Parameterizing the Heterogeneous Liquid‐Ice Mixing in Modeling Ice Growth Through the Wegener‐Bergeron‐Findeisen Process in CAM6
Abstract Accurate representation of cloud phase partitioning is critical for understanding the cloud feedback to climate change, but the supercooled liquid fraction is often underestimated in global climate models, in part due to the assumption of homogeneous distributions of hydrometeors in mixed‐p...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-04-01
|
| Series: | Geophysical Research Letters |
| Online Access: | https://doi.org/10.1029/2024GL114036 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849726378951311360 |
|---|---|
| author | Jing Yang Jianqiao Lu Yuting Deng Yong Wang Chunsong Lu Yan Yin Zhien Wang Xiaoqin Jing Kang Yang |
| author_facet | Jing Yang Jianqiao Lu Yuting Deng Yong Wang Chunsong Lu Yan Yin Zhien Wang Xiaoqin Jing Kang Yang |
| author_sort | Jing Yang |
| collection | DOAJ |
| description | Abstract Accurate representation of cloud phase partitioning is critical for understanding the cloud feedback to climate change, but the supercooled liquid fraction is often underestimated in global climate models, in part due to the assumption of homogeneous distributions of hydrometeors in mixed‐phase clouds. In this study, we take into account the heterogeneous liquid‐ice mixing in modeling the ice depositional growth using airborne in situ measurements. The impact of heterogeneous liquid‐ice mixing on the Wegener‐Bergeron‐Findeisen process is parameterized as the fraction of ice that is mixed with liquid water, which is a function of liquid‐ice mixing homogeneity and liquid fraction. The liquid‐ice mixing homogeneity, quantified using the information entropy theory, is parameterized using the total condensed water content and temperature. With this observationally constrained parameterization incorporated in the Community Atmospheric Model version 6, the modeled cloud phase partitioning and cloud radiative forcing are improved. |
| format | Article |
| id | doaj-art-e88cc01987c74c20af8c5f50ab16d7c0 |
| institution | DOAJ |
| issn | 0094-8276 1944-8007 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geophysical Research Letters |
| spelling | doaj-art-e88cc01987c74c20af8c5f50ab16d7c02025-08-20T03:10:11ZengWileyGeophysical Research Letters0094-82761944-80072025-04-01527n/an/a10.1029/2024GL114036Parameterizing the Heterogeneous Liquid‐Ice Mixing in Modeling Ice Growth Through the Wegener‐Bergeron‐Findeisen Process in CAM6Jing Yang0Jianqiao Lu1Yuting Deng2Yong Wang3Chunsong Lu4Yan Yin5Zhien Wang6Xiaoqin Jing7Kang Yang8Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC‐FEMD) China Meteorological Administration Aerosol‐Cloud and Precipitation Key Laboratory Nanjing University of Information Science & Technology Nanjing ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC‐FEMD) China Meteorological Administration Aerosol‐Cloud and Precipitation Key Laboratory Nanjing University of Information Science & Technology Nanjing ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC‐FEMD) China Meteorological Administration Aerosol‐Cloud and Precipitation Key Laboratory Nanjing University of Information Science & Technology Nanjing ChinaShanghai Key Laboratory of Ocean‐land‐atmosphere Boundary Dynamics and Climate Change Department of Atmospheric and Oceanic Sciences Fudan University Shanghai ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC‐FEMD) China Meteorological Administration Aerosol‐Cloud and Precipitation Key Laboratory Nanjing University of Information Science & Technology Nanjing ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC‐FEMD) China Meteorological Administration Aerosol‐Cloud and Precipitation Key Laboratory Nanjing University of Information Science & Technology Nanjing