Creation of a Statistical Ensemble for Tropical Cyclone Intensity Prediction Kate D. Musgrave 1, Brian D. McNoldy 1,3, and Mark DeMaria 2 1 CIRA/CSU, Fort.

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Creation of a Statistical Ensemble for Tropical Cyclone Intensity Prediction Kate D. Musgrave 1, Brian D. McNoldy 1,3, and Mark DeMaria 2 1 CIRA/CSU, Fort Collins, CO 2 NOAA/NESDIS/StAR, Fort Collins, CO 3 Current Affiliation: RSMAS, University of Miami, Miami, FL 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012 Acknowledgements: Yi Jin, Naval Research Lab Michael Fiorino, Jeffrey Whitaker, Philip Pegion, NOAA/ESRL Vijay Tallapragada, Janna O’Connor, NOAA/NWS/NCEP/EMC

Motivation for Statistical Ensemble The Logistic Growth Equation Model (LGEM) and the Statistical Hurricane Intensity Prediction Scheme (SHIPS) model are two statistical-dynamical intensity guidance models SHIPS and LGEM are competitive with dynamical models Both SHIPS and LGEM use model fields from the Global Forecast System (GFS) to determine the large-scale environment Runs extremely fast (under 1 minute), using model fields from previous 6 hr run to produce ‘early’ guidance Atlantic Operational Intensity Model Errors A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012 JTWC experience with a similar statistical model shows improvements with multiple inputs We focus on using Decay-SHIPS (DSHP) and LGEM, initialized with model fields from GFS, the Hurricane Weather Research and Forecasting (HWRF) model, and the Geophysical Fluid Dynamics Laboratory (GFDL) model to create an ensemble

SPICE (Statistical Prediction of Intensity from a Consensus Ensemble) Model Configuration for Consensus SPICE forecasts TC intensity using a combination of parameters from: – Current TC intensity and trend – Current TC GOES IR – TC track and large-scale environment from GFS, GFDL, and HWRF models These parameters are used to run DSHP and LGEM based off each dynamical model The forecasts are combined into two unweighted consensus forecasts, one each for DSHP and LGEM The two consensus are combined into the weighted SPC3 forecast 3 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012

SPICE (Statistical Prediction of Intensity from a Consensus Ensemble) Model Configuration for Consensus DSHP and LGEM Weights for Consensus Weights determined empirically from Atlantic and East Pacific sample 4 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012

SPICE Input – Model Diagnostic Files … For further discussion of the model diagnostic files, see 15A.3 Friday 11:00am 5 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012

SPICE Input – Model Diagnostic Files … For further discussion of the model diagnostic files, see 15A.3 Friday 11:00am 6 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012

SPICE Input – Model Diagnostic Files … For further discussion of the model diagnostic files, see 15A.3 Friday 11:00am 7 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012

SPICE Input – Model Diagnostic Files … For further discussion of the model diagnostic files, see 15A.3 Friday 11:00am 8 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012

SPICE Input – Model Diagnostic Files … For further discussion of the model diagnostic files, see 15A.3 Friday 11:00am 9 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012

Hurricane Forecast Improvement Program (HFIP) HFIP designates three streams for the testing and implementation of models (Streams 1, 1.5, and 2) – Further information on HFIP is available at SPC3 was tested with data from the Atlantic and East Pacific seasons (retrospective runs) to determine if it would be used as a Stream 1.5 model in 2011 As a Stream 1.5 model SPC3 would be run real time during the 2011 demonstration period (August-October 2011) Data from the Atlantic and East Pacific seasons were used to test SPC3 for Stream 1.5 in A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012

Retrospective Runs for HFIP Stream 1.5 Implementation 11 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012 SPICE showed an improvement in skill over SHIFOR when compared to both DSHP and LGEM at all times Percent improvements ranged up to 5-10% The components of SPICE based off each individual model also showed lower forecast errors than their parent models for both HWRF and GFDL

Results from 2011 Atlantic Season Average Intensity Error (kt)Average Intensity Bias (kt) (304) (301) (263) (225) (192) (150) (116) (92) 12 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012 Number of Cases

Results from 2011 Atlantic Season (304) (301) (263) (225) (192) (150) (116) (92) Number of Cases Skill Relative to SHIFOR 13 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012

Results from 2011 Atlantic Season (304) (301) (263) (225) (192) (150) (116) (92) Number of Cases Skill Relative to SHIFOR Figure courtesy of James Franklin 14 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012

2012 HFIP Stream 1.5 Implementation Additional Stream 1.5 model, named SPCR Adds Coupled Ocean/Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC, COTC) to regional models in ensemble SPC3SPCR 15 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012

Retrospective Runs for HFIP Stream 1.5 Implementation SPC3SPCR 16 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012 # cases Time (hr) # cases Time (hr) Average Intensity Error (solid) and bias (dashed) (kt)

Results from 2011 Atlantic Season HWRFGFDL 17 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012 Average Intensity Error (kt) Average Intensity Bias (kt)

2012 HFIP Stream 2 Implementation – SPCG Stream 2 model, named SPCG Uses GFS and global model ensembles as input models FIM 10-member Ensemble 18 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012

Plans for 2012 Season In 2012 we’ll run two separate versions of SPICE in HFIP Stream 1.5: – The first version (SPC3) is based off the 2011 SPICE model, with updated versions of SHIPS and LGEM – The second version (SPCR) includes COAMPS-TC We’ll also collect model diagnostic files for regional models from SUNY-Albany and University of Wisconsin and test after the season for inclusion in SPCR We’ll also run a version of SPICE in HFIP Stream 2: – The third version (SPCG) will include HFIP global model ensembles 19 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012

Summary Statistical ensemble (SPICE) is a weighted consensus of DSHP and LGEM, run from multiple dynamical models SPICE had better error statistics than SHIPS and LGEM in the Atlantic basin, with neutral results in the Eastern Pacific basin – Consistent in Retrospective Runs, 2011 Demonstration, and Retrospective Runs – SPC3 showed skill improvements of up to 5-10% over SHIPS and LGEM SPICE model components had lower errors than parent dynamical models (GFDL, HWRF) Limited storm development in 2011 may have favored SPICE model – Confirmation from additional tests needed 20 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012

Questions? 13A.1AMS 30 th Conf on Hurr and Trop Met, 4/19/2012