Improving the representation of Arctic clouds in atmospheric models across scales using observations
With a nearly twice as strongly pronounced temperature increase compared to that of the Northern Hemisphere, the Arctic is especially susceptible to global climate change. The effect of clouds on the Arctic warming is especially uncertain, which is caused by misrepresented cloud microphysical proces...
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| Format: | Doctoral or Postdoctoral Thesis |
| Language: | English |
| Published: |
2021
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| Online Access: | https://nbn-resolving.org/urn:nbn:de:bsz:15-qucosa2-752400 https://ul.qucosa.de/id/qucosa%3A75240 https://ul.qucosa.de/api/qucosa%3A75240/attachment/ATT-0/ |
| Summary: | With a nearly twice as strongly pronounced temperature increase compared to that of the Northern Hemisphere, the Arctic is especially susceptible to global climate change. The effect of clouds on the Arctic warming is especially uncertain, which is caused by misrepresented cloud microphysical processes in atmospheric models. This thesis aims at employing a scale- and definition-aware comparison of models and observations and will propose changes how to better parameterize Arctic clouds in atmospheric models. In the first part of this thesis, ECHAM6, which is the atmospheric component of the MPI-ESM global climate model, is compared to spaceborne lidar observations of clouds from the CALIPSO satellite. This comparison shows that ECHAM6 overestimates Arctic low-level, liquid containing clouds over snow- and ice-covered surfaces, which consequently leads to an overestimated amount of radiative energy received by the surface. Using sensitivity studies, it is shown that the probable cause of the model biases in cloud amount and phase is related to misrepresented cloud microphysical parameterization (i.e., parameterization of the Wegener-Bergeron-Findeisen process and of the cloud cover scheme) in ECHAM6. By revising those processes, a better representation of cloud amount and cloud phase is achieved, which helps to more accurately simulated the amount of radiative energy received by the Arctic in ECHAM6. The second part of this thesis will focus on a comparison of kilometer-scale simulation with the ICON model to aircraft observations from the ACLOUD campaign that took place in May/June 2017 over the sea ice-covered Arctic Ocean north of Svalbard, Norway. By comparing measurements of solar and terrestrial surface irradiances during ACLOUD flights to the respective quantities in ICON, it is shown that the model systematically overestimates the transmissivity of the mostly liquid clouds during the campaign. This model bias is traced back to the way cloud condensation nuclei get activated into cloud droplets in the ... |
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