12:00 〜 12:15
[AAS07-12] 全球データ同化ための、EarthCARE/CPRの予備評価
★招待講演
キーワード：データ同化、CPR、全球数値予報、衛星
The space-based cloud profiling radar (CPR) is valuable in evaluating and improving cloud processes of numerical weather prediction (NWP) and climate models. Assimilating CPR will also be beneficial for improving accuracy in NWP analysis and forecasts. Successful assimilation of CPR observations requires a deep understanding of the characteristics of CPR observation and its simulation from NWP model used in the data assimilation system. This study aims to evaluate simulation by comparing CPR observation and simulation made by the global model at Japan Meteorological Agency.
This comparison study started for CloudSat/CPR and now deals with EarthCARE/CPR. RTTOV ver13.0 is used as a radar simulator to simulate assimilation variables of radar reflectivity. EarthCARE/CPR reflectivity observations are obtained from L2a CPR One-sensor Echo Product and averaged to match an assimilation horizontal scale (~55 km). The comparison for three weeks in August 2024 shows that simulated reflectivity is smaller in its variability and slightly weaker in mean echo than observed reflectivity except at high altitudes. The reflectivity departure of observation from the simulation is carefully examined because it is especially important for data assimilation. For example, its probability density function, situation dependency, and scale representativity are being examined. In the meeting, we will present the latest findings and discuss how to effectively assimilate EarthCARE/CPR.
This comparison study started for CloudSat/CPR and now deals with EarthCARE/CPR. RTTOV ver13.0 is used as a radar simulator to simulate assimilation variables of radar reflectivity. EarthCARE/CPR reflectivity observations are obtained from L2a CPR One-sensor Echo Product and averaged to match an assimilation horizontal scale (~55 km). The comparison for three weeks in August 2024 shows that simulated reflectivity is smaller in its variability and slightly weaker in mean echo than observed reflectivity except at high altitudes. The reflectivity departure of observation from the simulation is carefully examined because it is especially important for data assimilation. For example, its probability density function, situation dependency, and scale representativity are being examined. In the meeting, we will present the latest findings and discuss how to effectively assimilate EarthCARE/CPR.