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http://dx.doi.org/10.7780/kjrs.2021.37.6.1.12

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)
Publication Information
Korean Journal of Remote Sensing / v.37, no.6_1, 2021 , pp. 1631-1645 More about this Journal
Abstract
This research aims to provide the characteristics of the world's first active lidar sensor Atmospheric Laser Doppler Instrument (ALADIN) wind data and Geostationary Korea Multi Purpose Satellite 2A (GK2A) Atmospheric Motion Vector (AMV) data by comparing two wind data. As a result of comparing the data from September 2019 to August 1, 2020, The total number of collocated data for the AMV (using IR channel) and Mie channel ALADIN data is 177,681 which gives the Root Mean Square Error (RMSE) of 3.73 m/s and the correlation coefficient is 0.98. For a more detailed analysis, Comparison result considering altitude and latitude, the Normalized Root Mean Squared Error (NRMSE) is 0.2-0.3 at most latitude bands. However, the upper and middle layers in the lower latitudes and the lower layer in the southern hemispheric are larger than 0.4 at specific latitudes. These results are the same for the water vapor channel and the visible channel regardless of the season, and the channel-specific and seasonal characteristics do not appear prominently. Furthermore, as a result of analyzing the distribution of clouds in the latitude band with a large difference between the two wind data, Cirrus or cumulus clouds, which can lower the accuracy of height assignment of AMV, are distributed more than at other latitude bands. Accordingly, it is suggested that ALADIN wind data in the southern hemisphere and low latitude band, where the error of the AMV is large, can have a positive effect on the numerical forecast model.
Keywords
Aeolus; ALADIN; GEO-KOMPSAT-2A Atmospheric Motion Vector(AMV);
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