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(B1) EPS design, objectives and interpretation

2009.05.12-15 1st TRCG Technical Forum. (B1) EPS design, objectives and interpretation. “Why we need Ensemble Prediction System for TC forecasts?”. Takuya KOMORI ( komori@met.kishou.go.jp ) Numerical Prediction Division Japan Meteorological Agency. My Lectures in 1 st TRCG Technical Forum.

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(B1) EPS design, objectives and interpretation

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  1. 2009.05.12-15 1st TRCG Technical Forum (B1) EPS design, objectives and interpretation “Why we need Ensemble Prediction System for TC forecasts?” Takuya KOMORI( komori@met.kishou.go.jp )Numerical Prediction Division Japan Meteorological Agency

  2. My Lectures in 1st TRCG Technical Forum 12 May (Tue) • (B1) EPS design, objectives and interpretation • “Why we need Ensemble Prediction System for TC forecasts?” • (C2) EPS perspectives • “Status of TIGGE Activities of JMA” • (B2) Application for TC forecasts • 　　　“How to use the products of JMA Ensemble Prediction System?” 13 May (Wed) 14 May (Thu) “Please feel free to ask me a question at any time in the lectures.”

  3. Contents • Introduction of Ensemble Forecast • Objectives • Statistical Methods • JMA Numerical Weather Prediction System • GSM Forecast Performance • Typhoon Ensemble Prediction System (TEPS) • One-week Ensemble Prediction System (WEPS) • Updated Typhoon Bogus System in March 2009 • Introduction of JMA EPS-WEB

  4. Forecast Uncertainty: Sources of Error The forecast error is inevitable for Numerical Weather Prediction (NWP). There are two sources of error in NWP system; • Errors in Initial Condition • Errors in Raw Observational Data • Errors in Objective Analysis Procedures for NWP Model • Errors in Forecast Model (NWP model) • Limitation in the Spatial Resolution • Errors in Physical Processes Owing to the strong non-linearity and chaotic nature of atmosphere, the small error grows with forecast time immediately.

  5. Larger Position Error Best track of Typhoon Dolphin (black line) Time Series of Forecast Error Size: TC Position All forecasted typhoon tracks (for Typhoon Dolphin, T0822) of JMA Operational Global Spectral Model (green Lines). The forecast position errors are not constant and change from day to day. The growth rate of forecast error depends on the atmospheric condition. The ensemble forecasting aims at estimating the rage of forecast error in advance. Typhoon Dolphin took a sharp turn in the tropics. At that time, GSM could not swim with the Dolphin … If we know that the TC position error of GSM forecast will be large in advance, we can use the forecast with care.

  6. Estimate of Forecast Uncertainty Basic Numerical Weather Prediction System provide “one future atmospheric condition” starting from one initial atmospheric condition. Analysis Field Single deterministic forecast Single Deterministic Forecast Forecast Error truth There is no information about uncertainty of forecast.

  7. Estimate of Forecast Uncertainty In addition to the future atmospheric condition, we would like to predict the range of forecast error: Probability Density Function (PDF) of atmospheric condition. Analysis Field Single deterministic forecast (control run) Target is to know this size and shape Initial PDF of atmospheric condition Single Deterministic Forecast Forecast Error truth Prediction of PDF Forecasted PDF of atmospheric condition It is difficult to estimate the PDF, directly. The Ensemble Prediction System is a feasible method to estimate the PDF of forecast field.

  8. Forecast P(t=t2) Forecast of Each Member Initial Time x(t0) Ensemble Mean Forecast x(t1) Analysis Field Deterministic Forecast Initial PDF is represented by multiple initial conditions which are slightly different from analysis field. Future PDF (range of forecast error ) is estimated from multiple forecast. Forecast by same model Schematic Image of the Ensemble Prediction The ensemble prediction is a set of forecasts generated by NWP started from only slightly different initial conditions (added the perturbation into the analysis field).

