Munehiko Yamaguchi 12, Takuya Komori 1, Takemasa Miyoshi 13, Masashi Nagata 1 and Tetsuo Nakazawa 4 ( ) 1.Numerical Prediction.

Slides:



Advertisements
Similar presentations
RSMC La Réunion activities regarding SWFDP Southern Africa Matthieu Plu (Météo-France, La Réunion), Philippe Arbogast (Météo-France, Toulouse), Nicole.
Advertisements

Recent Developments of Medium-Range EPS at JMA
Ensemble Sensitivity Analysis Applied to Tropical Cyclones: Preliminary Results from Typhoon Nuri (2008) Rahul Mahajan & Greg Hakim University of Washington,
1 (B1) EPS design, objectives and interpretation st TRCG Technical Forum Takuya KOMORI ( ) Numerical Prediction.
Munehiko Yamaguchi Typhoon Research Department, Meteorological Research Institute of the Japan Meteorological Agency 9:00 – 12: (Thr) Topic.
Data rescue of historical typhoon tracks over the western north Pacific back to late 19 th century Hisayuki Kubota Research Institute for Global Change,
Introduction of numerical storm surge prediction models Dr.Wattana Kanbua Marine Meteorological Center Thai Meteorological Department.
C ontacts: Marit Helene Jensen, Norwegian Meteorological Institute, P.O.Box 43 Blindern, N-0313 OSLO, NORWAY. HIRLAM at met.no.
Figure 1.1 Area of responsibility of the RSMC Tokyo - Typhoon Center.
Munehiko Yamaguchi Typhoon Research Department, Meteorological Research Institute of the Japan Meteorological Agency 9:00 – 12: (Thr) Topic.
5/22/201563rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL Experiments of Hurricane Initialization with Airborne Doppler.
Initializing a Hurricane Vortex with an EnKF Yongsheng Chen Chris Snyder MMM / NCAR.
Forecasting Tropical cyclones Regional Training Workshop on Severe Weather Forecasting and Warning Services (Macao, China, 9 April 2013)
Kenji KISHIMOTO Forecast Division Japan Meteorological Agency.
Impact of the 4D-Var Assimilation of Airborne Doppler Radar Data on Numerical Simulations of the Genesis of Typhoon Nuri (2008) Zhan Li and Zhaoxia Pu.
Tropical cyclone analysis and forecasting : products and tools
The Impact of GPS Radio Occultation Data on the Analysis and Prediction of Tropical Cyclones Bill Kuo UCAR.
JMA Global Model Hiromi Owada Numerical Prediction Division, Forecast Dept. Japan Meteorological Agency 1.
Data Assimilation and Predictability Studies for Improving Tropical Cyclone Intensity Forecasts PI: Takemasa Miyoshi University of Maryland, College Park.
Observing Strategy and Observation Targeting for Tropical Cyclones Using Ensemble-Based Sensitivity Analysis and Data Assimilation Chen, Deng-Shun 3 Dec,
Munehiko Yamaguchi 1 21 August 2014 (Thu.) Multi-model ensemble forecasts of tropical cyclones using TIGGE World Weather Open Science Conference Montreal,
STATISTICAL ANALYSIS OF ORGANIZED CLOUD CLUSTERS ON WESTERN NORTH PACIFIC AND THEIR WARM CORE STRUCTURE KOTARO BESSHO* 1 Tetsuo Nakazawa 1 Shuji Nishimura.
Current status of AMSR-E data utilization in JMA/NWP Masahiro KAZUMORI Numerical Prediction Division Japan Meteorological Agency July 2008 Joint.
Large Ensemble Tropical Cyclone Forecasting K. Emanuel 1 and Ross N. Hoffman 2, S. Hopsch 2, D. Gombos 2, and T. Nehrkorn 2 1 Massachusetts Institute of.
30 November December International Workshop on Advancement of Typhoon Track Forecast Technique 11 Observing system experiments using the operational.
Celeste Saulo and Juan Ruiz CIMA (CONICET/UBA) – DCAO (FCEN –UBA)
On the ability of global Ensemble Prediction Systems to predict tropical cyclone track probabilities Sharanya J. Majumdar and Peter M. Finocchio RSMAS.
1 Takuya KOMORI 1 Kiyotomi SATO 1, Hitoshi YONEHARA 1 and Tetsuo NAKAZAWA 2 1: Numerical Prediction Division, Japan Meteorological Agency 2: Typhoon Research.
JOINT TYPHOON WARNING CENTER 2010 YEAR IN REVIEW Mr. Robert (Bob) Falvey Director, Joint Typhoon Warning Center 65th INTERDEPARTMENTAL HURRICANE CONFERENCE.
Tropical Cyclone Information Processing System (TIPS) Li Yuet Sim Hong Kong Observatory May 2009.
TIGGE and operational EPS 経田 正幸 KYOUDA Masayuki Numerical Prediction Division, Japan Meteorological Agency 9 th THORPEX GIFS-TIGGE Working Group meeting.
1 Results from Winter Storm Reconnaissance Program 2008 Yucheng SongIMSG/EMC/NCEP Zoltan TothEMC/NCEP/NWS Sharan MajumdarUniv. of Miami Mark ShirleyNCO/NCEP/NWS.
Munehiko Yamaguchi Typhoon Research Department, Meteorological Research Institute of the Japan Meteorological Agency 9:00 – 12: (Thr) Topic.
