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23 - Geophysical Studies, Natural Hazards, and Climate Change

from Part VII - Future Earth and Risk, Safety and Security

Published online by Cambridge University Press:  22 October 2018

By
Jaime Urrutia-Fucugauchi  and
Ligia Pérez-Cruz
Edited by
Tom Beer ,
Jianping Li  and
Keith Alverson
Tom Beer
Affiliation:
IUGG Commission on Climatic and Environmental Change (CCEC)
Jianping Li
Affiliation:
Beijing Normal University
Keith Alverson
Affiliation:
UNEP International Environmental Technology Centre
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Summary

Case studies, such as the multi-year droughts and wildfires in the southwestern United States and northern Mexico and the intense precipitation and flooding disasters in southern Mexico, illustrate the impacts of repeat events in identified disaster-prone areas. A geophysical perspective indicates that there are a range of tools available, including Earth satellite observation systems, instrumental networks, geophysical observatories, geographic information systems and high-resolution aerial, marine and ground-based geophysical methods. These tools coupled with improved understanding of phenomena, higher computational capacity, risk analysis, databases and numerical simulations provide a scientific-technical framework for developing improved monitoring and response strategies.
Type
Chapter
Information
Global Change and Future Earth
The Geoscience Perspective
 , pp. 313 - 327
Publisher: Cambridge University Press
Print publication year: 2018

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References

AchutaRao, K. and Sperber, K.R. (2006). ENSO simulation in coupled ocean-atmosphere models: Are the models better? Climate Dynamics, 27, 1–15.Google Scholar
Aguilar, E., Peterson, T.C., Obando, P.R., Frutos, R., Retana, J.A., Solera, M., Soley, J., Garcia, I.G., Araujo, R.M., Santos, A.R. and Valle, V.E. (2005). Changes in precipitation and temperature extremes in Central America and northern South America, 1961–2003, Journal of Geophysical Research – Atmospheres, 110, D23.Google Scholar
Alexeev, V.A. (2003). Sensitivity to CO2 doubling of an atmospheric GCM coupled to an oceanic layer: A linear analysis, Climate Dynamics, 20, 775–787.Google Scholar
Allen, M.R. and Ingram, W.J. (2002). Constraints on future changes in climate and the hydrologic cycle, Nature, 419, 224–231.Google Scholar
Alley, R.B., Marotzke, J., Nordhaus, W.D., Overpeck, J.T., Peteet, D.M., Pielke, R.A. Jr., Pierrehumbert, R.T., Rhines, P.B., Stocker, T.F., Talley, L.D., Wallace, J.M. (2003). Abrupt climate change, Science, 299, 2005–2010.Google Scholar
Aparicio, J., Martinez-Austria, P.F., Guitron, A. and Ramirez, A.I. (2008). The October-November 2007 floods in Tabasco, Mexico: An interim diagnosis and courses of action. 4th International Symposium on Flood Defense, Toronto, Ontario, Canada, 58–1–7.Google Scholar
Arredondo-Moreno, T. and Huber-Sannwald, E. (2011). Impact of drought in agriculture in northern Mexico. Coping of Global Environmental Change, Disasters and Security, 5, 875–891.Google Scholar
Arriaga-Ramirez, S. and Cavazos, T. (2010). Regional trends of daily precipitation indices in northern Mexico and southwest United States. Journal of Geophysical Research: Atmospheres, 115, D14. doi:10.1029/2009/DOI3248.Google Scholar
Ault, T.R., Cole, J.E., Overpeck, J.T., Pederson, G.T. and Meko, D.M. (2014). Assessing the risk of persistent drought using climate model simulations and paleoclimate data. Journal of Climate, 27, 7529–7549.Google Scholar
