Improvements for Atmospheric Motion Vectors Algorithm Using First Guess by Optical Flow Method |
Oh, Yurim
(Department of Atmospheric Sciences, Division of Earth Environmental System, Pusan National University)
Park, Hyungmin (Department of Atmospheric Sciences, Division of Earth Environmental System, Pusan National University) Kim, Jae Hwan (Department of Atmospheric Sciences, Division of Earth Environmental System, Pusan National University) Kim, Somyoung (Department of Atmospheric Sciences, Division of Earth Environmental System, Pusan National University) |
1 | Kim, S., J.-H. Park, M.-L. Ou, H. Cho, and E.-H. Sohn, 2012. Optimization of mesoscale atmospheric motion vector algorithm using Geostationary Meteorological Satellite Data, Atmosphere, 22(1): 1-12 (in Korean with English abstract). DOI |
2 | Langland, R. H., C. Velden, P. M. Pauley, and H. Berger, 2009. Impact of satellite-derived rapid-scan wind observations on numerical model forecasts of Hurricane Katrina, Monthly Weather Review, 137(5): 1615-1622. DOI |
3 | Le Marshall, J., Y. Xiao, D. Howard, C. Tingwell, J. Freeman, P. Gregory, T. Le, D. Margetic, T. Morrow, and J. Daniels, 2016. First results from the generation and assimilation of 10-minute atmospheric motion vectors in the Australian region, Journal of Southern Hemisphere Earth Systems Science, 66(1): 12-18. DOI |
4 | Lee, J.-K. and C.-J. Park, 2007. Algorithm for Arbitrary Point Tracking using Pyramidal Optical Flow, Journal of Korea Multimedia Society, 10(11): 1407-1416 (in Korean with English abstract). |
5 | Lee, S., K. Salonen, and N. Bormann, 2015. Assessment of AMVs from COMS in the ECMWF system, ECMWF (European Centre for Medium-Range Weather Forecasts), Reading, Berkshire, UK. |
6 | Lucas, B. D. and T. Kanade, 1981. An iterative image registration technique with an application to stereo vision, Proc. of 7th International Joint Conference on Artificial Intelligence, Vancouver, BC, Aug. 24-28, pp. 674-679. |
7 | Mecikalski, J. R. and K. M. Bedka, 2006. Forecasting convective initiation by monitoring the evolution of moving cumulus in daytime GOES imagery, Monthly Weather Review, 134(1): 49-78. DOI |
8 | National Meteorological Satellite Center (NMSC), 2012. Atmospheric Motion Vector (AMV) Algorithm Theoretical Basis Document, National Meteorological Satellite Center, Jincheon, South Korea, pp. 1-30. |
9 | Oh, Y., J. H. Kim, H. Park, and K. Baek, 2015. Development and analysis of COMS AMV target tracking algorithm using gaussian cluster analysis, Atmosphere, 31(6): 531-548 (in Korean with English abstract). |
10 | Oh, S. M., R. Borde, M. Carranza, and I.-C. Shin, 2019. Development and Intercomparison Study of an Atmospheric Motion Vector Retrieval Algorithm for GEO-KOMPSAT-2A, Remote Sensing, 11(17): 2054. DOI |
11 | Oyama, R., M. Sawada, and K. Shimoji, 2018. Diagnosis of tropical cyclone intensity and structure using upper tropospheric Atmospheric Motion Vectors, Journal of the Meteorological Society of Japan, 96B: 3-26. DOI |
12 | Salonen, K., J. Cotton, N. Bormann, and M. Forsythe, 2015. Characterizing AMV height-assignment error by comparing best-fit pressure statistics from the Met Office and ECMWF data assimilation systems, Journal of Applied Meteorology and Climatology, 54(1): 225-242. DOI |
13 | Shimoji, K., 2014. Motion tracking and cloud height assignment methods for Himawari-8 AMV, Proc. of 12th International Winds Workshop, Copenhagen, Denmark, Jun. 16-20, pp. 80-90. |
