Articles | Volume 7, issue 7
11 Apr 2007
11 Apr 2007

The Assimilation of Envisat data (ASSET) project

W. A. Lahoz, A. J. Geer, S. Bekki, N. Bormann, S. Ceccherini, H. Elbern, Q. Errera, H. J. Eskes, D. Fonteyn, D. R. Jackson, B. Khattatov, M. Marchand, S. Massart, V.-H. Peuch, S. Rharmili, M. Ridolfi, A. Segers, O. Talagrand, H. E. Thornton, A. F. Vik, and T. von Clarmann

Abstract. This paper discusses the highlights of the EU-funded "Assimilation of Envisat data" (ASSET) project, which has involved assimilation of Envisat atmospheric constituent and temperature data into systems based on Numerical Weather Prediction (NWP) models and chemical transport models (CTMs). Envisat was launched in 2002 and is one of the largest Earth Observation (EO) satellites ever built. It carries several sophisticated EO instruments providing insights into chemistry and dynamics of the atmosphere. In this paper we focus on the assimilation of temperature and constituents from Envisat.

The overarching theme of the ASSET project has been to bring together experts from all aspects of the data assimilation problem. This has allowed ASSET to address several themes comprehensively: enhancement of NWP analyses by assimilation of research satellite data; studies of the distribution of stratospheric chemical species by assimilation of research satellite data into CTM systems; objective assessment of the quality of ozone analyses; studies of the spatial and temporal evolution of tropospheric pollutants; enhanced retrievals of Envisat data; and data archival and dissemination.

Among the results from the ASSET project, many of which are firsts in their field, we can mention: a positive impact on NWP analyses from assimilation of height-resolved stratospheric humidity and temperature data, and assimilation of limb radiances; the extraction of temperature information from the assimilation of chemical species into CTMs; a first intercomparison between ozone assimilation systems; the extraction of information on tropospheric pollution from assimilation of Envisat data; and the large potential of the Envisat MIPAS dataset. This paper discusses these, often novel, developments and results. Finally, achievements of, and recommendations from, the ASSET project are presented.

Final-revised paper