Workshop: Dados e Produtos Meteosat e MetOp em Tempo Quase Real via EUMETCast para Aplicações Meteorológicas e Ambientais. Stephen English CPTEC-INPE

Applications in

Applications in

Atmospheric Data

Atmospheric Data

Assimilation for

Assimilation for

Workshop: Dados e Produtos Meteosat e MetOp em Tempo Quase Real via EUMETCast para Aplicações Meteorológicas e Ambientais

Contents

Contents

1) Os produtos EUMETCast

1) Os produtos EUMETCast

-- Relevância para assimilicao

Relevância para assimilicao

2) Uso de dados por assimilicao

2) Uso de dados por assimilicao

2) Uso de dados por assimilicao

2) Uso de dados por assimilicao

-- CPTEC e o resto do mundo

CPTEC e o resto do mundo

3) Que dados queremos via

3) Que dados queremos via

EUMETCast?

Objective

The

objective of this workshop

is to provide for

the academic and scientific communities the

distribution of

near-real time

data and

weather satellite

-

derived products from the

European Organization for the Exploitation of

European Organization for the Exploitation of

Meteorological Satellites (EUMETSAT) s

EUMETCast system

and their applications to

the atmospheric convection,

atmosphere-biosphere interaction, agriculture and

EUMETCast for DA for NWP

EUMETCast-Europe = 177 products (102 weather)

EUMETCast-Americas

+ Level 1 SEVIRI channel radiances

+ Level 2 products: atmospheric temperature and humidity ATOVS + Level 2 products: Surface fields (SST, Sea ice, fire, vegetation) + Level 2 products: ASCAT winds

+ Level 2 products: ASCAT winds

+ Level 2 products: Clouds, stability, preciptation

+ Level 2 products: FY-2E (AMVs, clouds)

EUMETCast-Europe

+ EUMETCast-Americas

+ Level 1 raw data: ATOVS, IASI, GRAS, GOME, MODIS, ASCAT + Level 1 Clear sky radiances

+ Level 2 Polar AMVs

Can we get the data another way?

•

ATOVS

–

Dados globais so esta disponivel no CLASS server

(para FTP)

–

Dados de RARS no GTS (NOAA-18, 19)

–

Dados de RARS e globais de MetOp nao esta

–

Dados de RARS e globais de MetOp nao esta

disponivel no GTS em Brazil

•

IASI

–

So no CLASS server (NOAA) para FTP

–

IASI nao esta disponivel ainda no GTS em Brazil

AIRS ~4,500

AMVs ~9,000

GPSRO ~800

IASI ~3,000

© Crown copyright Met Office

SSMIS ~4,500

ATOVS ~36,000

Scat ~16,500

Observacoes agora e 12

anos atras

5 SSMIS + SSM/I + AMSR-E + TMI

4 AVHRR 1 SEVIRI plus other Geo imagers 2 AVHRR 2 SSM/I

Cloud and rain, snow

4 Scat-like (QuikScat, ERS, ASCAT, WindSat) 5 SSMIS + SSM/I + AMSR-E + TMI

4 AVHRR 1 SEVIRI plus other Geo imagers 1 ERS Scat,

2 AVHRR Surface

(sea ice, SST, Surface wind, snow,

3 HIRS 6 AMSU-B + MHS 5 SSMIS + SSM/I + AMSR-E + TMI 2 AIRS/IASI Many Ground based GPS

2 HIRS Humidity

5 Geo AMVs 6 AMVs Some Geo AMVs

Wind

3 HIRS 6 AMSU-A 2 SSMIS 2 AIRS/IASI 9 GPSRO 2 HIRS, 2 MSU

Mass

Now or soon (METOP, POESS, DMSP, Research) > 12 years ago

© Crown copyright Met Office

4 AVHRR 1 SEVIRI plus other Geo imagers

Assimilation of observations

MWS (AMSU, MHS) MWI (SSMIS, AMSR)

Bias correction y* = y + c AMVs (Geo + polar)

Conventional GPSRO+WV _(nuvens T*, Є) NWP analysis ensemble x_ai NWP short range forecast ensemble x_fi 4D-LETKF x_ai =x_fi + W(x_fi)(y*-H(x_fi)) Forecast model x_fi = M(x_ai) GPSRO+WV

Weight to background vs observations

New Obs

Red – Used (Sea/Land, Clear/MWcloud) Yellow – Used (Sea/Clear only) Blue – Used

1000s of channels, use 150

Complex Radiative Transfer (2)

Algumas vezes os Jacobians

estao muito complicado e

dificil usar...

Clouds: 1D-var analysis to select channels

CF

CTP

CF

CTP

LETKF ou 4D-Var

1D-Var • Escolhar canais que nao _{tem muito sensitividade} de nuvens

• Usar radiancias em 4D-var ou LETKF

From Ed Pavelin, Met Office

Adjoint-sensitivity: que canais estao mais

importante?

From Richard Marriot, Met Office

Microwave (AMSU-A)

Hyperspectral IR (IASI)

-1.5 -1.0 -0.5 0.0

Adjoint sensitivity is a measure of the ability of each observation to reduce

forecast error for a specified metric.

Dados para mandar no EUMTCast

•

Que e oa canais certo para um centro tem

dependencia que eles querem fazer,

detalhes de sistema, que outros dados eles

estao usando.

•

Entao mesmo que centros vao usar talvez

•

Entao mesmo que centros vao usar talvez

menos de 300 canais melhor mandar tudo

•

Mas tudo para todos satelites e demais...

•

Mandar Principal Components

•

E um medo que PCs vai perder algumas

Erros e importante

•

Se nos nao sabemos os erros de

background e observacoes e possivel fazer

um analise que e pior que background.

•

=> Ensemble Kalman Filter para erro de

•

=> Ensemble Kalman Filter para erro de

background

Sensitivity to errors in description of error

Based on Hilton and Eyre 2010

Que nos precisamos no EUMETCast

por assimilicao no modelos?

•

Observacoes

–

Hiperspectral sondas com qualidade de IASI

•

Radiancias brutos

•

Informacao em nuvens e superficie, GHGs

•

Os erros dos observacoes

–

Sondas microndas com qualidade de AMSU e MHS

•

Radiancias brutos

•

Radiancias brutos

•

Informacao em precipitacao, superficie

–

The 1b radiances are a “product” and we want the best quality,

best characterised 1b radiance product possible.

•

Near real time

–

Rapid dissemination: goal timeliness 30 minutes

and send data to

NWP centre partners as soon as available to Sat Agencies so

Conclusions

•

EUMETCast-Americas currently supports SEVIRI and some

derived products

–

Use of SEVIRI in dat assimilation is limited at present

•

Use is mostly for imagery, products or regional model

assimilation

•

Other EUMETCast products are of little value to

•

Other EUMETCast products are of little value to

assimilation

•

Assimilation interest is for raw radiances for sounders (ATOVS,

IASI)

•

It is possible to acquire some of these data via GTS or FTP

•

But EUMETCast may be more complete, robust, faster and