Showing papers by "Baike Xi published in 2023"

Insights of warm cloud biases in CAM5 and CAM6 from the single-column modeling framework and ACE-ENA observations

Abstract: Abstract. There has been a growing concern that most climate models predict too frequent precipitation, likely due to lack of reliable sub-grid variability and vertical variations of microphysical processes in low-level warm clouds. In this study, the warm cloud physics parameterizations in the singe-column configurations of NCAR Community Atmospheric Model version 6 and 5 (SCAM6 and SCAM5, respectively) are evaluated using ground-based and airborne observations from the DOE ARM Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign near the Azores islands during 2017–2018. Eight-month SCM simulations show that both SCAM6 and SCAM5 can generally reproduce marine boundary-layer cloud structure, major macrophysical properties, and their transition. The improvement of warm cloud properties from CAM5 to CAM6 physics can be found compared to the observations. Meanwhile, both physical schemes underestimate cloud liquid water content, cloud droplet size, and rain liquid water content, but overestimate surface rainfall. Modeled cloud condensation nuclei (CCN) concentrations are comparable with aircraft observed ones in the summer but overestimated by a factor of two in winter, largely due to the biases in the long-range transport of anthropogenic aerosols like sulfate. We also test the newly recalibrated autoconversion and accretion parameterizations that account for vertical variations of droplet size. Compared to the observations, more significant improvement is found in SCAM5 than in SCAM6. This result is likely explained by the introduction of sub-grid variations of cloud properties in CAM6 cloud microphysics, which further suppresses the scheme sensitivity to individual warm rain microphysical parameters. The predicted cloud susceptibilities to CCN perturbations in CAM6 are within a reasonable range, indicating significant progress since CAM5 which produces too strong aerosol indirect effect. The present study emphasizes the importance of understanding biases in cloud physics parameterizations by combining SCM with in situ observations.

Assessing Radiative Impacts of African Smoke Aerosols over the Southeastern Atlantic Ocean

Abstract: Biomass burning smoke aerosols exhibit complex impacts on the temperature profile of the atmosphere and cloud development. Central Africa is a region where smoke aerosols are constantly being transported westward over the remote southeastern Atlantic Ocean. A dedicated measurement platform located on Ascension Island, maintained by the U. S. Department of Energy, observed several plumes of biomass burning smoke during the 2016 and 2017 austral burn season months. It was found that the smoke aerosols displayed different radiative properties while readily activating as cloud condensation nuclei. An anomalously strong African Easterly Jet was responsible for facilitating extreme fire conditions in 2016. During the 2017 burn season, an anomalously weaker jet led to more mixing of mineral dust and marine aerosols which were more efficient at cooling the atmosphere than in 2016.

Insights of warm cloud biases in CAM5 and CAM6 from the single-column modeling 1 framework and ACE-ENA observations 2

Abstract: 11 There has been a growing concern that most climate models predict too frequent precipitation, 12 likely due to lack of reliable sub-grid variability and vertical variations of microphysical processes 13 in low-level warm clouds. In this study, the warm cloud physics parameterizations in the singe- 14 column configurations of NCAR Community Atmospheric Model version 6 and 5 (SCAM6 and 15 SCAM5, respectively) are evaluated using ground-based and airborne observations from the DOE 16 ARM Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign 17 near the Azores islands during 2017-2018. Eight-month SCM simulations show that both SCAM6 18 and SCAM5 can generally reproduce marine boundary-layer cloud structure, major macrophysical 19 properties, and their transition. The improvement of warm cloud properties from CAM5 to CAM6 20 physics can be found compared to the observations. Meanwhile, both physical schemes 21 underestimate cloud liquid water content, cloud droplet size, and rain liquid water content, but 22 overestimate surface rainfall. Modeled cloud condensation nuclei (CCN) concentrations are 23 comparable with aircraft observed ones in the summer but overestimated by a factor of two in 24 winter, largely due to the biases in the long-range transport of anthropogenic aerosols like sulfate. 25 We also test the newly recalibrated autoconversion and accretion parameterizations that account 26 for vertical variations of droplet size. Compared to the observations, more significant improvement 27 is found in SCAM5 than in SCAM6. This result is likely explained by the introduction of sub-grid 28 variations of cloud properties in CAM6 cloud microphysics, which further suppresses the scheme 29 sensitivity to individual warm rain microphysical parameters. The predicted cloud susceptibilities 30 to CCN perturbations in CAM6 are within a reasonable range, indicating significant progress since 31 CAM5 which produces too strong aerosol indirect effect. The present study emphasizes the 32 importance of understanding biases in cloud physics parameterizations by combining SCM with 33 in situ observations.