Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Which ENSO index best represents its global influences?
by
Li, Xiaofan
, Ding, Ruiqiang
, Hu, Zeng-Zhen
, Liu, Yunyun
in
Australia
/ Climate
/ climate models
/ Climate prediction
/ Climate variability
/ Climatic indexes
/ Climatology
/ Convection
/ Correlation
/ Earth and Environmental Science
/ Earth Sciences
/ El Nino
/ El Nino phenomena
/ El Nino-Southern Oscillation event
/ Geophysics/Geodesy
/ Global climate
/ Global precipitation
/ Influence
/ Mean precipitation
/ Oceanography
/ Physics
/ Precipitation
/ Representations
/ Southern Oscillation
/ Southern Oscillation Index
/ Surface temperature
2023
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Which ENSO index best represents its global influences?
by
Li, Xiaofan
, Ding, Ruiqiang
, Hu, Zeng-Zhen
, Liu, Yunyun
in
Australia
/ Climate
/ climate models
/ Climate prediction
/ Climate variability
/ Climatic indexes
/ Climatology
/ Convection
/ Correlation
/ Earth and Environmental Science
/ Earth Sciences
/ El Nino
/ El Nino phenomena
/ El Nino-Southern Oscillation event
/ Geophysics/Geodesy
/ Global climate
/ Global precipitation
/ Influence
/ Mean precipitation
/ Oceanography
/ Physics
/ Precipitation
/ Representations
/ Southern Oscillation
/ Southern Oscillation Index
/ Surface temperature
2023
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Which ENSO index best represents its global influences?
by
Li, Xiaofan
, Ding, Ruiqiang
, Hu, Zeng-Zhen
, Liu, Yunyun
in
Australia
/ Climate
/ climate models
/ Climate prediction
/ Climate variability
/ Climatic indexes
/ Climatology
/ Convection
/ Correlation
/ Earth and Environmental Science
/ Earth Sciences
/ El Nino
/ El Nino phenomena
/ El Nino-Southern Oscillation event
/ Geophysics/Geodesy
/ Global climate
/ Global precipitation
/ Influence
/ Mean precipitation
/ Oceanography
/ Physics
/ Precipitation
/ Representations
/ Southern Oscillation
/ Southern Oscillation Index
/ Surface temperature
2023
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Which ENSO index best represents its global influences?
2023
Request Book From Autostore
and Choose the Collection Method
Overview
Knowledge about the El Niño-Southern Oscillation (ENSO) is the scientific foundation for short-term climate prediction, due to its global influence. In operation and research communities, the ENSO state is often represented by various ENSO indices. However, it is unclear which index is the strongest for capturing ENSO’s global climate influence. By examining the correlations of eleven ENSO indices with monthly mean global precipitation and surface temperature (TS), we illustrate the similarities and differences in the connections, identify the strongest index, and discuss the physics behind the differences. For the global average, the Niño3.4 and relative Niño3.4 indices are the two strongest indices and the warm pool index is the weakest one for capturing the impact of ENSO on global precipitation, while the Niño4 and Niño3.4 indices are the two strongest indices and the Modoki index is the weakest one for capturing the ENSO’s influence on TS variations. In addition to the dependence on the variables and ENSO indices, the representations of climate variability associated with ENSO depend on the region. For example, in Australia, the southern oscillation index has the most significant correlations with precipitation and its correlations with TS are relatively weaker than those of some of the other indices. These differences associated with the various ENSO indices may be due to their representation of the deep convection in the tropical Pacific. These results can serve as a benchmark to understand the global picture of monthly mean precipitation and TS influenced by ENSO and to verify model’s ability in capturing these connections.
Publisher
Springer Berlin Heidelberg,Springer Nature B.V
Subject
This website uses cookies to ensure you get the best experience on our website.