CIMSS SATellite CONsensus (SATCON) Derrick Herndon and Chris Velden University of Wisconsin - Madison Cooperative Institute for Meteorological Satellite Studies Presented at International Workshop on Satellite Analysis of Tropical Cyclones 17-19 February, 2016 Honolulu, HI Microwave Sounders ADT ARCHER
IWSATC-II center No single intensity algorithm can perfectly assess the intensity of all these storms
In order to account for storms with different structures an all the above approach is needed. Multiple satellite scanning strategies Multiple channels to measure the various TC features that are related to intensity. Geostationary Intensity Position Structure MW Imager Position Structure MW Sounder Intensity Structure
The strengths and weaknesses of each method are assessed based on statistical analysis, and that knowledge is used to assign weights to each method in the consensus algorithm based on situational performance to arrive at a single intensity estimate. SATellite CONsensus (SATCON) AMSU/SSMIS/ATMS ADT ARCHER SATCON
Cross-algorithm information sharing ADT Estimate of Eye Size Compare to Sounder FOV resolution Adjust sounder-based pressure if needed Example: ADT provides information to MW Sounder algorithms During eye scenes infrared imagery can be used to estimate eye size Sounder algorithm uses eye size information to correct resolution under-sampling
Cross-algorithm information sharing Example: Objective estimates of eye size from CIMSS ARCHER method (using MW imagery) MW imagery (MI) often depicts eyes when IR/ADT cannot ARCHER method (Wimmers and Velden, 2015) uses objective analysis of MI and accounts for eyewall slope ARCHER eye = 33 km Information can be input to AMSU/SSMIS and ATMS algorithms SATCON uses ARCHER intensity score and eye size
Weights are based on situational analysis for each member Weights are RMSE for each member in given scenario Example criteria: scene type (ADT) scan geometry/under-sampling bias (AMSU/SSMIS/ ATMS) Example: ADT Scene type vs. performance CDO EYE SHEAR RMSE 14 knots RMSE 12 knots RMSE 18 knots
A B C SSMIS RMSE 9.4 knots AMSU RMSE 10 knots AMSU RMSE 12 knots SSMIS RMSE 14.6 knots AMSU RMSE 15 knots AMSU weights are dependent on: TC position relative to AMSU warm core position TC eye size (AMSU resolution is 50 km at nadir) SSMIS weights are dependent on TC eye size
Changes since 2011 Interpolate the MW Sounder estimates then weight the interpolated values. - Result is increased number of members available to match to ADT - Smoother changes from one estimate to the next Add 2 Standard Deviation bounds for Vmax Address sounder too strong bias during early stages Apply correction for SATCON too weak bias for storms > 100 kts TIME SSMIS AMSU ADT
TCC-2016 Changes since IWSATC 2011 Use SATCON weighted MSLP to get pressure-wind estimate - make adjustments for TC size, latitude and storm motion - correction for TC eyes that are smaller/larger than climo value of 46 km. Objective eye size value comes from ARCHER or ADT Adjust P-W Vmax to account for storm organization using ARCHER intensity scores. Higher score -> stronger Vmax ARCHER score 85 ARCHER score 15 Same MSLP for these 2 storms but different MSW
Changes since 2011 Final Vmax estimate is 0.75*Vmax_SATCON + 0.25 * Vmax_PW SATCON estimate are emailed to users, sent to ATCF for JTWC and distributed on CIMSS webpage along with a history file. S-NPP ATMS is currently included on SATCON plots but not part of SATCON yet. Plan to add ATMS from CIRA/CIMSS this year. SATCON weighting equation for three member estimate for both MSLP and Vmax
Temporal fluctuations as each polar pass is processed
Bias correction increases peak intensity ERC not captured in BT Smoother transitions
for Super Typhoon Haiyan 2013 ERC
TC Winston 11P (2016)
