NDLI: Analysis study on perturbation energy and predictability of heavy precipitation in South China

Content Provider	Springer Nature Link
Author	Zhu, Benlu Lin, Wantao Zhang, Yun
Copyright Year	2010
Abstract	The AREMv2.3 mesoscale numerical model is used to explore storm processes in South China during the pre-rainy season in 2006 by imposing perturbations on the initial fields of physical variables (temperature, humidity, and wind fields). Sensitivity experiments are performed to examine the impacts of initial uncertainties on precipitation, on the error growth, and on the predictability of mesoscale precipitation in South China. The primary conclusion is that inherent initial condition uncertainties can significantly limit the predictability of storm. The 24-h accumulated precipitation is most sensitive to temperature perturbations. Larger-amplitude initial uncertainties generally lead to larger perturbation energies than those with smaller amplitude, but these kinds of differences decrease with time monotonically so the mechanism for the growth of perturbation energy is nonlinear. The power spectra of precipitation differences indicate that predictability increases with accumulated time. This also indicates the difficulties faced for short-term, small-scale precipitation forecasting.
Starting Page	382
Ending Page	392
Page Count	11
File Format	PDF
ISSN	02561530
Journal	Advances in Atmospheric Sciences
Volume Number	27
Issue Number	2
e-ISSN	18619533
Language	English
Publisher	SP Science Press
Publisher Date	2010-02-16
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	initial perturbation error growth DTE predictability Geophysics/Geodesy Meteorology/Climatology
Content Type	Text
Resource Type	Article
Subject	Atmospheric Science

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