preliminary analysis on the global features of the ncep cfsv2 seasonal hindcasts

Clicks: 120
ID: 211429
2014
Free PDF
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
Steady

Ranked #141 of 174 articles by views in The Journal of biological chemistry

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 174 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
Sign in to mint
Abstract
The representation of the CFSv2 ocean-atmosphere ensemble hindcasts is investigated during Dec-Jan-Feb (DJF) and Jun-Jul-Aug (JJA) from 1983 to 2010. The skill anomaly correlations showed that in some continents the forecasts do not have dependency with changes in the initial conditions. Also, in both seasons the model has a higher skill at the 0-month lead time with the largest spatial biases occurring over the North America, South America, and Oceania. Over the continents the largest biases in the nonlinearity of El Niño minus La Niña events are found over the eastern South Africa, part of Oceania, and central-southeastern parts of South America. During DJF the main biases are related to double-ITCZ, strengthening of SPCZ, and deepening of the Aleutian and Icelandic low pressures. The simulation of a warmer SST on the eastern of most austral oceans, the strengthening (weakening) of the Subtropical (Polar) Jet over the Southern Hemisphere, and the weakening of the zonal circulation near the Antarctic continent are also found in both seasons. Over the central-eastern Equatorial Pacific a cooler bias in SST is found during JJA. These biases are interpreted by analyses of the simulated global mean-state and their impact on the main patterns of variability.
Reference Key
silva2014advancespreliminary Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Gyrlene A. M. Silva;Lívia M. M. Dutra;Rosmeri P. da Rocha;Tércio Ambrizzi;Érico Leiva
Journal The Journal of biological chemistry
Year 2014
DOI
10.1155/2014/695067
URL
http://dx.doi.org/10.1155/2014/695067
Keywords
meteorology climatology

Citations

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

Comments

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