Abstract Langmuir turbulence, a dominant process in the ocean surface boundary layer, drives substantial vertical mixing that influences temperature, salinity, mixed layer depth, and biogeochemical tracer distributions. While direct resolution of Langmuir turbulence in ocean and climate models remains computationally prohibitive, its effects are commonly parameterized, frequently within established turbulent mixing frameworks like the K‐profile parameterization (KPP). This study utilizes a modified KPP that determines boundary layer depth through an integral criterion, diverging from the conventional KPP's dependence on the bulk Richardson number. The modified KPP demonstrates markedly lower sensitivity to model vertical resolution than its conventional counterpart. Building upon this modified KPP framework, we introduce an innovative parameterization scheme for Langmuir mixing effects. We evaluate the performance of this new scheme against existing approaches using a one‐dimensional (1D) column model across four different scenarios, incorporating validation against both large eddy simulation (LES) results and field measurements. Our analysis reveals that the new Langmuir mixing scheme, explicitly designed for the modified KPP framework, performs competitively while maintaining reduced sensitivity to vertical resolution.
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Improving lake mixing process simulations in the Community Land Model by using <i>K</i> profile parameterization
Abstract. 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.
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- Award ID(s):
- 1637459
- PAR ID:
- 10213330
- Date Published:
- Journal Name:
- Hydrology and Earth System Sciences
- Volume:
- 23
- Issue:
- 12
- ISSN:
- 1607-7938
- Page Range / eLocation ID:
- 4969 to 4982
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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