Uncertainties and error growth in forecasting the record-breaking rainfall in Zhengzhou, Henan on 19–20 July 2021

This study explores the controlling factors of the uncertainties and error growth at different spatial and temporal scales in forecasting the high-impact extremely heavy rainfall event that occurred in Zhengzhou, Henan Province China on 19–20 July 2021 with a record-breaking hourly rainfall exceeding 200 mm and a 24-h rainfall exceeding 600 mm. Results show that the strengths of the mid-level low-pressure system, the upper-level divergence, and the low-level jet determine both the amount of the extreme 24-h accumulated and hourly rainfall at 0800 UTC. The forecast uncertainties of the accumulated rainfall are insensitive to the magnitude and the spatial structure of the tiny, unobservable errors in the initial conditions of the ensemble forecasts generated with Global Ensemble Forecast System (GEFS) or sub-grid-scale perturbations, suggesting that the predictability of this event is intrinsically limited. The dominance of upscale rather than upamplitude error growth is demonstrated under the regime of k−5/3 power spectra by revealing the inability of large-scale errors to grow until the amplitude of small-scale errors has increased to an adequate amplitude, and an apparent transfer of the fastest growing scale from smaller to larger scales with a slower growth rate at larger scales. Moist convective activities play a critical role in enhancing the overall error growth rate with a larger error growth rate at smaller scales. In addition, initial perturbations with different structures have different error growth features at larger scales in different variables in a regime transitioning from the k−5/3 to k−3 power law. Error growth with conditional nonlinear optimal perturbation (CNOP) tends to be more upamplitude relative to the GEFS or sub-grid-scale perturbations possibly owing to the inherited error growth feature of CNOP, the inability of convective parameterization scheme to rebuild the k−5/3 power spectra at the mesoscales, and different error growth characteristics in the k−5/3 and k−3 regimes.

This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s11430-022-9991-4



Work Title Uncertainties and error growth in forecasting the record-breaking rainfall in Zhengzhou, Henan on 19–20 July 2021
Open Access
  1. Yunji Zhang
  2. Huizhen Yu
  3. Murong Zhang
  4. Yawen Yang
  5. Zhiyong Meng
  1. Extremely heavy rainfall
  2. Forecast error
  3. Predictability
  4. Ensemble forecast
  5. Henan
License In Copyright (Rights Reserved)
Work Type Article
  1. Science China Earth Sciences
Publication Date September 19, 2022
Publisher Identifier (DOI)
  1. https://doi.org/10.1007/s11430-022-9991-4
Deposited March 18, 2024




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Work History

Version 1

  • Created
  • Added 10.1007-s11430-022-9991-4.pdf
  • Added Creator Yunji Zhang
  • Added Creator Huizhen Yu
  • Added Creator Murong Zhang
  • Added Creator Yawen Yang
  • Added Creator Zhiyong Meng
  • Published
  • Updated Keyword, Publication Date Show Changes
    • Extremely heavy rainfall, Forecast error, Predictability, Ensemble forecast, Henan
    Publication Date
    • 2022-10-01
    • 2022-09-19
  • Updated