The aforementioned methodologies are highly tuned as a function of NWP model type and there- fore must be modified in accordance with the respective NWP model changes. This can often result in countless forecast cycles to determine if the tuning coefficients required to filter the TC from the synoptic environment and then relocate the respective TC, have been chosen correctly. In this study we seek an algorithm that is agnostic to both the atmospheric NWP model’s grid-length resolution and grid architecture and is thus applicable to any NWP model (regional-scale or global) capable of producing TCs. Further, the TC filtering methodology presented in this study is bound by meteorological analysis techniques and current observational understandings of TC structure.
We will first present an overview and application of the TC filtering algorithm to several TC cases. We will then apply the algorithm to relocate the TC for HWRF vortex-scale data assimilation and assess the impacts compared to the current operational HWRF forecast results.