Identifying Model Biases in the Arctic Boundary Layer: Insights From Comparing the Community Atmosphere Model to the MOSAiC Field Campaign
Jacobs, A., Bacmeister, J., Bitz, C., Roy, P.. (2025). Identifying Model Biases in the Arctic Boundary Layer: Insights From Comparing the Community Atmosphere Model to the MOSAiC Field Campaign. , doi:https://doi.org/10.5065/t3sk-6v46
| Title | Identifying Model Biases in the Arctic Boundary Layer: Insights From Comparing the Community Atmosphere Model to the MOSAiC Field Campaign |
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| Genre | Manuscript |
| Author(s) | Ariel Jacobs, Julio Bacmeister, C. Bitz, Puja Roy |
| Abstract | The Arctic is warming faster than the rest of the globe and this trend is expected to continue going forward. Therefore, it is imperative to study the weather patterns of the Arctic. One important component of the Arctic system is the Arctic atmospheric boundary layer. While regional and forecast models have been compared to observations, this is the first study to compare the Community Atmosphere Model (CAM) to Arctic boundary layer observations from MOSAiC data. We aim to uncover model biases associated with the atmospheric boundary layer scheme and the microphysics parameterizations used in Community Earth System Model version 2.2 (CESM2.2) and more recent development versions of CAM (CAM7). We have identified a low liquid water path (LWP) bias in winter in the Arctic in nudged simulations using CAM7. We discovered this had implications for a low bias in downwelling longwave radiation, especially in December 2019. We attempted to rectify this bias by modifying the microphysics in the model. While this improved the LWP and downwelling radiation in January, there was still a large discrepancy in December. Analyzing model profiles for December 2019 for times in which MOSAiC LWP was significant suggested that the boundary layer scheme may be contributing to the bias as well. We plan to run more simulations with a different radiative transfer scheme, different sub-stepping in the model, and tuning of Cloud Layers Unified By Binormals (CLUBB), the current boundary layer parameterization in CAM7, to potentially address the low LWP bias. |
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| Publication Date | Aug 1, 2025 |
| Publisher's Version of Record | https://doi.org/10.5065/t3sk-6v46 |
| OpenSky Citable URL | https://n2t.net/ark:/85065/d78w3jr6 |
| OpenSky Listing | View on OpenSky |
| CGD Affiliations | AMP |