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Frontogenesis of the Angola–Benguela Frontal Zone

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Frontogenesis of the Angola–Benguela Frontal Zone Ocean Sci., 15, 83–96, 2019 https://doi.org/10.5194/os-15-83-2019 © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License. Frontogenesis of the Angola–Benguela Frontal Zone Shunya Koseki1, Hervé Giordani2, and Katerina Goubanova3,4 1Geophysical Institute, University of Bergen, Bjerknes Centre for Climate Research, Bergen, Norway 2Centre National de Recherches Météologiques, Météo-France, UMR-3589, Toulouse, France 3Centro de Estudios Avanzados en Zonas Áridas, La Serena, Chile 4CERFACS/CNRS, CECI UMR 531, Toulouse, France Correspondence: Shunya Koseki (shunya.koseki@gfi.uib.no) Received: 10 July 2018 – Discussion started: 11 September 2018 Revised: 28 January 2019 – Accepted: 30 January 2019 – Published: 8 February 2019 Abstract. A diagnostic analysis of the climatological annual rates the warm sea water of the Angola Current (e.g., Kopte mean and seasonal cycle of the Angola–Benguela Frontal et al., 2017) from the cold sea water associated with the Zone (ABFZ) is performed by applying an ocean frontoge- Benguela Current and upwelling system (e.g., Mohrholz et netic function (OFGF) to the ocean mixing layer (OML). The al., 2004; Colberg and Reason, 2006, 2007; Veitch et al., OFGF reveals that the meridional confluence and vertical tilt- 2006; Fennel et al., 2012; Chen et al., 2012; Santos et al., ing terms are the most dominant contributors to the fronto- 2012; Goubanova et al., 2013; Junker et al., 2015, 2017; Vizy genesis of the ABFZ. The ABFZ shows a well-pronounced et al., 2018). The ABFZ is characterized by a smaller spa- semiannual cycle with two maximum (minimum) peaks in tial extent and weaker sea surface temperature (SST) gra- April–May and November–December (February–March and dient compared to the major oceanic fronts generated by July–August). The development of the two maxima of fron- the western boundary currents (Fig. 1). However, due to its togenesis is due to two different physical processes: en- near-coastal location, the ABFZ plays important roles for hanced tilting from March to April and meridional conflu- the southern African continent, strongly impacting the lo- ence from September to October. The strong meridional con- cal marine ecosystem (e.g., Auel and Verheye, 2007; Chavez fluence in September to October is closely related to the and Messié, 2009) and regional climate (Hirst and Has- seasonal southward intrusion of tropical warm water to the tenrath, 1983; Rouault et al., 2003; Hansingo and Reason, ABFZ that seems to be associated with the development of 2009; Manhique et al., 2015). In particular, the main mode the Angola Dome northwest of the ABFZ. The strong tilt- of interannual variability in SST in the ABFZ, the so-called ing effect from March to April is attributed to the meridional Benguela Niño/Niña (e.g., Florenchie et al., 2003; Rouault et gradient of vertical velocities, whose effect is amplified in al., 2018), influences the local rainfall along the southwest- this period due to increasing stratification and shallow OML ern African coast of Angola and Namibia via moisture flux depth. The proposed OFGF can be viewed as a tool to di- anomalies associated with the SST anomalies (Rouault et al., agnose the performance of coupled general circulation mod- 2003; Hanshingo and Reason, 2009; Lutz et al., 2015) and els (CGCMs) that generally fail at realistically simulating the tends to have a remote impact on rainfall activity over the position of the ABFZ, which leading to huge warm biases in southeastern African continent (e.g., Manhique et al., 2015). the southeastern Atlantic. The ABFZ region also poses one of the major challenges for the global climate modeling community. Most CGCMs exhibit a huge warm SST bias in the ABFZ (e.g., Zuidema et al., 2016) and fail to reproduce the realistic SST, its seasonal 1 Introduction cycle, and the right location of the ABFZ (e.g., Koseki et al., 2017). While Colberg and Reason (2006) and Giordani and The Angola-Benguela Frontal Zone (ABFZ, see Fig. 1), sit- Caniaux (2011) concluded that the position of the ABFZ is uated off the coast of Angola and Namibia, is a key oceanic controlled, to a large extent, by the local wind stress curl, feature in the southeastern Atlantic Ocean. The ABFZ sepa- Published by Copernicus Publications on behalf of the European Geosciences Union. 