______2008/SOM3/ISTWG/SYM/031 Agenda Item: 4-05
APEC Climate Center (APCC) Climate Prediction and Information Activities: New Developments
Submitted by: APEC Climate Center (APCC)
APEC Climate Symposium Lima, Peru 19-21 August 2008
20 August, 2008 APEC Climate Symposium, 2008 Abstract 4-05
APCC Climate Prediction and information activities: New developments
Dr.Karumuri Ashok, APCC, Korea
ABSTRACT
The talk covers the new operational efforts and developmental projects in APCC since the beginning of 2008. The APCC has been issuing the rolling monthly 3-month forecast since 2008, with due verification. It has also been supporting KMA by providing downscaled forecasts for 60 Korean stations. The APCC has also initiated experimental 1-tier 6-month MME prediction, slated on seasonal basis, and so far developed two forecasts. The SNU, SINTEX-F (FRCGC), UH data (all three datasets provided by CliPAS), NCEP, and POAMA datasets are used in this efforts. To boost this effort, APCC has also started to develop an in-house coupled prediction model based on the CCSM3. To do this, APCC has developed a coupled SST nudging scheme.
The presentation will briefly touch about other ongoing development projects such as a probabilistic downscaling system, a drought monitoring system etc.
The presentation will also introduce issues such as the need for longer hindcast data, need for more 1-tier forecast datasets etc. The climate conditions of since 2007 spring will also be briefly presented, along with the performance of the APCC MME system for some of the seasons. The presentation will also seek guidelines on future activities of APCC. The APCC climate prediction activities: New Developments
Australia Asia Brunei Darussalam Canada Chile People’s Republic of China Pacific Hong Kong, China Indonesia Economic Cooperation Japan Korea Malaysia Mexico Climate New Zealand APEC Climate Center (APCC) Papua New Guinea Peru for Climate Information Services to Society, Philippines enter Russia C Busan, Republic of Korea Singapore Chinese Taipei Thailand United States Viet Nam
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2008 projects
Operations
• Operationalization of monthly 3-month forecast since January, with upgraded hindcast verification. • Downscaled forecast provision at 60 Korean stations to KMA with due hindcast verification • New monitoring products
Development • 6-month MME seasonal prediction • In-house development of coupled prediction system • Probabilistic downscaling
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1 Operational Products
Enhancement of MME forecast for APCC economies Æ 12 times/yr
Operation schedule
10 ~ 15 16 ~ 18 19 ~ 23 production of MME MME forecast outlook & climate Data acquisition & analysis forecast highlights services
Multi-institutional cooperation and sharing of high-cost data
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Models
Start End SST Specification Ensemble Name/Economy Variables Model Designation Focal Point/E-Mail Year/Month Year/Month (Hindcast/Forecast) (H/F)
BCC NCC-CGCM Peiqun Zhang 1983/Jan. 20008/Present PREC,T850,Z500 Predicted SST/ 8/8 China T63L16 [email protected]
COLA T2M, PREC, MSLP, T850, U850, COLA AGCM v2.2.6 OISSTv2/ Daniel Paolino 1981/Dec. 2002/Dec. 10/10 U.S.A. V850, U200, V200, Z500, OLR T63L18 IRI SST Forecast [email protected]
