[1822] - Connection between root zone soil moisture and surface energy flux partitioning using modeling, observations and data assimilation for a temperate grassland site in Germany

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Citation
Shrestha, P., Kurtz, W., Vogel, G., Schulz, J. P., Sulis, M., Hendricks-Franssen, H., Kollet, S., Simmer, C., 2018. Connection between root zone soil moisture and surface energy flux partitioning using modeling, observations and data assimilation for a temperate grassland site in Germany. Journal of Geophysical Research, Biogeosciences, 1 - 24. DOI: 10.1029/2016JG003753.
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Identification
Title(s):Main Title: Connection between root zone soil moisture and surface energy flux partitioning using modeling, observations and data assimilation for a temperate grassland site in Germany
Description(s):Abstract: Land surface models (LSMs) with different degrees of complexity are in use as lower boundary conditions for atmospheric models with the simpler LSMs preferentially used in numerical weather forecasting. This study evaluates the second generation TERRA Multi‐Layer (TERRA‐ML) and the third generation Community Land Model (CLM) to better understand the connection between root zone soil moisture and surface energy fluxes, which is important for predictions. Both LSMs were compared in multi‐year, observation‐driven simulations at the Falkenberg grassland site (Germany), and their results were compared to observations. With their default settings for the site, both LSMs tend to overestimate the Bowen ratio, while CLM additionally exhibited a wet bias and a too low soil moisture variance. With modified photosynthetic parameters in CLM, the Bowen ratio improved considerably, but the soil moisture bias and its too low variance remained. Joint data assimilation with soil parameter update significantly improved the soil moisture variance, but degraded the Bowen ratio. We could identify the default shallow root fraction distribution to be responsible for the overestimated Bowen ratio, which could be largely reduced by increasing the root fractions in deeper layers. This study demonstrates, how observations and data assimilation with joint state‐parameter updating can be used to improve the realism of third‐generation LSMs, and thus our understanding of the connection between root zone soil moisture and surface energy flux partitioning.
Identifier(s):DOI: 10.1029/2016JG003753
Responsible Party
Creator(s):Author: Prabhakar Shrestha
Author: Wolfgang Kurtz
Author: Gerd Vogel
Author: Jan Peter Schulz
Author: Mauro Sulis
Author: Harrie-Jan Hendricks-Franssen
Author: Stefan Kollet
Author: Clemens Simmer
Publisher:AGU
Topic
TR32 Topic:Vegetation
Related Sub-project(s):Z4
Subject(s):CRC/TR32 Keywords: Modelling
File Details
File Name:Shrestha_et_al-2018.pdf
Data Type:Text
File Size:2138 kB (2.088 MB)
Date(s):Date Accepted: 2018-08-12
Mime Type:application/pdf
Language:English
Status:Completed
Constraints
Download Permission:Free
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Licence:TR32DB Data policy agreement
Geographic
North:52.82606
East:14.01977
South:52.77251
West:13.91884
Measurement Region:Germany
Measurement Location:--Germany--
Specific Informations - Publication
Status:Published
Review:PeerReview
Year:2018
Type:Article
Article Type:Journal
Source:Journal of Geophysical Research, Biogeosciences
Page Range:1 - 24
Metadata Details
Metadata Creator:Prabhakar Shrestha
Metadata Created:2018-09-07
Metadata Last Updated:2018-09-07
Subproject:Z4
Funding Phase:3
Metadata Language:English
Metadata Version:V43
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