AOD Assimilation with CMA 3-D Var Scheme

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AOD Assimilation with CMA 3-D Var Scheme. Sunling Gong. Why AOD Data Assimilation?. PM Predictions at US and Europe. US. Europe. Gong et al. submitted. PM 10 Predictions in China. AOD Comparisons. Gong et al. submitted. Year 1 Annual Correlation (R) Values. Moran et al. - PowerPoint PPT Presentation

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AOD Assimilation with CMA 3-D Var Scheme

Sunling Gong

Why AOD Data Assimilation?

PM Predictions at US and Europe

PM10 (1997-2004)

EMEP-Observation [ g m-3 ]

0 20 40 60 80 100

GE

M-A

Q-S

imu

lati

on

[ g

m-3

]

0

20

40

60

80

100Spring (26.30; 73.32; 0.38)%Summer (5.25; 94.36; 0.39)%Autumn (35.84; 64.16; 0.0)%Winter (63.69; 35.71; 0.60)%Y=0.2069X+7.0222; r = 0.3064

PM2.5 (1998-2004)

EMEP-Observation [ g m-3 ]

0 10 20 30 40 50

GE

M-A

Q-S

imu

lati

on

[

g m

-3 ]

0

10

20

30

40

50Spring (9.69; 82.70; 7.61)%Summer (0.68; 94.54; 4.78)%Autumn (16.61; 81.73; 1.66)%Winter (47.01; 51.87; 1.12)%Y=0.2052X+7.2826; r = 0.2544

Gong et al. submitted

US

Europe

PM 10 Predictions in China

PM10 (2004)

China-Observation [ g m-3 ]

0 100 200 300 400 500

GE

M-A

Q-S

imu

lati

on

[

g m

-3 ]

0

100

200

300

400

500Spring (100.0; 0.0; 0.0)%Summer (100.0;0.0;0.0)%Autumn (100.0; 0.0;0.0)%Winter (100.0; 0.0;0.0)%Y=0.0484X+11.4929; r = 0.3899

AOD Comparisons

AOD (1995-2004)

AERONET-Observation

0.0 0.5 1.0 1.5 2.0 2.5

GE

M-A

Q-S

imu

lati

on

0.0

0.5

1.0

1.5

2.0

2.5Spring (2.09; 67.14; 30.77)%Summer (1.94; 65.44; 32.62)%Autumn (5.60; 63.55; 30.85)%Winter (3.17; 63.03; 33.80)%Y=0.3473X+0.1903; r = 0.5787

Gong et al. submitted

Year 1 Annual Correlation (R) Values

Moran et al. 10th CMAS Conference

Application of near-real-time (NRT) data:

(1) Provide more realistic initial conditions;(2) Emission corrections.

AOD Data Assimilation System

AODAS

3D-Var is to minimize objective function J(x):

))(())(()()(2

1)( 1T1T

oobb xHxHxxxxxJ yOyB

3D-Var Method

where x is the analysis field of AOD, xb the background field of AOD provided by model, B the background error covariance matrix, y0 the observation of AOD and O the observation error covariance matrix. H is the observation operator matrix that transfers the variables from model space to observational space.

Obs. Model

DAS for Dust

First Guess

3D-Var

analysis-field

Forecast result

Satellite: IDDISurface: Visibility

Satellite: FY-2C

Surface: Visibility

CMA Dust Assimilation System

CUACE/Dust

With DASWith DASNo DASNo DAS

CUACE/Dust : WMO SDS-WAS

Niu et al 2008

2006 Spring Forecasts: threat Score (TS) increased from 0.22 to 0.31, a 41% enhancement.

2006 Spring Forecasts: threat Score (TS) increased from 0.22 to 0.31, a 41% enhancement.

GEM-MACH AOD Assimilation Scheme

GEM-MACH AOD12 size bins of 5 aerosol types

3-D Var

MODIS or others AOD

Assimilated AOD

NRT AOD from GOES Satellite

0 010E 30E 50E 70E 90E 110E 130E 150E 170E 170W 150W 130W 110W 90W 70W 50W 30W

90S

80S

70S

60S

50S

40S

30S

20S

10S

0

10N

20N

30N

40N

50N

60N

70N

80N

90N

Undef

< 0.4

0.4 - 0.8

0.8 - 1.2

1.2 - 1.6

1.6 - 2

2 - 2.4

2.4 - 2.8

2.8 - 3.2

3.2 - 3.6

3.6 - 4

> 4

MeteoInfo: Meteological Data Information System

A Daily AOD from MODIS

Deep Blue” AOD productover bright land surface

0.55 μm bandfrom both Terra and Aqua.

M O D - TerraM YD - Aqua

AOD Assimilation for GEM-MACH Globe

Future Work

GEM-MACH Global Futures

• Implement into GEM-MACH Global and late in to GEM-MACH regional;

• Evaluate the results;

• Compare the assimilation results with MODIS and GOES AOD;

• More ......

Thanks!

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