Initial attempt to assess the impact of Geostationary Hyperspectral Data using Observing Simulation System Experiment (OSSE)

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Monday, 3 February 2014
Hall C3 (The Georgia World Congress Center )
Agnes Lim, CIMSS/Univ. of Wisconsin, Madison, WI; and J. A. Jung, Z. Li, and A. Huang

Higher spatial, temporal and spectral resolution will considerably enhance the information available, particularly to monitor and predict rapidly-evolving, small-scale phenomena. Such observations can be provided by hypersepctral infrared sensors placed in geostationary orbit. The Observing System Simulation Experiment (OSSE) will be used to assess the impact of geostationary hyperspectral data on a forecast system. In an OSSE, simulated observations are used as inputs into data assimilation systems. These simulated observations are drawn from a Nature Run (NR) which serves as a proxy to the real atmosphere. As OSSEs are computationally intensive, an internationally collaborative effort called the joint OSSE (Andersson and Masutani, 2010) had been formed. The Nature Run was generated by the European Centre for Medium Range Weather Forecasts (ECMWF) and had been verified by Masutani et. al, (2009). In addition, conventional and existing satellite sensors valid for the Nature run period (2005-2006) had also been simulated by NOAA/NCEP (Masutani et al, 2011) and made available to the research community through NCAR. Those data will be used in baseline experiment. We will focus on simulating the geo-hyperspectral data generated from the ECMWF Nature Run. In our study, clear sky geostationary hypersepoctral radiances are simulated using the Stand Alone AIRS Radiative Transfer Algorithm (SARTA). To mimic the planned mission, we are simulating an Infrared Atmospheric Sounding Interferometer (IASI) in geostationary orbit centered at 122oE. The OSSE will be conducted using the GSI and WRF at regional scale. Prior to conducting the actual OSSE, calibration of the data assimilation system will be carried out. OSSE calibration verifies that the simulated data impact by comparing it to the real data impact. Pairs of experiments are run in real and OSSE context. All major existing observations are used in the calibration experiments. Metrics of the data assimilation and forecast are compared between the real world and OSSE.


Andersson, Erik and Michiko Masutani 2010: Collaboration on Observing System Simulation Experiments (Joint OSSE), ECMWF News Letter No. 123, Spring 2010, 14-16.

Masutani, M., L.-P. Riishojgaard, R. Errico, E. Andersson, J. S. Woollen, A. Stoffelen, G.-J. Marseille, O. Reale, Y. Xie, N. Prive, T. Zhu, F. Weng, G. D. Emmitt, T. W. Schlatter, S. J. Lord, S. Greco, S. A. Wood, R. Yang, H. Sun, T. J. Kleespies, and Y. Song 2009: International collaborative Joint OSSEs,Toward reliable and timely assessment of future observing systems, Extended Abstract, The Anthony J. Hollingsworth Symposium, Phoenix, AZ, Amer. Meteor. Soc., P1.2

Masutani, M. and co authrs 2011 : Simulation of observation and calibrations for Joint OSSEs, Extended abstract, 15th Symposium on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS), Seattle, WA, Amer. Meteor.P199.