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Toward enhanced understanding and projections of climate extremes using physics-guided data mining techniques

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Ganguly, A. R., Kodra, E. A., Agrawal, A., Banerjee, A., Boriah, S., Chatterjee, Sn., Chatterjee, So., Choudhary, A., Das, D., Faghmous, J., Ganguli, P., Ghosh, S., Hayhoe, K., Hays, C., Hendrix, W., Fu, Q., Kawale, J., Kumar, D., Kumar, V., Liao, W., Liess, S., Mawalagedara, R., Mithal, V., Oglesby, R., Salvi, K., Snyder, P. K., Steinhaeuser, K., Wang, D., and Wuebbles, D., 2014-07-28, Toward enhanced understanding and projections of climate extremes using physics-guided data mining techniques: Nonlinear Processes in Geophysics, v. 21, iss. 4.

Summary

Extreme events such as heat waves, cold spells, floods, droughts, tropical cyclones, and tornadoes have potentially devastating impacts on natural and engineered systems and human communities worldwide. Stakeholder decisions about critical infrastructures, natural resources, emergency preparedness and humanitarian aid typically need to be made at local to regional scales over seasonal to decadal planning horizons. However, credible climate change attribution and reliable projections at more localized and shorter time scales remain grand challenges. Long-standing gaps include inadequate understanding of processes such as cloud physics and ocean–land–atmosphere interactions, limitations of physics-based computer models, and the importance [...]

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  • National and Regional Climate Adaptation Science Centers
  • Southeast CASC

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Created from Item #5408e31fe4b0621a5983c437

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journalNonlinear Processes in Geophysics
parts
typevolume
value21
typeissue
value4
typeissn
value1023-5809
typedoi
valuedoi:10.5194/npg-21-777-2014
typestartPage
value777
typeendPage
value795

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