337 Diagnosing Tropical Cyclones in the Central Pacific with the VIIRS Day Night Band

Monday, 11 January 2016
Eric Lau, NOAA/NWS, Honolulu, HI; and J. J. Gerth

As Tropical Storm Ela decayed to the east of Hawaii on 8 July 2015, night fell and meteorologists at the Central Pacific Hurricane Center (CPHC) were left with infrared imagery from geostationary satellites that depicted the nature of storm tops but little about the storm structure. In the early morning hours of 9 July 2015, the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (NPP) satellite provided a visible image of Ela with moonlight illuminating the clouds, and providing operational meteorologists the ability to distinguish Ela's low-level center of circulation, a critical piece of information in assessing the strength of the storm and forecasting future movement. This is not the first time that the Day Night Band (DNB) on VIIRS has provided important information to forecasters; the first was on 29 July 2013 with Tropical Storm Flossie encountering an organization-hostile sheared environment overnight. The DNB has become an important tool in the CPHC forecasters' arsenal for storm diagnosis. The timely delivery of this imagery to the field has been made possible by two complementary L/X-band receiving antennas in Honolulu, Hawaii, that capture data from the Suomi NPP satellite, and other polar-orbiting satellites, in real-time and process it with the Community Satellite Processing Package (CSPP) to deliver to the field. In part due to the exceptional utility of these antennas and the Suomi NPP imagery to CPHC, an additional antenna is planned for installation in Guam by early 2016. This poster will show examples of several tropical systems from the 2015 Central Pacific hurricane season and how the VIIRS DNB contributed to critical forecast decisions at CPHC, with excerpts from storm advisories. The poster will also describe the other satellites and types of imagery that are available to forecasters, and how they apply to the tropical cyclone forecast process.
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