Grapes model research progresses at cma
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GRAPES Model Research Progresses at CMA. Chen D.H., Wang J.J., Shen X.S. et al. Numerical Weather Prediction Center China Meteorological Administration with thanks to our colleagues who contribute to the presentation. (The 4th THORPEX-ASIA Science Workshop and ARC-8 Meeting

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Grapes model research progresses at cma

GRAPES Model Research Progresses at CMA

Chen D.H., Wang J.J., Shen X.S. et al.

Numerical Weather Prediction Center

China Meteorological Administration

with thanks to our colleagues who contribute to the presentation

(The 4th THORPEX-ASIA Science Workshop and ARC-8 Meeting

30Oct.~3 Nov., 2012, Kunming, China )


Outline

Outline

  • 1 Current Operational NWP Systems

  • 2 Efforts for improving GRAPES_GFS

  • 3 Progresses in GRAPES_VAR

  • 4 Implementation of GRAPES_TYM

  • 5 High resolution modeling activities

  • 6 Future Plan


Grapes model research progresses at cma

Data assimilation group

Ensemble prediction Group

Dynamic process group

Typhoon prediction group

Parallel computing group

Observation data quality control group

Physical process group

Post process and products development group

Regional model group

System pre-operational test group

Model version manage and information technology group

Numerical Weather Prediction Center of CMA

Director: Dr. WANG Jianjie

Chief Engineer: Dr. CHEN Dehui

Deputy-directors:

Dr. GONG Jiandong and Dr. SHEN Xueshun

System & Operation Division

General Office

R&D Division

Model verification group

The restructured organization of Numerical Prediction Center


1 current operational nwp systems at cma

1 Current Operational NWP Systems at CMA


Grapes model research progresses at cma

Current NWP Operational System in NMC

In general, there were no big changes in the operational NWP systems


Grapes tcm at shanghai typhoon institute for east c s

GRAPES_TCM at Shanghai Typhoon Institute for East C.S.


Grapes model research progresses at cma

Fig: Topography of the domain of GRAPES_TCM

  • Configuration

    • Domain: E90º~E170º,N0º~N50º

    • Hor. Res.: 0.25ºx0.25º

    • Grids: 321x201

    • V. res.: 31(ztop: 35000m)

  • Physics

    • Cumulus:KF-eta

    • PBL: YSU

    • Micro: NCEP cloud3

    • LSM: SLAB scheme

    • Radia.: RRTM scheme

(From Wang et al., 2010)


Assessment of tc forecast methods

Assessment of TC forecast methods

  • TRaP: extrapolating method based satellite-estimated precipitation

  • TAPT: tropical cyclone precipitation analogue method

  • GRAPES_TCM: numerical forecast

(From Wang et al., 2010)


Evolution of yearly mean track errors

Evolution of yearly mean track errors

hrs

hrs

Bogus initialization + cumulus schemes

(From Wang et al., 2012)


Grapes tmm at guangzhou tropical meteor institute for s c s

GRAPES_TMM at Guangzhou Tropical Meteor. Institute for S. C. S.


Domains of grapes tmm

Domains of GRAPES_TMM

0.12o

0.36o

0.03o

GRAPES_TMM(Tropical Meteorological Model), which is a three-nested model system

(From Wan et al., 2010)


Grapes model research progresses at cma

+ 5d Tro. weather forecast

+ T. Cyclone forecast

+ SST, sea flow forecast

GRAPES_TMM

(0.36o)

MOM-sea flow model

+ 36 hrs Meso-scale forecast

+ S.C. fine w. forecast

+ sea waves, surge forecast

Storm surge

GRAPES_TMM

(0.12o)

Sea waves

CHAF-1h-cyc

+ hourly rapid cycling anal.

+ 1~3 hrs nowcast

+ 3~12 hrs sort-term forecast

GRAPES_TMM

(0.03o)

SWIFT-nwcst

Radar-extrap.

Since 2003, GZ began to operationally implement GRAPES_3DVAR, and then GRAPES_Meso for establishment of GRAPES_TMM, which is a three-nested model system:

Global model

(From Wan et al., 2010)


Grapes model research progresses at cma

Evolution of Yearly Mean Track Errors

48 hrs F.

24 hrs F.

TL

Grapes

DAS/optimal use of data+ cumulus/PBL schemes

Mean Track errors2012

24h 48h 72h

96.5 km 176.7km 235.6km

(From Chen et al., 2012)


Grapes model research progresses at cma

Obs.