CWB T2M, PREC, MSLP, T850, U850, OISSTv2/ Jyh-Wen Hwu 1979/Jan. 2003/Dec. CWB T42L18 5/10 Chinese Taipei V850, U200, V200, Z500 IRI SST Forecast [email protected]
GCPS T2M, PREC, MSLP, T850, U850, KMA/SNU SST Forecast/ Jeong-Seok Lee 1979/Jan. 2008/Present GCPS T63L21 4/4 Republic of Korea V850, U200, V200, Z500 KMA/SNU SST Forecast [email protected]
GDAPS T2M, PREC, MSLP, T850, U850, Won-Tae Yun 1979/Jan. 2008/Present GDAPS T106L21 OISSTv2/OISSTv2 1/20 Republic of Korea V850, U200, V200, Z500 [email protected]
HMC SL-AV Persistent SST/ Dmitry Kiktev 1979/Mar. 2003/Dec. T2M, PREC, MSLP, T850, Z500 10/10 Russia 1.125 x 1.406, L28 Persistent SST [email protected]
T2M, PREC, MSLP, T850, U850, IAP9L-AGCM Observed SST/ Huijun Wang IAP 1979/Jan. 2004/Jan. 7/7 V850, U200, V200, Z500, OLR 5.0 x 4.0, L9 IAP-TOGA SST Forecast [email protected]
T2M, SST, PREC, MSLP, T850, U850, Observed SST/ David G. Dewitt IRI 1979/Jan. 2005/Dec. ECHAM4.5 T42L19 24/24 V850, U200, V200, Z500, OLR Forecasted SST [email protected]
Kiyotoshi Takahashi T2M,SST,PREC,MSLP,OLR,T850, GSM Persistent SST/ JMA 1979/Jan. 2006/Dec. 51/51 Kiyotoshi.takahashi- Z500,U850,V850,U200,V200 TL95, L40 Persistent SST [email protected]
PREC, MSLP, T850, U850, V850, METRI AGCM Persistent OISST/ Won-Tae Kwon METRI 1979/Jan. 2008/Present 10/10 U200, V200, Z500 5.0 x 4.0, L17 Persistent OISST [email protected]
MGO T2M, SST, PREC, MSLP, T850, U850, Observed SST/ Vadim Matyugin 1979/Jan. 2004/Dec. MGOAM2 T42L14 6/10 Russia(((( V850, Z500, OLR Persistent SST [email protected]
MSC T2M, PREC, MSLP, T850, U850, RPN GEM Persistent ERA40-SST/ Normand Gagnon 1969/Jan. 2003/Dec. 10/10 Canada V850, U200, V200, Z500 1.875 x 1.875, L50 Persistent CMC SST [email protected]
NASA T2M, SST, PREC, MSLP, T850, U850, NASA-GSFC Predicted SST/ Myong-In Lee 1993/Feb. 2007/Sep. 6/18 U.S.A.. V850, U200, V200, Z500, OLR 2.5x2.0, L34 Predicted SST [email protected]
NCEP T2M, SST, PREC, MSLP, T850, U850, Predicted SST/ Jae-Kyung E. Schemm 1981/Dec. 2003/Feb. NCEP CFS T62L64 15/15 U.S.A.. V850, U200, V200, Z500, OLR Predicted SST [email protected]
POAMA T2M, SST, PREC, MSLP, T850, U850, Predicted SST/ Oscar Alves 1981/Dec. 2003/Feb. POAMA 1.5 T47L17 15/15 Australia V850, U200, V200, Z500, OLR Predicted SST [email protected]
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2 High Performance Computing System
Korea Meteorological Administration Korea Institution of Science & (Cray X1E) Technology Information (IBM)
- IBM System p5 595 server - Storage System : IBM 366 TB DS4700 - Shared storage : 460 TB - Speed : 37 TF - Memory : 1024 GB memory per 1 node
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APCC Dynamical Climate Forecast System (Tier2)
Training Phase Forecast Phase
t=0 N MME Real-time S = O + ∑ai (Fi − Fi ) i=1 Prediction
train 2 The weights are computed at each grid point by minimizing the function: G = ∑()St − Ot t=0
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3 Procedure of MME Seasonal Prediction System
Collection : 17 Models
Quality Check
Composite: Deterministic Forecast (4 kinds of schemes) Probabilistic Forecast
Verification: Application: Graphic •Previous prediction • Index forecast •Hindcast • Statistical downscaling
Outlook: Interpretation and Description of Global/Regional Prediction
Dissemination: Web information & Backup of the Data and Doc.
