cline, so that source waters of the coastal upwelling are deeper, cooler Chavez et al., 2003). An atmospheric linkage between the PDO and the South Pacific Anticyclone through teleconnections has been evidenced

136 C. Grados et al. Progress in Oceanography 165 (2018) 123–144

Fig. 11. Impact of ENSO variability on the surface characteristics. (a–b) Mean SST and (e–f) SSS obtained considering data acquired only during El Niño (left panel) and La Niña (right panel) events. (c–d) SST and (g–h) SSS anomalies relative to neutral periods. Dotted areas correspond to the grid points where the search radius for the interpolation of the data was higher than 300 km and the results are probably less robust.

137 C. Grados et al. Progress in Oceanography 165 (2018) 123–144

EL NIÑO LA NIÑA 0 3 Temperature(°C) Anomaly

2

100 1 0

200 −1 Depth (m) −2 (a) (b) 300 −3 0 0.3

0.2 Salinity Anomaly

100 0.1 0

200 -0.1 Depth (m) (c) (d) -0.2 300 -0.3 20°S 16°S 12°S 8°S 4°S 0 16°S 12°S 8°S 4°S 0 Latitude Latitude

Fig. 12. Mean alongshore vertical section of temperature (in °C, upper panel) and salinity (lower panel) anomalies at 100 km from the coast obtained from El Niño (left panel) and La Niña events (right panel). Anomalies were computed relative to neutral periods. Hatched areas in Figures (c) and (d) correspond to areas where the search radius for the interpolation of the data was higher than 300 km and the results are probably less robust. but its impact on the NHCS SST is supposed to be weak (Montecinos (Fig. 14b). Note that during the first cold (1960–1979) and warm et al., 2007). (1979–1999) periods, the total number of offshore data is reduced The 3 interdecadal periods depicted in Fig. 13 are associated with (Fig. 13d) as no Argo floats were available, increasing the uncertainty mean low-frequency SST anomalies in the near-coastal Peruvian region on the interpolated fields in the offshore regions. Consequently, the of −0.2 °C, 0.4 °C and −0.3 °C respectively. These low-frequency var- offshore signal during the cold phase is mainly representative of the iations are strongly correlated (r = 0.92) with the low-frequency var- recent cold period (2000–2014), and the offshore signal during the iations of the 17 °C isotherm depth (Fig. 13b) determined from the warm phase should be interpreted with caution. available in-situ profiles in the near-coastal region (0–100 km; Due to the low-frequency fluctuations of the thermocline depth 4°S–18°S) and associated with the seasonal thermocline (see Figs. 6–9). (Fig. 13b), the interdecadal signal extends relatively deep in the water Along the Peruvian coast, the seasonal thermocline shows typical column with temperature anomalies of ± 0.1 °C extending to ∼100 m fluctuations of ± 5–10 m at interdecadal scales (Fig. 13b). The inter- depth at 100 km from the coast (Fig. 14c–d). In terms of salinity our decadal fluctuations of both the SST ( ± 0.5 °C) and the 17 °C isotherm composite analysis suggests weak interdecadal fluctuations with var- depth ( ± 10 m) are in agreement with previous regional estimates iations of few hundredth of pss (maximum of ± 0.05, not shown). On along Peru and Chile (Montecinos et al., 2003; Pizarro and Montecinos, average, weak positive (negative) SSS anomalies are observed during 2004). warm (cold) periods but the SSS patterns are noisier and the presence of In order to investigate more in detail the impact of the these so- numerous mesoscale structures in the composite fields prevents any called warm and cold periods on the NHCS thermohaline structure, our robust conclusions. whole T/S database was further classified among two distinct categories depending whether the casts were acquired during warm (1979–1998, Fig. 13c) or cold interdecadal phases (1960–1978 and 1999–2014, 4. Conclusion and discussion Fig. 13d). Composite fields were constructed from these 2 categories applying the four-dimensional interpolation and the obtained mean The main objectives of this study were (i) to provide an updated fields are compared with the mean regional climatology computed from description of the hydrography and geostrophic circulation in the the whole database. Fig. 14a–b shows the mean SST anomaly dis- NHCS, (ii) to investigate the mean impact of the interannual ENSO tributions for the warm and cold phases compared to the mean regional events on the temperature and salinity structure and (iii) to determine climatology (salinity is not shown due to a weak signal to noise ratio). the interdecadal changes since the 1960s. Based on the combined On average during warm periods, the strongest SST anomalies reaches analysis of in-situ temperature and salinity profiles from the World 0.7–0.9 °C over a ∼100 km-wide band on the Peru shelf, and extends as Ocean Database, complemented by more than 370 cruises realized by far as ∼300 km offshore near 14°S–17°S where the intense Pisco-San IMARPE between 1960 and 2014, we constructed a seasonal T/S cli- Juan upwelling cell is found (Fig. 14a). Strong mesoscale positive SST matology in the NHCS. After data processing, the four-dimensional anomalies of ∼1 °C are also observed offshore in the southwestern part interpolation scheme retained to obtain the gridded fields was the al- of the study region and North of 5°S. More surprisingly are the weak gorithm developed for the CARS climatology (Ridgway et al., 2002; negative SST anomalies (−0.1 °C to −0.3 °C) observed between 4°S and Dunn and Ridgway, 2002). Compared to more commonly used inter- 12°S in the offshore region (Fig. 14a). In contrast, during cold phases, polation procedures, this method, applied on a high-resolution grid of SST anomalies are weaker (Fig. 14b). A thin (< 50 km) coastal band of 0.1° × 0.1° in longitude-latitude, provides more realistic near-coastal negative anomalies reaching −0.5 °C is found between 8°S and 20°S properties and cross-shore gradients. extending further offshore between 12°S and 16°S. In the offshore On average, the SST displays an intense along-coast front associated ocean, negative anomalies are generally very weak except North of 4°S with the coastal upwelling, which is more marked in summer than in near the mean equatorial front position and weak positive anomalies winter, likely due to enhanced wintertime wind-driven mixing and re- are observed between 4°S and 12°S at 100–300 km from the coast duced heat fluxes. SSS also displays a frontal structure parallel to the coast separating coastal upwelled-water from saltier STSW, but the