Beer, T. (Ed) (2010). Geophysical Hazards Minimizing Risk Maximizing Awareness. International Year of Planet Earth Series. Dordrecht: Springer Science and Business Media.Google Scholar
Beer, T. and Ismail-Zadeh, A. (Eds) (2003). Risk Science and Sustainability: Science for Reduction of Risk and Sustainable Development of Society. Dordrecht: Kluwer Academic.CrossRefGoogle Scholar
Bronstert, A. (2003). Floods and climate change: Interactions and impacts. Risk Analysis, 23, 545–557.Google Scholar
Chavez, M., Ghil, M. and Urrutia-Fucugauchi, J. (Eds) (2016). Extreme Events: Observations, Modeling and Economics. Wiley, American Geophysical Union Monograph 214.Google Scholar
Cook, B.I., Ault, T.R. and Smerdon, J.E. (2015). Unprecedented 21st century drought risk in the American Southwest and Central Plains. Science Advances, 1(1), e1400082.Google Scholar
Cook, B.I., Cook, E.R., Smerdon, J.E., Seager, R., Williams, A.P., Coats, S., Stahle, D.W. and Diaz-Villanueva, J. (2016). North American megadroughts in the Common Era: Reconstructions and simulations. Wiley Interdisciplinary Reviews: Climate Change, 7(3), 411–432.Google Scholar
Davey, M. et al. (2002). STOIC: A study of coupled GCM climatology and variability in tropical ocean regions. Climate Dynamics, 18, 403–420.Google Scholar
Diffenbaugh, N.S., Swain, D.L. and Touma, D. (2015). Anthropogenic warming has increased drought risk in California. Proceedings of the National Academy of Sciences, 112(13), 3931–3936.CrossRefGoogle ScholarPubMed
Doutriaux-Boucher, M. and Quass, J. (2004). Evaluation of cloud thermodynamic phase parametrization in the LMDZ GCM by using POLDER satellite data. Geophysical Research Letters, 31, L06126.Google Scholar
Emori, S., Hasegawa, A., Suzuki, T. and Dairaku, K. (2005). Validation, parametrization dependence and future projection of daily precipitation simulated with an atmospheric GCM. Geophysical Research Letters, 32, L06708.Google Scholar
FAO, IFAD and WFP (2015). The State of Food Insecurity in the World. Meeting the 2015 international hunger targets: Tacking stock of uneven progress. Rome: Publ. Food and Agriculture Organization, United Nations, FAO.Google Scholar
Flato, G.M. (2005). The Third Generation Coupled Global Climate Model (CGCM3). www.cccma.bc.ec.gc.ca/models/cgcm3.shtml.Google Scholar
FONDEN. (2012). FONDEN El Fondo de Desastres Naturales de México – Una Reseña. Libro Fondo Nacional de Desastres Naturales. Banco Mundial, México: Sistema de Gestión de Riesgo de Desastres.Google Scholar
Francis, P. and Rothery, D. (2000). Remote sensing of active volcanoes. Annual Review of Earth and Planetary Sciences, 28(1), 81–106.Google Scholar
Gleick, P.H. (1989). Climate change, hydrology, and water resources. Reviews of Geophysics, 27(3), 329–344. doi:10.1029/RG027i003p00329.Google Scholar
Griffies, S.M. (2004). Fundamentals of Ocean Climate Models. Princeton, NJ: Princeton University Press.Google Scholar
Griffin, D. and Anchukaities, K.J. (2014). How unusual is the 2012–2014 California drought? Geophysical Research Letters, 41(24), 9017–9023.Google Scholar
Hagemann, S. (2002). An Improved Land Surface Parameter Dataset for Global and Regional Climate Models. Max Planck Institute Meteorology Report 162, Hamburg, Germany 21 pp.Google Scholar
Hallack-Alegria, M., Ramirez-Hernandez, J. and Watkins, D.W. (2012). ENSO-conditions rainfall drought frequency analysis in northwest Baja California, Mexico. International Journal of Climatology, 32(6), 831–842.Google Scholar
Haug, G. et al. (2001). Southward migration of the Intertropical Convergence Zone through the Holocene. Science, 293, 1304–1308.Google Scholar
