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Investigating Runoff Sensitivity in the Land-Surface Model MATSIRO to Reduce Low Runoff Bias

Overview of attention for article published in Journal of the Meteorological Society of Japan, January 2021
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

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5 X users
facebook
1 Facebook page

Citations

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3 Dimensions

Readers on

mendeley
5 Mendeley
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Title
Investigating Runoff Sensitivity in the Land-Surface Model MATSIRO to Reduce Low Runoff Bias
Published in
Journal of the Meteorological Society of Japan, January 2021
DOI 10.2151/jmsj.2021-034
Authors

Kumiko TAKATA, Naota HANASAKI

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 20%
Unknown 4 80%
Readers by discipline Count As %
Environmental Science 1 20%
Computer Science 1 20%
Unknown 3 60%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 17 October 2021.
All research outputs
#7,966,302
of 25,387,668 outputs
Outputs from Journal of the Meteorological Society of Japan
#138
of 1,021 outputs
Outputs of similar age
#187,402
of 519,506 outputs
Outputs of similar age from Journal of the Meteorological Society of Japan
#10
of 76 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 1,021 research outputs from this source. They receive a mean Attention Score of 3.2. This one has done well, scoring higher than 85% of its peers.
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 519,506 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.
We're also able to compare this research output to 76 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.