Comparison of Wind Vectors Derived from GK2A with Aeolus/ALADIN |
Shin, Hyemin
(Department of Climate and Energy Systems Engineering)
Ahn, Myoung-Hwan (Department of Climate and Energy Systems Engineering) KIM, Jisoo (Department of Climate and Energy Systems Engineering) Lee, Sihye (Assimilation Technique Team, Data Assimilation Group Korea Institute of Atmospheric Prediction Systems) Lee, Byung-Il (Satellite Planning Division, National Meteorological Satellite Center) |
1 | Baars, H., A. Herzog, B. Heese, K. Ohneiser, K. Hanbuch, J. Hofer, and U. Wandinger, 2020. Validation of Aeolus wind products above the Atlantic Ocean, Atmospheric Measurement Techniques, 13(11): 6007-6024. DOI |
2 | Borde, R., M. Doutriaux-Boucher, G. Dew, and M. Carranza, 2014. A direct link between feature tracking and height assignment of operational EUMETSAT atmospheric motion vectors, Journal of Atmospheric and Oceanic Technology, 31(1): 33-46. DOI |
3 | Bormann, N., S. Saarinen, G. Kelly, and J.N. Thepaut, 2003. The spatial structure of observation errors in atmospheric motion vectors from geostationary satellite data, Monthly Weather Review, 131(4): 706-718. DOI |
4 | Borde, R. and P. Dubuisson, 2010. Sensitivity of atmospheric motion vectors height assignment methods to semitransparent cloud properties using simulated Meteosat-8 radiances, Journal of applied meteorology and climatology, 49(6): 1205-1218. DOI |
5 | Pauley, P., N. Baker, R. Langland, L. Xu, C. Velden, and M. Forsythe, 2012. The impact of satellite atmospheric motion vectors in the U.S. Navy Global Data Assimilation System: The superob procedure, Proc. of 11th international winds workshop, Auckland, NZL, Feb. 20-24, p. 10. |
6 | Schmetz, J. and K. Holmlund, 1992. Operational cloud motion winds from Meteosat and the use of cirrus clouds as tracers, Advances in Space Research, 12(7): 95-104. DOI |
7 | Bormann, N. and J.-N. Thepaut, 2004. Impact of MODIS polar winds in ECMWF's 4DVAR data assimilation system, Monthly Weather Review, 132(4): 929-940. DOI |
8 | Cotton, J. and M. Forsythe, 2012. AMVs at the Met Office: Activities to improve their impact in NWP, Proc. of the 11th International Wind Workshop, Auckland, NZL, Feb. 20-24, pp. 1-7. |
9 | Cress, A., 2012. Recent progress in using satellite winds at the German Weather Service, Proc. of the 11th International Wind Workshop, Auckland, NZL, pp. 1-8. |
10 | Folger, K., and M. Weissmann, 2014. Height correction of atmospheric motion vectors using satellite lidar observations from CALIPSO, Journal of Applied Meteorology and Climatology, 53(7): 1809-1819. DOI |
11 | George, G., G. Halloran, S. Kumar, S.I. Rani, M.T. Bushair, B.P. Jangid, J.P. Georgea, and A. Maycock, 2021. Impact of Aeolus horizontal line of sight wind observations in a global NWP system, Atmospheric Research, 261: 105742. DOI |
12 | Gelaro, R., R.H. Langland, S. Pellerin, and R. Todling, 2010. The THORPEX observation impact intercomparison experiment, Monthly Weather Review, 138(11): 4009-4025. DOI |
13 | Han, H.-J., I.-H. Kwon, J.-H. Kang, H.-W. Chun, S. Lee, S. Lim, and T. Kim, 2019. Analysis of Forecast Performance by Altered Conventional Observation Set, Atmosphere, 29(1): 21-39. DOI |
14 | Hagelin, S., R. Azad, M. Lindskog, H. Schyberg, and H. Kornich, 2021. Evaluating the use of Aeolus satellite observations in the regional NWP model Harmonie-Arome, Atmospheric Measurement Techniques Discussions, 14(9): 5925-5938. DOI |
15 | Jung, J., J. Le Marshall, J. Daniels, and L.P. Riishojgaard, 2010. Investigating height assignment type errors in the NCEP global forecasting system, Proc. of the 10th International Wind Workshop, Tokyo, JPN, Feb. 22-26 p. 56. |
