Feature Sept. 02, 2010
NASA Hurricane Researchers Eye Earl's Eye
The full version of this story with accompanying images is at:
http://www.jpl.nasa.gov/news/news.cfm?release=2010-285&cid=release_2010-285
Hurricane Earl, currently a Category Two storm on the Saffir-Simpson scale with maximum sustained winds of 100 knots (115 miles per hour), continues to push relentlessly toward the U.S. East Coast, and NASA scientists, instruments and spacecraft are busy studying the storm from the air and space. Three NASA aircraft carrying 15 instruments are busy criss-crossing Earl as part of the agency's Genesis and Rapid Intensification Processes mission, or GRIP, which continues through Sept. 30. GRIP is designed to help improve our understanding of how hurricanes such as Earl form and intensify rapidly.
Among the instruments participating in GRIP is the High-Altitude Monolithic Microwave Integrated Circuit Sounding Radiometer, or HAMSR, developed by NASA's Jet Propulsion Laboratory, Pasadena, Calif. The instrument, which flies aboard NASA's Global Hawk uninhabited aerial vehicle, infers the 3-D distribution of temperature, water vapor and cloud liquid water in the atmosphere.
The Global Hawk left NASA's Dryden Flight Research Center, Edwards, Calif., at 9 p.m. PDT on Sept. 1, and emerged off the coast of Florida seven hours later to begin its first-ever flight over a hurricane. The plane spent the day today flying over Earl and is returning to Dryden tonight.
HAMSR has been able to make multiple passes straight across Earl's eye. Brightness temperature data were collected by HAMSR. The Global Hawk was flying at an altitude of about 19.2 kilometers (63,000 feet) approximately 1,125 kilometers (700 miles) off Florida's east coast.
HAMSR's many capabilities include measuring sea surface and atmospheric temperature, convection and precipitation. Scientists can determine the change of atmospheric temperatures at different altitudes within a storm's eye, an indication of the strength of convection in the core of the storm. This warming is due to the condensation of water vapor that has been lofted to higher altitudes by the strong convection. This is the engine that powers the storm. That temperature data, in turn, can be used to estimate the intensity of the hurricane. NOAA's National Hurricane Center is currently using this method to determine hurricane intensity.
A second JPL instrument participating in GRIP and flying over Earl is the Airborne Precipitation Radar (APR-2), a dual-frequency weather radar that is taking 3-D images of precipitation aboard NASA's DC-8 aircraft. APR-2 is being used to help scientists understand the processes at work in hurricanes by looking at the vertical structure of the storms.
Two APR-2 images reveal the early evolution of Hurricane Earl from a rather disorganized storm to a better developed hurricane with a more distinct and smaller eye and sharper eyewall. The data, taken during southbound passes over Earl's eye on Aug. 29 and 30, respectively, are essentially vertical slices of the storm. They correspond to the intensity of precipitation seen by the radar along the DC-8's flight track.
The progress of NASA's GRIP aircraft can be followed in near-real-time when they are flying by visiting: http://grip.nsstc.nasa.gov/current_weather.html . "Click to start RTMM Classic" will download a KML file that displays in Google Earth.
Near-real-time images from HAMSR and APR-2 are being displayed on NASA's TC-IDEAS website at http://grip.jpl.nasa.gov . The website is a near-real-time tropical cyclone data resource developed by JPL to support the GRIP campaign. In collaboration with other institutions, it integrates data from satellites, models and direct measurements, from many sources, to help researchers quickly locate information about current and recent oceanic and atmospheric conditions. The composite images and data are updated every hour and are displayed using a Google Earth plug-in. With a few mouse clicks, users can manipulate data and overlay multiple data sets to provide insights on storms that aren't possible by looking at single data sets alone.
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