THE NWP “BREAKTHROUGH” FOR CLIMATE ANALYSIS CENTER MONTHLY PREDICTIONS IN 1981
Center Report from CMA Short, Medium-range NWP Xueshun Shen Center for Numerical Weather Prediction...
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Transcript of Center Report from CMA Short, Medium-range NWP Xueshun Shen Center for Numerical Weather Prediction...
Center Report from CMA
Short, Medium-range NWP
Xueshun ShenCenter for Numerical Weather Prediction
China Meteorological Administration
WGNE, Tokyo, Japan, 18-22 Oct. 2010
Outline
• Short & Medium-range NWP systems– Current status of operation system– New implementation– GRAPES_GFS: improvement toward
operation– Research activities
• New organization for NWP development and operation
CMA headquarter decided:
Freeze the current operational global NWP model: TL639L60Put most of the resources to improve and develop the GRAPES system
Big transition of NWP-related policy
Last WGNE presentation
Global SpectralModel
(TL639L60)
Meso Scale Model
(GRAPES_Meso)
10dayEnsemble(TL213L31)
Typhoon deterministic &
Ensemble forecast
Forecast range
Short- and Medium-range
forecast
Rainfall forecastShort-range
forecast10day forecast Typhoon forecast
Forecast domain Global East Asia
(8340km x 5480km) Global
Horizontal resolution TL639(0.28125 deg) 15km T213(0.5625 deg)
Verticallevels / Top
600.1 hPa
3110hPa
3110 hPa
ForecastHours
(Initial time)
240 hours(00 、 12 UTC)
72 hours(00, 12UTC)
240 hours(00 、 12 UTC)15 members
120 hours(00, 06, 12, 18
UTC)120 hours
(00 、 12 UTC)15 members
Initial Condition
Global Analysis(NCEP GSI)
GRAPES_3DVAR
NCEP SSI + Vortex relocation and Intensity adjustment
with ensemble perturbationsPerturbations are produced by
Breeding-method
Current NWP Operational models in CMA
1990-2010 年 NMC全球数值预报模式北半球500hPa高度场距平相关系数
T 500hPa系列模式北半球 高度预报月平均距平相关系数演变图
0
0. 2
0. 4
0. 6
0. 8
1
1. 2T42
9001
9007
9101
9107
9201
9207
9301
9307
9401
9407
9501
T63 9
507960
1960
7970
1T10
6 9707
9801
9807
9901
9907
00'01
00'07
01'01
01'07
02'01
02'07
T213
301307 401 407 501 507 601 607 701 707 801
T639
807901 907 1001
时间
距平相关
系数
48h
96h
144h
Evolution of ACC of 500 hPa Z
T42 T63 T106 T213 T639
20021990 2008
forecast verification 200909-201008 12UTCgeopotential 500hPa
Correlation coefficent of forecast anomalyNH Extratropics Lat 20.0 to 90.0 Lon -180.0 to 180.0
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1 2 3 4 5 6 7 8 9 10
Forecast days
AC
C
T639JAPANECMWF
Performance of T213 medium-range ensemble forecastZ500 ACC (average for 20090901-20100831 :NH)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1 2 3 4 5 6 7 8 9 10Forecast days
AC
C
T213 Ensemble meanT213 Cntl. (0.5625°)
T639 (0.28125°)
0
50
100
150
200
250
300
350
400
450
JMA CMA JMA CMA JMA CMA EC
2007 2008 2009
Mea
n T
rack
err
ors(
km)
24h48h72h
TC Mean Track Errors from JMA, CMA and EC global models
GRAPES
WRF
Performance of operational GRAPES_Meso
New Implementationfor pre-operational test
GRAPES_MESO V3.0 with 4DVARGRAPES_MESO V3.0 with 4DVAR
Model:Model: GRAPES_MESO V3.0GRAPES_MESO V3.0Resolution:Resolution: 15 km (502x330), 31 levels 15 km (502x330), 31 levelsTime Step:Time Step: 300 seconds 300 seconds
Analysis System: GRAPES-4DVARAnalysis System: GRAPES-4DVAROuter loop resolution:Outer loop resolution: The same The same
resolution as the modelresolution as the modelInner loop resolution: Inner loop resolution: 45 km (167x111), 31 45 km (167x111), 31
levelslevelsPhysics process:Physics process: LSP; MRF PBL; CUDU LSP; MRF PBL; CUDU
convectionconvectionOuter loop:Outer loop: 1 iteration 1 iterationObs: TEMP, SYNOP, AIREP, SHIPSObs: TEMP, SYNOP, AIREP, SHIPSAssimilation Window:Assimilation Window: [-3, 0] [-3, 0]Analysis Time:Analysis Time: 00UTC and 12UTC 00UTC and 12UTCBackground Fields:Background Fields: T TLL639L60 12-hours 639L60 12-hours
forecastforecastForecast Range:Forecast Range: 48 hours 48 hours
ObservatioObservation Datan Data
Data Data ProcessingProcessing
GRAPES-4DVARGRAPES-4DVAR
GRAPES-ModelGRAPES-Model
BackgroundBackground
Analysis Analysis FieldsFields
ForecasForecastt
TTLL639L60 639L60
ForecastsForecasts
SiSi
Since Aug.2010
1-month averaged Ts score of 24 hour precipitation 1-month averaged Ts score of 24 hour precipitation forecast over whole Chinaforecast over whole China
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
1 2 3 4
3DVAR
4DVAR
LightLight ModerateModerate HeavyHeavy TorrentialTorrential
48-hour accumulated precipitation48-hour accumulated precipitation00Z03JUL2009-00Z04JUL200900Z03JUL2009-00Z04JUL2009
Initial time: 00Z02JUL2009Initial time: 00Z02JUL2009
Obs CTRL
3DVAR 4DVAR
dQv and w difference between 3DVAR and 4DVARdQv and w difference between 3DVAR and 4DVAR
Setup of GRAPES global forecast system since Jul.