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Deterministic MME Schemes
Simple Composite Method : 1 ′ P = F SCM Simple composite of individual forecast ∑ i with equal weighting M i
Stepwise Pattern Projection Method : 1 ′ Simple composite of individual forecasts, after ˆ SPPM P = ∑ Fi correction by SPPM (improved version of CPPM) M i
Multiple Regression Method: ′ MRG Optimally weighted composite of individual forecasts. P = a F The weighting coefficient is obtained by SVD based ∑ i i i regression
Synthetic Multi-Model Super Ensemble Method: 1 ′ Weighted combination of statistically corrected ˆ SSE P = ∑αi Fi multi model output M i
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4 Couple Pattern Projection Method
Forecast procedure – Pointwise regression method
Y(t) = αXP(t) + β
Predictor field X(i, j, t) XP(t) ( model forecast)
Predictand Y(t) Y(t) ( observation)
Coupled pattern projection coefficient 1 Σ (Y(t) – Ym)•(X(i,j,t)-Xm(i,j)) XP(t) = Σ COR(i,j)•X(i,j,t) COR(i,j)= N i,j σX(i,j) • σY
Calculate regression coefficient α, β in training period, forecast a regional climate from projection coefficient of the coupled pattern onto forecast field.
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Implemented MME-S in APCC
¾ SPPM and MME-S was tested on ¾ SPPM and MME-S was tested on prediction of 850 hPa temperature Advantage to using SPPM2 prediction of 850 hPa temperature precipitation using APCC hindcast precipitation using APCC hindcast data for the period 1983-2003 and (1) Computational Estimates data for the period 1983-2003 and operational forecast data for 2006 (per 1 model, 1 variable, 22 years) operational forecast data for 2006 and 2007. and 2007. ¾ SPPM code was transferred to CPPM- OLD version : 72 ¾ SPPM code was transferred to APCC and is now part of the hours APCC and is now part of the CPPM – New version : 12-15 Automated Forecast System. Automated Forecast System. hours
MME-S Procedure SPPM v2 : 5 hours (suggestion: If you use 8 cpu simultaneously, it takes 10 STEPSTEP 1: 1: Applying Applying statistical statistical correction correction hours for all models’ usingusing SPPM SPPM to to individual individual models models hindcast and forecast and (1) Prior prediction selection two variables) (2) Second Step: Pattern Projection (3) Optimal choice of prediction (2) Improved skill, especially for STEPSTEP 2: 2: Simple Simple multi-model multi-model precipitation compositecomposite using using available available predictions predictions
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5 Probabilistic MME Scheme
Defining Normal fitting method terciles - For the middle/upper tercile boundary : mean plus 0.43 times the standard deviation Æ μ + 0.43σ - For the lower/middle tercile boundary : mean minus 0.43 times the standard deviation Æ μ -0.43σ
Forecast probability
A Probability of Above-normal
N Probability of Near-normal
B Probability of Below-normal
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Monthly 3-Month Forecasts Operationalized
The APEC CLIMATE CENTER 4-deterministic and one probabilistic Climate Outlook for August-October, 2008 BUSAN, 23 July 2008 - Synthesis of the latest computer model MME forecasts carried out each month. forecasts for August to October, 2008 at the APEC Climate Center (APCC), located in Busan, Korea, predicts warmer than Best deterministic forecast for that month normal temperatures in Western Europe, Mediterranean, parts of selected on hindcast verification. middle East, Mongolia and the East Asian region covering China, Korea and Japanese archipelago. Many parts of Asia may experience near normal to drier-than normal conditions. The Forecast outlooks sent out by 25th of current conditions in the tropical Indian Ocean are indicative of each month to 21 NMHSs and to larger a positive IOD event.
climate prediction community. Current Climate Conditions Review of outlook by Working Group and During the past May-to-July period (based on data up to July 18, 2008), it has been drier than normal in the southeastern as well as SAC members prior to public release western part of US, while a larger region covering northeastern Brazil and the equatorial Atlantic has seen surplus rainfall. It has been warm and dry in the Middle East, midlatitude Central Asia and northeast Asia. Most part of the continental Australia also experienced deficiency in rainfall in the past three months or longer. On the other hand, it has been wetter than normal in the Philippines, the southern Polynesian Islands and also northern part of India. Current cooler than normal Sea Surface Temperature over equatorial eastern Indian Ocean and alongshore surface wind easterly anomalies off Sumatra persisted, indicative of a positive Indian Ocean Dipole (IOD) event.
