Validation of OMI and SCIAMACHY Satellite Data...

Validation of OMI and SCIAMACHY Satellite Data Products

Hennie KelderUniversity of Technology

Eindhoven, the Netherlands

Introduction A satellite mission is launched to answer certain science questions

ozone layer, climate change, air quality, aerosols, …

To answer these questions the satellite mission will deliver datatotal vertical column or vertical density profile of trace gases

This data needs to have a certain qualityaccuracy, continuity, reliability, coverage, repeat cycle

These needs for e.g. accuracy are translated into requirements with respect to a standard

% accurate with standard reference (ground based, satellite)

Validation is key to (1) quantify the quality of satellite data in terms of agreement

with well established reference data over all seasons and under all circumstances, and

(2) to obtain clues to how to solve protruding differences with reference data as feedback to algorithm developers.

Science Questions

http://www.knmi.nl/omi

Is the ozone layer recovering as expected ?

What are sources and sinks of aerosols and trace gasesthat affect air quality and how are they transported?

What are the roles of tropospheric ozone and aerosols in climate change ?

What are causes of surface UV-B change?

Validation RequirementsA

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Required Accuracy - Example

3% change1.5% accurate

100 DU change10 DU accurate

How To validate ?

Type 0: Quality Assurance Analyze data on means (expected) and extremes (outliers)Visual inspection of data plotted on global maps

Type 1: Statistical Comparisons to StandardGround based systems and networks, balloons, …Validated satellite instruments on same and other platformsPerform statistical comparisons, focus on differencesYields statistics on mean, median, variance, correlation, …Plots of difference versus measurement geometry parameters

Type 2: Different Algorithm Statistical ComparisonsRun different algorithms on same level 1 dataPerform statistical comparisons, focus on differencesYields statistics on mean, median, variance, correlation, …Benchmark effect of different assumptions and approaches

‘TOMS’ and ‘DOAS’ Retrieval Methods

TOMS : ratios of intensities of wavelength band pairs (USA)DOAS : spectral fitting of high resolution absorption (Europe)

Total O3 Column Single Orbits ECS2

Total O3 Column Single Orbits COL3

Influence of Clouds ECS2

Influence of Clouds COL3

Type 0 Validation

Type 0 validation will tell you:• whether satellite data values make sense (min, mean, max),• whether its spatial distributions (global maps) make sense,• Under which circumstances (clouds, dust storms, high sza) and

over which geographical regions (land, ocean, desert, snow) there are problems,

• to what aspect these problems are related (algorithmic, surface,measurement geometry, polarization),

• feed-back to algorithm developers,• feed-forward to scientific users!

Ground Based Validation - Ozone

OMI AO 2925 - Validation of OMI total ozone using ground-based Brewer observations. Dr. Dimitris Balis, Aristotle University of Thessaloniki - Laboratory of Atmospheric Physics, Greece

Ground Based vs OMI-DOAS

COL3

OMI AO 2925 - Validation of OMI total ozone using ground-based Brewer observations. Dr. Dimitris Balis, Aristotle University of Thessaloniki - Laboratory of Atmospheric Physics, Greece

Brewer Dobson

OMI DOAS 0.483 % 2.754 % 0.070 % 1.653 %

OMI DOAS* -0.555 % 0.200 % 0.086 % 1.601 %

OMI TOMS -0.504 % 2.704 % -0.631 % 1.032 %

OMI TOMS* -1.450 % 0.425 % -0.645 % 1.064 %

<O-G>/G σ(O-G) <O-G>/G σ(O-G)

* No South Pole (lat > 75 S)

Ground Based Validation - Ozone

NASA WB-57 no.926NASA DC-8 no.817

DOAS vs CAFS∆=10 DU=2.9%

TOMS vs CAFS∆= -5.8 DU=-1.8%

Polar-AVE 20050129 OMI Orbit 2890 CAFS

Aura Validation Experiment OMI CAFS

OMI-DOAS OMI-TOMSOMI-CAFS (O-C)/O STD OMI-CAFS (O-C)/O STD

Polar-AVE 10.12 DU 2.89 % 10.36 DU

9.09 DU

5.92 DU

11.70 DU

-5.85 DU -1.75 % 12.54 DU

Houston AVE -6.06 DU 2.09 % -2.27 DU -0.77 % 9.47 DU

Costa Rica AVE -8.12 DU -3.40 % -8.61 DU -3.62 % 3.89 DU

ALL AVE -2.02 DU -0.70 % -5.14 DU -1.79 % 9.59 DU

OMI – MLS Ozone Profiles

Preliminary results forOMI vs MLS ozone profiles

Distance < 100 kmSame orbit

Ground Based Validation - Surface-UV

OMI AO 2915 - Validation of the OMI surface UV irradiance products. Dr. Aapo Tanskanen, Finnish Meteorological Institute, Finland

