Open AccessConsiderations for Phased-Array Radar Data Use within the National Weather Service
Author(s) -
Katie A. Wilson,
Pamela L. Heinselman,
Charles M. Kuster
Publication year - 2017
Publication title -
weather and forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.393
H-Index - 106
eISSN - 1520-0434
pISSN - 0882-8156
DOI - 10.1175/waf-d-17-0084.1
Subject(s) - national weather service , thematic map , phased array , focus group , radar , computer science , service (business) , thematic analysis , focus (optics) , warning system , variety (cybernetics) , weather radar , data science , geography , business , meteorology , telecommunications , marketing , qualitative research , artificial intelligence , social science , physics , cartography , sociology , antenna (radio) , optics
Thirty National Weather Service forecasters worked with 1-, 2-, and 5-min phased-array radar (PAR) volumetric updates for a variety of weather events during the 2015 Phased Array Radar Innovative Sensing Experiment. Exposure to each of these temporal resolutions during simulated warning operations meant that these forecasters could provide valuable feedback on how rapidly updating PAR data impacted their warning decision processes. To capture this feedback, forecasters participated in one of six focus groups. A series of open-ended questions guided focus group discussions, and forecasters were encouraged to share their experiences and opinions from the experiment. Transcriptions of focus group discussions were thematically analyzed, and themes belonging to one of two groups were identified: 1) forecasters’ use of rapidly updating PAR data during the experiment and 2) how forecasters envision rapidly updating PAR data being integrated into warning operations. Findings from this thematic analysis are presented in this paper, and to illustrate these findings from the forecasters’ perspectives, dialogue that captures the essence of their discussions is shared. The identified themes provide motivation to integrate rapidly updating radar data into warning operations and highlight important factors that need to be addressed for the successful integration of these data.