Skip to main content

Advertisement

Log in

Exposure of Santos Harbor Metropolitan Area (Brazil) to Wave and Storm Surge Climate Changes

  • Original Paper
  • Published:
Water Quality, Exposure and Health Aims and scope Submit manuscript

Abstract

Santos Harbor Metropolitan Area (SHMA) in São Paulo Coastline (Brazil) is the most important marine cargo transfer terminal in the Southern Hemisphere. In previous studies, the authors showed how this area is subject to climate changes determining, in the long run, a sea level rise and, as a consequence, a consistent impact on the global sea level rise and subsidence. In this research, a further and innovative analysis of a long-term-wave database (1957–2002) generated from a comparison between wave data modeled on a “deep water model” (ERA-40 Wave model—ECMWF) and wave data measured by a coastal buoy, over the years 1982–1984, in SHMA littoral (São Paulo State, Brazil) was carried out. The calibration coefficients, according to angular sectors of the wave direction, were obtained by comparing the measured data with the modeled data and applying them to the original scenarios using a near-shore wave model (MIKE21). The analysis of the wave climate changes on the extreme storm surge wave conditions, selecting cases of \(H_{\text {s}}\) \(> 3.0\) m and using that virtual database, has shown an increase in the wave significant height (\(H_{\text {s}}\) ) and in the wave peak period (\(T_{\text {p}}\) ) and also in the frequency of storm surge events in the last decades. Considering the increase in the sea hazards and the high values of the facilities and infrastructures in SHMA, it is necessary to minimize the risks. Hence, the adaptation policies linked to climate changes which determine an impact on storm surges either for the SHMA or for São Paulo coastal area are highlighted on the basis of the results obtained by the authors.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

References

  • AA.VV. (1997) Approach channels—a guide for design. In: Final Report of the Joint Working Group II-30 PIANC-IAPH in cooperation with IMPA and IALA, Brussels (Belgium) and Tokyo (Japan)

  • Alfredini P, Arasaki E, Amaral RF (2008) Mean sea level rise impacts on Santos Bay, Southeastern Brazil–physical modelling study. Environ Monit Assess 144:377–387

    Article  Google Scholar 

  • Alfredini P, Araújo RN (2001) O cálculo do transporte de sedimentos litorâneo: estudo de caso das praias de Suarão e Cibratel (Município de Itanhaém, São Paulo). Revista Brasileira De Recursos Hìdricos 6–2:15–28

    Google Scholar 

  • Alfredini P, Marquez AL (2010) Reconstructing significant wave height and peak period time series for a coast location: Vitoria/ ES Bay study case. 1st Conference of Computational Interdisciplinary Sciences Pan, American Association of Computational Interdisciplinary Sciences, São José dos Campos, 23–27

  • Alfredini P, Pezzoli A, Cristofori E, Dovetta A, Arasaki E (2012) Wave and tidal level analysis, maritime climate change, navigation’s strategy and impact on the costal defenses—Study case of São Paulo State Coastline Harbor Areas (Brazil). Geophysical Research Abstracts, EGU 14:10735

  • Arasaki E, Alfredini P, Pezzoli A, Rosso M (2011) Coastal area prone to extreme flood and erosion events induced by climate changes: study case of Juqueriquerê River Bar navigation, Caraguatatuba (São Paulo State), Brazil. In: Weintrit A, Neumann T (eds) Human resources and crew management, vol 17. CRC Press, Balkema book, London

    Google Scholar 

  • Arcorace M (2012) Valutazione e modellizzazione delle condizioni meteo-marine nella zona costiera di San Paolo in Brasile. Tesi di Laurea Magistrale nel Corso di Laurea in Ingegneria Civile (MSc Thesis), Ed. Politecnico di Torino, Torino

  • Aura S, Ngunjiri C, Maina J, Oloo P, Muthama J (2011) Development of a decision support tool for Kenya’s coastal management. J Meteorol Relat Sci 5–1:37–47

