Using Passive Microwave Imagery to Develop Objective Tropical Cyclone Structure and Intensity Analysis and Improved Near-Realtime Products

The Naval Research Laboratory's (NRL) tropical cyclone (TC) web page (http://www.nrlmry.navy.mil/TC.html) has provided nearly two decades of near real-time access to TC-centric images and products by TC forecasters and enthusiasts around the world. Particularly, microwave imager and sounder information that is featured on this site provides crucial internal storm structure information by allowing users to perceive hydrometeor structure, providing key details beyond cloud top information provided by visible and infrared channels. Towards improving TC analysis techniques and helping advance the utility of the NRL TC webpage resource, new research efforts are presented. This work demonstrates results as well as the methodology used to develop new automated, objective satellite-based TC structure and intensity guidance and enhanced data fusion imagery products that aim to bolster and streamline TC forecast operations.

Specifically, a standardized digital database of global TCs in microwave imagery from 1987-2012 is employed to create a climatology of objectively identified TC features. Various analyses – including image processing techniques, descriptive statistics, symmetric decomposition, and morphometrics – are used linked to physical process that relate to a TC's meteorological evolution. The broad range of TC structures, from pinhole eyes through multiple eyewall configurations, is characterized as resolved by passive microwave sensors. The extraction of these characteristic features from historical data also lends itself to statistical analysis. By applying machine learning tools and comparative statistical testing to the resultant data set, an empirically-based algorithm to estimate current TC intensity is derived. Furthermore, histograms of brightness temperature distributions allows a rigorous examination of how structural features are conveyed in image products, allowing a better representation of colors and breakpoints as they relate to physical features. Such climatological work also suggests steps to better inform the near-real time application of upcoming satellite datasets to TC analyses.