The Quantile-Matching Approach to Improving Radar Quantitative Precipitation Estimation in South China

Yun Li,Duo Qi,Mingxuan Chen,Linye Song,Jiankun Wu,Weihua Cao,Shangfeng Chen

doi:10.3390/rs13234956

Abstract

Weather radar provides regional rainfall information with a very high spatial and temporal resolution. Because the radar data suffer from errors from various sources, an accurate quantitative precipitation estimation (QPE) from a weather radar system is crucial for meteorological forecasts and hydrological applications. In the South China region, multiple weather radar networks are widely used, but the accuracy of radar QPE products remains to be analyzed and improved. Based on hourly radar QPE and rain gauge observation data, this study first analyzed the QPE error in South China and then applied the Quantile Matching (Q-matching) method to improve the radar QPE accuracy. The results show that the rainfall intensity of the radar QPE is generally larger than that determined from rain gauge observations but that it usually underestimates the intensity of the observed heavy rainfall. After the Q-matching method was applied to correct the QPE, the accuracy improved by a significant amount and was in good agreement with the rain gauge observations. Specifically, the Q-matching method was able to reduce the QPE error from 39–44%, demonstrating performance that is much better than that of the traditional climatological scaling method, which was shown to be able to reduce the QPE error from 3–15% in South China. Moreover, after the Q-matching correction, the QPE values were closer to the rainfall values that were observed from the automatic weather stations in terms of having a smaller mean absolute error and a higher correlation coefficient. Therefore, the Q-matching method can improve the QPE accuracy as well as estimate the surface precipitation better. This method provides a promising prospect for radar QPE in the study region.

Highlights

Precipitation is a key variable of weather forecasting and water cycle regulation, and it has pronounced impacts on both meteorological and hydrological processes
This study evaluates the errors of 1 radar QPE precipitation products that have been accumulated hourly from the SWAN system in the South China region and further proposes a new Q-matching method to improve the radar quantitative precipitation estimations
The climatological scaling method, which was previously used for the North China region, is applied to correct the QPE to examine whether it is appropriate for use in the

Summary

Introduction

Precipitation is a key variable of weather forecasting and water cycle regulation, and it has pronounced impacts on both meteorological and hydrological processes. The Doppler weather radar has become an important method for precipitation monitoring [6,7,8] because accurate and timely areal rainfall data are crucial for hydrometeorological forecasting and early flash-flood warnings. Quantitative precipitation estimation (QPE) products can be generated by radar stereoscopic scanning observation by means of the transformational relationship between radar reflectivity (Z) and the surface rainfall rate (R). The radar QPE products are characterized by high spatial resolution and temporal continuity [9,10,11,12], which are crucial for hydrometeorological coupled forecasts and have already been wildly applied in many meteorological departments in China. The radar QPE products are characterized by high spatial resolution and temporal continuity [9,10,11,12], which are crucial for hydrometeorological coupled forecasts and have already been wildly applied in many meteorological departments in China. 4.0/).

Results

Discussion

Conclusion