Thomas Holzer-Popp , Lars Klüser Dymtro Martynenko ......Method description, Journal of Geophysical Research, 107, D21, pp. AAC16-1 – AAC16-17, 2002 Holzer-Popp, T., M. Schroedter,

Utilizationof synergetic aerosol retrieval from

ENVISAT (and METOP)

Thomas Holzer-Popp1, Lars Klüser 1,2,Dymtro Martynenko1, Kerstin Stebel3

1 German Aerospace Center (DLR), Wessling, Germany

2 University of Augsburg, Institute of Physics, Augsburg, Germany

3 NILU, Norway

Mineral dust detection from MSG SEVIRI IR observations > Lars Klüser > Eumetsat Conference 2008, Darmstadt

slide 2

Outline

SYNAER method

SYNAER utilizations focusing on aerosol componentsaerosol monitoring examples(data assimilation)air quality monitoringaerosol-cloud interactions

Conclusions and outlook


slide 3

Outline

SYNAER method




slide 4

SYNAER method

Spectrometer (With high spectral resolution) 60x30 km2

least square fit of simulated spectra for 40 aerosol typesusing AOD and surface albedo for each type from AATSR→ selection of most plausible aerosol typefit quality check

Radiometer (With high spatial resolution 1x1 km2,Accurate cloud detection and correctionDark field method (670nm land / 870 nm ocean)→ retrieval of AOD and surface albedo

for given aerosol typerepetition for 40 aerosol mixtures

Coregistration to spectrometer pixels


slide 5

Analyzed information content of spectrometer

with AOD

with surfacetype

Holzer-Popp et al., ACP, 2008

more than 2degrees of freedom

for aerosol, type


slide 6

SYNAER/ENV validation v2.27-10/2005, Europe (Africa), 50 coincidences

Bias: -0.04 / -0.01 / -0.01Stdv: 0.12 / 0.08 / 0.06Corr: 0.78 / 0.80 / 0.78


slide 7

SYNAER/ENV – limitations and strengths

- sensors as used were not specified (primarily) for aerosols

- limitations- spatial / temporal coverage and resolution (12 days, 60x30 km2)- dependence on pre-defined fixed aerosol mixtures- no retrieval over very bright surfaces (A670 > 0.25)- open issue over Atlantic ocean under investigation

- strengths- estimation of aerosol composition- partly cloudy SCIA pixels used (1km2 AATSR cloud detection)


slide 8

Outline

SYNAER method




slide 9

Utilizations (1)

Aerosol monitoring examples

daily examplesmulti-annual dataset 2003-2009 (under processing)regional time series


slide 10

SYNAER/ENV v1 daily result: SCIAMACHY + AATSRAerosol pollution over Po basin, 22 April 2006


slide 11

SYNAER/ENV v1 daily result: SCIAMACHY + AATSRAerosol pollution over Po basin, 22 April 2006

soot

mineral maritime

sulfate


slide 12

Seasonal soot 2003 – 2007 (2004 partial)

DJF MAM JJA SON


slide 13

Regional time series: „Angola basin“

2003 2005 2006 2007 2009

Pixe

l num

ber

AO

D55

0


slide 14

Utilizations (2)

Component-wise data assimilation (METOP)

-> see talk D. Martynenko THU 14:00

difference by assimilationWASO (incl. organic soot)

July, 23 2007


slide 15

Utilizations (3)

Air quality monitoring

Convert AOD into mass concentrations (PMx)using retrieved composition to estimate size distribution


slide 16

Converting SYNAER result into PMAOD-PM conversion requires SYNAER-PM product uses- information on size distribution - microphysical properties of retrieved aerosol mixture- information on vertical profile - auxiliary CTM profile shape correction

Particle mass concentrations PM10 [�g/m3]No. Name Total WASO INSO SSAM SSCM SOOT MITR1 Pure Watersoluble 148 1482 Continental I 206 140 663 Continental II 265 132 1334 Continental III 325 126 1995 Maritime I 296 44 2526 Maritime II 323 44 234 457 Maritime III 328 22 3068 Maritime IV 381 22 270 919 Polluted Watersoluble I 137 132 5