14 | Bessho, K., K. Date, M. Hayashi, A. Ikeda, T. Imai, H. Inoue, Y. Kumagai, T. Miyakawa, H. Murata, and T. Ohno, 2016. An introduction to Himawari-8/9-Japan's new-generation geostationary meteorological satellites, Journal of the Meteorological Society of Japan, 94(2): 151-183. DOI |
15 | Velden, C., J. Daniels, D. Stettner, D. Santek, J. Key, J. Dunion, K. Holmlund, G. Dengel, W. Bresky, and P. Menzel, 2005. Recent innovations in deriving tropospheric winds from meteorological satellites, Bulletin of the American Meteorological Society, 86(2): 205-224. DOI |
16 | Wu, Q., H.-Q. Wang, Y.-J. Lin, Y.-Z. Zhuang, and Y. Zhang, 2016. Deriving AMVs from geostationary satellite images using optical flow algorithm based on polynomial expansion, Journal of Atmospheric and Oceanic Technology, 33(8): 1727-1747. DOI |
17 | Wu, T.-C., H. Liu, S. J. Majumdar, C. S. Velden, and J. L. Anderson, 2014. Influence of assimilating satellite-derived atmospheric motion vector observations on numerical analyses and forecasts of tropical cyclone track and intensity, Monthly Weather Review, 142(1): 49-71. DOI |
18 | Apke, J. M., J. R. Mecikalski, and C. P. Jewett, 2016. Analysis of mesoscale atmospheric flows above mature deep convection using super rapid scan geostationary satellite data, Journal of Applied Meteorology and Climatology, 55(9): 1859-1887. DOI |
19 | Bedka, K. M. and J. R. Mecikalski, 2005. Application of satellite-derived atmospheric motion vectors for estimating mesoscale flows, Journal of Applied Meteorology, 44(11): 1761-1772. DOI |
20 | Borde, R. and M. Doutriaux-Boucher, 2014. Extraction des vecteurs vents a partir d'images satellite, La Meteorologie, 87: 27-33. |
21 | Garcia-Pereda, J. and R. Borde, 2014. The impact of the tracer size and the temporal gap between images in the extraction of atmospheric motion vectors., Journal of Atmospheric and Oceanic Technology, 31(8): 1761-1770. DOI |
22 | Borde, R. and J. Garcia-Pereda, 2014. Impact of wind guess on the tracking of atmospheric motion vectors, Journal of Atmospheric and Oceanic Technology, 31(2): 458-467. DOI |
23 | Bresky, W. C., J. M. Daniels, A. A. Bailey, and S. T. Wanzong, 2012. New methods toward minimizing the slow speed bias associated with atmospheric motion vectors, Journal of Applied Meteorology and Climatology, 51(12): 2137-2151. DOI |
24 | Forsythe, M., 2007. Atmospheric motion vectors: past, present and future, Presentation Paper of ECMWF Annual Seminar, Reading, UK, Sep. 3-7, pp. 1-79. |
25 | Hillger, D. W. and T. H. Vonder Haar, 1988. Estimating noise levels of remotely sensed measurements from satellites using spatial structure analysis, Journal of Atmospheric and Oceanic Technology, 5(2): 206-214. DOI |
26 | Holmlund, K., 1998. The utilization of statistical properties of satellite-derived atmospheric motion vectors to derive quality indicators, Weather and Forecasting, 13(4): 1093-1104. DOI |
27 | Holmlund, K., 2000. The atmospheric motion vector retrieval scheme for meteosat second generation, Proc. of 5th International Winds Workshop, Lorne, Australia, Feb. 28-Mar. 3, pp. 201-208. |
28 | 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 adjointbased observation impact method, Weather and Forecasting, 32(2): 579-594. DOI |
29 | Horn, B. K. and B. G. Schunck, 1981. Determining optical flow, Proc. of Techniques and Applications f Image Understanding Symposium, Washington, D.C., USA, Apr. 21-22, vol. 0281, pp. 185-203. |