H. Elbern, A. Strunk Rhenish Institute for Environmental Research at the University of Cologne

COST 723 kick-off workshop, ESTEC, Nordwijk, 11.-13.03.2003

Assimilation of space and air borne measurements in Assimilation of space and air borne measurements in a tropospheric chemistry transport model by 4D-vara tropospheric chemistry transport model by 4D-var

H. Elbern, A. Strunk

Rhenish Institute for Environmental Research

at the University of Cologne

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ContentsContents

• Introduction: why 4D-var

• Assimilation of flight campaign data

• Assimilation of satellite data

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Design of the case studyDesign of the case study

• CTM and adjoint CTM (symmetric operator split):

– RADM2 gas phase: 61 species

– 4th order Bott advection, horiz. & vert.

– Implicit diffusion (Thomas algorithm)

• Grid: 125/54 km horiz. spacing, 100 hPa

– large grid: 77 x 67 x 26 (refined tropopause: z ~1 km)

• Meteorological fields by MM5

• Case studies:

– CONTRACE: 14. November 2001

– SPURT: 17.-19. January 2002

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Design of the assimilation experiment Design of the assimilation experiment

• assimilation interval 00:00-16:00 UTC( max),

• optimisation:

– SPURT: chemical state variables

– CONTRACE: chemical state variables + emission rates

• isotrop. background error covariance matrix (BECM)

• L-BFGS (quasi-Newton) minimisation

• Preconditioning by square root (BECM)

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4D-var configuration

Mesoscale EURAD 4D-var data assimilation systemMesoscale EURAD 4D-var data assimilation system

meteorologicaldriver MM5

meteorologicaldriver MM5

EURADemission model

EEMemission 1. guess

EURADemission model

EEMemission 1. guess

direct CTM direct CTM

emission ratesemission rates

Initi

alva

lues

Initi

alva

lues

min

imis

atio

nm

inim

isat

ion

adjointCTM

adjointCTM

observationsobservationsanalysisanalysis

gra

die

nt

fore-cast

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SPURTSPURT: Trace gas Transport in the Tropopause RegionCoord.: A. Engel, Univ Frankfurt

17.-19. Jan. 2002

a.m. 17.

p.m. 17.

a.m. 18.

p.m. 18.

a.m. 19.

p.m. 19.•Original project objectives: to analyse transport signatures in terms of chemical ages in the mixing region of troposphere and

stratosphere

•However:not suitable for a limited area data assimilation set-up. Hence, find chemical states, correlation length.

Find chem state at 00:00 UTC to best match daytime observations

00 10 UTC 12

assimilation interval

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SPURT SPURT Jan 17, 2002

1. guessassimilation resultobservations

flight height [km]

O3

CO

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1. guess assimilation result observations flight height [km]

am: Canary Isl. Casablanca pm: Casablanca Hamburg

O3

CO

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O3

CO


am: Hamburg North Cape pm: North Cape Hamburg

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CONTRACECONTRACEConvective Transport

of Trace Gases into the upper Troposphere over

Europe: Budget and Impact of Chemistry

Coord.: H. Huntrieser, DLR

flight path Nov. 14, 2001

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CONTRACECONTRACE Nov. 14, 2001, southbound

1. guessassimilation resultobservations

flight height [km]

O3

H2O2

CO

NO

HCHO

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CONTRACECONTRACE Nov. 14, 2001 north (= home) bound

O3

H2O2

CO

NO


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Assimilated data typesAssimilated data types

• in situ– surface observations– radio sondes– aircraft – tethered balloons

• Satellites: GOME– tropospheric NO2 columns– tropospheric NN derived ozone profiles

(h=1km)

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Assimilation of GOME NOAssimilation of GOME NO22 tropospheric columns, 3.8.1997 tropospheric columns, 3.8.1997

GOME NO2 columns:Courtesy of A. Richter, IFE, U. Bremen

# m

olec

./cm

2

post assimilationforecaststarted:3.8.97 06:00 UTC

# m

olec

./cm

2

NOAA ch 3 (near infrared)

# m

olec

./cm

2

forecast without assimilation

GOME NO2 columns: Courtesy of A. Richter, IFE, U. Bremen

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GOME ozone profile assimilation (3.8.1993)GOME ozone profile assimilation (3.8.1993)Data: Neuronal Network retrieval (Müller et al., 2003)Data: Neuronal Network retrieval (Müller et al., 2003)

+ NN ozone retrieval

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GOME ozone profile assimilation II (3.8.1993)GOME ozone profile assimilation II (3.8.1993)Data: Neuronal Network retrieval (Müller et al., 2003)

+ NN ozone retrieval

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Assimilation of GOME NOAssimilation of GOME NO22 tropospheric columns, 5.8.1997 tropospheric columns, 5.8.1997

GOME NO2 columns: Courtesy of A. Richter, IFE, U. Bremen

# m

olec

NO

2/cm

2

NOAA ch 3 (near infrared)NOAA ch 3 (near infrared)

# m

olec

NO

2/cm

2#

mol

ec N

O2/

cm2

post assimilationforecaststarted:3.8.97 06:00 UTC

forecast without assimilation

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Conclusions:Conclusions:

• successful UTLS data assimilation in a mixing regime requires readiness to identify different chemical regimes locally:– strat. intrusions, free troposphere, updrafts

• problem of first guess with phase shifts (e.g. streamers must be captured correctly)

• smoother algorithms give qualitative indication on the ability to simulate observations

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AcknowledgmentsAcknowledgments

• Data provision– CONTRACE: Dr. H. Huntrieser and project, – SPURT: Dr. C. Schiller and group, ICG-I, FZ

Jülich; Dr. H. Fischer and group, MPI-C, Mainz

• Funding by BMBF

• ZAM, FZ Jülich for computational facilities

H. Elbern, A. Strunk Rhenish Institute for Environmental Research at the University of Cologne

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