Deep Convective Microphysics Experiment
DCMEX will run from 1/2/2020 – 31/1/2024.
The goal of the Deep Convective Microphysics Experiment (DCMEX) project is to ultimately reduce the uncertainty in equilibrium climate sensitivity by improving the representation of microphysical processes in global climate models (GCMs). It is the anvils produced by tropical systems in particular, that contribute significantly to cloud feedbacks. The anvil radiative properties, lifetimes and areal extent are the key parameters. DCMEX will determine the extent to which these are influenced, or even controlled by the cloud microphysics including the habits, concentrations and sizes of the ice particles that make up the anvils, which in turn depend on the microphysical processes in the mixed-phase region of the cloud as well as those occurring in the anvil itself.
The project gets going in July-August 2022 with a measurement campaign over the Magdalena mountains, New Mexico. The FAAM BAe-146 aircraft, dual-polarisation doppler radar, aerosol instruments and stereo-camera observations will generate novel data. Combined with modelling activities this will help improve the representation of deep convective microphysics within climate models.
The overall goal of the research is: To reduce the uncertainty in climate sensitivity in climate models by improving the representation of mixed-phase microphysical processes that occur in cumulus clouds and their anvils. The objectives outlined below are designed to consider parts of the overall problem that will collectively address this goal.
1. Ice nucleating particles and primary ice. Determine if the formation of primary ice particles in cumulus clouds can be explained by the observed INP activity spectrum.
2. CCN, including Ultra-giant CCN, and distribution of cloud droplets. (a) Reproduce the temporal and spatial distribution of cloud droplets using the UM. (b) Understand the reasons for the production of supercooled raindrops in the New Mexico clouds.
3. Secondary ice processes. (a) Determine if ice particle concentrations are greater than that predicted from the INP observations and if so, determine which secondary ice processes operate in the New Mexico clouds and why. (b) Determine the best representation of the secondary ice particle production process(es) and rates.
4. Characteristics of ice particles in anvils. Determine to what extent the radiative properties, lifetimes and areal extent of the anvil are influenced, or even controlled by the microphysical processes in the mixed-phase region and in the anvil itself.
5. Modifications to parametrisations in CASIM. Make modifications to the microphysics representation in the convection parametrisation to best represent the observations in the mixed phase and anvil regions as well as results from process modelling. 6. FAT hypothesis. Use model simulations to assess the FAT hypothesis and test its sensitivity to microphysical assumptions.