Advances in Techniques of Quantitative Precipitation Forecast
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Abstract
The quantitative precipitation forecast (QPF) is a core operation of weather forecast. Modern technological processes of the QPF include numerical weather forecast, verification and evaluation, objective calibration and integration, forecaster's subjective modification and gridding post-processing. Domestic and international research work covering these five aspects are investigated and summarized, to provide reference for development of the quantitative precipitation forecast.In the aspect of numerical weather forecast, the forecast skill of the operational global model for precipitation has been improving continuously (a gain of about 1 forecast day per decade), and developments of the high resolution model (especially the convection-permitting model) contribute to describing characteristics of the convective precipitation, while the ensemble models provide uncertainty information and the most possible outcome of the forecast. These two techniques are the main way to improve the fine level and accuracy of QPF, and improvement of short-term precipitation forecast by developing operational high-resolution model ensembles is the international tendency. Objective calibration and integration as well as gridding post-processing make up the statistical post-processing technique of the QPF, which now reach a level that applies multiple approaches of data mining to extract and integrate more useful information from massive data, and the emergence of reforecast dataset will further promote the development of statistical post-processing. In terms of verification and evaluation, to solve new problems in assessing the fine level and accuracy of the QPF, a variety of new verification approaches are developed and applied, such as the new score for verifying the precipitation forecast of different climate backgrounds, extremes and multiple types, spatial verification methods for avoiding dual punishments of traditional methods, as well as the probability verification methods for verifying the stability, sharpness, and resolution of the probability forecast. In the aspect of forecaster's subjective modification, although the value added to model and post-processing methods become more and more limited, forecasters still play a core role, gradually changing to help users make decision. The development of QPF techniques still face challenges of solving scientific problems such as the observation of atmosphere moisture and data assimilation methods, as well as heavy rain forecast in warm section and complex topography.
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