16 | 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 |
17 | Bormann, N., K. Salonen, C. Peubey, T. McNally, and C. Lupu, 2012. An overview of the status of the operational assimilation of AMVs at ECMWF, Proc. of the 11th International Wind Workshop, Auckland, NZL, Feb. 20-24, pp. 20-27. |
18 | Kelly, G., J.-N. Thepaut, R. Buizza, and C. Cardinali, 2007. The value of observations. I: Data denial experiments for the Atlantic and the Pacific, Quarterly Journal of the Royal Meteorological Society: A Journal of the Atmospheric Sciences, Applied Meteorology and Physical Oceanography, 133(628): 1803-1815 |
19 | Martin, A., M. Weissmann, O. Reitebuch, M. Rennie, A. Geiss, and A. Cress, 2021. Validation of Aeolus winds using radiosonde observations and numerical weather prediction model equivalents, Atmospheric Measurement Techniques, 14(3): 2167-2183. DOI |
20 | Menzel, W.P., 2001. Cloud tracking with satellite imagery: From the pioneering work of Ted Fujita to the present, American Meteorological Society, 82(1): 33-47. DOI |
21 | Velden, C.S. and Bedka, K.M. 2009. Identifying the uncertainty in determining satellite-derived atmospheric motion vector height attribution, Journal of Applied Meteorology and Climatology, 48(3): 450-463. DOI |
22 | Velden, C.S., 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): 205-223. DOI |
23 | Schulze, G.C., 2007. Atmospheric observations and numerical weather prediction, South African Journal of Science, 103(7): 318- -323. |
24 | Sienkiewicz, J.M., 1990. An example of the importance of ship observations, Weather and Forecasting, 5(4): 683-687. DOI |
25 | St-James, J.S. and S. Laroche, 2005. Assimilation of wind profiler data in the Canadian Meteorological Centre's analysis systems, Journal of Atmospheric and Oceanic Technology, 22(8): 1181-1194. DOI |
26 | KMA (Korea Meteorological Administration) / NMSC (National Meteorological Satellite Center), 2018. AMV: Atmospheric Motion Vector Algorithm Theoretical Basis Document (AMV-v4.0), National Meteorological Satellite Center, Jincheon, Chungbuk, KOR. |
27 | Nieman, S., J. Schmetz, and P. Menzel, 1993. A comparison of several techniques to assign heights to cloud tracers, Journal of Applied Meteorology and Climatology, 32(9): 1559-1568. DOI |
28 | Rennie, M.P., L. Isaksen, F. Weiler, J. de Kloe, T. Kanitz, and O. Reitebuch, 2021. The impact of Aeolus wind retrievals on ECMWF global weather forecasts, Quarterly Journal of the Royal Meteorological Society, 147(740): 3555-3586. DOI |
29 | Straume, A.G., M. Rennie, L. Isaksen, J. de Kloe, G.J. Marseille, A. Stoffelen, T. Flament, H. Stieglitz, A. Dabas, D. Huber, O. Reitebuch, C. Lemmerz, O. Lux, U. Marksteiner, F. Weiler, B. Witschas, M. Meringer, K. Schmidt, I. Nikolaus, A. Geiss, P. Flamant, T. Kanitz, D. Wernham, J. von Bismarck, S. Bley, T. Fehr, R. Floberghagen, and T. Parinello, 2020. ESA's space-based Doppler wind lidar mission Aeolus-First wind and aerosol product assessment results, Proc. of in EPJ Web of Conferences, Hefei, Anhui Province, CHN, Jun. 24-28, Vol. 237, p. 01007. |
30 | Su, X., J. Derber, and J. Jung, 2012: Recent work on satellite atmospheric motion vectors in the NCEP data assimilation system, Proc. of 11th 11th international winds workshop, Auckland, NZL, p.13. |
31 | Huber, D. and I. Nikolaus, 2018. Algorithm Theoretical Basis Document ATBD Level1B Products, Deutsches Zentrum fur Luft- und Raumfahrt, Cologne, Land Nordrhein-Westfalen, GER. |