  The application of models to assess the risk of the physical impacts of
weather and climate and their subsequent consequences for society and business
is of the utmost importance in our changing climate. The operation of such
models is historically bespoke and constrained to specific compute
infrastructure, driving datasets and predefined configurations. These
constraints introduce challenges with scaling model runs and putting the models
in the hands of interested users. Here we present a cloud-based modular
framework for the deployment and operation of geospatial models, initially
applied to climate impacts. The Climate Impact Modelling Frameworks (CIMF)
enables the deployment of modular workflows in a dynamic and flexible manner.
Users can specify workflow components in a streamlined manner, these components
can then be easily organised into different configurations to assess risk in
different ways and at different scales. This also enables different models
(physical simulation or machine learning models) and workflows to be connected
to produce combined risk assessment. Flood modelling is used as an end-to-end
example to demonstrate the operation of CIMF.