Validation Statistics for Daily Doses [kJ/m2]

Validation instrument n %Bias %RMS r

Jokioinen Brewer Mk-III #107 421 3.6% 33% 0.99

Sodankylä Brewer Mk-II #037 175 7.6% 22% 0.97

Toronto Brewer Mk-II #014 262 -3.7% 24% 0.98

Toronto Brewer Mk-III #145 232 -9.4% 25% 0.97

Barrow SUV-100 203 19% 36% 0.94

Palmer 438 7.3% 24% 0.97

San Diego SUV-100 293 31% 41% 0.95

Ushuaia SUV-100 339 2.6% 25% 0.97

Tokyo 251 58% 75% 0.92

Ground Based Validation - NO2

OMI AO 2926 - Validation of OMI ozone and NO2 vertical column data with ground-based spectroscopic measurements in Russia. Prof. Dr. Yury Timofeyev, St. Petersburg State University, Russian Federation

Systeme d’Analyse par Observations Zenithales (SAOZ)Zenith sky measurements at twilight (86°<SZA<91°)Differential Optical Absorption Spectroscopy (DOAS)

Ozone: 450-590 nm Chappuis Band, temperature independent

NO2: 400-550 nm

NDACC qualified

Ground Based Validation - NO2

OMI AO 2926 - Validation of OMI ozone and NO2 vertical column data with ground-based spectroscopic measurements. Prof. Dr. Yury Timofeyev, St. Petersburg State University, Russian Federation

Type 1 Validation

Type 1 validation will provide you with:• qualitative agreement of satellite and reference data,• qualitative differences between satellite and reference data,• to what aspect these differences are related (algorithmic,

surface, measurement geometry, polarization),• feed-back to algorithm developers,• feed-forward to scientific users!

Type 1 validation quantifies the data quality but only under those circumstances covered!

• airborne and balloon observations supplement fixed position ground based observations to a certain extent

• same platform satellite instrument extends global coverage

Time frame 14-27 October, 2005regridded to 1.0x1.0 collection 2

SOSO22

CloudsClouds

Algorithm Comparisons - OzoneOMI-TOMS minus OMI DOAS Total Ozone Column [DU]

Sea iceSea ice

Air massAir mass

Solar ZASolar ZA

Land iceLand ice

Algorithm Comparisons - Ozone

Time frame 14-27 October, 2005regridded to 1.0x1.0 collection 2

OMI-TOMS minus OMI DOAS Total Ozone Column [DU]

COL3

ECS2

Algorithm Comparisons - OzoneO

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Total Ozone Column ECS2 > COL3Whole Globe OMITotal Ozone ECS2

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OMI TOMSOMI DOAS

Whole Globe OMITotal Ozone COL3

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OMI TOMSOMI DOAS

Closer Match!

Close Match

Type 2 Validation

Type 2 validation will provide you with:• a test bed for algorithmic assumptions (cloud heights, types of

surface, ghost columns, aerosols, interfering gases, …),

• a qualitative assessment of the influence of such assumptions

(apply various approaches and benchmark effects) ,

• feed-back to algorithm developers (best choice),

• feed-forward to scientific users (optimal choice)!

Type 2 validation selects the best of both worlds for developing hybrid algorithms!

Data Availability and Information

Public OMI Production Data : NASA DISC and NASA AVDChttp://disc.gsfc.nasa.gov/Aura/OMI/index.shtmlhttp://avdc.gsfc.nasa.gov

Public OMI Near Real Time Data : KNMI TEMIShttp://www.temis.nl

Public OMI Very Fast Delivery Data : FMI OMIVFDhttp://omivfd.fmi.fi/cgi-bin/products.pl

OMI Project Websitehttp://www.knmi.nl/omihttp://www.knmi.nl/omi/research/validation

NASA EOS Aura Project Websitehttp://aura.gsfc.nasa.gov

The TTOC is the total amount of O3 between the surface and the tropopause

TM4 simulation for the year 2000, with daily columns based on ECMWF tropopause heights,data courtesy: Twan van Noije

Global annual average total tropospheric ozone column density &WOUDC ozone sonde platforms with measurements after the year 2000

Dobson units (DU)

= shadoz site

= other sites+

SCIAMACHY validation withModel output

Location: Cabauw, The Netherlands (51.971 N, 4.927 E) Site characteristics: Flat terrain, ~sea level, tower 213mNO2 situation: Cabauw is in a (background) polluted area Main local source: national road (mainly during rush hours)

Cabauw, High mast, validation with several instruments

Ozone measuring instruments

Ground/Air:

Satellite: Tropospheric O3 can be derived from GOME,SCIAMACHY, GOME-2, OMI and TES

