{'fraction_non_alphanumeric': 0.026458616010854818, 'fraction_numerical': 0.008141112618724558, 'mean_word_length': 5.020408163265306, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Analysis and Impact of Super-obbed Doppler Radial Velocity in the NCEP Grid-point Statistical Interpolation (GSI) Analysis System

Weather Doppler radar has the capability to scan large volumes of the atmosphere at high spatial and temporal resolutions. The real time access to the data from the entire WSR-88D network made possible by the fast internet now provides an unprecedented opportunity for using the data in operational numerical weather prediction (NWP) models. However, because of the huge volumes of radar data, the current operational data assimilation system cannot directly assimilate all of them. The relatively low resolutions of the current operational models also make the assimilation of full-volume data unnecessary. The fact that the definition of the radial velocity changes with the position of data relative to the radar poses an additional challenge not present with most other types of data; special treatment is therefore needed. The super-obbing technique is developed by Purser et al. (2000) to reduce redundant information in the observational data as well as the data density. In this paper, a “super-obbing” technique is used to preprocess the Level-II WSR-88D radar data (Parrish 2005) for thinning and combining radar radial velocity data. The “super-obbed” data are then analyzed in the NCEP unified GSI (Grid-point Statistical Interpolation) analysis system. The impact of the super-obbed data on the analysis is examined in this paper.