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Abstract
One of the microphysical variables, the rainwater mixing ratio qr, is retrieved from the observed reflectivity of Doppler radar by a 3D variational data assimilation system. The qr as an analysis variable is obtained by minimizing a cost function defined as the difference between observed radar reflectivity and its retrieval from qr, plus the difference between qr and its background field from a mesoscale model's prediction. Covariance matrix of the background field's error is determined by the so-called NMC method. A method called the second-order auto-regression (SOAR) is used to calculate the coefficients of regressive filtering to fit in
with small spatial scale such as cumulus in the process of spatial transformation. An ideal experiment demonstrates the correctness of this system and a sensitivity experiment proves that the random error of observed reflectivity has effect on the analyzed results. At last an experiment with observed data from the Doppler radar at Ma'anshan City in Anhui Province on 19 June 2002 was performed. The retrieved analysis variable qr in this test shows structures in detail, which coincide with the distribution of the echo picture
observed by the radar.
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Citation
LI Yongping, ZHU Guofu, XUE Jishan. 2006: Microphysical Retrieval from Doppler Radar Reflectivity Using Variational Data Assimilation. Journal of Meteorological Research, 20(1): 20-27.
LI Yongping, ZHU Guofu, XUE Jishan. 2006: Microphysical Retrieval from Doppler Radar Reflectivity Using Variational Data Assimilation. Journal of Meteorological Research, 20(1): 20-27.
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LI Yongping, ZHU Guofu, XUE Jishan. 2006: Microphysical Retrieval from Doppler Radar Reflectivity Using Variational Data Assimilation. Journal of Meteorological Research, 20(1): 20-27.
LI Yongping, ZHU Guofu, XUE Jishan. 2006: Microphysical Retrieval from Doppler Radar Reflectivity Using Variational Data Assimilation. Journal of Meteorological Research, 20(1): 20-27.
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