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			<titleStmt><title level='a'>Improved observed full raindrop size distributions and their normalization using double and triple moments</title></titleStmt>
			<publicationStmt>
				<publisher>Elsevier</publisher>
				<date>02/01/2026</date>
			</publicationStmt>
			<sourceDesc>
				<bibl> 
					<idno type="par_id">10680780</idno>
					<idno type="doi">10.1016/j.atmosres.2025.108675</idno>
					<title level='j'>Atmospheric Research</title>
<idno>0169-8095</idno>
<biblScope unit="volume">331</biblScope>
<biblScope unit="issue">C</biblScope>					

					<author>Sanghun Lim</author><author>Wonbae Bang</author><author>Kyo-Sun Sunny Lim</author><author>Merhala Thurai</author><author>GyuWon Lee</author>
				</bibl>
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		<profileDesc>
			<abstract><ab><![CDATA[The measurement of accurate full drop size distribution (DSD) is critical for its precise modeling and hydrometeorological application. However, its measurement hinders from instrumental limitation. We explored away of constructing full DSDs by combining the 2D-Video Distrometer (2DVD) and Meteorological ParticleSpectrometer (MPS) measurements based on instrumental uncertainty statistics, while other existing methods usea fixed critical diameter and weighting. First, the median relative bias (RB) of number concentration for eachdiameter between the two distrometers is used to determine the diameter range of their merging. Second, theweighting factors within the range were derived from normalized standard deviations of MPS and 2DVD numberconcentration by diameter during quasi-homogeneous microphysical process. The accuracy of derived full DSD isverified with the rainfall rate (R) and radar reflectivity (Z) from other independent instruments such as PLUVIOand Precipitation Occurrence Sensor System (POSS) that provide the best possible reference of R and Z. The newmethod is superior to the existing methods, providing relatively lower error statistics during summer rainfallevents in 2022. Additionally, the impact of the new method is analyzed on DSD variability using double-momentscaling normalization to derive a stable generic function. Four different triple-moment normalization methodsare also employed to describe the reduction of DSD variability. The results demonstrate  that the new full DSDsignificantly reduces DSD variability and better provides stable generic function of DSDs.]]></ab></abstract>
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