  9. Forecasts of Ensemble Prediction System • JMA One-Week Ensemble Prediction System (WEPS) provides much information (51 forecast fields). • JMA Typhoon Ensemble Prediction System (TEPS) has 11 members. • The statistical method is useful to compact and overview the ensemble forecast information. • Ensemble mean, Ensemble Spread, etc…

  10. Ensemble Mean Forecast • “Ensemble mean forecast” is average of all ensemble forecasts. It is approximately equal to the central value of forecast PDF. • Statistically, ensemble mean error, which is defined as the mean square distance between ensemble mean forecast and analysis, is almost half of deterministic forecast’s error. Ensemble Mean Forecast Analysis Field Deterministic Forecast

  11. Ensemble Spread Spread is the standard deviation of PDF. Generally, the “ensemble spread” is defined as the average of the root-mean-square distance between the ensemble mean forecast and each ensemble forecast. Large Spread Several scenarios are included in the ensemble forecast with large spread. Initial Condition Small Spread Small spread of ensemble forecast represents one scenario as deterministic forecast.

  12. JMA Typhoon EPS: Case Study Large Spread (T0822 Dolphin) Small Spread (T0815 Jangmi) Typhoon EPS captures the best track with its large spread. The Ensemble Prediction System is a feasible method to estimate the range of forecast error (PDF of forecast field) in advance.

  13. JMA Numerical Weather Prediction System

  14. Spatial Scale Global Spectral Model (GSM) planetary wave 20,000km Macro Baroclinic wave extratropical low 2,000km Meso-Scale Model (MSM) front system 200km tropical cyclone cloud cluster Meso 20km Thunder storm cumulo- nimbus 2km tornado Temporal Scale Micro 200m 0.1 hour 1 hour 10 hour 1 day 100 hour 1 week Deterministic Models (March 2009)

  15. Spatial Scale One-Week EPS 51 members Once a day planetary wave 20,000km Macro Baroclinic wave extratropical low 2,000km front system Typhoon EPS 11 members 4 times a day 200km cloud cluster Meso 20km Thunder storm cumulo- nimbus 2km tornado Temporal Scale Micro 200m 0.1 hour 1 hour 10 hour 1 day 100 hour 1 week Ensemble Prediction Systems (March 2009)

  16. Specifications of the NWP Models at JMA (Mar. 2009) In addition, One-month EPS and Seasonal EPS have been in operational . http://www.jma.go.jp/jma/jma-eng/jma-center/nwp/nwp-top.htm

  17. RMSE of 500 hPa Geopotential Height in Northern Hemisphere (GSM: T+48h) Revision of cumulus parameterization Revision of cumulus parameterization Revision of cloud T213L30 Use of QuikSCAT T213L40 Revision of radiation Use of MODIS 3D-Var Direct use of ATOVS Use of SSM/I and TMI Variational bias correction TL319L40 4D-Var TL959L60 Reduced Gaussian Grid 17

  18. 5-day forecasts 4-day forecasts 3-day forecasts 2-day forecasts 1-day forecasts Verification of 5-day TC Track Forecasts by GSM Theposition error of the 5-day forecasts in 2007 is equal to that of the 3-day forecasts in 1997. 18

  19. Typhoon KROSA: 6-7 October 2007 Analyzed Track by JMA Typhoon KROSA simulation by 20kmGSM GSM precisely simulated the rotate motion of KROSA.

  20. Typhoon JANGMI: 25 Sep. 2008 MTSAT-IR Observation GSM Forecast GSM provided good forecast performance for recurvature of Typhoon JANGMI.

  21. “Nevertheless, do we need Ensemble Prediction Systems for TC Forecasts?”

  22. Position error (km) average Why is a probabilistic approach needed? Position errors of each TC Track Forecast by GSM Position errors are sorted in ascending order Forecast time: 72 hours Total number of forecast events: 102

  23. Specification of JMA Typhoon EPS (TEPS) • The initial condition for the control forecast of TEPS is generated by simply eliminating higher wave number components of the high resolution global analysis. • The ensemble perturbations are generated by the singular vector (SV) method and added to the control initial condition.

