Advances of precipitation nowcasting and its application in hydrological forecasting

Abstract

With the global climate change and the imbalance of the ecological environment, extreme weather frequently occurs and presents multi-scale temporal and spatial variability characteristics. Early forecasting and warning of the extreme weathers has always been the focus of attention in the hydrometeorological field. Nowcasting can accurately predict the significant short-term changes of the future weather, and has become the main means of forecasting extreme weathers such as heavy precipitation events. In this study, a detailed overview of precipitation nowcasting is firstly given based on the developments of the 0-3 h weather radar extrapolation nowcasting and the 0-6 h blending nowcasting of weather radar and numerical weather prediction models. Special attentions are paid in briefing the developments of the radar extrapolation algorithms, and the blending techniques of weather radar and numerical weather prediction models. It is pointed out that there is great potential for the 0-6 h blending nowcasting in improving the accuracy of precipitation nowcasting and extending the forecast lead time, and to explore more advanced blending techniques is the core of the future development of nowcasting. At present, the application of precipitation nowcasting through atmospheric-hydrologic coupling is the main way to help improve the accuracy and guarantee the reliability of hydrological forecasting. Based on the discussion of the key issues in atmospheric-hydrologic coupling studies, e.g., the popular coupling mode, the matching problem of the spatial scale, and the uncertainties of hydrological models, the developments of studies incorporating radar extrapolation nowcasting and blending nowcasting into hydrological forecasting are presented, and the advantage of blending nowcasts in extending forecast lead time and improving forecast accuracy is illustrated. Finally, the research focus and future development is pointed out for blending nowcasting and its application in hydrological forecasting.