2007• GRAPES_GFS1.0 : medium-range global forecast
– GRAPES_Global 50km L36 with model top at 10 hPa
– GRAPES_3DVAR at 1.125 degree (global version)
– 6-hourly cycle
– 240 hour forecast (12UTC)
– Assimilated Obs.
GTS conventional data
NOAA15 、 16 、 17
METEOSAT-9 & MTSAT AMV
MODIS polar AMV
Presented in last WGNE
GRAPES_GFS 1.0global model
• SISL dynamical core with mass fixer• Physics
– Radiation: RRTMG LW(V4.71)/SW(V3.61)– Cumulus: Simplified Arakawa Schubert with modified
entrainment and detrainment rates– Grid-scale precipitation: WSM-6– Cloud: Xu & Randall diagnostic cloud– Land surface: CoLM – PBL: Modified Hong & Pan nonlocal PBL
– Gravity wave drag: McFarlane 1987
GRAPES_GFS 1.0global 3DVAR
• Incremental analysis• Digital filter• Recalculated background error covariance –
NMC method • 1.125x1.125 resolution, 17 standard pressure
levels• Bias correction scheme of satellite radiances
based on simple linear regression (Harris and Kelly,2001): (1) 1000-300 hPa thickness, (2)200-50 hPa thickness.
Efforts in improving the forecast skill of GRAPES_GFS
-toward operation-• Improve accuracy of initial values: data assimilation
– ATOVS(NOAA-18,19,METOP,FY3)– GPS Reflectivity (COSMIC)– AIRS– IASI
• Improve model performance– Improve the accuracy of finite difference scheme, especially, for PGF
calculation– Hybrid vertical coordinate: from terrain-following to terrain-following & Z– Tuning of physical processes
• Radiation: RRTMG• Land surface: SLAB to CoLM• GWD• SSO replaces the effective roughness length• Cumulus scheme tuning• Radiative energy budget (cloud-radiation)
– Improve the forecast of synoptic evolution and accuracy of local weather elements, particularly those which have large impact on East Asian weather
CAMS/CMA
Time series of Innvoationand Residual: Height(Sonde)N.H.
500hPa
100hPa
850hPa
CAMS/CMA
Using EC analysis as Reference(NCEP,GRAPES)500hPa
old
new
Zonal mean temp. biasJJA (3d fcst.)
By introducing the new radiationScheme: RRTMG
New cloud cover parameterization
New cloud water path parameterization
Radiative effect of fractional cloud
Radiative effect of cloud inhomogeneity
Cloud-radiation interaction Improvement
Original scheme: binary cloudcloud=1 , when QC+QI >1.0e-6cloud=0 , when QC+QI <1.0e-6effective cloud drop radius: liquid 10µm 、 ice 80µm
New scheme Liang and Wang ( 1995)Cloud cover: Combine Slingo and Slingo ( 1991 ) and Kiehl et al. ( 1994 ) ; 4 cloud genus : convective cloud, anvil cirrus, inversion stratus and stratiform cloud. Fractional cloud cover and vertical cloud overlapping are consideredeffective cloud drop radius: liquid cloud: Savijarvi 1997 ice cloud: Kiehl et al. 1996
Cloud cover parameterization
Cloud cover compared with ISCCP satellite data
Zonal mean total (TCC), high (HCC), middle (MCC) and low (LCC) cloud cover (%) of the ISCCP data (dashed) and the 5th day forecast by GRAPES using the ORG (thin solid) and NEW (thick solid) cloud scheme.