138 C. Grados et al. Progress in Oceanography 165 (2018) 123–144

(a) 4 Warm Period

2

0

SSTA (°C) −2

Cold Period Cold Period −4

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 Year

1 20

(b) 17°C Depth Anomaly (m) Warm Period Shallower 0.5 10 Shallower

0 0 SSTA (°C)

−0.5 Deeper −10 Cold Period −1 −20 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 Year

0 (c) (d) 380

Cold Periods 340 4°S Warm Period 300

260 Number of Data 8°S 220

180 12°S 140

100 16°S 60

20 20°S 90°W 86°W 82°W 78°W 74°W 70°W 86°W 82°W 78°W 74°W 70°W

Fig. 13. Time series of sea-surface temperature anomalies (SSTA) in the NHCS and spatial distribution of the number of available in-situ profiles at interdecadal scales. (a) SSTA computed from in-situ profiles available in a near-coastal region extending from the coast to 100 km offshore and from 4°S to 18°S (grey solid line). This time series has been low-pass filtered with a cutoff period of 8 years (black thick line) to identify interdecadal cold (in blue) and warm (in red) periods. The time series of the annual PDO index is also superimposed (green solid line). Note that the PDO time series is associated with the EOF decomposition of Northern Pacific SST and is thus non dimensional. (b) Low-pass filtered SSTA (black solid line, as in (a)) and anomaly of the depth of the 17 °C isotherm (orange solid line) in the near coastal region. The time series of the annual PDO index is also superimposed (green solid line). The 17 °C depth anomaly has also been computed from in-situ profiles and low-pass filtered with a cutoff period of 8 years. (c–d) Number of in-situ temperature profiles (in 1°×1° boxes) used to construct composite climatologies for interdecadal cold (c) and warm (d) periods. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) most striking feature is the strong horizontal gradients associated with the 6 main WMs (STSW, ESA, TSW in the surface layer and ESSW, the equatorial front that extends between Northern Peru and the ESPIW and AAIW in subsurface) found in the upper 1000 m of the Galapagos (e.g. Pak and Zaneveld, 1974; Fiedler and Talley, 2006). NHCS. These updated T/S characteristics slightly differ from those re- Based on mean T/S diagrams obtained in several key regions we pro- ported previously, due to (i) the different geographical extent of the vided a regional update of the mean temperature and salinity ranges of areas and time-periods used to determine these characteristics, and (ii)

