A case study of the error growth and predictability of a Meiyu frontal heavy precipitation event |
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Authors: | Yu Luo and Lifeng Zhang |
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Institution: | (1) Korea Ocean Research and Development Institute, Ansan, Korea;(2) School of Earth and Environment Sciences, Seoul National University, Seoul, Korea;(3) Center for Climate System Research, University of Tokyo, Tokyo, Japan;(4) Department of Meteorology, SOEST, University of Hawaii, Hawaii, USA |
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Abstract: | The Advanced Regional Eta-coordinate Model (AREM) is used to explore the predictability of a heavy rainfall event along the
Meiyu front in China during 3–4 July 2003. Based on the sensitivity of precipitation prediction to initial data sources and
initial uncertainties in different variables, the evolution of error growth and the associated mechanism are described and
discussed in detail in this paper. The results indicate that the smaller-amplitude initial error presents a faster growth
rate and its growth is characterized by a transition from localized growth to widespread expansion error. Such modality of
the error growth is closely related to the evolvement of the precipitation episode, and consequently remarkable forecast divergence
is found near the rainband, indicating that the rainfall area is a sensitive region for error growth. The initial error in
the rainband contributes significantly to the forecast divergence, and its amplification and propagation are largely determined
by the initial moisture distribution. The moisture condition also affects the error growth on smaller scales and the subsequent
upscale error cascade. In addition, the error growth defined by an energy norm reveals that large error energy collocates
well with the strong latent heating, implying that the occurrence of precipitation and error growth share the same energy
source—the latent heat. This may impose an intrinsic predictability limit on the prediction of heavy precipitation. |
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Keywords: | heavy precipitation predictability initial error model error growth AREM |
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