Calibration and Evaluation of Envisat Temperature and Ozone Data Using Statistics from the Uk Met. Office Nwp System

This paper discusses the latest results from ongoing work concerning the calibration and evaluation of temperature and ozone from the Microwave Limb Sounder (MLS) instrument aboard NASA’s Upper Atmosphere Research Satellite (UARS). The method involves using the data assimilation statistics from the UK Met. Office Numerical Weather Prediction (NWP) System. This work provides the template for future work on the calibration and evaluation of temperature and ozone data from the GOMOS, MIPAS and SCIAMACHY instruments aboard Envisat. The operational data routinely used by the weather agencies is assimilated together with the MLS data. The statistics generated by the assimilation procedure on the difference between the MLS observations and the analyses, and between the MLS observations and the forecasts, are used to calibrate and evaluate the MLS data. The statistics are used to identify and estimate biases in the data. The impact of the MLS datasets is tested using Observation System Experiments (OSEs) in which different sets of data are systematically removed from the assimilation. The meteorological analyses incorporating MLS data and operational data are evaluated using independent observations (i.e. observations not used in the assimilation). The error characteristics provided by the MLS instrument team are assessed. An attempt is made to identify shortcomings in the Met. Office assimilation system.