ALBERT

Description: An important component of the assimilation of radiance observations from the AIRS and IASI satellite instruments is the radiative transfer modelling. Currently, the RTTOV model used in the ECMWF IFS system uses a fixed value for CO 2 . Neglecting the spatio-temporal variability of CO 2 introduces an error in the simulation of the satellite radiances, which could affect the quality of the analyses and forecasts. The current assumption is that variational bias correction corrects most of this error and therefore minimizes the impact on the forecast scores. This paper investigates the possibility of modelling CO 2 within the IFS to improve the radiative transfer modelling. Results show that the required bias correction is significantly reduced when using more realistic CO 2 values. The impact on the analysis quality and forecast scores is mostly neutral with some indication of improvement in the Tropics and the stratosphere. Copyright © 2011 Royal Meteorological Society

Description: An important component of the assimilation of radiance observations from the AIRS and IASI satellite instruments is the radiative transfer modelling. Currently, the RTTOV model used in the ECMWF IFS system uses a fixed value for CO 2 . Neglecting the spatio-temporal variability of CO 2 introduces an error in the simulation of the satellite radiances, which could affect the quality of the analyses and forecasts. The current assumption is that variational bias correction corrects most of this error and therefore minimizes the impact on the forecast scores. This paper investigates the possibility of modelling CO 2 within the IFS to improve the radiative transfer modelling. Results show that the required bias correction is significantly reduced when using more realistic CO 2 values. The impact on the analysis quality and forecast scores is mostly neutral with some indication of improvement in the Tropics and the stratosphere. Copyright © 2011 Royal Meteorological Society

Description: In 2002, the European Space Agency (ESA) launched the ENVIromental SATellite (ENVISAT) that carried ten instruments to provide continuous observation of Earth's land, atmosphere, oceans and ice caps. During the satellite lifetime, the European Centre for Medium Range Weather Forecasts (ECMWF) has routinely monitored a variety of products from many of its instruments. A subset of these data has also been assimilated in the ECMWF operational system, and two of its applications: the reanalysis and the Monitoring Atmospheric Composition and Climate systems. This paper reviews those activities and summarises the lessons learnt in monitoring and assimilating data from a research satellite within a numerical weather prediction system. The value of continuous data monitoring and the benefits that a close collaboration between data provider and data user can bring to both parties are highlighted. For observations that were assimilated, impact assessments on the ECMWF products have periodically been performed. Two cases are presented in this paper. The first one shows that the assimilation of ocean wave information can reduce the wave height model random error by up to 8% at the analysis time, with benefits at later forecasts times extending to up to 5 days in the tropics. The second example shows that the assimilation of two ENVISAT ozone products improves the agreement of the ozone analyses with independent ozone observations obtained from sondes and the Microwave Limb Sounder. Finally, the use of ENVISAT reprocessed data is presented with emphasis on the importance of data reprocessing and long-term data preservation as key activities to ensure the future usage of these datasets.

Description: A representation of atmospheric chemistry has been included in the Integrated Forecasting System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF). The new chemistry modules complement the aerosol modules of the IFS for atmospheric composition, which is named C-IFS. C-IFS for chemistry supersedes a coupled system, in which the Chemical Transport Model (CTM) Model for OZone and Related chemical Tracers 3 was two-way coupled to the IFS (IFS-MOZART). This paper contains a description of the new on-line implementation, an evaluation with observations and a comparison of the performance of C-IFS with MOZART and with a re-analysis of atmospheric composition produced by IFS-MOZART within the Monitoring Atmospheric Composition and Climate (MACC) project. The chemical mechanism of C-IFS is an extended version of the Carbon Bond 2005 (CB05) chemical mechanism as implemented in the CTM Transport Model 5 (TM5). CB05 describes tropospheric chemistry with 54 species and 126 reactions. Wet deposition and lightning nitrogen monoxide (NO) emissions are modelled in C-IFS using the detailed input of the IFS physics package. A one-year simulation by C-IFS, MOZART and the MACC re-analysis is evaluated against ozonesondes, carbon monoxide (CO) aircraft profiles, European surface observations of ozone (O3), CO, sulphur dioxide (SO2) and nitrogen dioxide (NO2) as well as satellite retrievals of CO, tropospheric NO2 and formaldehyde. Anthropogenic emissions from the MACC/CityZen (MACCity) inventory and biomass burning emissions from the Global Fire Assimilation System (GFAS) data set were used in the simulations by both C-IFS and MOZART. C-IFS (CB05) showed an improved performance with respect to MOZART for CO, upper tropospheric O3, winter time SO2 and was of a similar accuracy for other evaluated species. C-IFS (CB05) is about ten times more computationally efficient than IFS-MOZART.