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1 Microwave Imager TC Applications Naval Research Laboratory, Monterey, CA 2 Jet Propulsion Laboratory, Pasadena, CA 3 Science Applications Inc. International,

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Presentation on theme: "1 Microwave Imager TC Applications Naval Research Laboratory, Monterey, CA 2 Jet Propulsion Laboratory, Pasadena, CA 3 Science Applications Inc. International,"— Presentation transcript:

1 1 Microwave Imager TC Applications Naval Research Laboratory, Monterey, CA 2 Jet Propulsion Laboratory, Pasadena, CA 3 Science Applications Inc. International, Monterey, CA Jeff Hawkins, Kim Richardson, Mindy Surratt, Tom Lee, Rich Bankert, Joe Turk 2, Charles Sampson, Jeremy Solbrig, Arunas Kuciauskas, John Kent 3, International Workshop on Satellite Analysis of Tropical Cyclones (IWSATC) Honolulu, HI April 15, 2010

2 2 Exposed LLCC Sheared Convection Apparent LLCC True LLCC

3 3 Good central mass Remove doubt Large rain- free eye Rainband structure

4 4 Automated Tropical Cyclone Forecasting (ATCF) System warning graphic Latest 1-km Visible/IR imagery (GEO/LEO) 30 minute MTSAT refresh with AVHRR/OLS as available Vis/IR imagery suite Scatterometer & CloudSat Storm Basins & Names Microwave imager/sounder product suite http://www.nrlmry.navy.mil/TC.html FNMOC: https://www.fnmoc.navy.mil/tcweb/cgi-bin/tc_home.cgi

5 5 Microwave Imager Temporal Changes 512 km Katrina

6 6 14 deg Tropical Cyclone Yasi Microwave Imager Temporal Changes

7 7 Concentric Mode 1: Evolve into one larger diameter eye 512 KM Microwave Imager Temporal Changes

8 8 Satellite – Aircraft Comparisons North NW TMI 85H 9- 22-05 1443Z NOAA 43 1430- 1520Z 10,000’ TMI Tb Flt level wind

9 9 Courtesy: Tom Lee COMET Module – TC Microwave http://meted.ucar.edu/npoess/ocean_winds/index.htm TC specific focus with microwave sensors

10 10 Microwave Imager Training http://www.nrlmry.navy.mil/training-bin/training.cgi

11 11 Automating TC Intensity??? Huge-Intense Shear - WeakAnnular - Intense Small-Intense Wrapping?Wrapping

12 12 Microwave Imager TC Intensity Estimation Machine Learning Application Leave-One(TC)-Out Cross Validation Training and Testing Atlantic Basin Data Set **319 samples from 60 TC’s** RMSE: 13.1 kts Segmented 85 GHz Image feature extraction Feature selection to reduce redundant and irrelevant features GOES VisibleSSM/I 85 GHz Microwave imager data provides structural characteristics not always found in typical Vis/IR imagery. Courtesy: Rich Bankert

13 13 Microwave Imager Top Impact “Features” 6. Area coverage of pixels with less than 228 K Tb 7. Number of 1-km rings (within 1-deg radius) with at least 33% pixels with < 253 K Tb 8. Average % encirclement of the 1-km wide rings within 1-2-degree radius (pixels < 253 K) 9. Maximum summation of pixel Tb values along a 1-km ring for pixels with < 228K Tb 10. Number of 1-km rings (within 1-deg radius) with at least 50% pixels with Tb < 253 K 1. Symmetry measure – based on the 2-deg radius gradient vector angles relation to center 2. Average % encirclement of 1-km wide rings within 1-deg radius area (pixels < 253 K) 3. Difference in Tb of warmest center pixel and coldest surrounding pixel 4. Summation of pixel Tb in the SE quadrant of the “eye” region 5. Average of the maximum Tb on each ring in the 1-degree radius area

14 14 IR ImageGradientDetail Artificial Vortex GradientDetail Ritchie: Gradient Vector Feature

15 15 TIMELINE RMSE (kts) 12.0 15.0 14.0 13.0 20.0 21.0 19.0 18.0 17.0 16.0 Cubist (machine learning tool) Cross Validation (CCV) - all original features Manual estimation (Jeff) CCV - new feature set (modified original, new features added) CCV - feature selection (remove redundant and irrelevant features) CCV - new features added to total set, re-do feature selection CCV - 277 samples - high shear samples removed, re-do feature selection (Jeff RMSE – 16.7 kts) CCV - 319 samples – add gradient vector (Ritchie) feature Automated Microwave Imager TC Intensity Estimates 319 Atlantic basin samples [1995-2005] Features computed from SSM/I 85 GHz channel data Manual estimation (Jeff) TC Intensity – Microwave Imager

16 16 Problematic TC Structure Cases High ShearCenter ConvectionDying Inner Eye SSM/I 85 GHz images (BT)

17 17 TC intensity – Microwave Imager (2006-2009 Data Sets) Adding Near Real-Time Data Sets from NRL-TC Web Page Includes AMSR-E, TMI, SSMIS in addition to original SSM/I

18 18 TC intensity – Microwave Imager (Adding 37 GHz Data) 85 GHz H-pol 37 GHz H-pol Tropical Cyclone Yasi (11P) 85 GHz H-pol 37 GHz H-pol Typhoon Sinlaku (15W)

19 19 F-15 SSM/I 0723ZAqua AMSR-E 0332Z 85 GHz H-pol89 GHz H-pol F-17 SSMIS 0750Z 91 GHz H-pol Colder Tb at higher frequencies imply stronger storm: Incorrect Microwave Channel Intercalibration

20 20 Hurricane Bonnie T B Simulations Passive Microwave Channel Intercalibration Process TMI 85 GHz H AMSR-E 89 GHz H TMI 85 GHz H - AMSR-E 89 GHz H 8-10 K Differences In Deep Convection Huge potential to create issues: - Qualitative assessments - Quantitative analyses (intensity alg)

21 21 SSM/I TRMM TMI AMSR-E AMSR WINDSAT SSMIS FY-3 MWRI Russia MTVZA YEAR96979899000102030405060708091011121314151617181920 Primary mission Extended mission March 2011 Hawkins Passive Microwave Imager Missions Launches Future Megha Tropiques MADRAS GCOM AMSR GPM DWSS-1 Satellite sensors soon to cease functioning

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