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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Bibliographic Details
Published in:Hydrology and Earth System Sciences
Main Authors: Q. Zhang, J. Jin, X. Wang, P. Budy, N. Barrett, S. E. Null
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2019
Subjects:
geo
Online Access:https://doi.org/10.5194/hess-23-4969-2019
https://www.hydrol-earth-syst-sci.net/23/4969/2019/hess-23-4969-2019.pdf
https://doaj.org/article/268af9164f6f4a77ba5266def5161124
Description
Summary: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.