part 2 applications testing of our understanding of the

Part 2 Applications

Testing of our understanding of the system earth

• Global view, discoveries

• Spatial & temporal patterns, correlations => sources, transport

• Direct comparisons of different parts of the world

• Time series, trends

• Comparison with models, determination of source strengths

Steffen Beirle, MPI Mainz

Tropospheric NO2 column density SCIAMACHY, 2003-07

NO2 VCD [1015 molec/cm²]

Trace gases UV/vis/NIR

GOME, 1996-2002

HCHO Thierry Marbach, MPI Mainz

1 day of H2O from GOME-2T. Wagner, K. Mies, MPI Mainz)

H2O SCD derived from GOME-2 for 20.01.2008. Due to the high spatial resolution and almost daily global coverage many details of the atmospheric H2O circulation can be seen.

Cloud top height T. Wagner et al., ACP 2008

Cloud Products from UV/vis/NIR

1996-2003

Cloud top height T. Wagner et al., ACP 2008

Cloud Products from UV/vis/NIR

1996-2003

1996-2003

Aerosol ProductsUV Absorbing Aerosol index

SCIAMACHY, JAS 2006

UV Scattering Aerosol index

M. Penning de Vries MPI Mainz

Trace gases from nadir IR (TES)

CO, August 2008

http://smsc.cnes.fr/IASI/

Trace gases from nadir IR (TES)

IR products:

CO, O3, etc.

http://tes.jpl.nasa.gov

O3, Oct 2005

The total vertical column density contains stratosphericand tropospheric concentrations

Enhanced Tropospheric BrO concentrations during polar spring

(Wagner & Platt, 1998)

‚Bromine Explosion‘

0 20 40mixing ratio [ppt]troposphericStratospheric

‘offset’

SCIAMACHY NO2

2003-2006,2D high-pass-filtered NO2 VCD

Steffen Beirle

Ship-emissions:

AMVER ship density

(% of total)

Ship-emissions:GOME HCHO

1996-2003, 1D high-pass-filtered HCHO SCD(winter)

Thierry Marbach MPI Mainz

AMVER ship density

(% of total)

Spy in the sky….

What is it?

Part 2 Applications

Testing of our understanding of the system earth

• Global view, discoveries

• Spatial & temporal patterns, correlations => sources, transport

• Direct comparisons of different parts of the world

• Time series, trends

• Comparison with models, determination of source strengths

Fine spatial structures even for trace gas observations with limited sensitivity for lowertroposphere (Clerbaux et al.):

CO from MOPITTPopulation density

Population density: source CIESIN, in million inhabitants http://sedac.ciesin.columbia.edu/gpw

Correlation over Europe:

1 2 3 4 [1013 molec/cm²]

40

45

50

55

60

65

70

75

80

85La

titud

e [d

egre

e]

SZA > 87

Dec January February March April May June

1 2 3 4 [1013 molec/cm²]

40

45

50

55

60

65

70

75

80

85

Latitud

e [deg

ree]

SZA > 87

Average Extension of Sea Ice

Jun July August September October November Dec

Dependence of tropospheric BrO on latitude and time

Arctic

Antarctic

=> Relationship between bromine explosion and one year old sea iceWagner et al., JGR, 2001

Frost Flowers

Barrow, Alaska

Holger Sihler

in-situ

BrO satellite

1996 - 2001W. Simpson

Seasonal variation of the CO distribution

JJA 2004, 2005

JFM 2004, 2005

JJA 2005

JFM 2005

(Cheng Liu, MPI Mainz)

ATSR fire countsSCIAMACHY CO

Time series of fire counts, CO and aerosols

(Cheng Liu, MPI Mainz)

Time series of fire counts, temperature and HCHO

Discriminination of sourcesIs HCHO caused by emissions of vegetation or fires?

(Thierry Marbach, MPI Mainz)

NO2 Production by Biomass Burning

(Steffen Beirle, MPI Mainz)

Correlation of the NO2 VCD with Fire Counts for different regions of the world

South America

North America

Central Africa (east)

Indonesia

North Australia

Eastern Russia

Anthropogenic Sources: Weekly Cycle of NO2

GOME-2 2007-2008Steffen Beirle, MPI Mainz

rel.

units

Anthropogenic Sources: Weekly Cycle of NO2

Beirle et al., Weekly cycle of NO2 by GOME measurements, ACP 3, 2225-2232, 2003

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1996 1997 1998 1999 2000 2001 2002 2003

Time

Tem

pera

ture

ano

mal

y [K

]

-4.E+21

-3.E+21

-2.E+21

-1.E+21

0.E+00

1.E+21

2.E+21

3.E+21

4.E+21

5.E+21

H2O

ano

mal

y [m

olec

/cm

²]

temp_anomalyH2O_anomaly

Time series of monthly anomalies of the H2O VCD and temperature

-4 .0 0 E + 2 1

-3 .0 0 E + 2 1

-2 .0 0 E + 2 1

-1 .0 0 E + 2 1

0 .0 0 E + 0 0

1 .0 0 E + 2 1

2 .0 0 E + 2 1

3 .0 0 E + 2 1

4 .0 0 E + 2 1

5 .0 0 E + 2 1

6 .0 0 E + 2 1

J a n . 9 6 J a n . 9 7 J a n . 9 8 J a n . 9 9 J a n . 0 0 J a n . 0 1 J a n . 0 2 J a n . 0 3-0 .1

0

0 .1

0 .2

0 .3

0 .4

0 .5

0 .6

0 .7

0 .8

0 .9

T ro p _ 3 0 3 0 _ H 2 O _ a n o m a lyT ro p _ -3 0 °b is + 3 0 °temp_anomalyH2O_anomaly