Initial time: 00Z21June2012

F. length: 48hrs

(From Chen et al., 2010)

GRAPES_TMM


Grapes model research progresses at cma

Obs.

Initial time: 00Z22June2012

F. length: 48hrs

(From Chen et al., 2010)

GRAPES_TMM


Grapes model research progresses at cma

Complicated Track of Prapiroon-2012

(From Chen et al., 2012)


Grapes model research progresses at cma

Inter-comparison to ECMWF, JMA, T639 and GRAPES_TMM (Initial Time: 12UTC, 00UTC)

(From Chen et al., 2012)


Implemented grapes meso forecast system

ImplementedGRAPES_Meso forecast system

  • GRAPES_Meso: operation in NMC

  • GRAPES_RUC: quasi-operation in NMC

  • GRAPES_TCM: operation in Shanghai I.

  • GRAPES_TMM: operation in Guangzhou I.

  • GRAPES_SDM: operation in CAMS

Extended to GRAPES_HMM: Basin flooding height and volume Prediction

  • GRAPES Model

  • GRAPES_VAR


Grapes model research progresses at cma

Prediction of 6hrs precipi. accumulated

Obs.

Obs.

GRAPES prediction

Estimated on hydro. stat

(Flooding height and volume; Initial time at 00UTC, 29th August, 2009.

from Wang and Chen, 2010)

(From Wang et Chen, 2012)


2 efforts in improvements of grapes gfs

2 Efforts in improvements of GRAPES_GFS


Flow chart of grapes gfs

Sat. data

First Quess

Flow chart of GRAPES_GFS

Pre-Processing

Cycling

Assimilation

and Forecast

GRAPES_3DVAR

Quality Control

Initial F.

Conventnl. data

Digital Filter

Pre-Processing

10 d forecast

GRAPES_GFS

Quality Control


Efforts in improving the forecast skill of grapes gfs toward operation

Efforts in improving the forecast skill of GRAPES_GFS-toward operation-

More satellite data

ATOVS(NOAA-19,METOP,FY3)

AIRS

IASI

Assimilation from pressure level to model grid space

Improve model performance

The dynamic core refinement: conservation issue

Hybrid vertical coordinate: from terrain-following to terrain-following & Z

Increase the vertical resolution and model top lift-up

Tuning of physical processes

Land surface: CoLM

GWD

SSO

Microphysics + fractional cloud treatment

Cumulus scheme tuning

cloud-radiation interaction issue

(From shen et al., 2012)


Grapes model research progresses at cma

GRAPES Global Forecast System(pre-operational)

S. Hemis.

N. Hemis.

GRAPES-GFS 2011

GRAPES-GFS 2011

S. Hemis.

N. Hemis.

reforecasts for 200906~200908

(From shen et al., 2012)


3 progresses in grapes var

3 Progresses in GRAPES_VAR


Grapes model research progresses at cma

Milestone of GRAPES variational data assimilation system

2001

Serial regional P3DVAR using pressure coordinate

2005

2005

Serial global P3DVAR

Serial regional M3DVAR using height-based terrain following coordinate

2008

2009

Parallel global P3DVAR

Serial regional 3DVAR operation running

2009

2005

2010

Quai-operation running

Serial regional 4DVAR

Serial global M3DVAR

2010

2010

Black: developed

Blue: in progress

Orange: Operation

Red: in the future

Serial global 4DVAR

Paral. Reg. M3DVAR/4DVAR

2013

Parallel global 4DVAR

(From Gong et al., 2012)


Grapes model level analysis grapes m3dvar and pressure level analysis grapes p3dvar

GRAPES model level analysis (GRAPES_M3DVAR) and pressure level analysis (GRAPES_P3DVAR)

(From Gong et al., 2012)


Grapes model research progresses at cma

OBS

OBS

OBS

forward integration using non-linear model at the higher resolution

outer loop

observation increments

observation increments

observation increments

cost function J

forward integration using tangent-linear model at the lower resolution

inner loop

forcing term

forcing term

forcing term

backward integration using adjoint model at the lower resolution

minimization process

GRAPES 4DVAR

analysis incrementδx

analysis results

(From Zhang et al., 2012)


1 month running

Since Aug.2010

1-month running

GRAPES_MESO V3.0 vs 4DVAR

Model:GRAPES_MESO V3.0

Resolution: 15 km (502x330), 31 levels

Time Step: 300 seconds

Analysis System: GRAPES-4DVAR

Outer loop resolution: The same resolution as the model

Inner loop resolution: 45 km (167x111), 31 levels

Physics process: LSP; MRF PBL; CUDU convection

Outer loop: 1 iteration

Obs: TEMP, SYNOP, AIREP, SHIPS

Assimilation Window: [-3, 0]