Forecast
The APCC forecasts for ASO, 2008 indicate that a broad region covering from north Australia, through most of the Maritime Continent and Indochina, till India is expected to see anomalously cool conditions. On the other hand, southeast Australian continent to New Zealand may experience slightly warmer and dry than normal conditions; the expected rainfall conditions are in agreement with the positive IOD-like conditions that currently prevail, indicating a possibility of continuation of the event. …..…………………
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6 Upgrading of the SVS
• APCC pursues the WMO-prescribed SVS measures. • We are upgrading our efforts of verification. We have upgraded our verification almost to level 3 suggested by WMO.
Level 1 Parameters Verification Regions Deterministic Forecasts Probabilistic Forecasts T2m anomaly Tropics MSSS (bulk number) ROC curves, ROC areas Precipitation anomaly Northern Extra-Tropics Reliability diagrams Southern Extra-Tropic Frequency histograms s Niño3.4 Index N/A MSSS (bulk number) ROC curves, ROC areas Reliability diagrams Frequency histograms Level 2 Parameters Verification Regions Deterministic Forecasts Probabilistic Forecasts T2m anomaly, SST grid point verification o MSSS and its three term ROC areas at each grid point anomaly n a 2.5° by 2.5° grid decomposition at each grid Precipitation anomaly point Level 3 Parameters Verification Regions Deterministic Forecasts Probabilistic Forecasts T2m anomaly, SST grid point verification o 3 by 3 contingency tables at ROC reliability tables at each anomaly n a 2.5° by 2.5° grid each grid point grid point Precipitation anomaly
Main Link
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Upgrading of the SVS
• Fig.: One of the level3 scores, based on 3X3 deterministic contingency tables • A new extreme event index has also been designed based on Gerrity Score.
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7 Some verification statistics
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Some verification statistics
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8 Some verification statistics
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Some verification statistics
Reliability Diagram, PREC, JJA (1983~2003) Reliability Diagram, T850, JJA (1983~2003)
ROC Curve, PREC, JJA (1983~2003) ROC Curve, T850, JJA (1983~2003)
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9 Some verification statistics
10% Significance 10% Significance
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Downscaled forecast provision
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10 Statistical Downscaling
1
0.8
0.6
Northern 0.4
Before Philippine 0.2 After
0
-0.2
-0.4
-0.6 12345678910AVE
Manila
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Statistical Downscaling : Precipitation
0.8
0.6
0.4
0.2 Before After 0
-0.2
-0.4
-0.6 12345678AVE
Bangkok
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11 Statistical Downscaling : Precipitation
Korea Station Skills
1
0.8
0.6 99% 0.4
0.2
Cor. Coeff. Cor. 0
-0.2
RAW MME -0.4 Downscaling -0.6
n n ju n in n u ju n u ju o ju n g n g n g o o g lj on a g n a j an e an n eo ng mi on choonge e n U e s o g s J in Inje eon n o y eup u namung eo an e k e h h onjuwonu osa n e n J o BuanImsilg heoe e e Gu neongSeoulc W h DaeJ Uls a Bu MokpoYeosu Icheo cheonch Boeun ye Bu mwon h h gdeok ch ch heongGeoje So lly g In SuC Se Daej PohangGu w Wando g r eumsan a nc g Ha o Uiseon g o Miryang Namhae a n Cheongju G Je Che N n G Yeongjuon nc w a SeogwipGanghwa Bo G Jeon Su a onGe Hapch g ChuncG Tongyeong Hon J MungyeongYe Sa Yangpyeong Seongsanpo Ye Dae Chupungnyeong Earlier, downscaling products succesfully developed for Thailand and the Philippines. Collaborative development also going on for Malaysia APEC Climate Center 23 APEC Climate Center
MME: Area-averaged JJA rainfall anomaly for Korea
4 COR=0.75 3
2
1 OBS 0 DSC -1
-2
-3