Herman, J. R., Bhartia, P. K., Torres, O., Hsu, C., Seftor, C. and Celarier, E. (1997). Global distribution of UV‐absorbing aerosols from Nimbus 7/TOMS data. Journal of Geophysical Research: Atmospheres, 102(D14), 16911–16922.Google Scholar
Hook, S.J., Myers, J.J., Thorne, K.J., Fitzgerald, M. and Kahle, A.B. (2001). The MODIS/ASTER airborne simulator (MASTER) – a new instrument for earth science studies. Remote Sensing of Environment, 76, 95–102.Google Scholar
Hwang, L., Jordan, T., Kellog, L., Tromp, J. and Wiellemann, R. (2014). Advancing solid Earth system science through high-performance computing. Computational Infrastructure for Geodynamics Publ., University of California, Davis.Google Scholar
ICSU. (2010). Earth System Science for Global Sustainability: The Grand Challenges. Paris: International Council for Science.Google Scholar
IPCC. (2014). Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the IPCC (Core Writing Team, Pachuri, R.K. and Meyer, L.A. Eds, Geneva, Switzerland.Google Scholar
Ismail-Zadeh, A., Urrutia-Fucugauchi, J., Kijko, A., Takeuchi, K. and Zialapin, I. (Eds) (2014). Extreme Natural Hazards, Disaster Risks and Societal Implications. Cambridge: Cambridge University Press.Google Scholar
Kaufman, Y.J., Tanré, D. and Boucher, O. (2002). A satellite view of aerosols in the climate system. Nature, 419, 215–223.CrossRefGoogle ScholarPubMed
Kearey, P., Brooks, M. and Hill, I. (2013). An Introduction to Geophysical Exploration. John Wiley & Sons.Google Scholar
Kleidon, A. (2004). Global datasets of rooting zone depth inferred from inverse methods. Journal of Climate, 17, 2714–2722.Google Scholar
Lal, R. et al. (2004). Soil carbon sequestration impacts on global climate change and food security. Science, 304, 1623–1627.Google Scholar
Lambert, S.J. and Boer, G.J. (2001). CMIP1 evaluation and intercomparison of coupled climate models. Climate Dynamics, 17, 83–106.Google Scholar
Latif, M. and Keenlyside, N.S. (2009). El Niño/Southern Oscillation response to global warming. Proceedings National Academy of Sciences, 106, 20578–20583.CrossRefGoogle ScholarPubMed
Lawrimore, J., Heim, R. R. Jr, Svoboda, M., Swail, V. and Englehart, P. J. (2002). Beginning a new era of drought monitoring across North America. Bulletin of the American Meteorological Society, 83(8), 1191–1192.Google Scholar
Mann, M.E. and Gleick, P.H. (2015). Climate change and California drought in the 21st century. Proceedings of the National Academy Sciences, 112(13), 3858–3859.Google Scholar
Manning, M.R., Petit, M., Easterling, D., Murphy, J., Patwardhan, A., Rogner, H., Swart, R. and Yohe, G. (Eds) (2004). IPCC workshop on describing scientific uncertainties in climate change to support analysis of risks of options. Geneva: IPCC Workshop Report.Google Scholar
McBean, G.A. (2002). Prediction as the basis for planning and response. Water International, 7, 70–76.CrossRefGoogle Scholar
McPhadden, M., Zhang, X., Hendon, H.H. and Wheeler, M.C. (2006). Large scale dynamics and MJO forcing of ENSO variability. Geophysical Research Letters, 33, L16702.Google Scholar
Mendez, M. and Magaña, V. (2010). Regional aspects of prolonged meteorological droughts over Mexico and Central America. Journal of Climate, 23, 1175–1188.Google Scholar
Medina-Cetina, Z. and Nadim, F. (2008). Stochastic design of an early warning system. Georisk, 2, 223–236.Google Scholar
Milly, P.C.D., Wetherald, R.T., Dunne, K.A. and Delworth, T.L. (2002). Increasing risk of great floods in a changing climate. Nature, 415, 514–517.CrossRefGoogle Scholar
Milly, P.C.D., Dunne, K.A. and Vecchia, A.V. (2005). Global pattern of trends in streamflow and water availability in a changing climate. Nature, 438, 347–350.CrossRefGoogle Scholar
