Satellites with microwave remote sensing capabilities can be utilized to study atmospheric phenomena through high-level cloud cover (particularly cirrus), an advantage over visible and infrared bands, which only sense cloud tops. This unique capability makes microwave imagery ideal for studying the cloud structures of tropical cyclones (TCs) in detail, and relating these features to TC intensity. Techniques to estimate the intensity of TCs using infrared imagery, such as the Dvorak technique, have been used in TC forecasting for 40 years. However, due to the inherent temporal limitations of microwave imagery, no such similar technique exists for the microwave spectrum. This study utilizes pattern recognition to develop a subjective technique for estimating TC intensity using microwave imagery. The dataset includes TC composite imagery from the Special Sensor Microwave Imager (85 GHz), Advanced Microwave Scanning Radiometer-Earth Observing System (89 GHz), Advanced Microwave Scanning Radiometer 2 (89 GHz), and the Special Sensor Microwave Imager/Sounder (91 GHz) from the Atlantic basin, and aircraft reconnaissance data are used for verification. The composite imagery is binned into four categories to facilitate detection of common patterns for TCs of similar size and estimated intensity. This analysis provides the foundation for a new method to estimate TC intensity when aircraft data are unavailable. Multiple techniques are applied to explore relationships between brightness temperature values and TC intensity, and ten test cases in the Western Pacific basin are presented to validate the results. Five out of the ten TCs were classified correctly applying the microwave intensity techniques developed by this analysis
