Abstract
Very short-term (0~3 h) radar-based quantitative precipitation forecasting (QPF), also known as nowcasting, plays an essential role in flash flood warning, water resource management, and other hydrological applications. A novel nowcasting method combining radar data and a model wind field was developed and validated with two hurricane precipitation events. Compared with several existing nowcasting approaches, this work attempts to enhance the prediction capabilities from two major aspects. First, instead of using a radar reflectivity field, this work proposes the use of the rainfall rate field estimated from polarimetric radar variables in the motion field derivation. Second, the derived motion field is further corrected by the Rapid Refresh (RAP) model field. With the corrected motion field, the future rainfall rate field is predicted through a linear extrapolation method. The proposed method was validated using two hurricanes: Harvey and Irma. The proposed work shows an enhanced performance according to statistical scores. Compared with the model only and centroid-tracking only approaches, the average probability of detection (POD) increases about 25% and 50%; the average critical success index (CSI) increases about 20% and 37%; and the average false alarm rate (FAR) decreases about 14% and 16%, respectively.
Highlights
Published: 13 June 2021Very short-term (0~3 h) radar-based quantitative precipitation forecasting (QPF), known as nowcasting, plays an essential role in flash flood warning, water resource, management and other hydrological applications
The extrapolation using a precipitation motion field derived from the cross-correlation or the numerical weather prediction (NWP) model is considered the optimum method for nowcasting widespread and persistent rains [7,8]
Derived the centroid-tracking from the method other two approaches, using the motion field derived from the centroid-tracking only and using the model field only
Summary
Published: 13 June 2021Very short-term (0~3 h) radar-based quantitative precipitation forecasting (QPF), known as nowcasting, plays an essential role in flash flood warning, water resource, management and other hydrological applications. Radar-based QPF approaches predict storm motions by extrapolating the radar observation patterns into the future. The precipitation motion field, called the velocity vector, plays a critical role in nowcasting. The motion field can be derived with either pattern matching approaches or centroid-tracking approaches. The entire field’s motions and components are established through the cross-correlation between two adjacent moments in the reflectivity fields [3,4,5,6]. The extrapolation using a precipitation motion field derived from the cross-correlation or the numerical weather prediction (NWP) model is considered the optimum method for nowcasting widespread and persistent rains [7,8]. The centroid-tracking approach derives a motion vector through tracking the temporal sequence of the centroid positions of observed
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