Coupled ocean–atmosphere modeling and predictions

Clicks: 1
ID: 298841
2017
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #1,065 of 1,397 articles by views in journal of marine research

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 1,397 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
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.
Reference Key
openalex_W2756068859 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Arthur J. Miller, Matthew Collins, Silvio Gualdi, Tommy G. Jensen, Vasu Misra, Luciano Ponzi Pezzi, David W. Pierce, Dian Putrasahan, Hyodae Seo, Yu‐Heng Tseng
Journal journal of marine research
Year 2017
DOI
10.1357/002224017821836770
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.