Munehiko Yamaguchi Typhoon Research Department, Meteorological Research Institute of the Japan Meteorological Agency 9:00 – 12: (Thr) Topic.
1st December 2009, Tokyo ( 日本財団ビル ) 台風の進路予測技術の高度化に関する国際会議 (International Workshop on Advancement of Typhoon Track Forecast Technique) Observing system.
On the Relative Benefits of Multi-Center Grand Ensemble for Tropical Cyclone Track Prediction in the Western North Pacific 2 Nov 2012 (Fri) The Fourth.
Munehiko Yamaguchi, Sharanya J. Majumdar (RSMAS/U. Miami) and multiple collaborators 3 rd THORPEX International Science Symposium 14 Sep Coordinated.
Introduction of temperature observation of radio-sonde in place of geopotential height to the global three dimensional variational data assimilation system.
AMS Annual Meeting - January NRL Global Model Adaptive Observing During TPARC/TCS-08 Carolyn Reynolds Naval Research Laboratory, Monterey, CA OUTLINE:
Munehiko Yamaguchi, Sharanya S. Majumdar (RSMAS/U. Miami) and multiple collaborators 3 rd THORPEX International Science Symposium 14 Sep Coordinated.
Adaptive Observation Techniques ENSEMBLE TRANSFORM KALMAN FILTER SINGULAR VECTORS Sensitive areas for adaptive sampling include both the hurricane core.
Improved Statistical Intensity Forecast Models: A Joint Hurricane Testbed Year 2 Project Update Mark DeMaria, NOAA/NESDIS, Fort Collins, CO John A. Knaff,
Improvement of the JMA typhoon track forecast Kenji KISHIMOTO National Typhoon Center Forecast Division JMA.
Table 2.1 Monthly and annual total numbers of products issued by the RSMC Tokyo - Typhoon Center in 2011.
Slide 1 International Typhoon Workshop Tokyo 2009 Slide 1 Impact of increased satellite data density in sensitive areas Carla Cardinali, Peter Bauer, Roberto.
Enrica Bellone, Jessica Turner, Alessandro Bonazzi 2 nd IBTrACS Workshop.
Munehiko Yamaguchi Typhoon Research Department, Meteorological Research Institute of the Japan Meteorological Agency 9:00 – 12: (Thr) Topic.
Fleet Numerical… Supercomputing Excellence for Fleet Safety and Warfighter Decision Superiority… 1 Chuck Skupniewicz Models (N34M) FNMOC Operations Dept.
MPO 674 Lecture 2 1/20/15. Timeline (continued from Class 1) 1960s: Lorenz papers: finite limit of predictability? 1966: First primitive equations model.
THORPEX THORPEX (THeObserving system Research and Predictability Experiment) was established in 2003 by the Fourteenth World Meteorological Congress. THORPEX.
One-dimensional assimilation method for the humidity estimation with the wind profiling radar data using the MSM forecast as the first guess Jun-ichi Furumoto,
1 Typhoon Track and Intensity Simulations by WRF with a New TC-Initialization Scheme HIEP VAN NGUYEN and YI-LENG CHEN Department of Meteorology, University.
Forecasting Oceanic Cyclones at the NOAA Ocean Prediction Center Joseph M. Sienkiewicz, D. Scott Prosise, and Anthony Crutch NOAA/NWS/NCEP/Ocean Prediction.
WGNE intercomparison of Tropical Cyclone Track forecast, Junichi Ishida Presentation is prepared by Hitoshi Sato, Takahiro Ito, Masahiro Sawada.
Fifth Session of the South Asian Climate Outlook Forum (SASCOF-5) JMA Seasonal Prediction of South Asian Climate for Summer 2014 Hitoshi Sato Climate Prediction.
A proposition on Seasonal Prediction of TC Activity over western North Pacific H. Joe Kwon Kongju National University, KOREA.
Figures from “The ECMWF Ensemble Prediction System”
JMA Seasonal Prediction of South Asian Climate for OND 2017
Seasonal outlook for summer 2017 over Japan
JMA Seasonal Prediction of South Asian Climate for OND 2017
Uncertainty cones deduced from an ensemble prediction system
Observation-Based Ensemble Spread-Error Relationship
SWFDP in the Antilles (RA IV)
Use of TIGGE Data: Cyclone NARGIS
Forecast Pressure.
Hui Liu, Jeff Anderson, and Bill Kuo
Ensemble tropical cyclone and windstorm forecast applications
Status Report of T-PARC/TCS-08
Update of NMC/CMA Global Ensemble Prediction System
Verification of Tropical Cyclone Forecasts
Presentation transcript:

Munehiko Yamaguchi 12, Takuya Komori 1, Takemasa Miyoshi 13, Masashi Nagata 1 and Tetsuo Nakazawa 4 ( ) 1.Numerical Prediction Division, Japan Meteorological Agency 2.University of Miami 3.University of Maryland 4.Meteorological Research Institute, Japan Meteorological Agency The 63th Interdepartmental Hurricane Conference 4 Mar Numerical model framework for typhoon prediction at the Japan Meteorological Agency

