Calhoun: The NPS Institutional Archive Theses and Dissertations Thesis Collection 2012-09 Statistical Analysis of Ensemble Forecasts of Tropical Cyclone Tracks over the Northwest Pacific Ocean Marino, David R. Monterey, California. Naval Postgraduate School http://hdl.handle.net/10945/17412 NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS STATISTICAL ANALYSIS OF ENSEMBLE FORECASTS OF TROPICAL CYCLONE TRACKS OVER THE NORTHWEST PACIFIC OCEAN by David R. Marino September 2012 Thesis Advisor: Patrick A. Harr Second Reader: Joshua P. Hacker Approved for public release; distribution unlimited THIS PAGE INTENTIONALLY LEFT BLANK REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188) Washington DC 20503. 1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE 3. REPORT TYPE AND DATES COVERED September 2012 Master’s Thesis 4. TITLE AND SUBTITLE Statistical Analysis of Ensemble Forecasts of Tropical 5. FUNDING NUMBERS Cyclone Tracks over the Northwest Pacific Ocean 6. AUTHOR(S) David R. Marino 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION Naval Postgraduate School REPORT NUMBER Monterey, CA 93943-5000 9. SPONSORING /MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSORING/MONITORING N/A AGENCY REPORT NUMBER 11. SUPPLEMENTARY NOTES The views expressed in this thesis are those of the author and do not reflect the official policy or position of the Department of Defense or the U.S. Government. IRB Protocol number ______N/A______. 12a. DISTRIBUTION / AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE Approved for public release; distribution is unlimited A 13. ABSTRACT (maximum 200 words) The skill of three ensemble prediction systems (EPS) is evaluated to focus on tropical cyclone (TC) track forecasting over the North Pacific. Probability ellipses are defined to represent ensemble spread and encompass 68 % of the ensemble members. The ellipses are centered on the ensemble mean forecast position. Forecast reliability is defined as whether the verifying position is within the ellipse 68% of the time. A statistical analysis of uncertainty in TC track forecasts examines the attributes of reliability and resolution of each EPS. The European Center for Medium- Range Forecasts (ECMWF) EPS had the highest degree of reliability and resolution. The sizes and shapes of the EPS ellipses varied with TC track characteristics. This suggests that EPS-based probability ellipses may provide value in identifying uncertainty with respect to likely TC track forecast errors. 14. SUBJECT TERMS Tropical Cyclone Track Errors, Ensemble Prediction Systems, Joint Typhoon 15. NUMBER OF Warning Center forecasts PAGES 83 16. PRICE CODE 17. SECURITY 18. SECURITY 19. SECURITY 20. LIMITATION OF CLASSIFICATION OF CLASSIFICATION OF THIS CLASSIFICATION OF ABSTRACT REPORT PAGE ABSTRACT Unclassified Unclassified Unclassified UU NSN 7540-01-280-5500 Standard Form 298 (Rev. 2-89) Prescribed by ANSI Std. 239-18 i THIS PAGE INTENTIONALLY LEFT BLANK ii Approved for public release; distribution unlimited STATISTICAL ANALYSIS OF ENSEMBLE FORECASTS OF TROPICAL CYCLONE TRACKS OVER THE NORTHWEST PACIFIC OCEAN David R. Marino Lieutenant Commander, United States Navy B.S. Oceanography, United States Naval Academy, 2002 Submitted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE IN METEOROLOGY AND OCEANOGRAPHY from the NAVAL POSTGRADUATE SCHOOL SEPTEMBER 2012 Author: David R. Marino Approved by: Patrick A. Harr Thesis Advisor Joshua P. Hacker Second Reader Wendell A. Nuss Chair, Department of Meteorology iii THIS PAGE INTENTIONALLY LEFT BLANK iv ABSTRACT The skill of three ensemble prediction systems (EPS) is evaluated to focus on tropical cyclone (TC) track forecasting over the North Pacific. Probability ellipses are defined to represent ensemble spread and encompass 68 % of the ensemble members. The ellipses are centered on the ensemble mean forecast position. Forecast reliability is defined as whether the verifying position is within the ellipse 68% of the time. A statistical analysis of uncertainty in TC track forecasts examines the attributes of reliability and resolution of each EPS. The European Center for Medium-Range Forecasts (ECMWF) EPS had the highest degree of reliability and resolution. The sizes and shapes of the EPS ellipses varied with TC track characteristics. This suggests that EPS-based probability ellipses may provide value in identifying uncertainty with respect to likely TC track forecast error. v THIS PAGE INTENTIONALLY LEFT BLANK vi TABLE OF CONTENTS I. INTRODUCTION........................................................................................................1 A. MOTIVATION ................................................................................................1 B. OBJECTIVE ....................................................................................................5 II. BACKGROUND ..........................................................................................................7 A. JOINT TYPHOON WARNING CENTER OPERATIONAL METHODS TO DEFINE TROPICAL CYCLONE TRACK FORECAST UNCERTAINTY .......................................................................7 1. Official Forecast Track with Area of Uncertainty ............................7 2. Wind Speed Probability Swath ...........................................................8 3. The Goerss Predicted Consensus Error (GPCE) ..............................9 4. Goerss Predicted Consensus Error Along- and Across-track (GPCE-X)............................................................................................11 B. ENSEMBLE PREDICTION SYSTEMS (EPS) ..........................................11 1. European Center for Medium Range Weather Forecasts (ECMWF) ...........................................................................................12 2. United Kingdom Meteorological Office (UKMO) ..........................13 3. Japan Meteorological Agency Global Spectral Model (JMA/GSM) ........................................................................................14 III. METHODOLOGY ....................................................................................................15 A. DATA ..............................................................................................................15 1. Data Source.........................................................................................15 2. Data Format .......................................................................................18 3. Data Homogeneity ..............................................................................19 4. Region and Sub-regions .....................................................................19 5. Developing the EPS Ellipse ...............................................................21 B. STATISTICAL ANALYSES ........................................................................23 1. Probability within Spread .................................................................23 2. Ellipse Reliability ...............................................................................24 3. Mean Area Difference (MAD) ..........................................................24 IV. ANALYSIS AND RESULTS ....................................................................................25 A. OVERVIEW ...................................................................................................25 B. ENSEMBLE-MEAN TRACK ERRORS .....................................................25 1. FTE ......................................................................................................25 2. ATE .....................................................................................................30 3. XTE .....................................................................................................35 C. PROBABILITY WITHIN SPREAD ............................................................40 D. ELLIPSE RELIABILITY .............................................................................42 E. MEAN AREA DIFFERENCE (MAD) .........................................................44 F. SUMMARY ....................................................................................................45 G. CASE STUDY TYPHOONS NANMADOL AND SONGDA ....................47 1. Typhoon Songda.................................................................................49 vii a. Typhoon Songda 1200 UTC 23 May 2011 .............................49 b. Typhoon Songda 1200 UTC 24 May 2011 .............................51 c. Typhoon Songda 1200 UTC 25 May 2011 .............................52 2. Typhoon Nanmadol ...........................................................................52 a. Typhoon Nanmadol 1200 UTC 23 August 2011 ....................53 b. Typhoon Nanmadol 1200 UTC 24 August 2011 ....................54 c. Typhoon Nanmadol 1200 UTC 25 August 2011