Analysis Time: 00UTC and 12UTC

Background Fields:TL639L60 12-hours forecast

Forecast Range: 48 hours

(From Zhang et al., 2012)


Grapes model research progresses at cma

Light

Heavy

Torrential

Moderate

1-month averaged Ts score of 24 hour precipitation forecast over whole China

(From Zhang et al., 2012)


Grapes model research progresses at cma

Flow Chart of Cloud Analysis Scheme

Data used: (1)NWP background; (2)Doppler Mosaic (3)reflectivity data; (4)sounding data collected per minute vertical interval; (5)surface obs; (6)Sat TBB; (7)Sat cloud total amount

(From Zhu et al., 2012)


Result of cloud cover

Result of Cloud Cover

background

used Surface data

used satellite tbb

used satellite cta

increment

used radar reflectivity

(From Zhu et al., 2012)


Grapes model research progresses at cma

3h forecast

With cloud analysis

Without cloud analysis

observation

6h forecast

12h forecast

(From Zhu et al., 2012)


Grapes model research progresses at cma

The first hour precipitation 12:00-13:00

Hourly accumulated precipitation

Hourly accumulated precipitation

Without cloud analysis

OBS

With cloud analysis

Hourly accumulated precipitation

(From Zhu et al., 2012)


Grapes model research progresses at cma

6h forecast composite reflectivity

Without cloud analysis

With cloud analysis

Radar OBS

(From Zhu et al., 2012)


4 implementation of grapes tym

4 Implementation of GRAPES_TYM


Grapes model research progresses at cma

4.1 Quasi-operational implementation in NMC

(From Ma et al., 2012)


Grapes model research progresses at cma

GRAPES_TYM

(From Ma et al., 2012)


Development of grapes tym for typhoon intensity forecast

Development of GRAPES_TYM for Typhoon intensity forecast

Track error

Minimum SLP error

Maximum V10m error

Mean track errors of GRAPES_TYM to GRAPES_TMM、GRAPES_TCM

(From Ma et al., 2012)


Grapes model research progresses at cma

Case of 2012-13 KAITAK

(From Ma et al., 2012)


Grapes model research progresses at cma

Case of 2012-13 KAITAK

(From Ma et al., 2012)


Grapes model research progresses at cma

Case of 2012-13 KAITAK

(From Ma et al., 2012)


Grapes model research progresses at cma

Case of 2012-11 HAIKUI

(From Ma et al., 2012)


Grapes model research progresses at cma

Case of 2012-11 HAIKUI

(From Ma et al., 2012)


Grapes model research progresses at cma

Case of 2012-11 HAIKUI

(From Ma et al., 2012)


Grapes model research progresses at cma

Regional air-sea

Coupled model

Atmosphere

Ocean

Wind stress

Heat flux

Water flux

GRAPES_TYM

(0.15*0.15)

Regional

ECOM-si

(0.25*0.25)

Coupler

(Oasis 3.0)

SST

Initial conditions/

Lateral boundary

condition

GFS

Initial conditions/

boundary condition

Global HYCOM

4.2 The Coupled Typhoon-Ocean Model

(From Sun et al., 2012)


Grapes model research progresses at cma

Model domain

ECOM:

Horizontal resolution: 0.25°x 0.25°

Domain:104°E~145°E, 8°N~43°N

Provided:SST

GRAPES:

Horizontal resolution : 0.15°x 0.15°

Domain:100°E~150°E, 5°N~45°N

Provided: wind stress, solar flux, heat flux, water flux;

Fluxes are exchanged every 360s.

(From Sun et al., 2012)


Grapes model research progresses at cma

O

A

O

A

Oasis3

O

A

O

OASIS3 coupler

OASIS:OceanAtmosphereSeaIceSoil

---------Developed since 1991 in CERFACS

  • performs:

    • synchronisation of the component models

    • coupling fields exchange and interpolation

    • I/O actions

  • External library and module used:

  • NetCDF/parallel NetCDF

  • libXML, mpp_io, SCRIP

  • MPI1 and/or MPI2

(From Sun et al., 2012)


Sst forecasted by the coupled model typhoon muifa

SST forecasted by the coupled model ---Typhoon Muifa

NCEP AVHRR + AMSR-E SST analysis

at 08/08/11, 00UTC

72 hour forecasted SST by the coupled model

Initialized at 00UTC 05 AUGUST, 2011

  • The coupled model reproduces the sea surface cooling that

  • is closed well to the analysis.