Office of Numerical Prediction Division at JMA

Present status of typhoon forecasts at JMA JMA issues forecasts up to 3 days as of We plan to extend the forecast range up to 5 days. Probability circle T+12h T+24h T+48h T+72h

Time series of annual average position errors in Tropical Cyclone (TC) Track Forecasts by the JMA Global Spectral Model - Western North Pacific from 1997 to 2007 (three-year running mean) - The position error of 5 day forecasts in 2007 is smaller than that of 3 day forecasts in Progress behind the planned 5 day forecasts

Time line of the upgrade of the systems Topography of 20kmGSM Topography of TEPS 20kmGSM: JMA Global Spectral Model. TYM: Typhoon Model. WEPS: One-Week Ensemble Prediction System. TEPS: Typhoon Ensemble Prediction System.

Two NWP systems supporting the forecasts  20kmGSM ( deterministic track and intensity forecast )  20km GSM runs 4 times a day (00, 06, 12 and 1800 UTC) with a forecast range of 90 hours except for 12UTC where it is 216 hours.  The data assimilation system is the 4DVAR, which has been in operation since 2005, and a typhoon bogus technique is used.  Typhoon Ensemble Prediction System ( deterministic track forecast for the extended forecast period and confidence information on track forecast )  TEPS uses the lower resolution version of 20kmGSM (TL319L60)  TEPS also runs 4 times a day with a forecast range of 132 hours for TCs in the responsibility area of RSMC Tokyo Typhoon Center.  The ensemble size is 11 and singular vectors are used to make initial perturbations.

Typhoon Bogus Technique TC central position, central pressure and the radius of 30kt wind analyzed by forecasters at JMA are reflected into the initial state of 20kmGSM Step1. Create a typhoon structure, considering the asymmetry, based on TC central position, central pressure and the radius of 30kt wind, which are analyzed by forecasters at JMA. Step2. Pick up points from the created structure (orange dots) and assimilate them in the 4DVAR assuming that they are observation data.

Performance of the two systems 1.TEPS of 2007 (quasi-operation) 2.TEPS of 2008 (operation) 3.20kmGSM of 2008

TEPS provides better deterministic forecasts Black line: Control run Red line: Ensemble mean 2 Black dots : number of sample Verification of track forecasts 1 verification period: May to Dec., The TC strength of L is not included in this verification 2. Ensemble mean tracks are defined using more than 1 ensemble member Ensemble mean track forecasts statistically have smaller position errors than those of control run. The error reduction is about 40 km at 5-day forecasts, which reduction corresponds to the gain of half a day lead time.

TEPS provides confidence information Ensemble spread of TC positions 2 (ensemble spread accumulated from 0 to 120 hours forecasts every 6 hours) Position Errors of Ensemble Mean at 5-day forecasts (km) Number of sample 1 : 149 Strong relationship between ensemble spread and position error of ensemble mean track forecasts 1.The TC strength of L is included in this verification 2. Ensemble mean tracks are defined using more than 1 ensemble member

Initial time: UTC Confidence: A Confidence: B Confidence: C Initial time: UTC Confidence: A Optimization of the probability circle The ensemble spread of TEPS would allow us to convey confidence information by optimizing the size and shape of the probability circle. The development of an application is now under way.

TEPS in kmGSM TEPS Control Member (TL319L60) TEPS Ensemble Mean (TL319L60) TEPS Control is much worse than 20km GSM. The benefit of Ensemble Mean with respect to the control had gone… TEPS Control is much worse than 20km GSM. The benefit of Ensemble Mean with respect to the control had gone…

What is the difference of TEPS between 2007 and 2008 ? In 2007, the model and data assimilation has the same horizontal resolution, TL319. In 2008, the analysis field for TEPS was created by interpolating the analysis field with a horizontal resolution of 20km, which might cause an unbalanced state in the initial field of TEPS. Miyoshi et al. (2009) showed that the track forecast of TEPS Control has improved by applying the 4DVAR to the interpolated analysis field, which is a TL319L60 resolution. Compared to the 4DVAR for 20kmGSM, the computer resources for the above 4DVAR is negligible. 20kmGSM TEPS Control (interp.) TEPS Test (interp. + 4 DVAR)

 Definition of development stage, maturation stage and dissipation stage is based on the differences of central pressures from initial time to the forecast time of 72 hours: development stage: -10hPa > ⊿ P maturation stage: -10hPa < ⊿ P < 10hPa dissipation stage: ⊿ P > 10hPa Intensity forecast by 20km GSM (2008)

Summary  JMA will extend the forecast range from 3 days to 5 days.  Typhoon EPS will support the extended forecast range.  TEPS will be useful in presenting confidence information on track forecasts. (an application is under development)  The deterioration of the control forecasts of TEPS in 2008 would be solved by another 4DVAR for a TL319L60 resolution.  For the intensity forecasts by 20kmGSM, there is a room for improvement, especially for the forecasts of tendency of intensity changes.