Metamodeling of Droplet Activation for Global Climate Models
The nucleation of cloud droplets from the ambient aerosol is a critical physical process that must be resolved for global models to faithfully predict aerosol–cloud interactions and aerosol indirect effects on climate. To better represent droplet nucleation from a complex, multimodal, and multicompo...
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| Format: | Article |
| Language: | en_US |
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American Meteorological Society
2017
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| Online Access: | http://hdl.handle.net/1721.1/108357 https://orcid.org/0000-0002-8270-4831 https://orcid.org/0000-0002-3979-4747 |
| _version_ | 1826206985240969216 |
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| author | Rothenberg, Daniel Alexander Wang, Chien |
| author2 | Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences |
| author_facet | Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences Rothenberg, Daniel Alexander Wang, Chien |
| author_sort | Rothenberg, Daniel Alexander |
| collection | MIT |
| description | The nucleation of cloud droplets from the ambient aerosol is a critical physical process that must be resolved for global models to faithfully predict aerosol–cloud interactions and aerosol indirect effects on climate. To better represent droplet nucleation from a complex, multimodal, and multicomponent aerosol population within the context of a global model, a new metamodeling framework is applied to derive an efficient and accurate activation parameterization. The framework applies polynomial chaos expansion to a detailed parcel model in order to derive an emulator that maps thermodynamic and aerosol parameters to the supersaturation maximum achieved in an adiabatically ascending parcel and can be used to diagnose droplet number from a single lognormal aerosol mode. The emulator requires much less computational time to build, store, and evaluate than a high-dimensional lookup table. Compared to large sample sets from the detailed parcel model, the relative error in the predicted supersaturation maximum and activated droplet number computed with the best emulator is -0.6% ± 9.9% and 0.8% ± 17.8% (one standard deviation), respectively. On average, the emulators constructed here are as accurate and between 10 and 17 times faster than a leading physically based activation parameterization. Because the underlying parcel model being emulated resolves size-dependent droplet growth factors, the emulator captures kinetic limitations on activation. The results discussed in this work suggest that this metamodeling framework can be extended to accurately account for the detailed activation of a complex aerosol population in an arbitrary coupled global aerosol–climate model. |
| first_indexed | 2024-09-23T13:41:41Z |
| format | Article |
| id | mit-1721.1/108357 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T13:41:41Z |
| publishDate | 2017 |
| publisher | American Meteorological Society |
| record_format | dspace |
| spelling | mit-1721.1/1083572022-10-01T16:35:05Z Metamodeling of Droplet Activation for Global Climate Models Rothenberg, Daniel Alexander Wang, Chien Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences Rothenberg, Daniel Alexander Wang, Chien The nucleation of cloud droplets from the ambient aerosol is a critical physical process that must be resolved for global models to faithfully predict aerosol–cloud interactions and aerosol indirect effects on climate. To better represent droplet nucleation from a complex, multimodal, and multicomponent aerosol population within the context of a global model, a new metamodeling framework is applied to derive an efficient and accurate activation parameterization. The framework applies polynomial chaos expansion to a detailed parcel model in order to derive an emulator that maps thermodynamic and aerosol parameters to the supersaturation maximum achieved in an adiabatically ascending parcel and can be used to diagnose droplet number from a single lognormal aerosol mode. The emulator requires much less computational time to build, store, and evaluate than a high-dimensional lookup table. Compared to large sample sets from the detailed parcel model, the relative error in the predicted supersaturation maximum and activated droplet number computed with the best emulator is -0.6% ± 9.9% and 0.8% ± 17.8% (one standard deviation), respectively. On average, the emulators constructed here are as accurate and between 10 and 17 times faster than a leading physically based activation parameterization. Because the underlying parcel model being emulated resolves size-dependent droplet growth factors, the emulator captures kinetic limitations on activation. The results discussed in this work suggest that this metamodeling framework can be extended to accurately account for the detailed activation of a complex aerosol population in an arbitrary coupled global aerosol–climate model. National Science Foundation (U.S.) (grant 1122374) National Science Foundation (U.S.) (AGS-1339264) United States. Department of Energy. Office of Science (DE-FG02-94ER61937) 2017-04-21T18:34:37Z 2017-04-21T18:34:37Z 2016-02 2015-08 Article http://purl.org/eprint/type/JournalArticle 0022-4928 1520-0469 http://hdl.handle.net/1721.1/108357 Rothenberg, Daniel and Wang, Chien. “Metamodeling of Droplet Activation for Global Climate Models.” Journal of the Atmospheric Sciences 73, no. 3 (March 2016): 1255–1272. © American Meteorological Society https://orcid.org/0000-0002-8270-4831 https://orcid.org/0000-0002-3979-4747 en_US http://dx.doi.org/10.1175/jas-d-15-0223.1 Journal of the Atmospheric Sciences Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf American Meteorological Society American Meteorological Society |
| spellingShingle | Rothenberg, Daniel Alexander Wang, Chien Metamodeling of Droplet Activation for Global Climate Models |
| title | Metamodeling of Droplet Activation for Global Climate Models |
| title_full | Metamodeling of Droplet Activation for Global Climate Models |
| title_fullStr | Metamodeling of Droplet Activation for Global Climate Models |
| title_full_unstemmed | Metamodeling of Droplet Activation for Global Climate Models |
| title_short | Metamodeling of Droplet Activation for Global Climate Models |
| title_sort | metamodeling of droplet activation for global climate models |
| url | http://hdl.handle.net/1721.1/108357 https://orcid.org/0000-0002-8270-4831 https://orcid.org/0000-0002-3979-4747 |
| work_keys_str_mv | AT rothenbergdanielalexander metamodelingofdropletactivationforglobalclimatemodels AT wangchien metamodelingofdropletactivationforglobalclimatemodels |