Abstract: In order to solve the problem that the current verification score (Threat Score, TS) for heavy rainfall forecasting severely suffers from the double punishment due to the relatively high level of missing rate and false alarm rate as well as the ignorance of the uneven temporal and spatial distribution of heavy rainfall in China, the present study designs a new verification method and computational model for heavy rainfall forecasts based on the predictability of heavy rainfall and analysis of the expectation scores of forecasters. A new score model is designed and tested using the 5 km×5 km gridded quantitative precipitation forecast and precipitation location forecast issued by the China Central Meteorological Observatory from April to October during 2015-2016. The results and conclusions are as follow. (1) Forecaster's expectation scores for heavy rainfall forecast show a staircase-like descending characteristic, which is different from the traditional TS score. (2) A new forecast verification method based on the predictability of heavy rainfall is designed, which constructs the heavy rainfall forecast score basic function by first introducing an exponential function and then constructing the heavy rainfall grading model. The model can well fit the expectation of the forecaster's score for the heavy rainfall, and improve the score by reducing its cliff-like mutation at different levels of the threshold. (3) A neighborhood method of matching forecasts and observations is proposed, that is, a forecasting point is matched with a set of observations in a defined neighborhood, and a distance-weighted maximum score method to define the weighting coefficient of the rainstorm score is used. Thereby, the closer the distance between the forecast point and the observation point is, the greater the distance-weighted coefficient is and the higher the contribution of this point to the score value is. This method improves the rationality of the score and avoids the problem that a high score from a distant matching station is not encouraging for forecasters to improve the accuracy of forecasts. (4) Quantitative gridded precipitation forecasts at the 5 km×5 km horizontal resolution and quantitative precipitation location forecasts of the China Central Meteorological Observatory are verified using this new method. The accuracy of heavy rainfall forecasts is over 60 paints on average over entire China, and the daily evolution characteristic of the new score is similar to that of the traditional TS score. However, for the forecasts whose TS scores are 0, this new score is more consistent with the psychological expectations of both the forecasters and the public.