-4 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 Anomaly
6 COR=-0.21 4
2
OBS 0 RAW
-2
-4
-6 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 Anomaly
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12 MME: Verification skills for Korea Precipitation
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Real Time Downscaling Forecast for Korea 2008JJA PREC T2m
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13 Forecast Verification
Precipitation anomaly for AMJ 2008
Stational observation MME prediction Downscaling prediction
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Spatial Distribution of Skills (DJF) over Malaysia
Downscaled APCC-MME
Downscaled CCA-MME
RAW MME
CCA-SST (pure statistical model)
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14 Forecast Verification for Korea
2 y 1 0 -1 -2 -3 -4 Observation -5 Raw MME
Area-averaged anomal -6 Downscaling -7 Mar Apr May Jun 2008 Month
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APCC Climate Monitoring Products
• Provided since summer 2008 • Weekly / monthly / seasonal SST, temperature, OLR, rainfall, geopotential height at 500hPa, surface wind anomalies http://www.apcc21.net/climate/climate03_07.php • Current (monthly) indices for tropical Indo-Pacific monitoring http://www.apcc21.net/climate/climate03_09.php
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15 Experimental Global Drought Monitoring
• Experimental drought monitoring system set up using Standardized Precipitation Index (SPI; McKee et al. 1993) • SPI is calculated for multiple time scales: 1, 3, 6, 12 months • Summary maps of rainfall deficiency on the short term (1 to 3 months) and intermediate term (6 to 12 months) are also provided. • Datasets: Japanese 25-year ReAnalysis and Japan Meteorological Agency Climate Data Assimilation System
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Standardized Precipitation Index (SPI)
• Precipitation is quantified by transforming its distribution (usually fitted to a Gamma) into a standardized normal distribution on a equal a probability basis
1 x αˆ −1 − t Gamma function G(x) = ∫0 t e dt Γ( αˆ) Cumulative probability H(x) = q + 1( 1 − q)G(x) ⎡ c + c t + c t 2 ⎤ Standard normal random variable Z = ± t − 0 1 2 ⎢ 2 3 ⎥ ⎣ 1 + d 0 t + d 1t + d 2 t ⎦
Climatological Gamma Standard Normal Distribution Distribution
P(SPI<-1) = .1587 P(SPI>1) = .1587 Frequency
Precipitation -1 0 1 amount SPI 32 APEC Climate Center
16 Quality Check of JRA-25/JCDAS
• Result is encouraging, especially for the Asia Pacific region.
of SPI
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Quality Check of JRA-25/JCDAS
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17 Development of drought prediction system
drought prediction system
Observation MME prediction (JRA or NCEP/NCAR) (SCM)
variance corrected forecast*
continuous precipitation data
standardized precipitation index
drought prediction
(*MME variance is smaller than observation)
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Performance in 3-Month MME Forecast
SON 2007 “Weak La Niña-like tropical Pacific conditions “
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18 Performance in 3-Month MME Forecast
DJF 2007/08 “Cold winter in the northern portion of North America”
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Performance in 3-Month MME Forecast
Jan 2008 Severe snow storms hit the Middle East, central and eastern China
Observations 3 month lead (NDJ 2007 MME)
2 month lead (DJF 2007/08 MME) 1 month lead (JFM 2008 MME)
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19 Performance in 3-Month MME Forecast
Jan 2008 Severe snow storms hit the Middle East, central and eastern China
Observations 3 month lead (NDJ 2007 MME)
2 month lead (DJF 2007/08 MME) 1 month lead (JFM 2008 MME)
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Performance in 3-Month MME Forecast
Anomaly Pattern Correlation for DJF 2007/08 T850 Forecast
DJF 2007/08 Jan 2008 MMEs 0.8
0.6
0.4 Global 0.2
