Improving lake mixing process simulations in the Community Land Model by using K profile parameterization
We improved lake mixing process simulations by applying a vertical mixing scheme, K profile parameterization (KPP), in the Community Land Model (CLM) version 4.5, developed by the National Center for Atmospheric Research. Vertical mixing of the lake water column can significantly affect heat transfe...
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ftcopernicus:oai:publications.copernicus.org:hess77762 2023-05-15T15:04:03+02:00 Improving lake mixing process simulations in the Community Land Model by using K profile parameterization Zhang, Qunhui Jin, Jiming Wang, Xiaochun Budy, Phaedra Barrett, Nick Null, Sarah E. 2019-12-05 application/pdf https://doi.org/10.5194/hess-23-4969-2019 https://www.hydrol-earth-syst-sci.net/23/4969/2019/ eng eng doi:10.5194/hess-23-4969-2019 https://www.hydrol-earth-syst-sci.net/23/4969/2019/ eISSN: 1607-7938 Text 2019 ftcopernicus https://doi.org/10.5194/hess-23-4969-2019 2019-12-24T09:48:07Z We improved lake mixing process simulations by applying a vertical mixing scheme, K profile parameterization (KPP), in the Community Land Model (CLM) version 4.5, developed by the National Center for Atmospheric Research. Vertical mixing of the lake water column can significantly affect heat transfer and vertical temperature profiles. However, the current vertical mixing scheme in CLM requires an arbitrarily enlarged eddy diffusivity to enhance water mixing. The coupled CLM-KPP considers a boundary layer for eddy development, and in the lake interior water mixing is associated with internal wave activity and shear instability. We chose a lake in Arctic Alaska and a lake on the Tibetan Plateau to evaluate this improved lake model. Results demonstrated that CLM-KPP reproduced the observed lake mixing and significantly improved lake temperature simulations when compared to the original CLM. Our newly improved model better represents the transition between stratification and turnover. This improved lake model has great potential for reliable physical lake process predictions and better ecosystem services. Text Arctic Alaska Copernicus Publications: E-Journals Arctic Hydrology and Earth System Sciences 23 12 4969 4982 |
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Open Polar |
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Copernicus Publications: E-Journals |
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ftcopernicus |
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English |
description |
We improved lake mixing process simulations by applying a vertical mixing scheme, K profile parameterization (KPP), in the Community Land Model (CLM) version 4.5, developed by the National Center for Atmospheric Research. Vertical mixing of the lake water column can significantly affect heat transfer and vertical temperature profiles. However, the current vertical mixing scheme in CLM requires an arbitrarily enlarged eddy diffusivity to enhance water mixing. The coupled CLM-KPP considers a boundary layer for eddy development, and in the lake interior water mixing is associated with internal wave activity and shear instability. We chose a lake in Arctic Alaska and a lake on the Tibetan Plateau to evaluate this improved lake model. Results demonstrated that CLM-KPP reproduced the observed lake mixing and significantly improved lake temperature simulations when compared to the original CLM. Our newly improved model better represents the transition between stratification and turnover. This improved lake model has great potential for reliable physical lake process predictions and better ecosystem services. |
format |
Text |
author |
Zhang, Qunhui Jin, Jiming Wang, Xiaochun Budy, Phaedra Barrett, Nick Null, Sarah E. |
spellingShingle |
Zhang, Qunhui Jin, Jiming Wang, Xiaochun Budy, Phaedra Barrett, Nick Null, Sarah E. Improving lake mixing process simulations in the Community Land Model by using K profile parameterization |
author_facet |
Zhang, Qunhui Jin, Jiming Wang, Xiaochun Budy, Phaedra Barrett, Nick Null, Sarah E. |
author_sort |
Zhang, Qunhui |
title |
Improving lake mixing process simulations in the Community Land Model by using K profile parameterization |
title_short |
Improving lake mixing process simulations in the Community Land Model by using K profile parameterization |
title_full |
Improving lake mixing process simulations in the Community Land Model by using K profile parameterization |
title_fullStr |
Improving lake mixing process simulations in the Community Land Model by using K profile parameterization |
title_full_unstemmed |
Improving lake mixing process simulations in the Community Land Model by using K profile parameterization |
title_sort |
improving lake mixing process simulations in the community land model by using k profile parameterization |
publishDate |
2019 |
url |
https://doi.org/10.5194/hess-23-4969-2019 https://www.hydrol-earth-syst-sci.net/23/4969/2019/ |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Alaska |
genre_facet |
Arctic Alaska |
op_source |
eISSN: 1607-7938 |
op_relation |
doi:10.5194/hess-23-4969-2019 https://www.hydrol-earth-syst-sci.net/23/4969/2019/ |
op_doi |
https://doi.org/10.5194/hess-23-4969-2019 |
container_title |
Hydrology and Earth System Sciences |
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23 |
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12 |
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4969 |
op_container_end_page |
4982 |
_version_ |
1766335868609495040 |