139 C. Grados et al. Progress in Oceanography 165 (2018) 123–144

Warm Period Cold Period 0 (a) (b)

4°S SSTA SSTA 0.9

0.7 8°S 0.5 Temperature(°C) Anomaly 12°S 0.3

0.1 16°S

-0.1

20°S 90°W 86°W 82°W 78°W 74°W 70°W 86°W 82°W 78°W 74°W 70°W -0.3

0 (c) (d) -0.5

100 -0.7

-0.9 200 Depth (m)

300 20°S 16°S 12°S 8°S 4°S0 16°S 12°S 8°S 4°S 0 Latitude Latitude

Fig. 14. Impact of the interedecadal variability on the temperature. (a–b) Mean temperature anomalies at the sea-surface (upper panel) and alongshore vertical section of temperature anomalies at 100 km from the coast (lower panel) for interdecadal warm (left panel) and cold (right panel) periods. Anomalies were computed relative to the mean fields of the regional climatology obtained using in-situ profiles for the whole period (1960–2014). Dotted areas in figure (a) correspond to the grid points where the search radius for the interpolation of the data was higher than 300 km and the results are probably less robust. the updated and increased number of observations in the present study. the one presented here), Messié et al. (2009) estimated the upwelling Alongshore modification of several WMs was evidenced, in particular depth to 75 m, which is also consistent with estimates of Zuta and due to the poleward transport of relatively warm and salty ESSW by the Guillén (1970) (75–100 m) and Wyrtki (1963) (< 100 m). These results PCUC, and mixing with cooler and fresher ESPIW in the 50–150 m are also supported by regional model experiments (Albert et al., 2010; range and AAIW between 500 m and 1000 m. Seasonal variability was Colas et al., 2012; Espinoza-Morriberón et al., 2017). Kessler (2002) more clearly observed in temperature, with a reduced stratification in speculates that the Peru upwelling (along with the Costa Rica Dome in winter due to enhanced vertical mixing by stronger winds during this the North Eastern Pacific) is the location where wind-driven upwelling season. However, to the North of ∼4°S, the fresh hence strongly stra- penetrates below the thermocline, and thus can drive the off-equatorial tified surface layer composed of TSW maintains a permanent halocline/ Tsuchiya Jets. By contrast, our analysis suggests that the Peru coastal pycnocline throughout the year. upwelling (within 100 km from the coast) is mainly a shallow phe- Alongshore distribution of the vertical stratification permitted to nomenon, and thus unlikely to be part of this larger cell. compute the cross-shore geostrophic flow in the upwelling region at Cross-shore sections off Paita (∼5°S), Chimbote (∼9°S) and San- 100 km from the coast. The onshore geostrophic transport must be on Juan (16.5°S) display distinct features from North to South. These 3 average compensated by the Ekman westward surface transport, as- sites display shoaling isotherms (within 0–100 m depth range) towards suming that the meridional transport at the extremities of the section the coast, indicative of coastal upwelling, and deepening isotherms in are negligible. This led to an estimation of the depth for which the the 100–300 m depth range, associated with the poleward PCUC. At 5°S transport compensation occurs, which can be considered as a proxy of (Paita), we observed a thin layer of fresh TSW which spreads offshore the maximum depth of source water parcels to be upwelled. On average due to Ekman transport, while the underlying ESSW is transported over the extent of the alongshore section (5.5°S–16°S) located 100 km onshore by the subsurface current compensating the Ekman flow. from the coast, the upwelling depth varies between 50 m in summer Salinity features suggest that the onshore ESSW transport could be and 110 m in winter. This calculation may depend on the distance be- larger in winter due to a stronger onshore flow compensating the en- tween the coast and the considered alongshore section (100 km), and hanced wind-driven surface Ekman flow. However, the cross-shore larger depths could be expected for alongshore sections located further geostrophic currents are slightly weaker in winter than in summer at from the coast due to the offshore increase of the wind stress amplitude. this latitude (Fig. 6). This suggests that other mechanisms, such as the Besides, the upwelling depth estimated over specific portions of the alongshore poleward flow, may also impact the subsurface salinity alongshore section could be shallower than 50–100 m in portions where feature. Indeed, the more intense alongshore flow in summer (Fig. 7c) is the eastward flow is intensified (e.g. between 6°S and 12°S, Fig. 6). prone to enhance barotropic/baroclinic instabilities and mesoscale Previous studies have assessed the depth of source waters by a different features that could stir the salinity vein and make it less visible in the method. Using the intersection of offshore (150–250 km from the coast) cross-shore sections. and inshore (between the coast and up to 50 km offshore) T-S diagrams At 9°S (Chimbote) the slope of the isotherms is steeper than at 5°S derived from the WODC and IMARPE datasets (a restricted dataset than due to the presence of an intensified upwelling cell, and the influence of