Using ISCCP Simulator
CERES ISCCP ORG NEW
Surface radiation balance (W m-2)
Upwelling LW 400 405 404 408
Downwelling LW 353 357 334 365
Net LW -47 -48 -71 -44
Upwelling LW CRF -- 2 0 1
Downwelling LW CRF -- 30 16 32
Net LW CRF 31 28 15 31
Upwelling SW 22 17 25 21
Downwelling SW 184 177 231 182
Net SW 162 160 206 161
Upwelling SW CRF -- -5 -3 -7
Downwelling SW CRF -- -57 -27 -71
Net SW CRF -42 -52 -24 -64
Comparison of surface radiation budget
Errors reduce 14-47 1-8
Improvement on radiation budget
TOA radiation balance (W m-2)
OLR 244 240 278 233
Net LW CRF 27 27 3 35
Upwelling SW 96 100 66 106
Net SW 235 231 265 225
Net SW CRF -48 -50 -21 -62
CERES ISCCP ORG NEW
Comparison of TOA radiation budget
Errors reduce from 29-34 3-8
Comparison of net flux
Statistical verification
Low-level southerly bias
GRAPES 3-day forecast
To mitigate southerly bias:• Introduce mountain blocking effect in GWD parameterization• Introduce small scale orography-induced form drag
24/48hr V-wind difference (20090701-0720)
By introducing the mountain blocking effect in GWD parameterization
Partly alleviated the low-levelsoutherly bias.
0 40 80 120 160 200
t(h)
-1
0
1
2
3
bia
s/r
mse(m
/s)
Impact of SSO on low-level wind prediction
Partly alleviated the low-levelsoutherly bias.
New version of GRAPES_GFS
• GRAPES_GFS1.2.0 : medium-range global forecast– GRAPES_Global 50km L36 with model top at 10 hPa
– GRAPES_3DVAR at 1.125 degree
– 6-hourly cycle
– 240 hour forecast (00,12UTC)
– Assimilated Obs.• GTS conventional data• NOAA15 、 16 、 17 、 18 、 19• METOP-2• AIRS• FY-3 radiance• METEOSAT-9 & MTSAT AMV• MODIS polar AMV• COSMIC Refraction
More satellite data assimilated
Improved model performance
forecast verification 200906-200908 12UTCgeopotential 500hPa
Correlation coefficent of forecast anomalySH Extratropics Lat -20.0 to -90.0 Lon -180.0 to 180.0
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1 2 3 4 5 6 7 8
Forecast days
AC
C
T639
GRAPES
forecast verification 200906-200908 12UTCgeopotential 500hPa
Correlation coefficent of forecast anomalyNH Extratropics Lat 20.0 to 90.0 Lon -180.0 to 180.0
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1 2 3 4 5 6 7 8
Forecast days
AC
C
T639
GRAPES
grapes
operation
N. Hemsiphere
S. Hemisphere
ACC 500hPa ZJJA 2009
Near future upgrade activities
• Global GRAPES_3DVAR– Arakawa-A & pressure level to Model grid space analysis– RTTOV: RTTOV7->RTTOV93– VarBC– More satellite data: IASI, GRAS etc.
• GRAPES global model– Hybrid vertical coordinate– Increase the vertical resolution– Conservative scalar SL advection: CSLR– Improve SL numerics
• SETTLS: Stable extrapolating two-time-level semi-Lagrangian scheme
– Continuous improvement of model physics
Research Activities
• More satellite data• Cloud microphysics parameterization• Global GRAPES-4DVAR• Yin-Yang GRAPES
– To avoid polar singularity problem– More homogeneous grid size
Progress of GRAPES Yin-Yang gridThe Helmholtz equation of GRAPES in the Yin-Yang overset grid are solved.The transplant of the whole GRAPES dynamical core is finished. However,some bugs exist and it need to be debuged in the next step.
2 2 H Helmholtz equation:
• Finish the coding of tangent linear & adjoint model
• Finish the accuracy check
Development of Global GRAPES_4DVAR
a F(a)10-1 0.999333329810-2 1.002537421210-3 1.134534128310-4 1.430711269510-5 1.000000206510-6 1.000000095910-7 0.999999987810-8 1.000001025810-9 1.000015335910-10 1.000092107110-11 1.000736213010-12 1.0499615795
)(M
)()()(
Xa
XMXaXMaF
1)(lim0
aFa
wleft = 362468.822258871398
wright = 362468.822258874832
XXXX T )),(M(M)(M)(M ,Adjoint code check
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