Several existing or promising satellite-based methods to estimate tropical cyclone (TC) intensity are available to forecasters today. Some of these, such as the Dvorak Technique (DT), have been utilized operationally for more than 30 years. Others, such as those based on microwave (MW) data, are just emerging as new, more capable, meteorological satellite instruments become operational. Each of the methods, by themselves, represents or promises significant contributions to TC intensity analysis. However, each technique (or instrument that it is based on) also has its limitations.

An effort is underway at CIMSS to build an integrated algorithm that is fully automated, objective, and utilizes a multispectral approach. This system would integrate and build on the latest science advances in existing (and emerging) methods. The components would include: Geostationary satellite IR/VIS/WV image interpretation methods (including DT and Automated Objective Dvorak Technique/TC Intensity Estimation model (AODT/TIE)), geostationary products (shear indicator and feature-tracked winds), and polar orbiting satellite observations such as those from the Advanced Microwave Sounding Unit (AMSU), Special Sensor Microwave Imager (SSMI), Tropical Rainfall Measuring Mission (TRMM), scatterometer, and Special Sensor Microwave Imager/Sounder (SSMIS). As a first step, each of these tools or methods will be individually characterized in terms of accuracy and consistency in estimating TC intensity. Most importantly, this “method benchmarking” will include a thorough analysis of the error distribution and characteristics, behavior in specific situations, data refresh and real-time availability issues, and the potential employment of time-averaging, blending, or morphing techniques. Reconnaissance ground truth reports of TC intensity will be used to validate each technique and develop situation-dependent confidence indicators.

This computer-based objective system would yield the "current state" of a TC from a unified satellite perspective by employing weighted consensus, decision tree, or “expert system” techniques to resolve or blend the independent estimates. The algorithm would output real time intensity parameters, trends, and possibly short-term outlooks pertinent to the forecaster needs for TC intensity/structure analysis and forecasts. It would also include an interactive visualization package that would enable forecasters to view the individual components of the system.