J5.5A From Sailing Ships to GOES-R: How Improving Technology for Observing Hurricanes Affects Climate Trends (Invited Presentation)

Tuesday, 8 January 2019: 12:00 AM
North 232AB (Phoenix Convention Center - West and North Buildings)
Christopher W. Landsea, NHC, Miami, FL

The database for tropical cyclones in the Atlantic basin (including the North Atlantic Ocean, Caribbean Sea, and Gulf of Mexico) extends back to 1851. Since the database ("HURDAT2") was initially developed in the 1960s, it has been used for a wide variety of purposes, such as setting appropriate building codes for coastal zones, risk assessment for emergency managers, analysis of potential losses for insurance and business interests, development of intensity forecasting techniques, verification of official and model projections of track and intensity, seasonal forecasting, and climatic change studies. Because of the nature of tropical cyclones being mesoscale, oceanic phenomenon, their analyses over time are extremely dependent upon the technology available to observe them. In the mid-1800s at the advent of the HURDAT2 database, tropical cyclone were only observable from ships and coastal stations. Today, the technology includes geostationary/low-earth orbiting satellite imagery, scatterometer data, NOAA/Air Force Hurricane Hunters (including flight-level observations, the Stepped Frequency Microwave Radiometer, Global Positioning System dropsondes, and airborne Doppler radar), moored and drifting buoys, and coastal Doppler radars, in addition to ships and coastal stations. These dramatic improvements in the way tropical cyclones are monitored directly impacts the frequency of the systems in the database as well as the recorded intensity. This presentations provides a discussion of the tropical cyclone observational advances that have occurred over many decades, what technology may be employed in the future for additional improvements, as well as methodology for determining the undersampling in the frequency and intensity of tropical cyclones to improve estimates of true climate trends and variability.
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