CBS EXPERT TEAM ON EXTENDED AND LONG-RANGE FORECASTING 26~30 March 2012, Geneva, Switzerland WMO Lead Center for Long-Range Forecast Multi-Model Ensemble (LC-LRFMME) : Status/progress.

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Transcript CBS EXPERT TEAM ON EXTENDED AND LONG-RANGE FORECASTING 26~30 March 2012, Geneva, Switzerland WMO Lead Center for Long-Range Forecast Multi-Model Ensemble (LC-LRFMME) : Status/progress.

CBS EXPERT TEAM ON EXTENDED AND LONG-RANGE FORECASTING
26~30 March 2012, Geneva, Switzerland
WMO Lead Center for
Long-Range Forecast Multi-Model Ensemble
(LC-LRFMME) : Status/progress report
Suhee Park
Korea Meteorological Administration
Contents
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
History & Acknowledgement
2005
WMO GPC meeting (October, Korea)
- KMA suggested the need of LC-LRFMME.
WMO CCL meeting (November, China)
- KMA presented the need for establishing LC-LRFMME.
2006
The joint ET of DPFS agreed needs of Lead Center(s) for collection of globally
available LRF to build MMEs (April, England).
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.
2007
LC-LRFMME established the data exchange system (June).
WMO/KMA GPC Workshop (September, Korea)
- Refining needs for and functions of LC-LRFMME
2008
2009
WMO Meeting of the ET on Extended and LRF (April, China).
- Redefining the goal and functions of LC-LRFMME
WMO CBS-XIV (April, Croatia)
- LC-LRFMME was officially endorsed.
www.themegallery.com
Functions of LC-LRFMME
Primary Functions
• 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
Data collection
Beijing
CPTEC
(BCC)
(CPTEC)
Melbourne
Montreal
Moscow
Pretoria
Seoul
Tokyo
Toulouse
Washington
(ECMWF) (EXETER)
(POAMA)
(MSC)
(HMC)
(SAWS)
(GDAPS)
(TCC)
(toulouse)
(NCEP)
6 months
6 months
5 months
6 months
3 months
3 months
3 months
3 months
3 months
6 months
9 months
Grib1
grib1
grib1
grib1
grib1
grib1
grib1
grib1
grib2
grib1
grib1
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
30
20
(2model x
10)
10
6
20
51
41
40
Hindcast
period
1983~
Forecasting
3 months
range
data
bin
Format
Forecast
2008.02~
period
ECMWF
EXETER
1979~2001 1981~2005 1989~2002 1980~2006 1981~2010 1979~2003 1982~2001
Ensemble
mean
Ensemble
collected
(raw),
(raw),
data
Ensemble
climatology
(raw),
climatology
x
Ensemble
mean
(raw)
members
11
12
-
-
8
additional
parameter U850, V850,
(without U200, V200
parameter)
10
x
Ensemble
(raw)
x
Ensemble
(raw)
10
6
20
10
11
15
(SST)
(SST)
-
-
20
(4model x
10)
U850, V850, U850,
U200, V200,V850,U200,
olr, Tsfc V200 (SST)
1979~2008 1979~2007 1981~2004
Ensemble
mean
(raw),
Ensemble
(raw),
climatology
Ensemble
Ensemble
mean
Ensemble
(raw),
(raw),
(raw)
climatology Ensemble
(raw)
10
1979~
U850,
U850, V850,
V850,U200,
U200, V200
V200 (SST)
resolution : 144x73, basic parameter : rain, mslp, t2m, z500, t850, sst, blue shading: tier-2, peach shading: coupled
Collecting time of each GPCs data
Collecting time of GPC
data
1
3
5
7
9
11
12
13
14
15
16
Period of research
relevant to GSCU
17
18
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
19
20
21
22
23
24
25
26
Period of producing
forecast data
&
Homepage display
27
28
29
31
LC-LRFMME Website
http://www.wmolc.org
No. of Members
: 343 members from
78 countries
Links to
12 GPCs
Membership & Data upload/download/plot
Membership Grades &
Access
• 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
 Access to data is available for registered members only.
LC-LRFMME Products
GPC digital data and graphical products in standard format available
from LC-LRFMME
Digital
products
Digital
products
Graphical products
Graphical
products
- Individual forecast
 plots for each GPC forecast anomalies in
- Both forecast and hindcast of monthly me
common graphical format (Rectangular,
an anomalies of the GPC ‘s ensemble mean
Time series, Stereographic type, etc.)
for lead 1~3), following the month of submis
 Consistency map
sions
 SST Plume (Nino3.4 SST anomalies)
 2m surface temperature
- Deterministic Multi-model Ensemble
 Precipitation
 Simple composite mean(SCM)
 Mean sea level pressure
 Regular Multiple Regression
 850hPa temperature
 Sigular Value Decomposition(SVD)
 500hPa geopotential height
 Sea surface temperature
- Probabilistic Multi-model Ensemble
 tercile-based categorical probabilities
Products Ⅰ: 6 Parameters
500hPa GPH
850hPa Temperature
Mean Sea Level Pressure
Precipitation
2m Temperature
Sea Surface Temperature
Products Ⅱ: 12 GPCs
Beijing
CPTEC
ECMWF
Exeter
Melbourne
Montreal
Moscow
Pretoria
Tokyo
Toulouse
Washington
Seoul
Products Ⅲ: Period
April
May
Forecast Time
• Monthly mean
• 3-month mean
June
AMJ
Products Ⅳ: Map Types
Rectangular
Time Series
Stereographic
All Map
Consistency Map
SST Plume
Products Ⅴ : Indices
AO
MME Plot of LC-LRFMME
Simple MME
MME Production : Deterministic MME
Biased-Corrected Ensemble Mean
Regular Multiple Regression
Singular Value Decomposition
MME Production : Probabilistic MME
 Since June 2011, categorical probabilities for terciles based on the Probabilistic Multi
Model Ensemble (PMME) prediction system have been synthesized.
Activities of LC-LRFMME
Support for
epidemic control
In the winters of
2007 and 2008
Support for RCOFs
In the spring of 2009
PRESAO, GHACOF,
FOCRAII
WMO
LC-LRFMME
Training
Improvement of Meteorological Disaster
Responsiveness for African Countries
(May 2009)
Climate Variability and Predictions in
South Asia, Eastern and Southeastern
Africa (June 2009)
climate prediction for the
African region
WMO, IRI, SADC Drought
Monitoring Centre
Summary
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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Thank you!