140 C. Grados et al. Progress in Oceanography 165 (2018) 123–144 fresh surface waters of tropical origin is no longer evidenced. Further obtained interpolated fields. Second, in order to quantify the possible south at 16°S, the onshore transport of ESSW is no longer identified, but impact of the increase number of data in the early 2000s on the in- its signature remains near the coast as it is transported poleward by the terpolated fields (see Fig. 3), we artificially and randomly removed PCUC and mixed with fresher ESPIW that is observed in the NHCS at around 2/3 of the vertical profiles during 2000–2002 and rebuilt a new the base of the seasonal thermocline south of ∼16°S. climatology (not shown). The strongest differences, between the ob- A composite analysis of T/S characteristics during El Niño, La Niña tained (subsampled) climatology and the full climatology presented in or neutral periods revealed that the NHCS is strongly impacted by ca- this manuscript, were of ± 0.1 °C in temperature and ± 0.01 in salinity. nonical El Niño and La Niña events. On average during El Niño, rela- However, these relatively weak discrepancies were observed in the tively warm ESW is transported eastward towards the northern Peru surface layer and in the near-coastal region, and rapidly decrease with region and poleward by the currents forced by downwelling coastal depth suggesting that this temporal inhomogeneity does not strongly trapped waves. This generates positive temperature anomalies along affect the interpolated field. Third, to interpolate T/S data at any given the coast with averaged SSTA of ∼3–4 °C. In the north of Peru, these depth level, the four-dimensional interpolation scheme also includes anomalous poleward currents transporting fresh TSW and ESW further data from adjacent depth levels (Section 2.3). Since the number of south than during normal conditions might also create negative near- available T/S data decreases vertically from the surface to 1000 m shore SSS. However the lack of salinity observations to the North of 4°S depth (Fig. 3), the adjacent shallower depth surfaces might have a in our composite analysis prevented to represent negative SSS anoma- higher weight than the deeper depth surfaces. To test whether the in- lies that were only partly observed in the northern NHCS. In the south terpolated fields could be biased towards shallower observations (e.g. of Peru, the deepening of the thermocline/halocline during El Niño in warmer temperature), we rebuilt a climatology without considering conjunction with a still active coastal upwelling and related offshore adjacent layers in the interpolation. T/S differences between the cli- Ekman surface transport (e.g., Colas et al., 2008) brings warmer and matology presented in the manuscript and the rebuilt climatology that saltier ESSW to the surface. This mechanism together with the eastward does not consider adjacent levels are relatively weak and not system- displacement of STSW is probably responsible for the observed positive atically biased towards a direction (differences can be either positive or SSS anomalies in the near-coastal region of the southern NHCS and the negative), except in the seasonal thermocline. There, a slight positive reinforcement of SST anomalies. bias towards shallower values can be observed in the full climatology, During La Niña, the opposite situation occurs: the conjunction of the with maximum temperature differences of 0.2 °C. shoaling of the thermocline/halocline due to remotely-forced upwelling The seasonal T/S climatology constructed in this study and com- coastal trapped waves and an intensified (with respect to normal con- posite analyses at interannual and interdecadal scales provide a re- ditions) wind-driven coastal upwelling generates negative temperature ference for evaluating regional models focusing on the NHCS circula- and salinity anomalies. In contrast with the El Niño anomalies, the tion and ecosystem functioning (e.g., Penven et al., 2005; Lett et al., intensity of the anomalies is maximum ∼200–400 km off the coast 2007; Echevin et al., 2008; Albert et al., 2010). In turn, high-resolution during La Niña events, which suggests that the offshore POC, reinforced regional models may be used to better interpret the observed patterns by