(From Sun et al., 2012)


Typhoon muifa impact of coupling

Typhoon Muifa – impact of coupling

Tropical Cyclone Muifa (2011)

INITIAL TIME 00:00 UTC, 5 August 2011

Black –observation

Red-Uncoupled model

Green-Coupled model

  • Too strong in GRAPES_tym

  • Coupling weaken the intensity

(From Sun et al., 2012)


Forecast verification for muifa number of cases 21 21 19 17

Forecast verification for MUIFA Number of cases (21, 21,19,17)

(From Sun et al., 2012)


Typhoon muifa intensity forecast

Typhoon MUIFA intensity forecast

Minimum sea level pressure forecast

GRAPES_tym

Minimum sea level pressure forecast

Coupled model

Maximum wind forecast

GRAPES_tym

Maximum wind forecast

Coupled model

(From Sun et al., 2012)


Typhoon sinlaku impact of coupling

Typhoon SINLAKU – impact of coupling

Tropical Cyclone SINLAKU (2008)

INITIAL TIME 12:00 UTC, 12 September 2008

NCEP AVHRR + AMSR-E SST analysis

at 15/09/08, 00UTC

  • Too strong in GRAPES_TYM model

  • Coupling weaken the intensity

(From Sun et al., 2012)


Forecast verification for typhoon sinlaku number of cases 21 21 19 17

Forecast verification for Typhoon SINLAKUNumber of cases (21, 21,19,17)

(From Sun et al., 2012)


Forecast verification of nine tc in 2011 number of cases 72 72 56 56 49 44 44

Forecast verification of Nine TC in 2011 Number of cases (72,72,56,56,49,44,44)

(From Sun et al., 2012)


Intensity forecast of nine tc in 2011 number of cases 72 72 56 44

Intensity forecast of Nine TC in 2011Number of cases (72,72,56,44)

Minimum sea level pressure forecast

Coupled model

Minimum sea level pressure forecast

GRAPES_tym

Maximum wind forecast

GRAPES_tym

Maximum wind forecast

Coupled model

(From Sun et al., 2012)


5 high resolution modeling activities

5 High resolution modeling activities


5 1 high resolution modeling activities at cma based on grapes meso

5.1 High Resolution Modeling Activities at CMABased on GRAPES_Meso

Recent activities

  • Vertical coordinate from terrain-following Z to hybrid coordinate (Schar, 2002)

  • Inclusion of thermal expansion effect in continuity equation

  • Improve the interpolation accuracy in physics-dynamics interface

  • Refinement of 2-moment microphysics scheme

  • Some bug fix in land surface scheme

  • Refinement of back ground error covariance in 3DVAR


Modification of tf coordinate

Modification of TF coordinate

  • In order to design a new TF coordinate, we rewrite the formulation of Gal-Chen and Sommerville (1975) in a common formulation:

with

It is a decaying coefficient of the coordinate surface with

height. It is possible to use different “b” to accelerate the decaying.

(From Li et Chen, 2012)


New tf coordinates

New TF coordinates

The different decaying coefficients “b” can be defined as:

(Gal-Chen and Sommerville, 1974)

G.C.S.

SLEVE1

(Schar, 2002)

h*: scale of ref-topography; h*1 and h*2:

large and small-scale of ref-topogr.

SLEVE2

(similar to Klemp, 2011)

“n>2”: an empirical number; zc : a reference height from which the coordinate surface becomes horizontal.

COS

(From Li et Chen, 2012)


Grapes model research progresses at cma

1D test design

  • Test Objective :to compare the errors of PGF calculation of four coordinates in rest atmosphere over an artificial terrain.

  • Test design:

    • Reference rest atmosphere:

    • Classical algorithm used for PGF calculation

with

(From Li et Chen, 2012)


Grapes model research progresses at cma

Errors of PGF calculation induced by using TF coordinates

G.C.SSLEVE1SLEVE2COS

top

bottom

On different vertical levels: L2, L10, L20, L30 and L40 from bottom to top

(From Li et Chen, 2012)


Grapes model research progresses at cma

Relatively Reduced Errors: SLEVE1(SLEVE2, COS) against GCS

R.R.E. is defined as:

(From Li et Chen, 2012)


Grapes model research progresses at cma

2D test design (cont.)

