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Improved leading modes of interannual variability of the Asian-Australian monsoon in an AGCM via incorporating a stochastic multicloud model

Overview of attention for article published in Climate Dynamics, November 2019
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Mentioned by

twitter
1 tweeter

Readers on

mendeley
2 Mendeley
Title
Improved leading modes of interannual variability of the Asian-Australian monsoon in an AGCM via incorporating a stochastic multicloud model
Published in
Climate Dynamics, November 2019
DOI 10.1007/s00382-019-05025-3
Authors

Libin Ma, Zijun Jiang

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 50%
Researcher 1 50%
Readers by discipline Count As %
Earth and Planetary Sciences 2 100%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 November 2019.
All research outputs
#12,365,516
of 13,976,883 outputs
Outputs from Climate Dynamics
#2,532
of 3,493 outputs
Outputs of similar age
#220,314
of 267,473 outputs
Outputs of similar age from Climate Dynamics
#94
of 182 outputs
Altmetric has tracked 13,976,883 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,493 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.9. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 267,473 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 182 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.