This study evaluates the impact of observational data on understanding and analyzing the inner-core structure of tropical cyclones using ensemble-based methods. A 60-member ensemble simulation was performed for Typhoon Nanmadol (2022) during its rapid intensification, incorporating all-sky infrared radiances from Himawari-8. We computed storm-relative three-dimensional ensemble correlations between model variables and synthetic aircraft dropsonde observations, and investigated their dependence on the observation locations. To account for variation in storm size, the spatial scale was normalized by the radius of maximum wind (RMW). Finally, to compare the information content among various synthetic observations with complex correlation patterns, we used the mean absolute value and standard deviation of the correlations, as summary statistics, which were aggregated along concentric circles to assess extractable information on each radius under different observation conditions. The analysis demonstrated that the quality of obtainable information depends on both the observed variable and its spatial position relative to the storm center. Pressure and temperature, which reflect the axisymmetric and large-scale structure of the cyclone, showed high correlations, while water vapor mixing ratio, associated with finer-scale convection, exhibited weaker correlations. Strong correlations and spatially antisymmetric patterns were observed near the observation radius. Notably, inner-core observations provided information extending to outer regions, whereas outer-core observations contained less information about the storm center, revealing an asymmetry in information content.
Using this framework, we also evaluated the potential contributions of dropsonde observations from the T-PARC2 campaign by assimilating them into the storm-dependent scaled coordinates and assessing the ensemble spread reduction. These results suggest that dropsonde observations taken within or near the eyewall are highly valuable for improving analysis and prediction of inner-core dynamics, and should be prioritized in future observation strategies.
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