ChinaSchool of Marine and Atmospheric Sciences Stony Brook University Stony Brook NY USACollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC‐FEMD) China Meteorological Administration Aerosol‐Cloud and Precipitation Key Laboratory Nanjing University of Information Science & Technology Nanjing ChinaSchool of Marine and Atmospheric Sciences Stony Brook University Stony Brook NY USAAbstract Accurate representation of cloud phase partitioning is critical for understanding the cloud feedback to climate change, but the supercooled liquid fraction is often underestimated in global climate models, in part due to the assumption of homogeneous distributions of hydrometeors in mixed‐phase clouds. In this study, we take into account the heterogeneous liquid‐ice mixing in modeling the ice depositional growth using airborne in situ measurements. The impact of heterogeneous liquid‐ice mixing on the Wegener‐Bergeron‐Findeisen process is parameterized as the fraction of ice that is mixed with liquid water, which is a function of liquid‐ice mixing homogeneity and liquid fraction. The liquid‐ice mixing homogeneity, quantified using the information entropy theory, is parameterized using the total condensed water content and temperature. With this observationally constrained parameterization incorporated in the Community Atmospheric Model version 6, the modeled cloud phase partitioning and cloud radiative forcing are improved.https://doi.org/10.1029/2024GL114036 |
| spellingShingle | Jing Yang Jianqiao Lu Yuting Deng Yong Wang Chunsong Lu Yan Yin Zhien Wang Xiaoqin Jing Kang Yang Parameterizing the Heterogeneous Liquid‐Ice Mixing in Modeling Ice Growth Through the Wegener‐Bergeron‐Findeisen Process in CAM6 Geophysical Research Letters |
| title | Parameterizing the Heterogeneous Liquid‐Ice Mixing in Modeling Ice Growth Through the Wegener‐Bergeron‐Findeisen Process in CAM6 |
| title_full | Parameterizing the Heterogeneous Liquid‐Ice Mixing in Modeling Ice Growth Through the Wegener‐Bergeron‐Findeisen Process in CAM6 |
| title_fullStr | Parameterizing the Heterogeneous Liquid‐Ice Mixing in Modeling Ice Growth Through the Wegener‐Bergeron‐Findeisen Process in CAM6 |
| title_full_unstemmed | Parameterizing the Heterogeneous Liquid‐Ice Mixing in Modeling Ice Growth Through the Wegener‐Bergeron‐Findeisen Process in CAM6 |
| title_short | Parameterizing the Heterogeneous Liquid‐Ice Mixing in Modeling Ice Growth Through the Wegener‐Bergeron‐Findeisen Process in CAM6 |
| title_sort | parameterizing the heterogeneous liquid ice mixing in modeling ice growth through the wegener bergeron findeisen process in cam6 |
| url | https://doi.org/10.1029/2024GL114036 |
| work_keys_str_mv | AT jingyang parameterizingtheheterogeneousliquidicemixinginmodelingicegrowththroughthewegenerbergeronfindeisenprocessincam6 AT jianqiaolu parameterizingtheheterogeneousliquidicemixinginmodelingicegrowththroughthewegenerbergeronfindeisenprocessincam6 AT yutingdeng parameterizingtheheterogeneousliquidicemixinginmodelingicegrowththroughthewegenerbergeronfindeisenprocessincam6 AT yongwang parameterizingtheheterogeneousliquidicemixinginmodelingicegrowththroughthewegenerbergeronfindeisenprocessincam6 AT chunsonglu parameterizingtheheterogeneousliquidicemixinginmodelingicegrowththroughthewegenerbergeronfindeisenprocessincam6 AT yanyin parameterizingtheheterogeneousliquidicemixinginmodelingicegrowththroughthewegenerbergeronfindeisenprocessincam6 AT zhienwang parameterizingtheheterogeneousliquidicemixinginmodelingicegrowththroughthewegenerbergeronfindeisenprocessincam6 AT xiaoqinjing parameterizingtheheterogeneousliquidicemixinginmodelingicegrowththroughthewegenerbergeronfindeisenprocessincam6 AT kangyang parameterizingtheheterogeneousliquidicemixinginmodelingicegrowththroughthewegenerbergeronfindeisenprocessincam6 |