MIMIC: A New Approach to Visualizing Satellite Microwave Imagery of Tropical Cyclones

Satellite-based passive microwave imagery of tropical cyclones (TCs) is an invaluable resource for assessing the organization and evolution of convective structures in TCs when often no other comparable observations exist. However, the current constellation of low-Earth-orbiting environmental satellites that can effectively image TCs in the microwave range make only semirandom passes over TC targets, roughly every 3 - 6 h, but vary from less than 30 min to more than 25 h between passes. These irregular time gaps hamper the ability of analysts/forecasters to easily incorporate these data into a diagnosis of the state of the TC. To address this issue, we have developed a family of algorithms called Morphed Integrated Microwave Imagery at the Cooperative Institute for Meteorological Satellite Studies (MIMIC) to create synthetic “morphed” images that utilize the observed imagery to fill in the time gaps and present time-continuous animations of tropical cyclones and their environment. MIMIC-TC is a product th...

[1]  Wei Zhao,et al.  THE HURRICANE RAINBAND AND INTENSITY CHANGE EXPERIMENT Observations and Modeling of Hurricanes Katrina, Ophelia, and Rita , 2006 .

[2]  Jerry D. Gibson,et al.  Handbook of Image and Video Processing , 2000 .

[3]  Jeffrey D. Hawkins,et al.  Interpretation of TRMM TMI Images of Tropical Cyclones , 2002 .

[4]  Thomas A. Jones,et al.  Passive-Microwave-Enhanced Statistical Hurricane Intensity Prediction Scheme , 2006 .

[5]  Eric A. Smith,et al.  Possibilities and Limitations for Quantitative Precipitation Forecasts Using Nowcasting Methods with Infrared Geosynchronous Satellite Imagery. , 2002 .

[6]  I. Zawadzki,et al.  Scale-Dependence of the Predictability of Precipitation from Continental Radar Images. Part I: Description of the Methodology , 2002 .

[7]  George Wolberg,et al.  Image morphing: a survey , 1998, The Visual Computer.

[8]  K. Corbosiero,et al.  The Effects of Vertical Wind Shear on the Distribution of Convection in Tropical Cyclones , 2002 .

[9]  C. Kummerow,et al.  The Tropical Rainfall Measuring Mission (TRMM) Sensor Package , 1998 .

[10]  Charles R. Sampson,et al.  Real-Time Internet Distribution of Satellite Products for Tropical Cyclone Reconnaissance. , 2001 .

[11]  J. Janowiak,et al.  CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution , 2004 .

[12]  G. Holland.  An Analytic Model of the Wind and Pressure Profiles in Hurricanes , 1980 .

[13]  Hugh E. Willoughby,et al.  Concentric Eye Walls, Secondary Wind Maxima, and The Evolution of the Hurricane vortex , 1982 .

[14]  J. Kossin,et al.  Rapid Filamentation Zones in Intense Tropical Cyclones. , 2006 .

[15]  H. Michael Goodman,et al.  Precipitation retrieval over land and ocean with the SSM/I - Identification and characteristics of the scattering signal , 1989 .

[16]  Pertti Nurmi,et al.  Precipitation nowcasting using radar-derived atmospheric motion vectors , 2000 .

[17]  Alan C. Bovik,et al.  Basic Gray Level Image Processing , 2009 .

[18]  Edward J. Zipser,et al.  Relationships between Tropical Cyclone Intensity and Satellite-Based Indicators of Inner Core Convection: 85-GHz Ice-Scattering Signature and Lightning , 1999 .

[19]  N. Grody.  Remote Sensing of the Atmosphere from Satellites Using Microwave Radiometry , 1993 .

[20]  Heinrich Müller,et al.  Image warping with scattered data interpolation , 1995, IEEE Computer Graphics and Applications.