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An Improved Precipitation Nowcasting Algorithm Based on COTREC Method
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AI
DOI：10.1109/TGRS.2024.3446826.png)
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Abstract
En 中文
Accurate and refined nowcasting of short-term intense precipitation can be utilized to provide timely warnings and mitigate the damage caused by hydrological and meteorological disasters. Radar echo extrapolation can provide highly efficient forecasts of precipitation with high spatial and temporal resolution during the first 3 h and has been widely used in operational nowcasting systems in aviation, meteorology, hydrology, and other fields. However, these extrapolation methods still have drawbacks and need to be improved to provide more accurate nowcasting. In this article, an improved nowcasting method, based on the continuity of tracking of radar echo with correlations (COTREC), named ensembled COTREC (EnCOTREC), was proposed. A comparison was then made between the COTREC method and the EnCOTREC method for several types of precipitation processes. By comparing the EnCOTREC method and the COTREC method in squall line (SL), convective and stratiform precipitation processes, the results show that the EnCOTREC method is better at describing precipitation motion than the COTREC method and thus performs better in precipitation nowcasting. Especially for processes with a large precipitation area and uniform precipitation intensity, the accuracy improvement of EnCOTREC is more pronounced. Through time series analysis, the results of the EnCOTREC method are more stable than those of the COTREC method, and the EnCOTREC method can perform better than COTREC, with an overall improvement of 5%.
Keywords:
Precipitation
Storms
Radar tracking
Reflectivity
Vectors
Rain
Probabilistic logic
Continuity of tracking of radar echo with correlations (COTREC)
nowcasting
Journal
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8.6
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2.1W
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10.7W