Skip to main content

Climate Change Hazard Identification in the Maputo Area

  • Chapter
  • First Online:
Book cover Climate Change Vulnerability in Southern African Cities

Part of the book series: Springer Climate ((SPCL))

Abstract

As stated in the fourth report of the Intergovernmental Panel on Climate Change (IPCC), climate change is affecting temperatures, sea levels, and storm frequencies in the entire world. While changes in average conditions can have serious consequences by themselves, the main impacts of climate change will be felt through weather extremes and the consequent risk of natural disasters. This chapter provides an overall picture of the climate conditions in the Maputo region, through the analysis of climatic data from the Maputo-Mavalane station (1960–2006). The current climate dynamics are analyzed and future climate scenarios are briefly considered, based on the literature of Mozambique. The study is especially focused on the aspects that most influence the management of a large city like Maputo. As such, attention is centered on the analysis of intense phenomena. The aim of this work is to contribute to local administrators’ understanding of climatic phenomena and their processes.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    See http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ensoyears.shtml.

References

  • Boko M, Niang I, Nyong A, Vogel C, Githeko A, Medany M, Osman-Elasha B, Tabo R, Yanda P (2007) Africa. Climate change 2007: impacts, adaptation and vulnerability. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 433–467

    Google Scholar 

  • Bornstein R D (1968) Observations of the Urban Heat Island effect in New York City. J Appl Meteor 7:575–582. http://dx.doi.org/10.1175/1520-0450(1968)007<0575:OOTUHI>2.0.CO;2

  • Giridharan R, Ganesan S, Lau SSY (2004) Daytime urban heat island effect in high-rise and high-density residential developments in Hong Kong. Energy Build 36(6):525–534. http://dx.doi.org/10.1016/j.enbuild.2003.12.016

  • Gumbel EJ (1954) Statistical theory of extreme values and some practical applications. Applied mathematics series 33. U.S. Department of Commerce, National Bureau of Standards

    Google Scholar 

  • INGC (2009) INGC climate change report: study on the impact of climate change on disaster risk in mozambique. In: Asante K, Brundrit G, Epstein P, Fernandes A, Marques MR, Mavume A, Metzger M, Patt A, Queface A, Sanchez del Valle R, Tadross M, Brito R (eds) Main report. INGC, Mozambique

    Google Scholar 

  • Kottek M, Grieser J, Beck C, Rudolf B, Rubel F (2006) World map of the Köppen-Geiger climate classification updated. Meteorol Z 15:259–263. doi:10.1127/0941-2948/2006/0130

    Article  Google Scholar 

  • Li Q, Zhang H, Liu XJ (2004) Urban heat island effect on annual mean temperature during the last 50 years in China Huang. Theor Appl Climatol 79(3–4):165–174. doi: 10.1007/s00704-004-0065-4

  • McKee TB, NJ Doesken and J Kliest (1993) The relationship of drought frequency and duration to time scales. In: Proceedings of the 8th conference of applied climatology, 17–22 Jan, Anaheim, CA. American Meterological Society, Boston, pp 179–184

    Google Scholar 

  • New M et al (2006) Evidence of trends in daily climate extremes over Southern and West Africa. J Geophys Res 111:D14102. doi:10.1029/2005JD006289

    Article  Google Scholar 

  • Nicholson SE, Kim J (1997) The relationship of the El Nino-Southern oscillation to African rainfall. Int J Climatol 17(2):117–135

    Article  Google Scholar 

  • Oke TR (1982) The energetic basis of the urban heat island. QJR Meteorol Soc 108:1–24. 10.1002/qj.49710845502

  • Wessa P (2011) Free statistics software, office for research development and education, version 1.1.23-r6. http://www.wessa.net/

  • Zebiak SE, Cane MA (1987) A model EI Nino-Southern Oscillation. Mon Weather Rev 115(10):2262–2278

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Maurizio Bacci .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Bacci, M. (2014). Climate Change Hazard Identification in the Maputo Area. In: Macchi, S., Tiepolo, M. (eds) Climate Change Vulnerability in Southern African Cities. Springer Climate. Springer, Cham. https://doi.org/10.1007/978-3-319-00672-7_9

Download citation

Publish with us

Policies and ethics