Climatology of Passive Microwave Brightness Temperatures in Tropical Cyclones and their Relations to Storm Intensities as Seen by FY-3B/MWRI

A new database, the tropical cyclones passive microwave brightness temperature (TCsBT) database including 6273 overpasses of 503 tropical cyclones (TC) was established from 6-year (2011–2016) Fengyun-3B (FY-3B) Microwave Radiation Imager (MWRI) Level-1 brightness temperature (TB) data and TC best-track data. An algorithm to estimate the TC intensity is developed using MWRI TB’s from the database. The relationship between microwave TB and the maximum sustained surface wind (Vmax) of TCs is derived from the TCsBT database. A high correlation coefficient between MWRI channel TB and Vmax is found at the radial distance 50–100 km near the TC inner core. Brightness temperatures at 10.65, 18.70, 23.8, and 36.5 GHz increase but 89 GHz TB’s and polarization corrected TB at 36.5 GHz (PCT36.50) and PCT89 decrease with increasing TC intensity. The TCsBT database is further separated into the 5063 dependent samples (2010–2015) for the development of the TC intensity estimation algorithm and 1210 independent samples (2016) for algorithm verification. The stepwise regression method is used to select the optimal combination of storm intensity estimation variables from 12 candidate variables and four parameters (10.65h, 23.80v, 89.00v and PCT36.50) were selected for multiple regression models development. Among the four predictors, PCT36.50 contributes the most in estimating TC intensity. In addition, the errors are lower for estimating 6-h and 12-h future Vmax than estimating the current Vmax.

[1]  C. Landsea,et al.  Atlantic Hurricane Database Uncertainty and Presentation of a New Database Format , 2013 .

[2]  F. Weng,et al.  Applications of AMSR-E measurements for tropical cyclone predictions Part I: Retrieval of Sea Surface Temperature and Wind speed , 2008 .

[3]  V. F. Dvorak.  Tropical Cyclone Intensity Analysis and Forecasting from Satellite Imagery , 1975 .

[4]  Christopher S. Velden,et al.  Development of an Objective Scheme to Estimate Tropical Cyclone Intensity from Digital Geostationary Satellite Infrared Imagery , 1998 .

[5]  J. Knaff,et al.  An Evaluation of Dvorak Technique-Based Tropical Cyclone Intensity Estimates , 2010 .

[6]  G. Rao,et al.  The SSM/I Estimated Rainfall Amounts of Tropical Cyclones and Their Potential in Predicting the Cyclone Intensity Changes , 1994 .

[7]  Richard L. Bankert,et al.  An Automated Method to Estimate Tropical Cyclone Intensity Using SSM/I Imagery , 2002 .

[8]  T. Fujii.  Statistical Analysis of the Characteristics of Severe Typhoons Hitting the Japanese Main Islands , 1998 .

[9]  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 .

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

[11]  Timothy L. Olander,et al.  The Advanced Dvorak Technique: Continued Development of an Objective Scheme to Estimate Tropical Cyclone Intensity Using Geostationary Infrared Satellite Imagery , 2007 .

[12]  E. Zipser,et al.  Classifying Precipitation Types in Tropical Cyclones Using the NRL 37 GHz Color Product , 2018 .

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

[14]  Haiyan Jiang,et al.  Estimation of Tropical Cyclone Intensity in the North Atlantic and Northeastern Pacific Basins Using TRMM Satellite Passive Microwave Observations , 2019, Journal of Applied Meteorology and Climatology.

[15]  Timothy L. Olander.  The UW-CIMSS Advanced Dvorak Technique (ADT) - Current Status and Future Upgrades , 2018 .

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

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

[18]  F. Weng,et al.  Retrieval of cloud liquid water using the special sensor microwave imager (SSM/I) , 1994 .

[19]  Tetsuo Nakazawa,et al.  Estimation of tropical cyclone's intensity using TRMM/TMI brightness temperature data , 2007 .