0
-0.2
-0.4
0.8
0.6
0.4 East Asia 0.2 (80-180E, 10-60N) 0
-0.2
-0.4
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20 Performance in 2008
JJA 2008
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Performance in 2008
Aug 2008
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21 Experimental 6-Month 1-Tier MME Prediction
Objective • To provide a longer and more reliable forecast
Status • First forecast for MAMJJA - Three models were available (FRCGC, UH and NCEP) - Development of the relevant additional software unique 6-month prediction (especially deterministic) • Second forecast for JJASON - Five models were available (FRCGC, UH, NCEP, SNU and POAMA) - Development of probabilistic prediction system for 6-month - Development of hindcast verification for deterministic and probabilistic
→ Started, Hindcast packages completed in August
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Experimental 6-Month 1-Tier MME Prediction
• Participating Models - FRCGC/Japan, SNU/Korea, UH/USA, NCEP/USA, and BMRC/Australia
Ensemble Institute AGCM Resolution OGCM Resolution Member Reference 2o cos(lat)x2o lon FRCGC ECHAM4 T106 L19 OPA 8.2 9 Luo et al. (2005) L31 SNU SNU T42 L21 MOM2.2 1/3o lat x 1o lon L32 6 Kug et al. (2005) UH Fu and Wang UH ECHAM4 T31 L19 1o lat x 2o lon L2 10 Ocean (2001) NCEP GFS T62 L64 MOM3 1/3o lat x 1o lon L40 15 Saha et al. (2005) The Bureau of ACOM2 Ocean Model 72 x 144 grid Daily Meteorology Colman et al. BMRC unified T47 L17 based on points for the Ensemble climate/NWP GFDL MOM2 (2002) model (BAM) physics grid Generation version 3.0d
FRCGC, SNU, and UH : 10 Variables (tsfc, prcp, mslp, ts2m, t850, z500, u200, v200, u850, v850) NCEP, BMRC: 11 variables (olr, prec, slp, sst, t2m, t850, u200, u850, v200, v850, z500)
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22 Recent Forecasts : 2008JJASON
2008JJA 2008SON T850
PREC
SST
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Predictions for MAM
(left) from 6 month 1-tier MME (right) APCC operational MME
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23 Comparison : Deterministic MME for 2008JJA
APCC Operational MME 6-Month 1-Tier MME
T850
PREC
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Comparison : Probabilistic MME for 2008JJA
APCC Operational MME 6-Month 1-Tier MME
T850
PREC
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24 Verification : Deterministic Hindcast Forecast
T850, 1983-2003
JJASON
JJASON
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Verification : Deterministic Hindcast Forecast
JJASON
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25 Verification : Deterministic Hindcast Forecast
JJASON
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Verification : Probabilistic Hindcast Forecast
APCC Operational MME (JJA) (JJA) 6-Month 1-Tier MME (SON) T850
PREC
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26 Verification : Probabilistic Hindcast Forecast
APCC Operational MME (JJA) (JJA) 6-Month 1-Tier MME (SON) T850
PREC
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Development of an in-house coupled prediction system
To develop an in-house coupled climate prediction system suitable for 12- month climate prediction by 2010
2008 Plans
Phase 1 ¾ Porting the CCSM3 (T85L26) to KMA/KISTI computer. ¾ Development of an initialization package by APCC. ¾ Simple coupled SST nudging. ¾ NCEP/CDC OISST (Reynolds, 1992).
Phase 2 ¾ Coupled climate run and validation. ¾ Retrospective 6-month forecast with November 1 initial conditions. ¾ 20 years and 10 ensembles.
Phase 3 ¾ 6-month forecast with November, 2008 initial conditions. ¾ 10 ensembles.
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27 In-House Coupled Model (CCSM3)
• Overview - Coupled model forecasts are superior to the stand-alone AGCM forecasts on seasonal scale, particularly in the monsoon region. - It is expected that APCC operational MME prediction can be improved through using 1-tier model predictions.
