Thursday, 14 January 2016: 4:15 PM
Room 252/254 ( New Orleans Ernest N. Morial Convention Center)
Weather forecast operations at the National Weather Service (NWS) in Guam are heavily dependent on the Japan Meteorological Agency (JMA) geostationary satellite, since the Geostationary Operational Environmental Satellites (GOES) do not observe the western Pacific basin, and Guam is otherwise in a geographical region lacking extensive in-situ observations. Fortunately, the imagers on the JMA satellite and GOES have historically been similar, so special training for Guam has been unnecessary in the past. Ahead of the 2016 launch of the first GOES R-Series, JMA launched Himawari-8 in late 2014, which became operational in mid 2015. The Advanced Himawari Imager (AHI) is very similar to the Advanced Baseline Imager (ABI) on GOES-R. However, forecasters in Guam will be exposed to the improved spatial, spectral, and temporal resolution of the AHI imagery well before forecasters in the rest of the United States have access to ABI imagery. In order to prepare operational meteorologists at NWS Guam for the capabilities of AHI, the NWS is investing in a new prototype training method where trainers are dispatched to the field office to lead forecasters in several four-hour sessions over two to three days. Some of the sessions are tailored with examples from the common meteorological challenges and scenarios in the tropics. In each session, participants will hear a short presentation from a subject-matter expert (SME) and then, in small groups, investigate real imagery using a software application specifically designed for the training environment, with oversight from the SME. The intent of the immersive environment is for forecasters to obtain the necessary background knowledge about the satellite instrument and imagery, and then learn more about the relevant applications to operational meteorology and their local area through viewing and interrogating the imagery in a guided lab setting. This presentation will outline the curriculum for the NWS Guam Himawari training, highlight certain course materials, discuss the training software application, and propose future uses for this training delivery method in the context of the broader NWS training initiatives that are underway to assure NWS meteorologists are well prepared for the GOES-R ABI. With continued success and funding, this course could be tailored for other field offices, such as NWS Honolulu, and even those with responsibilities beyond the tropics, such as NWS Anchorage and NWS Fairbanks.
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