Can composite reflectivity be used as a predictor of convective precipitation in weather forecasting?
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Composite reflectivity can be used as a predictor of convective precipitation in weather forecasting. Deep learning techniques have been employed to predict future time steps of precipitation using historical composite reflectivity (CR) data . Geostationary meteorological satellites have also been used to estimate radar composite reflectivity, providing near global coverage and real-time observations . The assimilation of radar reflectivity data into convective-scale forecasts has been shown to improve forecast accuracy, with ensemble-based methods producing the highest verification scores . Additionally, a deep learning-based model has been proposed to retrieve radar composite reflectivity factor (RCRF) maps from satellite data, showing good agreement with precipitation patterns . Furthermore, the use of deep learning techniques, combined with 3D radar images, has shown promise in predicting the evolution of convective rain cells, including their reflectivity properties .
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4 Citations | No, the paper does not explicitly mention whether composite reflectivity can be used as a predictor of convective precipitation in weather forecasting. |
06 Jul 2023 | The paper does not mention the use of composite reflectivity as a predictor of convective precipitation in weather forecasting. The paper focuses on using 3D radar measurements and deep learning techniques to predict the evolution of convective rain cells. |
| No, the paper does not explicitly mention whether composite reflectivity can be used as a predictor of convective precipitation in weather forecasting. | |
| The paper does not explicitly mention whether composite reflectivity can be used as a predictor of convective precipitation in weather forecasting. |
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