Instruments measuring tropospheric or total ozone

Instrument Platform Method Timing Air massBrewer/Dobson ground-based Remote sensing continuous O3 total columns

SAOZ UV-VIS spectrometer ground-based Remote sensing sunrise/sunset O3 total columns

SAOZ VIS-IR spectrometer aircraft Remote sensing campaign O3 total columns

GAMS aircraft Remote sensing campaign O3 total columns

ASUR aircraft Remote sensing campaign O3 profiles

UV-filter ozonometer ground-based Remote sensing continuous O3 total columns

ECC Ozone sondes sonde In-situ 1~3 times/week O3 profiles

Instruments measuring stratospheric ozone

Instrument Platform Method Timing Air massSAOZ UV-VIS spectrometer balloon/aircraft Remote sensing campaign O3 profiles between 10-25

km

LPMA/DOAS Balloon Remote sensing campaign stratospheric O3 profiles

LIDAR Aircraft/ground-based Remote sensing campaign stratospheric O3 profiles

Fast OZone ANalizer(FOZAN)

Aircraft In-Situ campaign stratospheric O3

Microwave spectrometer ground-based Remote sensing continuous day/night

strato- & mesospheric O3 profiles

Microwave radiometer ground-based Remote sensing continuous day/night

strato- & mesospheric O3profiles

NO2 measuring instruments

Ground/Air:Instrument Platform Method Timing AirmassAMAXDOAS aircraft Remote sensing

Remote sensing

Remote sensing

Remote sensing

Remote sensing

Remote sensing

In-situ

Remote sensing

In-situIn-situ

Remote sensing

Remote sensing

campaign tropospheric column

(mini-)MAXDOAS ground-based Continous/campaign

Tropospheric column/profile

LPMA/DOAS balloon campaign vertical profiles of stratospheric NO2

SAOZ UV-VIS ground-based sunrise/sunset vertical column

DOAS UV-VIS ground-based columns, low resolution profiles

FTIR ground-based ~4 spectra per measurement day

NO2 columns

ChemiluminescentNOx analyzers

ground-based hourly surface/in situ

LIF (laser induced fluorescence)

aircraft campaign boundary layer profile

TILDAS truck campaign in situCARDS (pulsed cavity ring-down spectrometer)

ground-based campaign surface/in situ tropospheric NO2

NO2 lidar ground-based campaign boundary layer profiles/tropospheric NO2

PANDORA ground-based Continous/campaign

Tropospheric column/profile

Satellites: GOME, SCIAMACHY, GOME-2, OMI and TES

Comparison at Stations

=> excellent agreement with ground-based measurements

Izana data courtesy of M. Gil, INTA,

Picture: Andreas Richter, IFE

SCIA ozone versus ground based

• Average differences in 2003/2004

Eskes et al, ACPD, 2005

O3 column

• No dependence on sza, latitude, total ozone

• Average deviations 0-2%

• SCIA comparisons ‘noisier’ than GDP4 comparisons

black: old red: new

Sodankyla (67N)

© Lambert et al, Dec 2006

NO2 column

• No dependence on sza, latitude, clouds, total NO2

• Average deviations 0-1015 molec/cm2

black: old red: new

Sodankyla (67N)

© Lambert et al, Dec 2006

Brewer/Dobson comparison: instrument degradation

Sciamachy

O3 profiles

• SCIAMACHY OL v3.01 ozone profile concentrations between 20 and 35 km are lower (0-15%) than sonde and lidar measurements, SAGE II and HALOE. No seasonal dependence observed in differences.

• Below ozone maximum differences increase. • RMS differences between 10 and 20%. Between 35 and 40km

average differences vary between -25 and +25% (RMS values between 20 and 40%).

• No significant tangent height shifts have been observed.

A. Van GijselJanuary 2008

NO2 profiles

• SCIAMACHY OL v3.01 NO2 profile concentrations between 20 and 40km in good agreement with HALOE measurements in combination with a photochemical model to account for diurnal changes.

• On average, values within 10-18% with larger uncertainties in lower stratosphere (based on 2002-2003 data).

L. AmekudziJanuary 2008

CO monthly mean vs model

• CO retrieval error dominated by instrument noise !

•© de Laat et al, Dec 2006

2σ instrum. noise

SRON CO

Conclusions

Courtesy Dr Mark Kroon(KNMI) and Dr Ankie Piters(KNMI)De Bilt, The Netherlands

Validation or intercomparison is key (1) to quantify quality of satellite data

in terms of agreement with well established reference data over all seasons and under all circumstances, and

(2) to obtain clues to how to solve protruding differences with reference data as feedback to algorithm developers.

(3) to monitor degradation of satellite instruments

Validation is essential and needed during the whole life time of satellite instruments

Validation of OMI and SCIAMACHY Satellite Data...

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