Initial wind:

Analysis density distribution :

over

after mount

before mount

flow from L to R

density distribution

(From Li et Chen, 2012)


Grapes model research progresses at cma

Advection test : air mass moves over a topographic obstacle

GCS

SLEVE1

SLEVE2

COS-zc=15km

COS-zc=10km

without topography

left:density distribution at 0s,5000s,10000s right:the errors at 10000s after mountain

(From Li et Chen, 2012)


Grapes model research progresses at cma

The errors of the simulations

Defining two parameters as following, according to Williamson(et.al,1992)

is analytical solution

is numerical solution

Gal.C.S

Gal.C.S

SLEVE1

计算误差

SLEVE1

SLEVE2

SLEVE2

error

COS(15KM)

COS(15KM)

COS(10KM)

COS(10KM)

积分时间

integral time

integral time

right : temporal evolution of

left : temporal evolution of

(From Li et Chen, 2012)


The preliminary results with new tf coordinates in grapes meso

The preliminary results with new TF coordinates in GRAPES_Meso

The preliminary results with regional GRAPES (15km) are quite encouraging:

Monthly mean of 24h forecast of geopotential height at 100hPa

(From Li et Chen, 2012)


Grapes model research progresses at cma

The torrential rain-storm occurred on 21 Jul. 2012 in Beijing


Grapes model research progresses at cma

24 h accumulated precipitation from 00UTC 21 Jul to 00UTC 22 Jul

“The torrential rain-storm occurred on 21 Jul. 2012 in Beijing area: the worst the city has seen in more than 60 years, dumped an average of 215 millimeters of rain in 16 hours. Hebeizhen, a town in the suburban district of Fangshan (South-West), saw 460 millimeters for the same period. ”。

(From Chen et al., 2012)


Heavy rainfall event on jul 21 2012 beijing

Heavy rainfall event on Jul.21/2012 Beijing

  • Initial: global analysis

  • BC: global forecast

  • Grid size:3km

  • Physics:

  • - microphysics: WSM6

  • - radiation: RRTM S&L

  • - pbl : MRF

  • - land surface :NOAH

  • Obs.

    00z21Jul2012-00z22Jul2012

    Beijing

    24-hour accumulated rainfall

    Mean=190.3mm/24hr

    Max=460mm/24hr

    GRAPES_Meso-3km

    ECMWF

    Fcst.

    Max=341mm/24hr

    (From Huanget al., 2012)


    Grapes model research progresses at cma

    Comparison of precipitation every 6-hour forecasts against Obs.

    Fcst.0-6hr

    Fcst.6-12hr

    Fcst.12-18hr

    Fcst.18-24hr

    Obs.12-18hr

    Obs.18-24hr

    Obs.0-6hr

    Obs.6-12hr

    (GRAPES_Meso-3km)

    (From Huanget al., 2012)


    5 2 other research activities at cma

    5.2 other Research activities at CMA

    • GRAPES Yin-yang dynamic core

    • SV-based GRAPES ensemble forecast system

    • New algorithms of dynamic core


    Progress of grapes yin yang grid

    Progress of GRAPES Yin-Yang grid

    • The 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.

    Helmholtz equation:

    (From Peng et al., 2012)


    3d advection results

    3D advection results

    alpha=0.

    Instant image on the Yang grid

    5

    9

    1

    4

    6

    10

    8

    2

    alpha=45.

    day12

    7

    3

    alpha=90.

    The tracer follow the wave motion and undergo

    Three oscillations in the vertical direction.

    After one revolution(12 days), the tracer is back

    to the initial state.

    (From Peng et al., 2012)


    Grapes model research progresses at cma

    High order Multi-moment Constrained finite Volume (MCV) method

    We define the moments within single cell, i.e. the cell-averaged value, the point-wise value and the derivatives of the field variable

    Solutionpoints

    Constraint points

    Constraint conditons:

    Approximate Riemann solvers

    The unknowns (solution points) are updated in a fourth order mcv scheme, for example,

    (From Li et al., 2012)

    The same in multi-dimension, for example, y direction


    Grapes model research progresses at cma

    A nonhydrostatic atmospheric governing equation sets in the Cartesion system

    Height-based terrain-following vertical coordinate (Gal-chen & Somerville 1975) is used. is transformation Jacobian.

