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!