English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Coupled ocean-atmosphere modeling and predictions

MPS-Authors
/persons/resource/persons211267

Putrasahan,  Dian
Ocean Statistics, The Ocean in the Earth System, MPI for Meteorology, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Miller, A., Collins, M., Gualdi, S., Jensen, T., Misra, V., Pezzi, L., et al. (2017). Coupled ocean-atmosphere modeling and predictions. Journal of Marine Research, 75, 361-402. doi:10.1357/002224017821836770.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002E-0912-8
Abstract
Key aspects of the current state of the ability of global and regional climate models to represent dynamical processes and precipitation variations are summarized. Interannual, decadal, and globalwarming timescales, wherein the influence of the oceans is relevant and the potential for predictability is highest, are emphasized. Oceanic influences on climate occur throughout the ocean and extend over land to affect many types of climate variations, including monsoons, the El Niño Southern Oscillation, decadal oscillations, and the response to greenhouse gas emissions. The fundamental ideas of coupling between the ocean-atmosphere-land system are explained for these modes in both global and regional contexts. Global coupled climate models are needed to represent and understand the complicated processes involved and allow us to make predictions over land and sea. Regional coupled climate models are needed to enhance our interpretation of the fine-scale response. The mechanisms by which large-scale, low-frequency variations can influence shorter timescale variations and drive regionalscale effects are also discussed. In this light of these processes, the prospects for practical climate predictability are also presented. © 2017 Arthur J. Miller, Mat Collins, Silvio Gualdi, Tommy G. Jensen, Vasu Misra, Luciano Ponzi Pezzi, David W. Pierce, Dian Putrasahan, Hyodae Seo, and Yu-Heng Tseng.