    Google Scholar 

  • Barstow S, Mørk G, Lønseth L, Mathisen JP (2009) WorldWaves wave energy resource assessments from the deep ocean to the coast. In: 8th European Wave and Tidal Energy Conference-Fugro OCEANOR, Uppsala, Sweden, pp 149–159

  • Battjes JA, Janssen JPFM (1978), Energy loss and set-up due to breaking in random waves. Proceedings of Engineering Conference 16th, 569–587

  • Becker A, Inoue S, Fischer M, Schwegler B (2012) Climate change impacts on international seaports: knowledge, perceptions, and planning efforts among port administrators. Climate Change 100:5–29

    Article  Google Scholar 

  • Bindoff NL, Willebrand J, Artale V, Cazenave A, Gregory J, Gulev S, Hananawa K, Le Quéré C, Levitus S, Nojiri Y, Shum CK, Talley LD, Unnikrishnan A (2007) Observations: oceanic climate change and sea level. In: Solom S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of working Group I to the Fourth Assessment Report of the Intergovernmental panel on climate change. Cambridge University, New York

  • Carratù B (2004) Modellazione idrodinamica di onde off-shore nel Golfo del Leone. Tesi di Laurea Magistrale nel Corso di Laurea in Ingegneria Civile (MSc Thesis), Ed. Politecnico di Torino, Torino

  • Cristofori E, Pezzoli A, Rosso M (2004) Analisi dell’interazione vento-corrente di marea in zona costiera: applicazione al Golfo di Hauraki-Auckland (Nuova Zelanda). \(29^{\circ }\) Congresso Nazionale di Idraulica e Costruzioni Idrauliche 3:745–751

  • Debernard JB, Roed LP (2008) Future wind, wave and storm surge climate in the Northern Seas: a revisit. Tellus A 60:427–438

    Article  Google Scholar 

  • DHI Water and Environment (2009a) GEODESY IN MIKE ZERO. User guide, Mike by DHI Software,

  • DHI Water and Environment (2009b) MIKE 21 SW Spectral wave FM module. User guide, Mike by DHI Software,

  • DHI Water and Environment (2009c) MIKE 21 SW spectral wave FM module. Scientific Documentation, Mike by DHI Software,

  • DHI Water and Environment (2009d) MIKE ZERO PreProcessing and PostProcessing. User guide Generic editors and viewers, Mike by DHI software,

  • DHI Water and Environment (2009e) MIKE ZERO TOOLBOX. User guide, Mike by DHI Software

  • Dima IM, Wallace JM (2007) Structure of the annual-mean equatorial planetary waves in the ERA-40 reanalyses. J Atmos Sci 64:2862–2880

    Article  Google Scholar 

  • Dovetta A (2012) Analisi dell’influenza dei cambiamenti climatici sul moto ondoso: applicazione alla zona costiera dello Stato del São Paolo (Brasile). Tesi di Laurea Magistrale nel Corso di Laurea in Ingegneria Civile (MSc Thesis), Ed. Politecnico di Torino, Torino

  • Eldeberky Y, Battjes JA (1996) Spectral modeling of wave breaking: application to Boussinesq equations. J Geophys Res Oceans 101–C1:1253–1264

    Article  Google Scholar 

  • Etemad-Shahidi A, Moeini MH (2007) Application of two numerical models for wave hindcasting in lake Erie. Appl Ocean Res 29:137–145

    Article  Google Scholar 

  • European Centre for Medium-Range Weather Forecasts (2003) ERA-40 Project. ECMWF, Reading

  • Holthuijsen LH, Booij N, Herbers THC (1989) A prediction model for stationary, short-crested waves in shallow water with ambient currents. Coast Eng 13:23–54

    Google Scholar 

  • Kazeminezhad MH, Etemad-Shahidi A, Mousavi SJ (2005) Application of fuzzy inference system in the prediction of wave parameters. Ocean Eng 32/14–15:1709–1725

    Google Scholar 

  • Komen GJ, Cavaleri L, Donelan M, Hasselmann K, Hasselmann S, Janssen P (1994) Dynamics and modelling of ocean waves. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Makarynskyy O, Makarynska D, Kuhn M, Featherstone WE (2004) Predicting sea level variations with artificial neural networks at Hillarys Boat Harbour, Western Australia. Estuar Coast Shelf Sci 61:351–360

