American Meteorological Society Demo

properly. Given this, a forecaster can follow trends in a tropical cyclone’s structure more efficiently and effectively. Ultimately, it is hoped that this improved analysis could result in higher-confidence short-term intensity forecasts. The subject of morphing tropical cyclone imagery is a fresh topic with many exciting possibilities for visualization, and we see this product as merely a first step. With feedback from the community of users, we anticipate continued improvements over time toward this visualization strategy. Because we are now in the “golden age” of satellite microwave observation, such improvements in visualization will become increasingly important over time. ACKNOWLEDGMENTS. This work was sponsored by the Oceanographer of the Navy through the PEO C4I PMW-150 program office and the Naval Research Laboratory (Jeff Hawkins). We thank Joe Turk, Jeffrey Tesmer, and Hal Wolf for their kind assistance with microwave data access and decoding. We thank Tom Whittaker for contributing the Java module to read and reformat geostationary imagery. We also thank the reviewers for their constructive advice. FIG. 6. Demonstration of MIMIC-IR for Hurricane Wilma (2005) from 0000 UTC 20 October to 1200 UTC 22 October. The infrared layer is the GOES-12 longwave infrared brightness temperature, adjusted for parallax assuming cloudtops at 15 km and matched to the nearest display time. The PCT layer is semitransparent over the infrared layer, and it is corrected for parallax assuming a signal peak at 7 km in height. The semitransparent PCT layer allows breaks in the cloud cap to be seen as a darkening of PCT colors. Solid yellow areas are "no microwave data" regions. The microwave PCT later is created from 16 microwave overpasses. Labels are as follows: (upper-left label) NHC-reported maximum sustained winds ("Vmax"); (upper-right label) the temporal separation from the microwave overpass nearest in time (either before or after). APPENDIX: NORMALIZING BRIGHTNESS TEMPERATURES. The differences between the corresponding footprint sizes and response functions of each microwave instrument [Special Sensor Microwave Imager (SSM/I), Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Advanced Microwave Scanning Radiometer (AMSR)-Earth Observing System (E), Special Sensor Microwave Imager/Sounder (SSMI/S)] impart a noticeable brightness temperature bias in the morphing transitions if the imagery is not normalized allow for more physically based transitions between observations. This would be more difficult to constrain effectively because of the limited amount of independent data close in time to the satellite overpasses. On the other hand, the product in its current form is totally independent from models, which makes it an effective complement to the modelbased forecasts and analyses. As with every new observational tool, MIMIC requires the user to be familiar with its unique strengths and weaknesses in order to interpret it AMERICAN METEOROLOGICAL SOCIETY FIG. A1. Adjustments to SSM/I, AMSR-E, and SSMI/S brightness temperatures to minimize the bias in transitions between each instrument’s imagery. AUGUST 2007 | 1197

Table of Contents Feed for the Digital Edition of American Meteorological Society Demo

For optimal viewing of this digital publication, please enable JavaScript and then refresh the page. If you would like to try to load the digital publication without using Flash Player detection, please click here.