The impact of airborne radio occultation observations on the simulation of Hurricane Karl (2010)

TitleThe impact of airborne radio occultation observations on the simulation of Hurricane Karl (2010)
Publication TypeJournal Article
Year of Publication2018
AuthorsChen X.M, Chen S.H, Haase JS, Murphy B.J, Wang K.N, Garrison J.L, Chen S.Y, Huang C.Y, Adhikari L., Xie F.
JournalMonthly Weather Review
Date Published2018/01
Type of ArticleArticle
ISBN Number0027-0644
Accession NumberWOS:000428699000018
Keywordscyclones; data assimilation system; Ensemble Kalman filter; full spectrum; genesis potential index; inversion; Meteorology & Atmospheric Sciences; observation operator; rapid intensification; refractive-index; satellite radiance data; track forecasts; tropical

This study evaluates, for the first time, the impact of airborne global positioning system radio occultation (ARO) observations on a hurricane forecast. A case study was conducted of Hurricane Karl during the PreDepression Investigation of Cloud-Systems in the Tropics (PREDICT) field campaign in 2010. The assimilation of ARO data was developed for the three-dimensional variational (3DVAR) analysis system of the Weather Research and Forecasting (WRF) Model version 3.2. The impact of ARO data on Karl forecasts was evaluated through data assimilation (DA) experiments of local refractivity and nonlocal excess phase (EPH), in which the latter accounts for the integrated horizontal sampling along the signal ray path. The tangent point positions (closest point of an RO ray path to Earth's surface) drift horizontally, and the drifting distance of ARO data is about 2 to 3 times that of spaceborne RO, which was taken into account in these simulations. Results indicate that in the absence of other satellite observations, the assimilation of ARO EPH resulted in a larger impact on the analysis than local refractivity did. In particular, the assimilation of ARO observations at the actual tangent point locations resulted in more accurate forecasts of the rapid intensification of the storm. Among all experiments, the best forecast was obtained by assimilating ARO data with the most accurate geometric representation, that is, the use of nonlocal EPH operators with tangent point drift, which reduced the error in the storm's predicted minimum sea level pressure (SLP) by 43% beyond that of the control experiment.

Short TitleMon. Weather Rev.
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