    Article  Google Scholar 

  • Neumann JE, Hudgens DE, Herter J, Martinich J (2010) Assessing sea-level rise impacts: a GIS-based framework and application to coastal New Jersey. Coast Manag 38:433–455

    Article  Google Scholar 

  • Nicholls RJ, Hanson S, Herweijer C, Patmore N, Hallegatte S, Corfee-Morlot J, Chateau J, Muir-Wood R (2008) Ranking port cities with high exposure and vulnerability to climate extremes: exposure estimates. OECD Environment Working Papers, 1. 10.1787/011766488208

  • Nogueira JD, De L, Amaral RF (2009) Comparação entre os métodos de interpolação (Krigagem e Topo to Raster) na elaboração da batimetria na área da folha Touros - RN. Simpósio Brasileiro de Sensoriamento Remoto 25–30:4117–4123

    Google Scholar 

  • Nursey-Bray M, Blackwell B, Brooks B, Campbell ML, Goldsworthy L, Pateman H, Rodrigues I, Roome M, Wright JT, Francis J, Hewitt CL (2012) Vulnerabilities and adaptation of ports to climate change. J Environ Plann Manag. doi:10.1080/09640568.2012.716363

  • Osthorst W, Manz C (2012) Types of cluster adaptation to climate change. Lessons from the port and logistics sector of Northwest Germany. Marit Pol Manag 39:227–248

    Article  Google Scholar 

  • Pezzoli A, Alfredini P, Arasaki E, Rosso M, Sousa WC Jr (2013a) Impacts of climate changes on management policy of the harbors, land areas and wetlands in São Paulo State Coastline (Brazil). J Climatol Weather Forecasting 1:101. doi:10.4172/jcwf.1000101

    Google Scholar 

  • Pezzoli A, Cartacho DL, Arasaki E, Alfredini P, Sakai RO (2013b) Extreme events assessment methodology coupling rainfall and tidal levels in the coastal flood plain of the Sao Paulo North Coast (Brazil) for Engineering Projects Purposes. J Climatol Weather Forecasting 1:103. doi:10.4172/jcwf.1000103

    Google Scholar 

  • Pezzoli A, Tedeschi G, Resch F (2004) Numerical simulation of strong wind situations near the French Mediterranean Coast: comparison with FETCH data. J Appl Meteorol 43–7:997–1015

    Google Scholar 

  • Sterl A, van de Brink H, de Vries H, Haarsma R, van Meijgard E (2009) An ensemble study of extreme storm surge related to water levels in the North Sea in a changing climate. Ocean Sci 5:369–378

    Article  Google Scholar 

  • Trenberth KE, Jones PD, Ambenje P, Bojariu R, Easterling D, Klein Tank A, Parker D, Rahimzadeh F, Renwick JA, Rusticucci M, Soden B, Zhai P (2007) Observations: surface and atmospheric climate change. In: Solom S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate change. Cambridge University Press, New York, USA

  • WAMDIGroup (1988) The WAM model—a third generation ocean wave prediction model. J Phys Oceanogr 14:1775–1810

    Google Scholar 

  • Young IR (1999) Wind generated ocean waves, vol 2. Elsevier, Amsterdam

    Google Scholar 

Download references

Acknowledgments

This paper has the financial support of CAPES, Human Resources Improvement Agency of Brazilian Government. This paper has the scientific support of CPTEC (Centro de Previsao de Tempo e Estudos Climaticos – Brazil) for the access at the ERA-40 Wave model – ECMWF.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Paolo Alfredini.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Alfredini, P., Arasaki, E., Pezzoli, A. et al. Exposure of Santos Harbor Metropolitan Area (Brazil) to Wave and Storm Surge Climate Changes. Water Qual Expo Health 6, 73–88 (2014). https://doi.org/10.1007/s12403-014-0109-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12403-014-0109-7

Keywords

Navigation