CBS EXPERT TEAM ON EXTENDED AND LONG-RANGE FORECASTING CBS EXPERT TEAM ON EXTENDED AND LONG-RANGE FORECASTING 26~30 March 2012, Geneva, Switzerland26~30 March 2012, Geneva, Switzerland

Suhee ParkKorea Meteorological Administration

Suhee ParkKorea Meteorological Administration

WMO Lead Center for WMO Lead Center for

Long-Range Forecast Multi-Model EnsembleLong-Range Forecast Multi-Model Ensemble

(LC-LRFMME) : Status/progress report(LC-LRFMME) : Status/progress report

WMO Lead Center for WMO Lead Center for

Long-Range Forecast Multi-Model EnsembleLong-Range Forecast Multi-Model Ensemble

(LC-LRFMME) : Status/progress report(LC-LRFMME) : Status/progress report

ContentsContents ContentsContents

History of WMO LC-LRFMME

Function of WMO LC-LRFMME

WMO Global Producing Centre (GPC) Data collection

Products and Activities of WMO LC-LRFMME Multi-Model Ensemble Forecasts

Summary

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20052005 WMO GPC meeting (October, Korea)- KMA suggested the need of LC-LRFMME.

The joint ET of DPFS agreed needs of Lead Center(s) for collection of globally available LRF to build MMEs (April, England).

WMO CCL meeting (November, China)- KMA presented the need for establishing LC-LRFMME.

KMA, jointly with NCEP, completed submission of Lead Center application form to the WMO (September).

WMO CBS-Ext.06 (November, Korea)- The commission encouraged GPCs to provide their data to LC-LRFMME.

WMO Meeting of the ET on Extended and LRF (April, China).- Redefining the goal and functions of LC-LRFMME

WMO/KMA GPC Workshop (September, Korea)- Refining needs for and functions of LC-LRFMME

LC-LRFMME established the data exchange system (June).20072007

20062006

20082008

20092009 WMO CBS-XIV (April, Croatia)- LC-LRFMME was officially endorsed.

History & AcknowledgementHistory & Acknowledgement History & AcknowledgementHistory & Acknowledgement

Primary FunctionsPrimary Functions

Functions of LC-LRFMMEFunctions of LC-LRFMME Functions of LC-LRFMMEFunctions of LC-LRFMME

• Maintains a repository of documentation for the system configuration of all GPC LRF systems

• Collects an agreed set of forecast data from GPCs

• Generates an agreed set of Lead Centre (LC) products

• Redistributes digital forecast data for those GPC’s that allow it

• Handles requests for the password for the website and data distribution

DataData collectioncollection DataData collectioncollection　

Beijing CPTEC ECMWF EXETER Melbourne Montreal Moscow Pretoria Seoul Tokyo Toulouse Washington(BCC) (CPTEC) (ECMWF) (EXETER) (POAMA) (MSC) (HMC) (SAWS) (GDAPS) (TCC) (toulouse) (NCEP)

Forecastingrange

3 months 6 months 6 months 5 months 6 months 3 months 3 months 3 months 3 months 3 months 6 months 9 months

data Format

bin Grib1 grib1 grib1 grib1 grib1 grib1 grib1 grib1 grib2 grib1 grib1

Forecastperiod

2008.02~ 2009.12~ 2009.02~ 2009.09~ 2008.07~ 2011~ 2008.02~ 2009.08~ 2007.11~ 2010.02~ 2009.02~ 2008.02~

collected data

Ensemble mean(raw),

Ensemble(raw),

Ensemble(raw)

Ensemble mean(raw),

Ensemble(raw)

ensemble Mean(ano),

Ensemble(ano)

ensemble mean(raw)

Ensemble(raw, ano)

Ensemble(raw)

Ensemble mean(raw),

Ensemble(raw)

Ensemble mean(ano),

ensemble(ano)

Ensemble mean(raw)

Ensemble mean

(raw, ano), Ensemble(raw, ano)

ensemble Mean

(raw, ano)

ensemble mean(ano),

Ensemble(ano)

members 8 15 41 42 3020

(2model x 10)

10 6 20 51 41 40

Hindcastperiod

1983~ 1979~2001 1981~2005 1989~2002 1980~2006 1981~2010 1979~2003 1982~2001 1979~ 1979~2008 1979~2007 1981~2004

collected data

Ensemble mean(raw),

Ensemble(raw),

climatology

Ensemble (raw),

climatologyx

Ensemble mean(raw)

Ensemble(raw)

Ensemble(raw),

climatology

Ensemble mean(raw),

Ensemble(raw)

x

Ensemble mean(raw),

Ensemble(raw),

climatology

Ensemble(raw)

xEnsemble

(raw)

members 8 10 11 12 1020

(4model x 10)

10 6 20 10 11 15

additional parameter (without

parameter)

U850, V850,

U200, V200- -

U850, V850, U200,

V200, olr, Tsfc

U850, V850,U200, V200 (SST)

(SST) (SST)U850,

V850,U200, V200 (SST)

U850, V850, U200, V200

- -

resolution : 144x73, basic parameter : rain, mslp, t2m, z500, t850, sst, blue shading: tier-2, peach shading: coupled