84 S. Koseki et al.: Frontogenesis of the Angola–Benguela Frontal Zone Koseki et al. (2018) elucidated that the local wind stress curl Sect. 6. Finally we summarize and make some concluding bias in CGCMs contributes partly to the warm SST bias in remarks in Sect. 7. the ABFZ via erroneous intrusion of tropical warm water, which is induced by a negative wind stress curl and enhanced Angola Current. In order to comprehensively understand the 2 Data sources of such model biases, one needs to understand the For an overview of SST and its meridional gradient in the processes of generation of the ABFZ. ABFZ, and evaluation of the reanalysis data, we employ Previous studies have mainly focused on the SST variabil- the optimum interpolated sea surface temperature (OISST; ity at interannual to decadal timescales in the ABFZ, and/or Reynolds et al., 2007) released by the National Oceanic and on its impacts on regional climate that are well-studied (e.g., Atmospheric Administration (NOAA) that has 0.25◦of hor- Rouault et al., 2003; Lutz et al., 2015; Vizy et al., 2018). izontal resolution and daily temporal resolution from 1982 Whereas Morholz et al. (1999) analyzed the ABFZ during to 2010. For the 3-D diagnostic analysis of the ABFZ, we a particular event in 1999, to our knowledge there are few utilize 1 h forecast data of the Climate Forecast System Re- or no works quantitatively investigating dynamical and ther- analysis (CFSR; Saha et al., 2010) developed by the National modynamical processes responsible for the climatological Centers for Environmental Prediction (NCEP). The ocean state of the ABFZ and its seasonal cycle. A dynamical di- component of this system is based on Modular Ocean Model agnosis for the SST front in the north of the Atlantic cold (MOM) version 4p0d (Griffies et al., 2004) and implements tongue (e.g., Hasternrath and Lamb, 1978; Giordani et al., data assimilation for the forecast. This system provides 6- 2013) was proposed by Giordani and Caniaux (2014, here- hourly data with a 0.5◦ horizontal resolution and 70 vertical after referred to as GC2014). The frontogenetic function they layers for ocean. This resolution is relatively coarse com- use is, in general, adapted to explore sources of frontogene- pared to the resolution of simulations performed with re- sis of atmospheric synoptic-scale cyclones in the extratrop- gional ocean models in a forced mode using wind forcing ics (e.g., Keyser et al., 1988; Giordani and Caniaux, 2001). from satellite products. However, the advantage of a cou- Using a frontogenetic function, GC2014 clearly showed that pled ocean–atmosphere system like CFSR is that it allows for the convergence associated with the northern South Equa- avoiding spurious effects in wind forcing over coastal regions torial Current and Guinea Current forces the SST-front in- resulting from the extrapolation in a 25–50 km width coastal tensity (frontogenetic effect), whereas mixed-layer turbulent fringe where the wind cannot be observed by scatterometers flux destroys the SST front (frontolytic effect). Fundamen- (Astudillo et al., 2017). Moreover, the wind satellite products tally, the frontogenetic function consists of three mechanical are generally available for only a relatively short time period, terms (confluence, shear, and tilting) and two thermodynam- limiting investigation of long-term climatology and seasonal ical terms (diabatic heating and vertical mixing). Around the cycle. In this paper we will analyze daily means (the proce- ABFZ, all these terms can be considered to be contributors dure of data post-processing is given in the Supplement) and to the frontogenesis due to (1) the confluence zone associated utilize the CFSR outputs of velocity (horizontal and vertical), with the southward Angola and northward Benguela currents potential temperature, net surface heat flux, OML depth, and (confluence and shear), (2) strong coastal upwelling (tilting) sea surface height (SSH). associated with the Benguela Current, (3) spatial variations in radiative fluxes induced by the stratocumulus cloud deck (diabatic heating related to radiation) associated with the cold 3 Ocean frontogenetic function SST and subsidence due to the St. Helena anticyclone (e.g., Klein and Hartmann, 1993; Pfeifroth et al., 2012). So far, the The OFGF is defined and applied to the OML in order to relative roles of these different processes in the frontogenesis propose a dynamical diagnosis of the maintenance and gen- of the ABFZ still need to be investigated. erating process of the ABFZ. Following GC2014, we use the In this study, following the fundamental philosophy of OFGF as a tool to unravel the Lagrangian (pure) sources of GC2014, we attempt to understand the mechanisms respon- the oceanic front. While there is plenty of literature inves- sible for the climatological ABFZ development at a seasonal tigating the ocean-front dynamics (e.g., Dinniman and Rie- timescale based on a first-order estimation. We propose an necker, 1999), the concept of this OFGF has been hardly re- ocean frontogenetic function (OFGF) in a different way from ferred to. The Lagrangian frontogenesis function, F , is de- GC2014 focusing on the OML mean front. The structure of fined as the remainder of this paper is as follows. Sect. 2 gives de- d @θ tails of dataset used in this study. In Sect. 3, we derive the F ≡ ; (1) dt @y OFGF. Section 4 provides a description of the climatological state around the ABFZ. In Sect. 5, we apply our diagnostic where θ is the temperature.
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