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...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Text |
| Language: | unknown |
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Hosted by Utah State University Libraries
2019
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| Subjects: | |
| Online Access: | https://digitalcommons.usu.edu/wats_facpub/1102 https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=2122&context=wats_facpub |
| 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. |
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