Performance of a Global Spectral Model with Dry Air-Mass and Total Air-Mass Conserving Dynamical Cores: A Case Study of the July 2021 Henan Extreme Rainfall Event

This study investigates the effects of the assumption on the types of air-mass conservation prescribed in numerical models. First, predictions of the July 2021 (“21.7”) Henan extreme rainfall event from the Integrated Forecast System (IFS) at ECMWF were compared with those from the Yin-He Global Spectral Model (YHGSM), which is a global spectral model with total air-mass conservation (TMC) and dry air-mass conservation (DMC) options. Then, a sensitivity test between simulations from the YHGSM adopting TMC and DMC was conducted. The results show that both the IFS and YHGSM predicted relatively well the 24-h rainfall amount less than 100 mm day⁻¹ on 20 and 21 July 2021 at lead times of 84, 60, and 36 h. For heavy precipitation exceeding 100 mm day⁻¹, however, both models obviously underestimated the daily rainfall amount on 20 July 2021, but the YHGSM produced more precise and stable precipitation forecasts on these two days than the IFS, especially the maximum 24-h precipitation amount, with better consistency at lead times of 84, 60, and 36 h. These differences are further examined in the sensitivity test. Predictions from the YHGSM with DMC show rainfall distributions and daily rainfall amounts closer to the observations at longer lead times. It is inferred that considering sources or sinks of total water in dynamical cores with DMC may have positive feedback for the precise prediction of condensates. For extreme rainfall events, the high local loss of total water may have caused a loss of the atmospheric mass, leading to an additional decrease in surface pressure. Subsequently, the unbalanced pressure gradient force enhances the cyclonic rotation of surface wind and strengthens convergence in the lower troposphere, which in turn further strengthens the vertical velocity, circularly contributing to the enhanced precipitation if the water vapor condition is favorable.