• Goals/Objectives - To develop an in-house coupled model based on NCAR’s CCSM3 that would be capable of joining 12-month lead time climate prediction
• NCAR’s CCSM3 (T85L26, gx1v3L40) -Coupled global climate prediction model -Atmos., ocean, land, and sea-ice connected by a flux coupler -Resolution : AGCM = 256 Lon X 128 Lat X 26 Level OGCM = 320 Lon X 384 Lat X 40 Level - Simulation Time : approx. 1year / 1day (64 CPUs)
APEC Climate Center
In-House Coupled Model (CCSM3)
Import of an ocean-atmosphere CGCM & climate simulation Development of initialization scheme & hindcast experiment
Porting of CGCM • CCSM3 (T85L26) Atmos. Model • Porting and testing (CAM3)
Radiation sst Climate simulation Development of wind • 20 year integration initialization package • Coupled SST nudging Coupler • NOAA/CDC SST Land Model Sea-IceIce Model Model (clm3) (cpl6) (csim5) Analysis and validation Hindcast experiment and analysis Radiation Sensitive test • Drift sst • Monsoon • Retrospective 6-month wind • ENSO forecasts with May1 IC • 20 years and 5 ens. Ocean Model (pop)
Recommendations for improvements CCSM3.0 Framework
APEC Climate Center
28 In-House Coupled Model (CCSM3) Performance for CCSM3 Free-run
APEC Climate Center
Development of initialization scheme for CGCM
Background
• APCC is trying to predict 6~12-month forecast using in-house CGCM • Initialization scheme is important for the seasonal forecasting in order to provide skillful forecast • Nudging method shows successful prediction of the ENSO events (Luo et al. 2005)
Goal
• development of initialization scheme based on nudging for CCSM3 • hindcast experiment using the initialization scheme • sensitivity of the predictions to factors such as initial condition, boundary condition
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29 Framework of Initialization & Forecast
Forced run Initialization Hindcast & forecast (11 years) by nudging 3~12-month
AGCM (1) (3) (4) OGCM (2)
1971 1982 Jan 1983Jan AGCM forcing(τ, Q) Coupled nudging Coupled run
(1) generate 2-hourly forcing (τ, Q) for OGCM using AGCM. Then, observed SST is required for AGCM. (2) forced run of OGCM using AGCM forcing (3) generate initial data for forecast using OBS by nudging (CGCM) (4) run forecast from the initial data (CGCM)
APEC Climate Center
Nudging Performance for CCSM3
APEC Climate Center
30 Preliminary results for Hindcast (1983 DJF)
I.C. : Nov 1st, 1983 SST Precipitation
Observation
CCSM3
APEC Climate Center
Preliminary results for Hindcast
Time series of hindcast SSTA from Nov 1982 to May 1983 Climatology : 20 years mean of free run
APEC Climate Center
31 Visitor of ADSS website
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total
2007 10 29 24 2 65
2008 30 38 164 214 181 86 1042 59 1814
Visitor of ADSS
1200 1042
1000
Inside Outside Total 800 (staff)
600 2007 58 7 65 2008 272 1542 1814 400 Total 330 1549 1879 214 164 181 200 86 29 24 30 38 59 10 2 0 Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
Count of 2007 Count of 2008
APEC Climate Center
Visitor of APCC website
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total 2006 87 1510 1320 925 824 637 5303 2007 843 616 849 815 751 1116 1843 1644 1461 1831 1602 1499 14870 2008 2785 2567 3409 4104 3450 3605 3234 1555 24709
Visitor of APCC website Inside Outside Total (staff) 5000 2006 1445 3858 5303 4000 2007 2570 12300 14870 3000 2000 2008 1544 23165 24709
1000 Total 5559 39323 44882 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2006 2007 2008
APEC Climate Center
32 Plans for 2009
Development of ISV prediction
6-month operational prediction since next summer
Designing of the ENSO/ENSO Modoki/IOD indices for 1-tier MME system to facilitate the prediction of these events.
Experimental 6-month downscaling
Further development of in-house coupled model
Drought prediction
other applications (?)
APEC Climate Center
Plans for 2009
Development of extreme event prediction
6-month operational prediction since next summer
6-month downscaling
Further development of in-house coupled model
APEC Climate Center
33 Thanks for the attention
APCC New Building (To be completed in Dec. 2008)
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34