92nd American Meteorological Society Annual Meeting (January 22-26, 2012)

Wednesday, 25 January 2012
Use of Active and Passive Satellite Remote Sensing From the NASA A-Train to Investigate the Relationship Between Cloud Structure and Hurricane Intensification
Hall E (New Orleans Convention Center )
Elise M. Garms, CIMSS/Univ. of Wisconsin, Madison, WI; and R. Knuteson, P. Menzel, H. Revercomb, Y. Plokhenko, W. L. Smith, and E. Weisz
Manuscript (3.8 MB)

Poster PDF (5.3 MB)

Hurricane intensity forecast accuracy is extremely important in order to take necessary precautions for landfall events. Good intensity forecasts require a solid understanding of the underlying dynamics that cause a hurricane to strengthen or weaken. The causes of change in intensification of tropical storms and hurricanes have been widely studied, yet some aspects are still not well understood. Compared to the technical difficulty, cost, and danger associated with taking in situ measurements of these events, the use of satellite observation to study hurricanes presents a good way to attain timely data even in remote regions of the Earth. The EOS A-Train constellation of spacecraft provides unique insight into cloud geometric structure and atmospheric thermodynamic state from both active and passive sensors.

Active sensor measurement instruments used in this study include the A-Train satellites CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) and CloudSat. CALIPSO combines an active lidar instrument with passive IR and visible imagers to obtain the vertical structure and properties of thin clouds and aerosols. CloudSat, a Cloud Profiling Radar (CPR), operates at 94 GHz to determine cloud distribution and structure. Together, these active instruments provide a high-resolution view of cloud and atmospheric structure in the vertical cross-section below the satellite orbit. Passive hyperspectral infrared observations are obtained from the NASA Atmospheric Infrared Sounder (AIRS), onboard the Aqua satellite. AIRS measures upwelling Earth-emitted infrared spectra using more than 2300 IR channels between 3.7 and 15.4 microns. Several products derived from this high-spectral resolution data are used in this study. These products include a 3-D cloud amount vertical profile (CAVP) product as well as temperature and water vapor profiles retrieved using a Dual-Regression algorithm (DR), each of which were developed at the University of Wisconsin-Madison Space Science and Engineering Center (SSEC) Cooperative Institute for Meteorological Satellite Studies (CIMSS). These data will be used to characterize the three-dimensional structure of water vapor and clouds for selected tropical storms. Additionally, GOES visible, IR, and water vapor imagery will be used to examine the horizontal distribution of cloud and water vapor.

The purpose of this study is to investigate the relationship between hurricane intensity and the temporal changes in cloud structure and water vapor distribution of the storm and its environment. The passive and active remote sensing instruments mentioned previously and their derived products will be used to examine the 3-D cloud structure, temperature profiles, and water vapor profiles of Hurricane/Super Typhoon Ioke at various points in its life cycle.

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