A project funded by the UK Engineering and Physical Sciences Research Council's
Maths Foresees Network
Project period: 1 March - 30 September 2016
Summary
Clouds, convection and moist processes generally pose serious
challenges for modelling the Earth's climate and weather (e.g. Bony et
al., Nature Geoscience, 8.4, 2015). Such processes
involve small-scale interactions which are well beyond the resolution
of current global circulation models (GCMs). Instead, GCMs need to
parametrise such processes, usually by crude single-column
convection-adjustment schemes. Convection-Permitting Models (CPMs) go
further by attempting to explicitly-resolve these processes. These
models are increasingly used for Numerical Weather Prediction and
climate applications. Nevertheless, even these models are only crudely
resolving convective clouds, which leads to biases such as too intense
deep convection.
We propose a potentially revolutionary approach to this problem,
namely to model sub-grid processes explicitly using Lagrangian
particles. These particles represent miniature "cloud
parcels/cloud circulations", and each carries a number of attributes
such as liquid water content, buoyancy anomaly, and circulation (see
below). This explicit sub-grid model will be interfaced with a
conventional model (in the first instance a highly-simplified CPM), to
provide a representation of the dynamics over a greatly-extended range
of scales - efficiently. Though improving the representation of
small-scale vorticity is a topic of interest in studies of atmospheric
convection (Shutts and Allen, Atm. Sci. Lett.8.4,
2007), the current approach has not been applied in this context
before. Moreover, one of the key challenges of modelling convective
clouds is that microphysical processes (such as the conversion between
types of water droplet and ice crystal) are extremely nonlinear and
occur on microscopic (< 1 mm) length scales. In a turbulent cloud,
the nonlinearities are very challenging to model on an Eulerian
grid. The profound advantage of our proposed method is that the
nonlinear physical processes will be simulated in a framework which is
fundamentally Lagrangian.
A rising moist thermal computed by a test version of the new cloud model.
The gridded buoyancy field is displayed in a vertical cross section. In
this simulation, the thermal first rises through a region of neutral
stratification before encountering a deep layer of stable stratification.
The buoyancy in the plume allows part of it to penetrate the lower regions
of this stable stratification and reach the lifting condensation level. At
this point, additional buoyancy is created due to condensation.