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MJO Prediction Evaluation and Ensemble Developments in Beijing
Climate Center (BCC)
REN Hongli WU Jie Zhao Chongbo WU Yujie
National Climate CenterLaboratory for Climate Studies
China Meteorological Administration
MJO Workshop
Outline
• 1 MJO prediction skill in BCC-AGCM2/CSM1.2
• 2 Initialization hindcast experiments
• 3 MJO operational products in BCC
• 4 Conclusion and discussion
Model versions Model components Resolutions
DERF2.0 BCC-AGCM2.1Atmos:T106L26,Top:2.19hPaOcn:weakly persistentSST
BCC-CSM1.2
BCC-AGCM2.2BCC-AVIM1MOM4-L40v2
SIS
Atmos:T106L40,Top:0.5hPaOcn:1/3o in30S-30Nand1/3-1o in
30-60N/S,and1oinhighlatitudes
BCCModelsforExtendRangeForecast
Atmosphere(BCC_AGCM)
Coupler
Sea Ice(SIS)
Ocean(MOM4_L40)
Land(BCC_AVIM)
Climate System Model (BCC_CSM) Daily initialization4 members
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
Cor
rela
tion
Forecast Lead Time (Days)
BCC_AGCM2BCC_CSM1.2ENSEMBLEEMSEMBLE-Lag2
1.1 MJO prediction skill in BCC-AGCM2/CSM1.2
Based on bivariate RMM Index
(Hindcast period: 1994-2013)
Correlation Skill
BCC_AGCM2: 16 daysBCC_CSM1.2: 16 daysEnsemble (8 members): 19 daysEnsemble–lag 2 (24 members): 20 days
Composite lon-lead time sector of U850(contour) and OLR(shaded)
1)Eastward propagation is faster
Phase 2 Phase 4
OBS
FCS
1.2 MJO propagation characteristics in BCC-AGCM2
2)Encounter Maritime Continent barrier
1.3 Impacts of MJO on extratropical weather in BCC_AGCM2MJO-AO/NAO
(By ZUO Jingqing)
(Y)
(Y)
(Y)
(Y)
(N)
(N)
(Y)
(Y)
2 Initialization hindcastexperiments
Problem: 1)The direct replacing scheme may cause dynamic inconsistent2) Lack of moisture(q) initialization
Current Initialization of BCCCSM1.1m:Replacing by NCEP1/FNL data (U,V,T,Ps) on every step
Solution:Modify initialization scheme andincluding moisture variable (q)
The regression MJO moisture structure
MJO has a clear zonal asymmetry vertical moisture structure--Westward tilted
(Tim, 2014)
2.1 Modify initialization scheme (including Q)
OLD
Replacing(NDG.RPLC)
Implicit Nudging(NDG.UVT)
Implicit Nudging(NDG.UVTQ)
ENSEMBLE
NEW
The NDG.UVTQ scheme is slightly better !The ensemble of different initialization could extend the prediction skill for 3 days !
Experiment Design: 2001-2010 (10 years) 12 months (total 120 samples)
0
0.5
1
1.5
2
0 2 4 6 8 10 12 14 16 18 20 22 24 26FORECAST LEAD DAY
b) RMSE
CTLNDG.UVTNDG.UVTQENSEMBLE
00.10.20.30.40.50.60.70.80.9
1
0 2 4 6 8 10 12 14 16 18 20 22 24 26FORECAST LEAD DAY
a) COR
CTLNDG.UVTNDG.UVTQENSEMBLE
The regression MJO moisture structure during the initialization
More realistic moisture structure in NDG.UVTQ scheme !
Conclusion:Ø The new implicit nudging scheme ameliorate MJO moisture
structure during model initialization.Ø The ensemble of various initialization scheme can improve the
MJO prediction significantly.
MJO Prediction skill dependence on
Month Phase
3 MJO operational products in BCC
3.1 ISV/MJO Prediction System (IMPRESS)
ISV/MJO Monitoring & Prediction System (IMPRESS)
Real-time predictions of ISV/MJO indices & reconstructed fields
ISV/MJO-based extended-range forecasting & application
BCC-AGCM2.0prediction application
CMA T639 & FY-3B satellitereal-time data
BCC-CSM1.1mimproved version
prediction
ISV-based MJO STPM statistical
prediction
Real-time monitoring ISV/MJO indices & fields
OBS FCS
Operational products – RMM IndexDaily Real-time Update (latest result):http://cmdp.ncc-cma.net/Monitoring/moni_mjo.php
BCC_AGCM2 BCCCSM1.2 T639 STPM
Operational products - Diagnose
U850-Time V850&OLR
3.2 Forecasting Case
Red solid line:ObservationColor dash line:every 5 day forecast
Large MJO event of Mar 2015
RMM Monitoring and forecasting U850 forecasting and re-construction(2nd Mar)
WWB
Successfully forecast the WWB 2 weeks ahead – Which has great impact on El Nino
• Conclusion:
a) The MJO prediction skill of BCC-AGCM2 and BCC_CSM1.2 both reach to 16days, and the ensemble could extend the skill to 20 days. The impacts of MJO on extratropical weather can be described to some extents.
b) The prediction skill has been extended for about 3 days by modifying initialization scheme and ensemble perturbations in the limited case hindcastexperiments.
c) The IMPRESS1.0(ISV/MJO Monitoring and Prediction System)is capable of providing reasonable MJO forecasting products at least 2 weeks ahead.
• Discussion:a) The initialization experiments samples are limited, need more experimentb) The BCCCSM model conceives the similar prediction skill with AGCM model
rather than extend the skill, we need check the air-sea coupling and other physics process.
4 Conclusion and Discussion
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MJO single-member and ensemble-mean Predictability Estimate
Ø The predictability limit is much longer
than the current prediction skill
Ø The model still has significant potential
room to improve its MJO prediction
skill if we develop better initialization
and ensemble strategies
Discussion – MJO predictability Estimate (BCC_AGCM2)
Error
Signal
(Neena, etal., 2014)
1416
26
42
0
5
10
15
20
25
30
35
40
45
single ensemble
days
prediction skillPredictability Estimate
Reference:Wu J, Ren H L, Zhao C B, et al. MJO Prediction Skill, Predictability, and Teleconnection Impacts in the Beijing Climate Center Atmospheric General Circulation Model. Dynamics of Atmospheres and Oceans, 2016, doi:10.1016/j.dynatmoce.2016.06.001Ren H L, Wu J, Zhao C B, et al. MJO ensemble prediction in BCC-CSM1.1(m) using different initialization schemes. Atmospheric and Oceanic Science Letters, 2016, 9(1): 60-65.
0.48
0.49
0.5
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0.52
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corr
elat
ion
coef
ficie
nt
Lag Time
COR at Day 20