  24. SV Target Areas for TEPS Perturbation is calculated by the Singular Vector (SV) method in adaptive areas surrounding each tropical cyclone and an additional fixed area of 20-60N/100-180E.

  25. Generated Perturbations for TEPS • Singular Vector Method • Component of the state vector : T, Q, Vor, Div, Psurf One of the Generated Perturbations for TEPS (Wind Component)

  26. TEPS Case Study: 2008.07.15 18UTC （T0807 KALMAEGI） TEPS TL319L60 (FT132) GSM TL959L60 (FT84) Typhoon EPS could capture the best track with its large spread.

  27. TEPS Case Study: 2008.09.27 00UTC （T0815 JANGMI） TEPS TL319L60 (FT132) GSM TL959L60 (FT84) Spread of Typhoon EPS changes depending on the forecast uncertainty. You can get more information about GSM (Nakagawa, 2009) andTyphoon EPS (Yamaguchi and Komori, 2009) via the following website of RSMC Tokyo – Typhoon Center;http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/techrev.htm

  28. …… Specification of JMA One-Week EPS (WEPS) • Both TEPS and WEPS use same model (low-resolution version of GSM) and analysis field. • The One-week EPS consists of 1 control-run which forecasts from low-resolution analysis field, and 50 perturbed-runs. 50 + 1 = 51 global predictions for one ensemble forecast starting at one initial time.

  29. Perturbation Perturbed analysis Initial Perturbation for WEPS The initial conditions of ensemble member are defined by adding (subtracting) initial perturbation to the control analysis field. Initial perturbation is generated by Singular Vectors (SVs). = Control analysis Uncertainty of initial condition 51 (1 + 25 x 2) 25 x 2

  30. Specifications of TEPS and WEPS at JMA Yamaguchi and Komori (2009); http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/techrev.htm

  31. One-Week Forecast Website for public users at JMA JMA issues the probabilistic forecast for public users Probability of Precipitation Reliability of Forecast (represented as A, B or C) Error Range of High/Low Temperature Probability and uncertainty used in the One-week forecast is derived from the One-week Ensemble Prediction System (WEPS).

  32. Recent Revision of Typhoon Bogus Technique (Mar. 2009)

  33. For Preventing disasters It is important to analyze TC correctly for exact forecast. Location, size, intensity, … In many cases, observational data do not exist around a TC to represent its structure properly (TC locates in the ocean). It must be always high quality. Directly-connected to heavy disasters. It is operational, not research. Although the basis is physically consistent, technical adjustments are sometimes required. Operational TC Bogus - Necessity - 33

  34. GSM TL959L60 20km res. in horizontal with top level at 0.1hPa Typhoon EPS Using GSM TL319L60, 11 members One-week EPS Using GSM TL319L60, 51 members Regional model MSM (Meso Scale Model) NHM (Non-Hydrostatic Model) 5km res. in horizontal with 50 layers in vertical. 4D-var (res. 10km outer, 20km inner, hydrostatic) Models using TC Bogus Data The pseudo observational bogus data are put into analysis as upper observational data (1000,925,850,800,700,600,500,400hPa ). 34

  35. Revision of Typhoon Bogus Technique OLD Bogus Technique NEW Bogus Technique Horizontal distribution of the pseudo data is revised on the basis of statistical investigation. TC central position in the first guess field is properly fit to the analyzed position. First guess field (Vor. 850hPa) Analysis field (Vor. 850hPa) Bogus data (wind vector 850hPa) First guess (wind vector 850hPa) Analysis (wind vector 850hPa)