10 Polluted Watersoluble II 128 118 1011 Polluted Continental I 256 118 133 512 Polluted Continental II 247 104 133 1013 Polluted Maritime I 272 60 162 45 514 Polluted Maritime II 289 44 144 91 1015 Desert Outbreak I 109 109 31816 Desert Outbreak II 72 72 63617 Desert Outbreak III 38 38 95418 Biom. Burn. / High Poll. I 133 126 719 Biom. Burn. / High Poll. II 118 103 1520 Biom. Burn. / High Poll. III 103 80 23


slide 17

SYNAER PM validation EMEP


slide 18

SYNAER PM validation EMEP


slide 19

Monthly means PM10 and PM2.5 summer 2006

EMEP model data: S. Tsyro, met.no


slide 20

SYNAER PM10 / PM2.5 summer 2006 / 2007 episode

min: 5 data-points in 50x50 km

min: 5 data-points in 50x50 km


slide 21

Utilizations (4)

Aerosol-cloud interactions

Correlate SYNAER 2003-2005soot and dust with cloud / precipitation datasets

APOLLO and beyond (AATSR)- Cloud Cover- Cloud Top Temperature

TRMM precipitation observations- Daily Precipitation amounts


slide 22

no seasonalseparation here

AOD < 0.05 overbackground: no aerosol

WASO dominates signalof total aerosol

different effects of sootand dust

cloud cover observationdensities skewed to lowcloud cover due to low-cloud bias of theSYNAER retrievalmethod

Mediterranean cloud cover

Mediterranean basin: cloud cover


slide 23

Mediterranean basin: cloud top temperature

seasonal variation of aerosol cloudinteractions

indirect aerosol effectsof mineral dust and sootcan counteract, typedependence is important

aerosol effects on CTT important for cloudmicrophysics, in-cloudthermodynamics, precipitation and climate(outgoing longwaveradiation)


slide 24

Mediterranean basin: precipitation comparison with MODIS

spatial coverage of SYNAER-ENVISAT is insufficient forsophisticated statistical analyses

MODIS and comparable products: much better spatial coverage, but no real aerosol species differentiation

aerosol species have different indirectaerosol effects, partly counteracting

→ need for species differentiatingaerosol retrieval with good spatialcoverage / statistics

SYNAER/ENV 2003-2009

SYNAER/METOP

SYNAER

MODIS


slide 25

Outline

SYNAER method




slide 26

Conclusions

• First applications of SYNAER show potential and limitations

• aerosol monitoring

• data assimilation -> talk D. Martynenko THU 14:00

• air quality / PM

• aerosol-cloud effects (soot / dust)

• weak sampling needs to be handled with care -> SYNAER/METOP

• validation and processing ongoing

• data available at: http://wdc.dlr.de


slide 27

ReferencesHolzer-Popp, T., M. Schroedter, and G., Gesell, Retrieving aerosol optical depth and type in the boundary layer over land and ocean from simultaneous GOME spectrometer and ATSR-2 radiometer measurements, 1, Method description, Journal of Geophysical Research, 107, D21, pp. AAC16-1 – AAC16-17, 2002

Holzer-Popp, T., M. Schroedter, and G., Gesell, Retrieving aerosol optical depth and type in the boundary layer over land and ocean from simultaneous GOME spectrometer and ATSR-2 radiometer measurements, 2, Case study application and validation, Journal of Geophysical Research, 107, D24, pp. AAC10-1 – AAC10-8, 2002

Holzer-Popp T., Schroedter-Homscheidt, M., Breitkreuz, H., Klüser, L., Martynenko, D., Synergistic aerosol retrieval from SCIAMACHY and AATSR onboard ENVISAT, Atmospheric Chemistry and Physics, 8, 7651-7672, 2008

Thomas Holzer-Popp , Lars Klüser Dymtro Martynenko ......Method description, Journal of Geophysical Research, 107, D21, pp. AAC16-1 – AAC16-17, 2002 Holzer-Popp, T., M. Schroedter,

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