Abstract

Abstract. The extrapolation of the precipitation to the ground from radar reflectivities measured at the beam altitude is one of the most delicate phases of radar data processing for producing quantitative precipitation estimations (QPEs) and remains a major scientific issue. In many operational meteorological services such as Météo-France, a vertical profile of reflectivity (VPR) correction is uniformly applied over a large part or the entire radar domain. This method is computationally efficient, and the overall bias induced by the bright band is most of the time well corrected. However, this way of proceeding is questionable in situations with high spatial and vertical variability of precipitation (during the passage of a cold front or in a complex terrain, for example). This study initiates from two statements: first, radars provide information on precipitation with a high spatio-temporal resolution but still require VPR corrections to extrapolate rain rates at the ground level. Second, the horizontal resolution of some numerical weather prediction (NWP) models is now comparable with the radar one, and their dynamical core and microphysics schemes allow the production of realistic simulations of VPRs. The present paper proposes a new approach to assess surface rainfall from radar reflectivity aloft by exploiting simulated VPRs and rainfall forecasts from the high-resolution NWP model AROME-NWC. To our knowledge, this is the first time that simulated precipitation profiles from an NWP model are used to derive radar QPEs. The implementation of the new method on two stratiform situations provided significant improvements on the hourly and 6 h accumulations compared to the operational QPEs, showing the relevance of this new approach.

Highlights

  • Precise quantitative precipitation estimates (QPEs) are critical for many applications including nowcasting, hydrology and flood forecasts

  • The present paper proposes a new approach to assess surface rainfall from radar reflectivity aloft by exploiting simulated vertical profile of reflectivity (VPR) and rainfall forecasts from the high-resolution numerical weather prediction (NWP) model AROME-NWC

  • Hydrometeors may be liquid or solid or a mixture of two states and can precipitate to the ground in the form of rain or snow depending on several factors

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Summary

Introduction

Precise quantitative precipitation estimates (QPEs) are critical for many applications including nowcasting, hydrology and flood forecasts. High-resolution QPEs are necessary to correctly predict the occurrence and intensity of heavy rainfall events and flash floods. Operational rain gauges can provide accurate measurements of the rainfall, but the operational networks are generally too sparse to capture the high spatial and temporal variability of precipitation, especially over complex terrain. Weather radars provide spatially continuous precipitation estimates at very high spatial and temporal resolutions, filling the gaps in in situ observation networks. The radar does not provide direct estimates of precipitation but rather an indirect measure which is the backscattered signal of hydrometeors in the atmosphere. Hydrometeors may be liquid or solid or a mixture of two states and can precipitate to the ground in the form of rain or snow depending on several factors. The estimation of precipitation by radar is subject to several sources of error that need to be understood and evaluated (Zawadzki, 1984; Joss and Lee, 1995; Dinku et al, 2002; Villarini and Krajewski, 2010)

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