cwb.gov.tw

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Outline

BackgroundA demand for CWB to improve heavy rainfall forecasts.

Taiwan suffered severe floods in 1981, causing more than NT$ 10 billion dollars lossand many people to die.

In 1980s, the NWP technology popularly used by other nationalmeteorological services.

Introduction of NWPCWB started the NWP development in 1983.Taiwanese-American experts organized to assist CWBA strategy proposed for the whole process

Take progress step by step to ensure CWB’s staff to get trained, aiming toCultivate in-house professionals, in the end toEstablish in-house capability for independent maintenance and development

Since 1983, CWB had been through four phases of NWP relateddevelopment project. The fifth-phase development project from 2010to 2015 is undergoing.

The sixth-phase one from 2016-2021 will be submitted this year.

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1983-1994(starting from scratch)

Overseas experts dominated the implementation of NWP systems, but trained CWB staff to create

in-house professionals.

1995-2009(Establishing in-house capability)

CWB staff were getting skilled in NWP technology and gradually dominated the development work.

CWB extended the application of numerical prediction technology from weather to short-term

climate forecast.

2010-2015Sustain the advance of numerical prediction technology, particularly improving the skill for high-impact weathers. Goals including:•Higher resolution: GFS~20km, Reg.~3-2km•More advanced DA system to enhance the use of

satellite and radar observations.•High resolution ensemble prediction system

1994: The 2nd generation global spectral and regional

models operational at CWB with resolution of

T79L18 and 60/20km nested domains.

1989: The 1st generation global/regional models operational

at CWB with resolution of 275km/90km.

2008：CWB WRF (45/15/5km) operational.

2007：CWB spectral GFS upgraded to T239L30.

2001：CWB non-hydrostatic regional model

operational with 45/15/5km domains.

2015 : Higher resol. WRF (15/3km) and

GFS (T512L60) operational.

2011：CWB WRF ensemble prediction

system, 20 members per run.

2011：CWB spectral GFS upgraded to

T319L40.

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• Averagely, CWB upgrades the supercomputer every 6-7 years, able to gain 15-20 times more computing power than the old one.

1987

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2006

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• Three-year installment, providing 6%, 6% and 88% capacity from 2012 to 2014 respectively.

• The new supercomputer will be a Peta-Scale machine, near 100 times faster than the old one.

Fujitsu HPC

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• Data Assimilation Method and Obs.

Before2003

• OI• Only GTS convectional obs. assimilated

2003• NCEP/SSI (Spectral Statistical Interpolation)• Besides GTS, radiance added but very limited

2010• NCEP/GSI (Grid Statistical Interpolation)• GPS/RO and more radiance assimilated

2014 • NCEP/ Hybrid EnKF-GSI DA (Be operational July)

Data assimilation method

Observations GTS – through the channel of JWA and NOAA/GSD

Radiance – from NCEP FTP Site starting 2003

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• Radiance Assimilation

20%

40%

60%

80%

Only NOAA15 AMUSA before 2010

all AMUSA assimilated by GSI in 2012

IASI added in 2013

AIRS added in 2014

6hr gain in forecast

500hPa Anomaly Correlation

20N-80N

CWB/GFS radiance use relative to NCEP/GFS

According to assessment of data contribution to forecast improvement by ECMWF, satellite observations of AMUSA, IASI and AIRS are the top priority of radiance assimilation for CWB/GFS.

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• Model PhysicsResolution

T319L40 (~42km) for 8-day forecast.T119L30 (~110km) for 45-day forecast at 00/12Z, participating in aNCEP’s activity for dynamical model MJO forecast.

Physics

Year Parameterization Old Version Updated version

2005

2013

Land surface model Bucket method Two-layer land model(Pan and Mahrt 1987)

NCEP/Noah land model

2007 Grid scale precip. Diagnostic method Cloud microphysics scheme(Zhao and Carr 1997)

2008

2015

Radiation Radiation package by Hashvardhan et al. 1987

Unified two-stream scheme with k-correlated method (Fu and Liou 1992;1993)

RRTMG (undergoing)

2009

2014

Cumulus Relaxed A-S scheme NCEP/Simplified A-S scheme(Pan and Wu 1994)

NCEP/New Simplified A-S scheme

2009 Boundary layer TKE- scheme NCEP/First-order non-local scheme(Troen and Mahrt 1986)

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• Forecast Performance Progress

1999年至2013年期間，CWBGFS在20-80N內，第5日預報500hPa高度場之距平相關(AC,縱軸)。黑線帶實心圓點為月平均變化，紅色粗實線為12個月移動平均(running mean)。

Day 5 Anomaly Correlation over 20N-80N for 500hPa H(1999-2013)

Continuous forecast improvement over the years due to:Better forecast modelBetter initial state (better data assimilation system, more observations)

Red line : 12-month running mean

ARW-WRF, NCAR community model system, was implemented atCWB in 2004 and had been through comprehensive evaluations.