Whole Earth

Tropics

(30°N - 30°S)

Wagner et al., JGR, 2006

y = 9.6E+21x - 3.2E+21R2 = 0.57

-5E+21

-3E+21

-1E+21

1E+21

3E+21

5E+21

7E+21

0 0.2 0.4 0.6 0.8Temperature anomaly [K]

H2O

VC

D a

nom

aly

[mol

ec/c

m²]

=> strong water vapour feedbackSimilar findings from study after Pinatuboeruption (Soden et al., 2002)

Correlation of the monthly anomalies of the H2O VCD and surface temperature

Change of the H2O VCD per Kelvin

[1021 molec/cm²]

Correlation of the monthly anomalies of the cloud fraction and surface temperature

Change of the effective cloud fraction per Kelvin

[%]

Variation of the cloud top height with surface temperature derived from the correlation analysis

Change of the cloud top heightper Kelvin

[km]Wagner et al., ACPD 2008

SO2 from IASI (thermal IR)06.10.2007

30.09.2007 11.10.2007

SO2 from Jebel at Tair eruption on 30.09.2007

Data shown from 30.09. – 11.10.

Clarisse et al., ACP, 2008

SO2 from IASI

Wind fields at 100hPa 6.10.2007 (ECMWF)

Clarisse et al., ACP, 2008

Part 2 Applications

Testing of our understanding of the system earth

• Global view, discoveries

• Spatial & temporal patterns, correlations => sources, transport

• Direct comparisons of different parts of the world

• Time series, trends

• Comparison with models, determination of source strengths

One of our first GOME tropospheric NO2 maps

Carsten Leue, 1998 Tropospheric NO2 VCD

GOME 1996 - 1998

-direct comparisons of different part of the world become possible….

GOME (narrow mode) 1996 - 2002

NO2 VCD [1015 molec/cm²]Steffen Beirle, MPI Mainz, Germany

-direct comparisons of different part of the world become possible….

SCIAMACHY 2003 - 2004

NO2 VCD [1015 molec/cm²]Steffen Beirle, MPI Mainz, Germany

Steffen Beirle, MPI Mainz, Germany

GOME-2 2007 - 2008

Part 2 Applications

Testing of our understanding of the system earth

• Global view, discoveries

• Spatial & temporal patterns, correlations => sources, transport

• Direct comparisons of different parts of the world

• Time series, trends

• Comparison with models, determination of source strengths

1996 1997 1998 1999 2000 2001 2002 2003 2004Time

0.00

0.40

0.80

tem

p.

anom

. [K]

-0.04

0.00

0.04H

ICR

U

anom

aly

-0.04

0.00

0.04

O2

anom

aly

temperature +0.10 K over 7 years

HICRU cloud fraction+0.33% over 7 years

O2 absorption-0.80% over 7 years

Monthly anomalies from 60°S to 60°N

-4E+21

0E+0

4E+21

H2O

ano

mal

y [m

olec

/cm

]

H2O VCD+2.1% over 7 years

Cloud top height

+0.2km over 7 years

Global average trends

Temperature [K]

Spatial trend patterns 1996 - 2002

Water vapor[relative trend / year]

Wagner et al., JGR, 2006

Temperature [K]

Spatial trend patterns 1996 - 2002

Water vapor[relative trend / year]

Wagner et al., JGR, 2006

Andreas Richter, IUP Bremen

Time series of tropospheric NO2 columns above East Central China from GOME, SCIAMACHY, OMI and GOME-2.

Andreas Richter, IUP Bremen

time series of GOME (blue) and SCIAMACHY (red) SO2-columns above the industrialised part of China (20°N, 100°E) – (40°N, 125°E

Systematic Increase of areas with enhanced BrO from 1996 to 2001

Monthly meanareas with enhanced BrO VCD

J. Hollwedel, IUP-Heidelberg

CO2 seasonality and trend from SCIAMACHY

Michael Buchwitz, IUP Bremen

Part 2 Applications

Testing of our understanding of the system earth

• Global view, discoveries

• Spatial & temporal patterns, correlations => sources, transport

• Direct comparisons of different parts of the world

• Time series, trends

• Comparison with models, determination of source strengths

Intercontinental transport of anthropogeneous NO2 measured by GOME and modeled by FLEXPART [Stohl et al., ACP, 2003]

Investigation of transport processes: comparison with models

Difference: NAO+ - NAO-

(winter 1996-2002)

Model results from FLEXPART GOME tropospospheric NO2

Investigation of transport processes: comparison with models

Influence of the North Atlantic Oscillation on the tropospheric transport paths [Eckhardt et al., ACP, 2003]

Original CH4emission inventory

Changes from comparison to in-situ-data

Changes from additional comparison to SCIAMACHY-data

Emissions [Tg CH4/yr]

Wetlands: 174Rice: 60

Wetlands: 181Rice: 62

Wetlands: 201Rice: 52

Inverse modelling of the global distribution of CH4

=> Adjustement of CH4 emission inventories for different sources and regions Peter Bergamaschi et al. JGR, 2007

Conclusions – I hope I could show that:

• Satellite observations enable a completely new view on our planet and its atmosphere

• Satellite observations are important to study globalphenomena like climate change, air quality, and their interactions

• Satellite observations are important to test our understandingof the system Earth on a global scale

The timeline of UV / VIS / NIR Satellite instruments(1995 - 2021) coversa very interesting period

SCIAMACHY

OMI

GOME-II

GOME-I

1990 2000 2010 2020 2030year

GOME-II

global temperature evolution (IPCC)

GOME-II