a. FY12-13 GIMPAP Project Proposal Title Page version 25 October 2011

1. a. FY12-13 GIMPAP Project Proposal Title Pageversion 25 October 2011 Title: Combining Probabilistic and Deterministic Statistical Tropical Cyclone Intensity Forecast Models Status: New Duration: 2 years Project Leads: John Knaff, NESDIS/STAR/RAMMB John.Knaff@noaa.gov Mark DeMaria, NESDIS/STAR/RAMMB Mark.DeMaria@noaa.gov Other Participants: Andrea Schumacher, CIRA/CSU, schumacher@cira.colostate.edu James Franklin, NCEP/NHC, James.Franklin@noaa.gov

2. b. Project Summary • Statistical-Dynamical intensity forecast models (SHIPS and LGEM) have been the most skillful over the past few years • Don’t perform as well for rapid intensification cases • Rapid Intensification Index (RII) • Complements SHIPS/LGEM forecasts • Provides probability of RI (next 24 hr) • Subset of SHIPS/LGEM predictors most related to RI and RW • GOES input much more important than in SHIPS/LGEM • Develop method to improve LGEM for rapid intensity cases by including RII as predictor

3. c. Motivation / Justification NHC and JTWC Forecast Priorities** Improved Guidance on Rapid Intensification is No. 1 Priority of NHC and JTWC **From OFCM Working Group For Tropical Cyclone Research Presentation, Interdepartmental Hurricane Conference, March 2011

4. 2006-2011 Atlantic Intensity Model Error (homogeneous sample) 48 hr Predicted (LGEM) vs. Observed Intensity Changes 2006-2010 Atlantic Sample

5. d. Methodology • RII identifies combination of predictors most conducive to rapid intensity changes • Provides quantitative estimate of probability of rapid intensification and rapid weakening • Assimilate RII probabilities into deterministic LGEM forecast model

6. LGEM forecasts for Adrian (2011) RII > 50%

7. Modification of LGEM Growth  Based on RII and RWI* • Increase  at 0-24 hr when RII > X • Decrease  at 0-24 hr when RWI > Y

8. Procedure for Adjusting  • Assume functional form for adjusted  = a(t) • a(t) = (t) + [1 - H(t - ti)][a*Pri + b*Prw] • H(t - ti) = Heaviside function • H=0 for t < ti , H=1 for t ≥ ti • Pri = probability of Rapid Intensification • Prw = probability of Rapid Weakening • H(t - ti) • Find values of model parameters ti, a, b to minimize Cost Function for many forecast cases • Cost function E = ∑(Vpred – Vobs)2 • Adjoint of LGEM provides gradients for minimization: ∂E/∂a, ∂E/∂b, ∂E/∂ti

9. Increased Influence of GOES Input in LGEM 0-24 hr Average LGEM Normalized Growth Rate Predictor Coefficients Normalized RII Discriminant Function Coefficients

10. e. Expected Outcomes • Improved intensity forecasts from LGEM • Especially for RW and RI cases • Better use of GOES for its ability to identify RW and RI cases

11. e. Possible Path to Operations • LGEM and RII are already operational at NHC • West Pac version under development for JTWC • Experimental real time tests through Proving Ground or Joint Hurricane Testbed • If successful, transition improved LGEM through coordination with NHC and JTWC

12. f. Milestones • Year 1 • Modify LGEM adjoint to include gradients needed for RW, RI inclusion • Perform parameter estimation analysis for Atlantic and east/central Pacific • Test on independent cases • Year 2 • Repeat analysis for western North Pacific • Perform real time tests • Leverage Proving Ground and Joint Hurricane Testbed projects at CIRA • Evaluate real time tests, adjust algorithm as needed • Implement in NHC/JTWC operations if appropriate

13. g. Funding Request (K)

14. g. Spending Plan • FY12 $49,000 Total Project Budget • Grant to CIRA – 46,300 • 0.5 CIRA FTE • Federal Travel – 2,700 • (M. DeMaria to AMS tropical conf., Ponte Vedra, FL, Apr 2012) • FY13 $50,000 Total Project Budget • Grant to CIRA – 45,800 • 0.5 CIRA FTE • Federal Travel – 2,200 • (PI to Interdepartmental Hurricane Conference) • Federal Publications – 2,000