@misc{74412,
  author = {S.J. English and A. McNally and Niels Bormann and Kirsti Salonen and Marco Matricardi and Andras Horányi and Michael Rennie and Marta Janiskova and S. Di Michele and Alan Geer and Enza di Tomaso and Carla Cardinali and Patricia de Rosnay and J.M. Sabater and Massimo Bonavita and C. Albergel and Richard Engelen and Jean-Noël Thépaut},
  title = {Impact of satellite data},
  abstract = {This report reviews the current value of satellite data assimilation activities at ECMWF and outlines the strategy for future development. The Centre makes extensive use of satellite observations in atmospheric, ocean and land surface analyses, and also for atmospheric composition both in the Integrated Forecasting System and in MACC (Monitoring Atmospheric Composition and Climate). Many satellite data types such as the sounders are very well established and form the backbone of the observing system. It is essential for any state of the art Numerical Weather Prediction system to get the sounder assimilation right, and properly maintain it. Whilst recognising the importance of what we might call conventional satellite data this report will focus on new developments and areas that are increasingly important. ECMWF contribute very significantly to the future development of the global observing system both through assessing the potential impact of new data and by being pioneering in the use of innovative satellite data, including data from research satellites such as those in the A-train and ESA's Earth Explorer missions. As NWP systems improve it is becoming harder to acquire observations good enough to improve further the accuracy of the forecast. It is important to make well informed choices about which new observations investment should be made and then to do the hard work to make sure we can exploit these observations. Through better observations, advances in data assimilation techniques and in the way observations are handled satellite data is continuing to make a major contribution to improve medium range weather forecast skill.},
  year = {2013},
  journal = {ECMWF Technical Memoranda},
  number = {711},
  pages = {46},
  month = {11/2013},
  publisher = {ECMWF},
  url = {https://www.ecmwf.int/node/9301},
  doi = {10.21957/b6596ot1s},
  language = {eng},
}