MSW (Kts) CIMSS AMSU CIMSS ADT CIRA AMSU CIMSS SSMIS SATCO N Subj. Dvorak (Operational) BIAS -1.0-0.6-5.2-0.6-0.7 0.2 AVG ERRO R 10.0 9.0 12.1 8.3 6.7 7.0 RMSE 12.4 11.6 16.0 10.5 8.3 9.2 2006-2012 Homogenous sample of N=275 matches (except CIRA AMSU=187) with NHC recon-aided Best Track estimates. Subj. Dvorak is the average of subjective operational Dvorak estimates from TAFB and SAB. MSW (Kts) CIMSS AMSU CIMSS ADT CIMSS SSMIS SATCON BIAS -1.0 0.2-1.0-0.9 AVG ERROR 9.8 9.3 8.2 6.9 RMSE 12.1 12.0 10.4 8.6 SATCON Performance compared to individual members 2006-2012. N= 1467 (interpolated values)
SATCON Performance compared to individual members 2006-2012. N= 1467 (interpolated values) MSW (Kts) CIMSS AMSU CIMSS ADT CIMSS SSMIS SATCON BIAS -1.0 0.2-1.0-0.9 AVG ERROR 9.8 9.3 8.2 6.9 RMSE 12.1 12.0 10.4 8.6
Future Work Loss of SSMIS F-16 and F-18 increases interpolation errors - use time-weighted weighting scheme that scales to 0 after 3 hours Investigate Bayesian approach Add S-NPP ATMS Potential new members (DAV, NRL MW Imager etc)
CIMSS TC Homepage http://tropic.ssec.wisc.edu
REFERENCES Brueske K. and C. Velden 2003: Satellite-Based Tropical Cyclone Intensity Estimation Using the NOAA-KLM Series Advanced Microwave Sounding Unit (AMSU). Monthly Weather Review Volume 131, Issue 4 (April 2003) pp. 687 697 Demuth J. and M. DeMaria, 2004: Evaluation of Advanced Microwave Sounding Unit Tropical- Cyclone Intensity and Size Estimation Algorithms. Journal of Applied Meteorology Volume 43, Issue 2 (February 2004) pp. 282 296 Herndon D. and C. Velden, 2004: Upgrades to the UW-CIMSS AMSU-based TC intensity algorithm. Preprints, 26th Conference on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., 118-119 Olander T. and C. Velden 2007: The Advanced Dvorak Technique: Continued Development of an Objective Scheme to Estimate Tropical Cyclone Intensity Using Geostationary Infrared Satellite Imagery. Wea. and Forecasting Volume 22, Issue 2 (April 2007) pp. 287 298 Velden C. et al., 2006: The Dvorak Tropical Cyclone Intensity Estimation Technique: A Satellite- Based Method that Has Endured for over 30 Years. Bulletin of the American Meteorological Society Volume 87, Issue 9 (September 2006) pp. 1195 1210 Wimmers, A., and C. Velden, 2010: Objectively Determining the Rotational Center of Tropical Cyclones in Passive Microwave Satellite Imagery. Submitted to JAMC.
REFERENCES Herndon, D., and C. Velden, J. D Hawkins 2012: Update on SATellite-based CONsensus (SATCON) Approach to TC Intensity Estimation. 30th Conference on Hurricanes and Tropical Meteorology. Ponte Vedra Beach, FL Herndon, D., and C. Velden, 2012: Estimating Tropical Cyclone Intensity Using the SSMIS and ATMS Sounders. 30th Conference on Hurricanes and Tropical Meteorology. Ponte Vedra Beach, FL Herndon, D., 2014: An Update on Tropical Cyclone Intensity Estimation from Satellite Microwave Sounders. 31st Conference on Hurricanes and Tropical Meteorology. San Diego, CA
Algorithm Western Pacific (WPAC) Validation N = 18 SATCON Vmax Dvorak Vmax BIAS - 1.5-4.9 AVG ERROR 8.4 10.8 RMSE 9.9 13.1 N=14 cases from TCS-08 double blind Dvorak experiment. 4 cases from ITOP 2010 Independent sample. Vmax validation in knots vs. BT. MSLP validation in hpa vs. recon. Neg. bias = method was too weak. Dvorak is average of operational centers (ITOP-2010) and five expert Dvorak analysts (TCS-08)
Analysis of Sat-Based TC Intensity Estimation in the WPAC 2008 and 2010 Comparison of All Satellite-based Estimates Vmax (Kts) N=14 Dvorak Consensus Oper Dvorak Consensus (w/koba) ADT w/mw CIMSS AMSU SATCON Bias 3.6 2.0-3.6 2.9-0.1 Abs Error 9.3 12.0 13.6 8.6 9.0 RMSE 11.9 14.9 17.4 10.1 10.6 Positive Bias indicates method estimates are too strong
Analysis of Sat-Based TC Intensity Estimation in the WNP During TCS-08 Comparison of All Satellite-based Estimates MSLP (mb) N=14 Blind Dvorak Consensus Oper Dvorak Consensus (w/koba) ADT w/mw CIMSS AMSU SATCON Bias 0.7 0.1-1.0-1.9-1.3 Abs Error 5.2 7.5 10.7 4.9 6.0 RMSE 6.6 8.9 12.8 6.3 7.2 Positive Bias indicates method estimates are too strong. 2mem SATCON RMSE= 4.7 Blind and Oper Dvorak conversion is Knaff/Zehr