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contributor authorPutnam, Bryan
contributor authorXue, Ming
contributor authorJung, Youngsun
contributor authorSnook, Nathan
contributor authorZhang, Guifu
date accessioned2019-10-05T06:54:29Z
date available2019-10-05T06:54:29Z
date copyright3/28/2019 12:00:00 AM
date issued2019
identifier otherMWR-D-18-0251.1.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4263803
description abstractAbstractReal polarimetric radar observations are directly assimilated for the first time using the ensemble Kalman filter (EnKF) for a supercell case from 20 May 2013 in Oklahoma. A double-moment microphysics scheme and advanced polarimetric radar observation operators are used together to estimate the model states. Lookup tables for the observation operators are developed based on T-matrix scattering amplitudes for all hydrometeor categories, which improve upon previous curved-fitted approximations of T-matrix scattering amplitudes or the Rayleigh approximation. Two experiments are conducted: one assimilates reflectivity (Z) and radial velocity (Vr) (EXPZ), and one assimilates in addition differential reflectivity (ZDR) below the observed melting level at ~2-km height (EXPZZDR). In the EnKF analyses, EXPZZDR exhibits a ZDR arc that better matches observations than EXPZ. EXPZZDR also has higher ZDR above 2 km, consistent with the observed ZDR column. Additionally, EXPZZDR has an improved estimate of the model microphysical states. Specifically, the rain mean mass diameter (Dnr) in EXPZZDR is higher in the ZDR arc region and the total rain number concentration (Ntr) is lower downshear in the forward flank than EXPZ when compared to values retrieved from the polarimetric observations. Finally, a negative gradient of hail mean mass diameter (Dnh) is found in the right-forward flank of the EXPZZDR analysis, which supports previous findings indicating that size sorting of hail, as opposed to rain, has a more significant impact on low-level polarimetric signatures. This paper represents a proof-of-concept study demonstrating the value of assimilating polarimetric radar data in improving the analysis of features and states related to microphysics in supercell storms.
publisherAmerican Meteorological Society
titleEnsemble Kalman Filter Assimilation of Polarimetric Radar Observations for the 20 May 2013 Oklahoma Tornadic Supercell Case
typeJournal Paper
journal volume147
journal issue7
journal titleMonthly Weather Review
identifier doi10.1175/MWR-D-18-0251.1
journal fristpage2511
journal lastpage2533
treeMonthly Weather Review:;2019:;volume 147:;issue 007
contenttypeFulltext


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