WRF operational in 2008 as a new generation regional forecast system.

Current status of CWB/WRF system as follows:45/15/5km three nested domains with 45 layers in the vertical

WRF 3DVar using partial cycling similar to NCEP

Lateral boundary condition from NCEP GFS output as primary option

84 hrs forecasts at 00/06/12/18Z

WRF-based high-resolution ensemble system operational in 2011Same domain design as deterministic model

20 members predictions at 00/06/12/18Z using multi-physics suites

Support 368 townships weather forecast

Provide better typhoon QPF over Taiwan

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• WRF-Based Forecast System

Although WRF started to be operational at CWB in 2008, the performance was not very satisfied particularly for typhoon track forecasts.

Continuous improvements for CWB/WRF have been done over the years:

Initial field improved by

Implementation of typhoon vortex relocation (2010)

Use of Partial Cycle (2011)

Assimilation of Ground GPS (2012)

Use of Blending Method (2013)

Model physics improved by

Improvement of Cumulus Parameterization (2011)

Use of Gravity Wave Drag Parameterization (2012)

Update of Radiation Scheme (RRTMG) (2013)

Update of Land Data based on MODIS (2013)

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• Improvement for CWB/WRF

Poor WRF typhoon track forecasts for Morakot of 2009

Typhoon Morakot devastated Taiwan in August 2009, killing near 700 people.

CWB has a close cooperation with NCAR’s scientists on WRF improvement.

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• Typhoon Morakot Track Reforecast

Operational model in 2009 Re-forecast using the model in 2010

Re-forecast using the model in 2011 Re-forecast using the model in 2012

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• Typhoon track forecast improvement

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97 100 9683

191200

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450

2008 2009 2010 2011 2012 2013

24hr

48hr

72hr

CWB-24hr

CWB-48hr

CWB-72hr

WRF Model

CWB Official

Yearly Statistics of Typhoon Track Forecast Error (Km)

Km

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• Progress of Synoptic ForecastDay 3 forecast verification for 45km domain

Yearly averaged RMSE

850hPa Temperature

500hPa Height

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• Typhoon QPF Climatology

Due to mountainous terrain, rainfall distribution and amount is closely linked to the relative location of a typhoon to Taiwan.

A climatology of typhoon QPF over Taiwan can be obtained based on a statistical relationship between the historical rainfall data and typhoon tracks.

55 57

66 6668

47

3129

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36

37 29

55 57

66 6668

103 5979

55 80

65 59

29

239

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54

47

3129

26

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0.5o x 0.5o Mean rainfall rate base on typhoon position

Each panel represents a composite rainfall distribution as a typhoon is located at that panel center.

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• Weakness of Typhoon QPF Climatology

Climatology QPF tends to be significantly underestimated for cases of extreme rainfall, particularly associated with an interaction with the southwest or northeast monsoon flow like Morakot (2009).

However, numerical modelling detected the occurrence of abnormal rainfall.

Typhoon Morakot (2009) embedded in a large-scale convection zone

>1200mm in a day

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• Ensemble Typhoon QPF

Distribution of the predicted typhoon locations from EPS Given a specified track scenario, a

composite rainfall map can be made with predicted rainfall of points within a certain circle around the track.

Based on the concept of the climatology method, a dynamical ensemble method for typhoon QPF was established by using real-time predicted rainfall and typhoon tracks from WRF ensemble system instead of historical database.

3-hour accumulated rainfall predictions from members in a specific circle

ModelGFS - go to 25km first, aiming to reach 15km

Global ensemble system for week 2 forecast

WRF - 15/3km nested

A rapid-cycling WRF-based model with a very high resolution (~2km)over Taiwan area for very short-range QPF

Data assimilationEnsemble-3D/4D variation hybrid DA

Enhance the use of local observations particularly from the radarnetwork to improve short-range QPF

Physical parameterizationBetter physics for hydrological cycle, particularly over Taiwan’s complextopography

15km3km

2km

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CDCCyber 205

Computing power 1/3704

CRAYYMP-8i

Computing power1/303

FUJITSUVPP5000

Computing power1/15

IBMP5-575

Computing power1

2012-2014FUJITSU

FX10/PFX10

Computing power~100

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2006

2012-2014

Global : <20KM Regional : 1~2KM (finest) Ensemble : >100 members

per days, more freq. and members

Radar and satellite observations well assimilated by more advanced technology

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GFS : 40KM WRF-based : 45/15/5KMWRF EPS : 40 members/day

GFS : 165KM RFS : 65/20KM

GFS : 110KM NFS : 45/15/5KM

GFS : 275KM RFS : 90KM

NWP at CWB has made continuous progress over the years. The new Fujitsu supercomputer offers CWB an unprecedented opportunity for NWP development. With more advanced NWP

technology and higher resolution models implemented in the near future, CWB is looking forward to providing the nation more accurate weather information, particularly for typhoon

forecast, week 2 forecast and overall QPF.

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Thank you for your attention.