validation of omi and sciamachy satellite data...
TRANSCRIPT
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
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
MI-
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Total Ozone Column ECS2 > COL3Whole Globe OMITotal Ozone ECS2
260
270
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Sep
-04
Nov
-04
Jan-0
5
Mar
-05
May
-05
Jul-05
Sep
-05
Nov
-05
Jan-0
6
Mar
-06
May
-06
Jul-06
Sep
-06
Nov
-06
Jan-0
7
Mar
-07
May
-07
Jul-07
Sep
-07
Time (months)
Tota
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DU
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OMI TOMSOMI DOAS
Whole Globe OMITotal Ozone COL3
260
270
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Oct-0
4Ja
n-05
Apr-0
5Ju
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Oct-0
5Ja
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Apr-0
6Ju
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Oct-0
6Ja
n-07
Apr-0
7Ju
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Oct-0
7Ja
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Apr-0
8
Time (months)
Tota
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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
Example: validation of CO
© Dils et al, Dec 2006
IFE CO v0.6 largely improved
O3 column• Peaks > 7% wrt
WFMDOAS and TOSOMI:– Related to
clouds?To be
investigated
© Bracher 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