1 3 5 7 9 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 31

Collecting time of GPC data

Collecting time of GPC data

GPC Collecting time

Beijing 10~15th

CPTEC 14~17th

ECMWF 14~17th

EXETER 14~18th

Melbourne 12~15th

Montreal 1~3th

Moscow 11~16th

Pretoria 14~17th

Seoul 12~14th

Tokyo 18~20th

Toulouse 14~18th

Washington 14~18th

Period of producing forecast data

&Homepage display

Period of producing forecast data

&Homepage display

Period of research relevant to GSCUPeriod of research relevant to GSCU

Collecting time of each GPCs Collecting time of each GPCs datadata Collecting time of each GPCs Collecting time of each GPCs datadata

http://www.wmolc.org

No. of Members

: 343 members from 78 countries

Links to 12 GPCs

LC-LRFMME WebsiteLC-LRFMME Website LC-LRFMME WebsiteLC-LRFMME Website

Membership & Data Membership & Data upload/download/plotupload/download/plot Membership & Data Membership & Data upload/download/plotupload/download/plot

• Grade A (GPCs) :- Upload & Download Digital data(limited) - Download Image plots • Grade B (NMHSs, RCCs) : - Download Digital data(limited) & Image plots

• Grade C (Others) : - Image plots

Membership Grades & Membership Grades & AccessAccess

Access to data is available for registered members only.

GPC digital data and graphical products in standard format available GPC digital data and graphical products in standard format available from LC-LRFMMEfrom LC-LRFMMEGPC digital data and graphical products in standard format available GPC digital data and graphical products in standard format available from LC-LRFMMEfrom LC-LRFMME

LC-LRFMME ProductsLC-LRFMME Products LC-LRFMME ProductsLC-LRFMME Products

Digital products Graphical products

- Both forecast and hindcast of monthly mean anomalies of the GPC ‘s ensemble mean for lead 1~3), following the month of submissions 2m surface temperature Precipitation Mean sea level pressure 850hPa temperature 500hPa geopotential height Sea surface temperature

- Individual forecast plots for each GPC forecast anomalies in common graphical format (Rectangular, Time series, Stereographic type, etc.) Consistency map SST Plume (Nino3.4 SST anomalies)- Deterministic Multi-model Ensemble Simple composite mean(SCM) Regular Multiple Regression Sigular Value Decomposition(SVD) - Probabilistic Multi-model Ensemble tercile-based categorical probabilities

Digital productsDigital products Graphical productsGraphical products

Products Products Ⅰ: 6 ParametersⅠ: 6 Parameters Products Products Ⅰ: 6 ParametersⅠ: 6 Parameters

850hPa Temperature850hPa Temperature Mean Sea Level PressureMean Sea Level Pressure

PrecipitationPrecipitation 2m Temperature2m Temperature Sea Surface TemperatureSea Surface Temperature

500hPa GPH500hPa GPH

Products Products ⅡⅡ: 12 GPCs: 12 GPCs Products Products ⅡⅡ: 12 GPCs: 12 GPCs

BeijingBeijing ECMWFECMWF ExeterExeter

MelbourneMelbourne MontrealMontreal MoscowMoscow

WashingtonWashingtonToulouseToulouseTokyoTokyoSeoulSeoul

CPTECCPTEC

PretoriaPretoria

April May

AMJ

Forecast TimeForecast Time• Monthly meanMonthly mean• 3-month mean3-month mean

Products Products ⅢⅢ: Period: Period Products Products ⅢⅢ: Period: Period

June

RectangularRectangular Time SeriesTime Series StereographicStereographic

Products Products ⅣⅣ: Map Types: Map Types Products Products ⅣⅣ: Map Types: Map Types

All MapAll Map Consistency MapConsistency Map SST PlumeSST Plume

AO

Products Products Ⅴ Ⅴ : Indices: Indices Products Products Ⅴ Ⅴ : Indices: Indices

Simple MMESimple MME

MME Plot of LC-LRFMMEMME Plot of LC-LRFMME MME Plot of LC-LRFMMEMME Plot of LC-LRFMME

Biased-Corrected Ensemble MeanBiased-Corrected Ensemble Mean

Regular Multiple RegressionRegular Multiple Regression

Singular Value DecompositionSingular Value Decomposition

MME Production : Deterministic MME Production : Deterministic MMEMME MME Production : Deterministic MME Production : Deterministic MMEMME

MME Production : Probabilistic MME Production : Probabilistic MMEMME MME Production : Probabilistic MME Production : Probabilistic MMEMME

Since June 2011, categorical probabilities for terciles based on the Probabilistic Multi Model Ensemble (PMME) prediction system have been synthesized.

WMOWMOLC-LRFMMELC-LRFMME

Activities ofActivities of LC-LRFMMELC-LRFMME Activities ofActivities of LC-LRFMMELC-LRFMME

Support for RCOFsSupport for RCOFs

Support for epidemic controlSupport for epidemic control

In the spring of 2009

PRESAO, GHACOF, FOCRAII

In the winters of 2007 and 2008

climate prediction for the African region

WMO, IRI, SADC Drought Monitoring Centre

TrainingTrainingImprovement of Meteorological Disaster

Responsiveness for African Countries (May 2009)

Climate Variability and Predictions in South Asia, Eastern and Southeastern

Africa (June 2009)

LC-LRFMME established by GPC-Seoul and GPC-Washington is fully functional and meets the requirements set by the “Expert Team on Extended and Long-Range Forecasts (ET-ELRF)”

LC-LRFMME standardizes GPCs’ data for better usage of WMO Members and has already entertained requests from RCOFs

LC-LRFMME would be a valuable asset to the long-range forecast communities

LC-LRFMME makes an important contribution to increasing the resources available for disaster prevention and mitigation, and for better social-economic planning

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SummarySummary SummarySummary

Thank you!Thank you!