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Evaluating uncertainty in estimates of soil moisture memory with a reverse ensemble approach

Abstract:

Soil moisture memory is a key component of seasonal predictability. However uncertainty in current memory estimates is not clear and it is not obvious to what extent these are dependent on model uncertainties. To address this question, we perform a global sensitivity analysis of memory to key hydraulic parameters, using an uncoupled version of the land surface model H-TESSEL. Results show significant dependency of estimates of memory and its uncertainty on these parameters, suggesting that...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.5194/hess-20-2737-2016

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Atmos Ocean & Planet Physics
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Role:
Author
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Funding agency for:
Cloke, H
Grant:
NE/L010488/1
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Funding agency for:
Macleod, D
Grant:
308378
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Funding agency for:
Pappenberger, F
Grant:
641811
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Funding agency for:
Weisheimer, A
Grant:
308378
Publisher:
European Geosciences Union Publisher's website
Journal:
Hydrology and Earth System Sciences Journal website
Volume:
20
Pages:
2737-2743
Publication date:
2016-02-17
Acceptance date:
2016-02-12
DOI:
ISSN:
1607-7938
Source identifiers:
629056
Pubs id:
pubs:629056
UUID:
uuid:d0d2d512-ae84-49e0-a2b1-c658d07c9397
Local pid:
pubs:629056
Deposit date:
2016-06-20

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