Abstract
In the past few years a growing amount of space observations focusing on atmospheric composition has become available and this trend will continue with the launch of new satellites (ESA-Sentinels, NASA-TEMPO and JAXA air quality and climate mission) in the near future. To justify the production and launch of these expensive instruments, there is a need for determining the added value of future satellite instruments and their optimal design in an objective way. One methodology that can do so is the OSSE (Observing System Simulation Experiment). Although extensively used in the meteorological community, it’s use in the field of air quality and climate is still limited and a common approach is desirable. Based on existing studies and experience in the meteorological community we have identified requirements for each of the OSSE elements for performing a realistic OSSE. Using illustrative examples from existing air quality OSSEs we will present the methodology and the requirements for the application of OSSEs to satellite observations of atmospheric composition.
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Questioner: F. Lenartz
Question: Do you transform your data to make them Gaussian? If yes what is the impact of the distribution?
Answer: We do not transform the data itself to a Gaussian distribution but we do add noise with a Gaussian distribution to simulate instrument and other random errors.
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Timmermans, R. et al. (2016). Observing System Simulation Experiments (OSSEs) for Air Quality Applications. In: Steyn, D., Chaumerliac, N. (eds) Air Pollution Modeling and its Application XXIV. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-319-24478-5_94
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DOI: https://doi.org/10.1007/978-3-319-24478-5_94
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