The primary data used in this study are calibrated hyperspectral infrared radiances 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. From these radiances, a 3-D cloud amount vertical profile (CAVP) product developed at the University of Wisconsin-Madison Space Science and Engineering Center (SSEC) Cooperative Institute for Meteorological Satellite Studies (CIMSS) will be derived. The CAVP product will be used to measure the slope of the cloud tops of rainbands in a tropical cyclone (TC). Observations from the UW Scanning High-resolution Interferometer Sounder (S-HIS), NASA Micro Pulse Lidar (MPL), and NCAR dropsondes taken during the 2012 season of the Hurricane and Severe Storm Sentinel (HS3) field experiment will be used to validate the cloud top product.
The methodology behind the TC rainband slope analysis, which is hypothesized to correlate with TC intensity, will be discussed. This product will then be used to obtain a TC intensity estimate, which will be compared to other accepted intensity indices like the Advanced Dvorak Technique (ADT), Advanced Microwave Sounding Unit (AMSU), and Satellite Consensus (SATCON) estimates.
The purpose of this study is to determine the usefulness of a TC rainband slope index derived from AIRS L1B radiances in TC intensity analysis and short-term intensity change trending. Examples of the TC rainband slope analysis will be presented, as well as statistics for intensity estimate agreement with accepted intensity indices and a possible correlation with intensity change. Conclusions regarding the utility of this measure in passively monitoring intensity and predicting near-term intensity change of a TC will be discussed.
References: Dvorak, V., 1975: Tropical cyclone intensity analysis and forecasting from satellite imagery. Mon. Wea. Rev., 103, 420-430. Velden, C. S., and T. Olander, 1998: Evaluation of an Objective Scheme to Estimate Tropical Cyclone Intensity from Digital Geostationary Satellite Infrared Imagery. Wea. and Forecasting, 13, 172-186.