| Autor: |
Mangla, Rohit, Borderies, Mary, Chambon, Philippe, Geer, Alan, Hocking, James |
| Předmět: |
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| Zdroj: |
Atmospheric Measurement Techniques Discussions; 9/4/2024, p1-50, 50p |
| Abstrakt: |
Because of their high sensitivity to hydrometeors and their high vertical resolutions, space-borne radar observations are emerging as an undeniable asset for Numerical Weather Prediction (NWP) applications. The EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) NWP SAF (Satellite Application Facility) released an active sensor module within version 13 of the RTTOV (Radiative Transfer for TOVS) software with the goal of simulating both active and passive microwave instruments within a single framework using the same radiative transfer assumptions. This study provides an in-depth description of the radar simulator available within this software. In addition, this study proposes a revised version of the existing melting layer parametrization scheme of Bauer (2001) within the RTTOV-SCATT v13.1 model to provide a better fit to observations below the freezing level. Simulations are performed with and without melting layer schemes for the Dual precipitation radar (DPR) instrument onboard GPM using the ARPEGE (Action de Recherche Petite Echelle Grande Echelle) global NWP model running operationally at Météo-France for two different one-month periods (June, 2020 and January, 2021). Results for a case study over the Atlantic ocean show that the revised melting scheme produces more realistic simulations as compared to the default scheme both at Ku (13.5 GHz) and Ka (35.5 GHz) frequencies and these simulations are much closer to observations. A statistical assessment using more samples show significant improvement of the first-guess departure statistics with the revised scheme compared to the existing melting scheme. As a step further, this study showcases the use of melting layer simulations for the classification of precipitation (stratiform, convective and transition) using the Dual Frequency Ratio algorithm (DFR). The classification results also reveal a significant overestimation of the rain reflectivities in all hemispheres, which can either be due to a tendency of the ARPEGE model to produce a too large amount of convective precipitation, or to a mis-representation of the convective precipitation fraction within the forward operator. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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