Precipitation sensitivity to autoconversion rate in a numerical weather-prediction model

摘要: Aerosols are known to significantly affect cloud and precipitation patterns intensity, but these interactions ignored or very simplistically handled in climate numerical weather-prediction (NWP) models. A suite of one-way nested Met Office Unified Model (UM) runs, with a single-moment bulk microphysics scheme was used study two convective cases contrasting characteristics observed southern England. The autoconversion process that converts water rain is directly controlled by the assumed droplet number. impact changing number concentration (CDNC) on evolution can be inferred through changes rate. This done for range resolutions ranging from regional NWP (1 km) high resolution (up 100 m grid spacing) evaluate uncertainties due CDNC as function horizontal resolution. The first case characterised moderately intense showers forming below an upper-level potential vorticity anomaly, low freezing level. second case, one persistent stronger storm, warmer deeper boundary layer. colder almost insensitive even large CDNC, while change factor 3 affects total surface rate ∼17%. In both sensitivity similar at all spacings <1 km. sensitivities induced their ice-phase proportion. ice processes this model damp CDNC. For convection sensitive when accretion more significant than melting vice versa.