the stronger subtropical anticyclone (e.g., Schwing et al., 2002), may and understand the processes responsible of the observed anomalies. In also play a role by transporting cooler and fresher water from the the future, additional data will become available and might subse- Southern HCS to the Peru region. quently be included to update the climatology. In particular, the con- Interdecadal variability was also investigated by a composite ana- tinuous increased number of Argo float deployments in the NHCS, lysis during two cold periods (1960–1978 and 1999–2014) and a warm might permit to reduce the strong uncertainties of our composite results period (1979–1998), which approximately correspond to negative and in the offshore region (more particularly in salinity). Similarly, sus- positive phases of the Pacific Decadal Oscillation (e.g., Chavez et al., tained long-term efforts of IMARPE for surveying the near-coastal re- 2003). During the warm interdecadal periods, anomalously warm wa- gion will allow refining the resolution and con fidence of T/S properties ters are found mainly nearshore between 8°S and 17°S whereas weaker in this important upwelling region. It is important to note that the offshore (∼100 km from coast) negative anomalies are encountered seasonal climatology developed is currently used as an operational between 8°S and 13°S. Expectedly, the opposite pattern is evidenced product during the IMARPE cruises to determine in near-real time the during cold periods. The spatial structure of the anomalies at inter- vertical temperature and salinity anomalies of the Peruvian upwelling decadal scales, which strongly differs from the averaged anomalies region. This product will be updated routinely as new data become observed during La Niña and El Niño conditions, is mainly restricted available and is publicly available upon request to the corresponding around the near-coastal upwelling cells. This suggests that the observed author. Finally, the methodology described in this paper is also cur- interdecadal anomalies, which are associated with vertical movements rently applied to biogeochemical properties (nutrients, oxygen, chlor- of ± 5 m of the seasonal thermocline, could be due to a modification of ophyll) collected by the historical IMARPE cruises. This additional the wind-driven upwelling (e.g., reduction during warm periods). As product will be presented in a future independent work. coastal winds are strongly related to the position and intensity of the South Pacific Anticyclone (Goubanova et al., 2011; Dewitte et al., Acknowledgements 2011), the upwelling variability could be mainly associated to atmo- spheric changes, rather than to a remote oceanic influence due to wind We express our gratitude to crewmembers, oceanographers and changes in the equatorial wave guide (Pizarro and Montecinos, 2004). supporting staff of IMARPE, especially L. Vásquez and the physical It is important to keep in mind that the climatology presented in this oceanography team, and international institutions that collected and study could potentially be biased, in particular due to the rather in- made freely available the data used in this work. Argo data (http://doi. homogeneous spatio-temporal distribution of the data. Although not org/10.17882/42182) were collected and made freely available by the detailed in the manuscript, several complementary analyses have been International Argo Program and the national programs that contribute conducted. First, to reduce possible distortions of interpolated fields to it. (http://www.argo.ucsd.edu, http://argo.jcommops.org). The Argo due to enhance sampling density in given regions we removed closely Program is part of the Global Ocean Observing System. We particularly packed clusters of data. As in Ridgway et al. (2002), any groups of at thank J. Dunn from CSIRO for having kindly shared his codes for the 4- least 10 profiles acquired the same month (independently of the year) D interpolation of the data. We are also grateful to A. Harang, G. Luque, and within a radius 250 m, were replaced by monthly averages before F. Monetti, I. Puillat, K. A. Sanchez, and M. Wach for their respective mapping. Only 20 clusters were found, and 17 of them were located help. 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