Dynamical evolution of the 2003 southern hemisphere stratospheric winter using Envisat trace-gas observations

Data from the MIPAS instrument on Envisat, supplemented by meteorological analyses from ECMWF and the Met Office, are used to study the meteorological and trace-gas evolution of the stratosphere in the southern hemisphere during winter and spring 2003. A pole-centred approach is used to interpret the data in the physically meaningful context of the evolving stratospheric polar vortex. The following salient dynamical and transport features are documented and analysed: the merger of anticyclones in the stratosphere; the development of an intense, quasi-stationary anticyclone in spring; the associated top-down breakdown of the polar vortex; the systematic descent of air into the polar vortex; and the formation of a three-dimensional structure of a tracer filament on a planetary scale. The paper confirms and extends existing paradigms of the southern hemisphere vortex evolution. The quality of the MIPAS observations is seen to be generally good. though the water vapour retrievals are unrealistic above 10 hPa in the high-latitude winter.

Influence-matrix diagnostic of a data assimilation system

The influence matrix is used in ordinary least-squares applications for monitoring statistical multiple-regression analyses. Concepts related to the influence matrix provide diagnostics on the influence of individual data on the analysis - the analysis change that would occur by leaving one observation out, and the effective information content (degrees of freedom for signal) in any sub-set of the analysed data. In this paper, the corresponding concepts have been derived in the context of linear statistical data assimilation in numerical weather prediction. An approximate method to compute the diagonal elements of the influence matrix (the self-sensitivities) has been developed for a large-dimension variational data assimilation system (the four-dimensional variational system of the European Centre for Medium-Range Weather Forecasts). Results show that, in the boreal spring 2003 operational system, 15% of the global influence is due to the assimilated observations in any one analysis, and the complementary 85% is the influence of the prior (background) information, a short-range forecast containing information from earlier assimilated observations. About 25% of the observational information is currently provided by surface-based observing systems, and 75% by satellite systems. Low-influence data points usually occur in data-rich areas, while high-influence data points are in data-sparse areas or in dynamically active regions. Background-error correlations also play an important role: high correlation diminishes the observation influence and amplifies the importance of the surrounding real and pseudo observations (prior information in observation space). Incorrect specifications of background and observation-error covariance matrices can be identified, interpreted and better understood by the use of influence-matrix diagnostics for the variety of observation types and observed variables used in the data assimilation system. Copyright © 2004 Royal Meteorological Society

Updated estimates of the costs associated with thirty four endemic livestock diseases in Great Britain: A note

This Note outlines the further development of a system of models for the estimation of the costs of livestock diseases first presented by Bennett (2003). The models have been developed to provide updated and improved estimates of the costs associated with 34 endemic diseases of livestock in Great Britain, using border prices and including assessments of the impact of diseases on human health and animal welfare. Results show that, of the diseases studied, mastitis has the highest costs for cattle diseases, enzootic abortion for sheep diseases, swine influenza for pig diseases and salmonellosis for poultry diseases.