References
- Baker, N. L., and R. Daley, 2000: Observation and background adjoint sensitivity in the adaptive observationtargeting problem. Quart. J. Roy. Meteor. Soc., 126, 1431-1454, doi:10.1002/qj.49712656511.
- Cardinali, C., 2009: Monitoring the observation impact on the short-range forecast. Quart. J. Roy. Meteor. Soc., 135, 239-250, doi:10.1002/qj.366.
- English, S., U. O'Keeffe, and M. Sharpe, 2007: Assimilation of cloudy AMSU-A microwave radiances in 4D-VAR. proc. 15th International TOVS Study Conference, Maratea, Italy, 4-10 October 2006.
- Gelaro, R., and Y. Zhu, 2009: Examination of observation impacts derived from observing system experiments (OSEs) and adjoint models. Tellus, 61, 179-193, doi:10.1111/j.1600-0870.2008.00388.x.
- Gelaro, R., R. H. Langland, S. Pellerin, and R. Todling, 2010: The THORPEX observation impact intercomparison experiment. Mon. Wea. Rev., 138, 4009-4025, doi:10.1175/2010MWR3393.1.
- Joo, S., J. Eyre, and R. Marriott, 2013: The impact of Metop and other satellite data within the Met Office global NWP system using an adjoint-based sensitivity method. Mon. Wea. Rev., 141, 3331-3342, doi:10.1175/MWR-D-12-00232.1.
- Jung, B.-J., H. M. Kim, T. Auligne, X. Zhang, and X.-Y. Huang, 2013: Adjoint-derived observation impact using WRF in the western North Pacific. Mon. Wea. Rev., 141, 4080-4097, doi:10.1175/MWR-D-12-00197.1.
- Kidder, S. Q., and T. H. Vonder Harr, 1995: Satellite Meteorology: An Introduction. Academic Press, San Diego, 466 pp.
- Kim, H. M., B.-J. Jung, S. Park, J. Kay, S.-M. Kim, J. Kim, S. Kim, and E. Yang, 2012: Development of scientific tools for evaluating the forecast sensitivity to remote sensing observations. CATER 2011-2211, KMA, 1-114.
- Kim, H. M., S.-M. Kim, and B.-J. Jung, 2011: Real-time adaptive observation guidance using singular vectors for typhoon Jangmi (200815) in T-PARC 2008. Wea. Forecasting, 26, 634-649, doi:10.1175/WAF-D-10-05013.1.
- Kim, M., H. M. Kim, J. Kim, S.-M. Kim, C. Velden, and B. Hoover, 2017: Effect of enhanced satellite-derived atmospheric motion vectors on numerical weather prediction in East Asia using an adjoint-based observation impact method. Wea. Forecasting, 32, 579-594, doi:10.1175/WAF-D-16-0061.1.
- Kim, S., H. M. Kim, E.-J. Kim, and H.-C. Shin, 2013: Forecast sensitivity to observations for high-impact weather events in the Korean Peninsula. Atmosphere, 23, 171-186, doi:10.14191/Atmos.2013.23.2.171 (in Korean with English abstract).
- Kim, S. M., 2016: Forecast Sensitivity to Observations in the KMA UM and the Effect of Observations on Numerical Weather Prediction. Ph.D. Thesis, Yonsei University, 183 pp.
- Kim, S. M., and H. M. Kim, 2014: Sampling error of observation impact statistics. Tellus, 66, 25435, doi:10.3402/tellusa.v66.25435.
- Liu, Z., C. S. Schwartz, C. Snyder, and S. Ha, 2012: Impact of assimilating AMSU-A radiances on forecasts of 2008 Atlantic tropical cyclones initialized with a limited-area ensemble Kalman filter. Mon. Wea. Rev., 140, 4017-4034, doi:10.1175/MWR-D-12-00083.1.
- Lorenc, A. C., and R. Marriott, 2014: Forecast sensitivity to observations in the Met Office Global numerical weather prediction system. Quart. J. Roy. Meteor. Soc., 140, 209-224, doi:10.1002/qj.2122.
- Reynolds, C. A., and R. Gelaro, 2001: Remarks on Northern Hemisphere forecast error sensitivity from 1996 to 2000. Mon. Wea. Rev., 129, 2145-2153, doi:10.1175/1520-0493(2001)129<2145:RONHFE>2.0.CO;2.
- Rodgers, C. D., 1990: Characterization and error analysis of profiles retrieved from remote sounding measurements. J. Geophys. Res., 95, 5587-5595. https://doi.org/10.1029/JD095iD05p05587
- Salonen, K., and N. Bormann, 2011: Accounting for the characteristics of AMV observations errors in data assimilation. EUMETSAT Tech. Note, 7 pp.
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