2D Assimilation of dynamical information from satellite imagery

Cloud imagery is not currently used in NWP to extract the type of dynamical information that experienced forecasters have extracted subjectively for many years. For example, rapidly developing mid-latitude cyclones have characteristic signatures in the cloud imagery that are most fully appreciated from a sequence of images rather than from a single image. Indeed, such information is already used by forecasters as a "quality control" tool for NWP products, as it allows them to see when a sequence of NWP fields is not developing consistently with the latest satellite image.

The Met Office is currently developing a technique to extract dynamical information from satellite imagery using their 4D VAR system. We investigate a simplified form of this technique, converting information on the vertical wind field to brightness temperatures. We consider a 2D system (vertical and time). Vertical profiles of temperature, T(z, t), total water, qt(z, t) and vertical velocity, w(z, t) are updated using a simple vertical advection scheme. A simple cloud scheme is used to obtain fractional cloud and, when combined with the temperature field, is then converted to a brightness temperature using a simple radiative transfer scheme.

The first test of our model is to prescribe the "true" vertical profiles of T, qt and w, and then try to recover these profiles using our 2D-VAR system. We shall present an overview of the algorithm and our latest results.