华南带状对流典型个例的误差增长与内在可预报性
ID:204 View Protection:ATTENDEE Updated Time:2026-08-01 12:52:29 Hits:0 Invited speech

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Abstract
This talk will present our recent work of Weng et al. (2026, JGR). Intrinsic predictability of the weather defines the ultimate limit of our day-to-day weather forecasts. This study aims to investigate the variable- and scale-dependent intrinsic predictability of wave-convection coupled bands lasting nearly 10 hours near the south coast of China on 30 January 2018, by conducting perturbed and unperturbed convection-permitting simulations with 1-km horizontal grid spacing under varying initial moisture conditions. In particular, the predictability time scale of each selected forecast variable is quantified in the current study via the Loss Predictability Index (LPI), defined as the ratio of the forecast error (difference between perturbed and unperturbed) power spectrum to the reference (unperturbed) power spectrum at a given scale or within a range of scales. Spectral analysis reveals substantial differences in the reference power spectral slopes among variables, while their error growth behaviors consistently exhibit upscale features. The intrinsic predictability limit of the banded convection, measured by the difference total energy (DTE), is approximately 7 hours. Predictability varies with both scale and altitude: smaller scales (i.e., ~10 km) have shorter limits than larger scales (i.e., ~40 km), and the middle-level moist neutral stability layer is less predictable than the low-level ducting stable layer. In particular, for the moist neutral stability layer, different variables become more correlated under the coupling between gravity waves and moist convection, yielding more coherent predictability characteristics. In the dry experiment, predictability exceeds 12 hours with minimal error growth, regardless of the variable, scale, or altitude. Finally, the decomposition of the horizontal kinetic energy spectrum into divergent and rotational components (proxies for unbalanced and balanced components, respectively), demonstrates contrasting power spectra, intrinsic predictability limits, and their sensitivity to initial moist content, with the divergent component exhibiting longer predictability in the ducting stable layer at wavelengths <40 km. These findings highlight how vertical flow structure, moisture content, and distinct dynamical components jointly constrain the intrinsic predictability of mesoscale convective systems.

Reference:
Weng, Manshi, Junhong Wei, Yu Du, Y. Qiang Sun, and Xubin Zhang, 2026: Revisiting intrinsic predictability of wave-convection coupled bands over southern China: Variable and scale-dependent error growth characteristics. Journal of Geophysical Research: Atmospheres, 131: e2025JD045130. doi: https://doi.org/10.1029/2025JD045130
 
Keywords
重力波,中小尺度波动,对流,中尺度对流系统,暴雨,内在可预报性,误差增长,能谱
Speaker
卫俊宏
副教授 中山大学

Submission Author
翁曼诗 中山大学
卫俊宏 中山大学
杜宇 中山大学
孙永强 南京大学
张旭斌 中国气象局广州热带海洋气象研究所
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Important Date
  • Conference Date

    Aug 12

    2026

    to

    Aug 15

    2026

  • Aug 05 2026

    Draft paper submission deadline

  • Aug 12 2026

    Registration deadline

Sponsored By
成都信息工程大学
Organized By
成都信息工程大学
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