{"title":"The Sensitivity of Supercell Cold Pools to the Lifting Condensation Level and the Predicted Particle Properties Microphysics Scheme","authors":"S. Murdzek, Yvette P. Richardson, P. Markowski","doi":"10.1175/mwr-d-23-0092.1","DOIUrl":null,"url":null,"abstract":"\nPrevious work found that cold pools in ordinary convection are more sensitive to the microphysics scheme when the lifting condensation level (LCL) is higher owing to a greater evaporation potential, which magnifies microphysical uncertainties. In the current study, we explore whether the same reasoning can be applied to supercellular cold pools. To do this, four perturbed-microphysics ensembles are run, with each using an environment with a different LCL. Similar to ordinary convection, the sensitivity of supercellular cold pools to the microphysics increases with higher LCLs, though the physical reasoning for this increase in sensitivity differs from a previous study. Using buoyancy budgets along parcel trajectories that terminate in the cold pool, we find that negative buoyancy generated by microphysical cooling is partially countered by a decrease in environmental potential temperatures as the parcel descends. This partial erosion of negative buoyancy as parcels descend is most pronounced in the low-LCL storms, which have steeper vertical profiles of environmental potential temperature in the lower atmosphere. When this erosion is accounted for, the strength of the strongest cold pools in the low-LCL ensemble is reduced, resulting in a narrower distribution of cold pool strengths. This narrower distribution is indicative of reduced sensitivity to the microphysics. These results suggest that supercell behavior and supercell hazards (e.g., tornadoes) may be more predictable in low-LCL environments.","PeriodicalId":18824,"journal":{"name":"Monthly Weather Review","volume":null,"pages":null},"PeriodicalIF":2.8000,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Monthly Weather Review","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1175/mwr-d-23-0092.1","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Previous work found that cold pools in ordinary convection are more sensitive to the microphysics scheme when the lifting condensation level (LCL) is higher owing to a greater evaporation potential, which magnifies microphysical uncertainties. In the current study, we explore whether the same reasoning can be applied to supercellular cold pools. To do this, four perturbed-microphysics ensembles are run, with each using an environment with a different LCL. Similar to ordinary convection, the sensitivity of supercellular cold pools to the microphysics increases with higher LCLs, though the physical reasoning for this increase in sensitivity differs from a previous study. Using buoyancy budgets along parcel trajectories that terminate in the cold pool, we find that negative buoyancy generated by microphysical cooling is partially countered by a decrease in environmental potential temperatures as the parcel descends. This partial erosion of negative buoyancy as parcels descend is most pronounced in the low-LCL storms, which have steeper vertical profiles of environmental potential temperature in the lower atmosphere. When this erosion is accounted for, the strength of the strongest cold pools in the low-LCL ensemble is reduced, resulting in a narrower distribution of cold pool strengths. This narrower distribution is indicative of reduced sensitivity to the microphysics. These results suggest that supercell behavior and supercell hazards (e.g., tornadoes) may be more predictable in low-LCL environments.
期刊介绍:
Monthly Weather Review (MWR) (ISSN: 0027-0644; eISSN: 1520-0493) publishes research relevant to the analysis and prediction of observed atmospheric circulations and physics, including technique development, data assimilation, model validation, and relevant case studies. This research includes numerical and data assimilation techniques that apply to the atmosphere and/or ocean environments. MWR also addresses phenomena having seasonal and subseasonal time scales.