Moss, R., Edmonds, J.A., Hibbard, K.A., Manning, M.R., Rose, S.K., van Vuueren, D.P., Carter, T.R., Emori, S., Kainuma, M., Kram, T., Meehl, G.A., Mitchel, J., Nakicenovic, N., Rihai, K., Smith, S.J., Stouffer, R.J., Thompson, A.M., Weyyant,. P. and Wilbanks, T.J. (2010). The next generation of scenarios for climate change research and assessment. Nature, 463, 747–756.Google Scholar
Mourtzinis, S., Ortiz, B.V. and Damianidis, D. (2016). Climate change and ENSO effects on southwestern US climate patterns and maize yield. Scientific Reports, 6(29777), 1–7.Google Scholar
MunichRe. (2015). NatCatSERVICE Download Center. Natural catastrophes 2014 Report. www.businesswire.com/news/home/20150107005586/en/Review-natural-catastrophes-2014-losses-weather-extremes.Google Scholar
NASA. (2011). National Aeronautics and Space Administration, NPP NPOESS Preparatory Project. www.nasa.gov/NPP.Google Scholar
Parry, M. and Livermoore, M. (2002). Climate change, global food supply and risk of hunger. Issues in Environmental Science and Technology, 17, 109–136.Google Scholar
Paul, F., Huggel, C. and Kääb, A. (2004). Combining satellite multispectral image data and digital elevation model for mapping debris-covered glaciers. Remote Sensing of Environment, 89, 510–518.Google Scholar
Pérez-Cruz, L. (2006). Climate and ocean variability during mid-late Holocene recorded in laminated sediments from Alfonso basin, Gulf of California, Mexico. Quaternary Research, 65, 401–410.Google Scholar
Pérez-Cruz, L. (2013). Hydrological changes and paleoproductivity in the Gulf of California during middle and late Holocene and their relationship with ITCZ and North American Monsoon variability. Quaternary Research, 79, 138–151.Google Scholar
Peterson, T.C., Zhang, A., Brunet-India, M. and Vazquez-Aguirre, J.L. (2008). Changes in North American extremes derived from daily weather data. Journal of Geophysical Research: Atmospheres, 113(D7).Google Scholar
Power, S.B. and Colman, R. (2006). Multi-decadal predictability in a coupled GCM. Climate Dynamics, 26, 247–272.Google Scholar
Ramanathan, V.C.P.J., Crutzen, P.J., Kiehl, J.T. and Rosenfeld, D. (2001). Aerosols, climate, and the hydrological cycle. Science, 294(5549), 2119–2124.Google Scholar
Ramos, J., Marrufo, L. and Gonzalez, F.J. (2009). Use of Lidar data in floodplain risk management planning: The experience of Tabasco 2007 flood. In: Advances in Geoscience and Remote Sensing, Gary Jedlovec (Ed). Available from: www.intechopen.com/books/advances-in-geoscience-and-remote-sensing/use-of-lidar-data-in-floodplain-risk-management-planning-the-experience-of-tabasco-2007-flood.Google Scholar
Reynolds, J.M. (2011). An Introduction to Applied and Environmental Geophysics. John Wiley & Sons.Google Scholar
Rivera-Trejo, F., Soto-Cortés, G. and Méndez-Antonio, B. (2010). The 2007 flood in Tabasco, Mexico: An integral analysis of a devastating phenomenon. International Journal of River Basin Management, 8(3–4), 255–267.CrossRefGoogle Scholar
Rosenzweig, C. and Parry, M.L. (1994). Potential impacts of climate change in world food supply. Nature, 367, 133–138.Google Scholar
Santos-Reyes, J. and Beard, A.N. (2011). Applying the SDMS model to the analysis of the Tabasco flood disaster in Mexico. Human Ecol. Risk Assessment: An International Journal, 17, 643–677.Google Scholar
Schmidhuber, J. and Tubiello, F.R. (2007). Global food security under climate change. Proceedings of the National Academy of Sciences, 104(50), 19703–19708.CrossRefGoogle ScholarPubMed
Seager, R. Goddard, L., Nakamura, J., Henderson, N. and Eun Lee, D. (2014). Dynamical causes for the 2010/11 drought in Texas–northern Mexico. Journal of Hydrometereolgy, 15, 39–68.Google Scholar