  36. Let’s take a break now, and resume in 5 minutes.

  37. Real-time JMA Products and Tools for TC operations Observation & analysis SAREP -tropical cyclone (TC) satellite image analysis (TCNA20/21 RJTD, IUCC10 RJTD: via GTS) RSMC Data Serving System –surface, upper air, atmospheric motion vector (for registered users) GMSLPD-satellite image analysis tool Numerical Weather Prediction RSMC Guidance for Forecast -TC prediction of JMA/GSM -TC prediction of JMA/Typhoon EPS (FXPQ20-25 RJTD: via GTS) Numerical Typhoon Prediction Web Site -TC prediction of major NWP centers in the world (for registered users) JMA EPS-WEB -JMA one-week EPS products (for registered users) RSMC Data Serving System -GPV data of global atmosphere, global wave (for registered users) Operational forecast RSMC TC Advisory -for 3-day forecast (WTPQ20-25 RJTD: via GTS) RSMC TC Advisory -for 5-day track forecast (WTPQ50-55 RJTD: via GTS) Prognostic reasoning (WTPQ30-35 RJTD: via GTS) RSMC Tokyo-Typhoon Center Website -for 3-day forecast & 5-day track forecast (open)

  38. Ensemble products on the “JMA EPS-WEB”

  39. JMA EPS-WEB • The products in JMA EPS-WEB are recommended • by Manual on the GDPFS (WMO No.485). • In addition to the web-site for public users, JMA provides a web-site for meteorologists and forecasters in foreign countries. • The special forecast products derived from WEPS are disseminated on the website, “JMA EPS-WEB”, supporting the activity of National Meteorological and Hydrological Services (NMHSs) in Asia. • The data in this website is available for operational weather forecasting in your countries.

  40. Introduction (JMA EPS-WEB) JMA EPS-WEB provides visualized EPS products. • JMA operates an EPS web-site (EPS-WEB) for supporting the activity of National Meteorological and Hydrological Services (NMHSs). • The EPS-WEB is intended for NMHSs forecasters, not for public use. • This web site provides the JMA One-week EPS products. • Caution! The links to this website are strictlyprohibited. • Address of this web site is ….

  41. JMA EPS-WEB (Visualized EPS products) This website provides products derived from the Ensemble Prediction System (EPS) of Japan Meteorological Agency (JMA) to National Meteorological and Hydrological Services (NMHSs), as part of a pilot project of JMA aiming at improving the EPS and increasing the availability of its products.For further improvement of JMA's EPS and its products, users' feedback, especially on comparison of EPS products with local observation and actual weather, is welcomed and should be directed to the JMA Medium-range EPS group at the following email address: eps-admin@naps.kishou.go.jp .Information on this website is guidance and intended to be provided for use by forecasters and meteorologists in NMHSs. Please consult your national meteorological agency/administration for official forecasts of your country, region and/or local area.

  42. 1 2 3 JMA EPS-WEB (Visualized EPS products) All contents are updated at 03 UTC.

  43. 1 2 3 JMA EPS-WEB (Visualized EPS products)

  44. Contents 1: Forecast Chart (Stamp Map)

  45. “Forecast Chart” – all members - “Stamp” displays all synoptic weather forecast maps, 51 maps with ensemble mean, ensemble spread and spaghetti map derived from WEPS, at the same valid time. The range of forecast time is from initial to 9-day with 12-hour interval. spread mean spaghetti Control 50 perturbed runs

  46. “Forecast Chart” – each forecast - “Sequence” displays a forecast map of selected member from initial time up to 9-day forecast. FT=0 FT=12hr FT=24hr FT=36hr FT=48hr FT=60hr FT=72hr FT=84hr FT=96hr FT=108hr FT=120hr FT=132hr FT=144hr FT=156hr FT=168hr FT=180hr FT=192hr FT=204hr FT=216hr

  47. “Forecast Chart” – area and element - 500hPa Geopotential Height Asia Mean Sea Level Pressure WesternPacific SouthChinaSea

  48. Control Run Ensemble Mean Ensemble Member Spread Spaghetti diagram Configurations of “Forecast Chart” “Forecast chart “ page consists of the following five charts.

  49. Control Run Ensemble Member Control Run is a forecast from an unperturbed initial condition (analysis field). Control Run and Ensemble Members Ensemble member is a forecast from perturbed initial conditions (slightly different initial conditions from analysis field ).

  50. Ensemble Mean – definition - • The ensemble mean is an average of all ensemble forecasts (50-perturbed and 1-control run). averaging ……… ex. The Ensemble mean of geopotential height at 500hPa 51-ensmble forecasts

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