    MCV4 results

    (From Li et al., 2012)


    Grapes model research progresses at cma

    Linear nonhydrostatic

    mountain case

    Analytic solution:

    red dash line

    Discontinuous Galerkin results (Giraldo & Restelli, JCP, 2008)

    zero contours

    Fourth order MCV results

    (From Li et al., 2012)


    6 future plan

    6 Future Plan


    Grapes model research progresses at cma

    3DVAR, 24-60h

    Δx=3-10km, L45

    3DVAR/Bogus,

    72h, Δx=10km, L45

    SV+Sto.Phy, 10d

    Δx=50km, L60

    GRAPES_Meso

    + RAFS

    GRAPES_EPS

    GRAPES_TYM

    GRAPES_GFS

    Strategic Plan

    (~2015)

    GRAPES_GFS

    3DVAR, 10 d

    Δx=25km, L60


    Global grapes var research operation plan

    Global GRAPES_VAR Research & Operation Plan

    • GRAPES P3DVAR a new fixed version

      (res:1 deg—>0.5deg)

    • FY-3A MWTS、FY-2E IR AMV

    • GRAPES-M3DVAR

    • FY3-B MWTS、FY3-A/B MWHS、FY-2D/F IR AMV

    • GRAPES-M3DVAR oper. run

    • NPP satellite data used

    • More data from FY2/FY3

    GRAPES-4DVAR real-time running

    2015

    2013

    2012

    2020

    2014

    • Satellite vertical sounding high level channel used

    • GRAPES-4DVAR develop;

    • New version data preprocessing used

    • GRAPES-4DVAR real-time trial

    • More FY satellite data

    • GRAPES P3DVARM3DVAR;

    • Conventional data QC re-check

    • Data Preprocessing system re-design

    (From Gong et al., 2012)


    Regional grapes var research and operation plan

    Regional GRAPES_VAR research and operation plan

    • GPS/PW oper used.

    • Cloud analysis oper used

    • GRAPES_RAFS quasi-oper. running

    • GRAPES 3DVAR parallel version operation

    • Radar VAD、AWS humidity data operational used

    2015

    2013

    2012

    2020

    2014

    • Radar precipitation heating profile;

    • Radar reflectivity QC;

    • Wind profile QC

    • Continue GRAPES_4DVAR?

    • 3DVAR system improvement;

    • B matrix re-estimate and tuning

    • Conventional data QC recheck.

    • Pressure-wind balance re-tunning;

    • Eliminate boundary noise in B matrix;

    • GPS/PW QC;

    • Cloud analysis improvement;

    • GRAPES-4DVAR real-time test;

    • Radar data QC

    • Unified global / regional 3DVAR

    • Satellite data used in regional model

    Regional GRAPES_VAR: 4DVAR or 3DVAR+EnKF?

    (From Gong et al., 2012)


    Grapes model research progresses at cma

    EnKF analysis 2

    EnKF analysis k

    EnKF analysis 1

    GRAPES analysis

    GRAPES forecast

    Future HR GRAPES -DA and Prediction System

    observations

    Re-center EnKF analysis ensemble

    to control analysis

    member 1 forecast

    member 1 analysis

    member 1 forecast

    GRAPES-DFL

    0 20m 40m

    3DVAR

    Multi model EPS

    Innovation

    member 2 forecast

    member 2 analysis

    member 2 forecast

    EnKF

    GRAPES-DFL

    0 20m 40m

    ……

    ……

    ……

    ……

    member k forecast

    member k analysis

    member k forecast

    Ensemble covariance

    GRAPES-DFL

    0 20m 40m

    control forecast

    GRAPES-DFL

    0 20m 40m

    3DVAR-ECV

    H.R. Model

    First guess forecast

    data assimilation

    DAS: EnKF/3DVAR Hybrid DA System; Multi Models: WRF, GRAPES_Meso

    (modified from talk of Xue et al., 2012)


    Grapes model research progresses at cma

    GRAPES_3DVAR(or 4DVAR)-Hybrid: Method

    Extended control variable method (Lorenc 2003; Wang 2010):

    Extra term associated with extended control variable

    Extra increment associated with ensemble

    (modified from talk of Xue et al., 2012)


    Blending nowcast with grapes hr

    Blending Nowcast with GRAPES_HR

    • Implement a very-short term forecast system with 3km resolution based on multi-model ensemble including GRAPES_Meso, WRF and ARPS (collaborate with Nanjing University)

    • Data assimilation: hybrid DA (3DVAR+EnKF) (collaborate with Ming Xue, Oklahoma Univ.)

    (from Chen et al., 2012)


    Grapes model research progresses at cma

    THANK YOU


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