Seager, R., Ting, M., Held, I., Kushnir, Y., Lu, J., Vecchi, G., and Li, C. (2007). Model projections of an imminent transition to a more arid climate in southwestern North America. Science, 316(5828), 1181–1184.Google Scholar
Seager, R., Ting, M., Davis, M., Cane, M., Naik, N., Nakamura, J., Li, C., Cook, E. and Stahle, D.W. (2009). Mexican drought: An observational modeling and tree ring variability and climate change. Atmosfera, 22, 1–31.Google Scholar
Silva, I.H., Miranda, F, Beisl, C.H. and Landau, L. (2011). System for flooding alert in tropical coastal zones using GIS and remote sensing: A case study Villahermosa, Mexico. Journal of Coastal Research, 64, 1734–1736.Google Scholar
Soden, B.J. (2000). The sensitivity of the tropical hydrological cycle to ENSO. Journal of Climate, 13, 538–549.Google Scholar
Southgate, R.J., Roth, C., Schneider, J., Shi, P., Onishi, T., Wenger, D., Amman, W., Ogallo, L., Beddington, J. and Murray, V. (2013). Using Science for Disaster Risk Reduction. UNISDR Report, www.preventionweb.net/go/scitech.Google Scholar
Stephens, G.L. (2005). Cloud feedbacks in the climate system: A critical review. Journal of Climate, 18, 237–273.Google Scholar
Svoboda, M. et al., (2002). The Drought Monitor. Bulletin American Metereological Society, 83, 1181–1190.Google Scholar
Swain, D. L., Tsiang, M., Haugen, M., Singh, D., Charland, A., Rajaratnam, B. and Diffenbaugh, N. S. (2014). The extraordinary California drought of 2013/2014: Character, context, and the role of climate change. Bulletin of the American Meteorological Society, 95(9), S3.Google Scholar
Tanré, D., Kaufman, Y. J., Holben, B. E. A., Chatenet, B., Karnieli, A., Lavenu, F., and Smirnov, A. (2001). Climatology of dust aerosol size distribution and optical properties derived from remotely sensed data in the solar spectrum. Journal of Geophysical Research: Atmospheres, 106(D16), 18205–18217.Google Scholar
Trenberth, K.E. (2011). Changes in precipitation with climate change. Climate Research, 47(1–2), 123–138.Google Scholar
UNISDR. (2009). Reducing Disaster Risks Through Science: Issues and Actions. ISDR Scientific and Technical Committee Full Report, Geneva www.unisdr.orgfiles/11543 STCReportlibrary.pdf.Google Scholar
Urrutia-Fucugauchi, J. (2014). Magnetic studies of active volcanoes in Mexico: Implications for volcanic hazards and volcano monitoring. In: Ismail-Zadeh, A. et al. (Eds), Extreme Natural Hazards, Disaster Risks and Societal Implications. Cambridge: Cambridge University Press, 152–166.Google Scholar
Urrutia-Fucugauchi, J. and Pérez-Cruz, L. (2016). Planetary sciences, geodynamics, impacts, mass extinctions and evolution: Developments and interconnections. International Journal Geophysics, 2016, ID 4703168. doi:10.1155/2016/4703168.Google Scholar
WCDRR. (2015). SATELLITE Earth Observations in Support of Disaster Risk Reduction. Special 2015 WCDRR edition. European Space Agency, CEOS Earth Observation Handbook for WCDRR.Google Scholar
Wentz, F.J. and Schabel, M. (2000). Precise climate monitoring using complementary data sets. Nature, 403, 414–416.Google Scholar
Wirtz, A., Löw, P., Mahl, T. and Yildrim, S. (2014). Hitting the poor: Public-private partnership as an option. In: Ismail-Zadeh, A. et al. (Eds), Extreme Natural Hazards, Disaster Risks and Societal Implications. Cambridge: Cambridge University Pres, 386–398.Google Scholar
Woodhouse, C.A., Meko, D.M., MacDonald, G.M., Stahle, D.W. and Cook, E.R. (2010). A 1,200-year perspective of 21st century drought in southwestern North America. Proceedings National Academy Science, 107, 21283–21288.Google Scholar

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