J. Tamminen

Finnish Meteorological Institute

TROPOMI workshop

KNMI, De Bildt, March 5-6, 2008

FMI participation in OMI and plans for TROPOMI

Finland’s role in OMI project

Instrument

• VTT: Detectors

• Patria: Electronics unit

• SSF: Processing software for ground segment

• FMI: Project management in Finland

Scientific products (FMI)

• OMUVB - Global surface UV radiation product

• Very Fast Delivery (VFD) processing

OMUVB - Global surface UV radiation product

• Off-line processing (Level 2 UV-B)

• UV radiation (305, 310, 324 and 380 nm), UVB erythemal dose rate and daily dose

• Archiving and distribution

Global OMUVB example: UV Index (clear-sky and cloud corrected)

Surface UV derived from OMI/Aura measurementsElevated surface UV amounts were observed

in Ushuaia in spring 2004 after the breakdown of the Antarctic polar vortex and entering of the ozone depleted polar air masses into the lower latitudes

Surface UV and total ozone in Ushuaia

• The UV measurement data of Ushuaia were provided by the Antarctic NILU-UV network maintained by INM, FMI, DNA/IAA, and CADIC.

OMTO3

Clear-sky UV Index on October 12, 2004 according to OMI

Status of global surface UV products

• Public release summer 2007

• OMI UV (OMUVB) data used in WMO’s Ozone Assessment 2006.

• Validation:

• OMI measurements are suitable for continuation of the global satellite-derived surface UV time series using a surface UV algorithm similar to the original TOMS UV algorithm

Future plans: Surface UV radiation On-going and future plans

• Algorithm development:

• A correction is needed to account for absorbing aerosols and trace gases

• The quality of the assumed surface albedo (snow/ice) needs to be improved

• Science

• Long time series

VFD - Very Fast Delivery processing system

• Sodankylä satellite data receiving station receives EOS-Aura Direct Broadcast data

• High latitude site: 3-5 orbits/day

• Coverage: northern Europe• Allows fast data processing • 15 min for O3 and UV

products

Sodankylä

Very-Fast-Delivery OMI data - processing

Processing of the OMI data

Total ozone (DOAS / KNMI)

UV-products (TOMS / NASA+FMI)

In 15 min the images are available in the Internet

http://omivfd.fmi.fi

2.4 m dish antenna,receivers andcontrol computer

FMI ARC (Arctic Research Center)Processing facility: Linux clusters for processing, controlling and archiving

VFD service status• VFD service started as a

technology demonstration.

• Ozone and UV images available since March 2006.

• Working reliably.

• Products validated:• “Description and validation of the

OMI Very Fast Delivery products” by Hassinen et al. accepted to JGR special issue

Future plans - VFD Other data products possible

+ Local products (Northern Europe)+ Fast availability, regular time coverage+ If fast decisions required

VFD data • Atmospheric correction (AOD and ozone) in the estimation of

surface reflectances• Relevant e.g. for monitoring of snow cover conditions and

lake/coastal water quality (interest by Finnish Institute of Marine Research and Finnish Environmental Institute)

• Methods:• Combine ground-based observations of relevant atmospheric

and surface characteristics as reference information

Future plans - Aerosols

Background• Co-operation with Univ. of Helsinki and FMI

• Aerosol modelling

• Ground based measurements of aerosol optical properties

• Surface albedo, snow, ice

On-going work and future plans:• Collaboration with KNMI to further improve of OMAERO algorithm. Evaluate the opportunities to improve the single scattering albedo

retrieval by OMI/CALIOP synergy. Focus on improving the surface reflectance treatment. Validation of AOD and SSA: establish Finnish AOD network

• Bayesian model selection using RJMCMC technique

Future plans - Climate modelling

• Aerosols

• Improved aerosol parametrization in the state-of-the-art climate models

• AOD new important parameter in climate models

• Global measurements of aerosols important for climate model validations

• Long time series

• evaluating climate modelling

• Assimilation

• Environmental prediction: physical composition

Future plans: Climate

• Development methods to estimate greenhouse gas concentrations (CH4) from TROPOMI data• Applying ground-based reference

Fourier Transform spectrometer (FTS) observations from Sodankylä-Pallas site as reference data

• High resolution reference spectra for calibration and validation purposes

• Implementation in 2008

• System relevant for:• OCO (Orbiting Carbon Observatory)

of NASA: CO2• TROPOMI: methane (CH4) products

Sodankylä-Pallas validation siteMeasured spectrum from mast 30.6.06

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

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350 442 534 626 718 810 902 994 1086 1178 1270 1362 1454 1546 1638 1730 1822 1914 2006 2098 2190 2282 2374 2466

Wavelenght

Radi

ance

[W/m

^2]

Measured referencespectrum

Measured forestspectrum

Measured open landspectrum

Examples of other monitoring programmes• CAL-VAL site for remote sensing satellites

observing Earth’s surface and atmosphere • Complete surface (soil/snow), vegetation (land

cover) and atmospheric monitoring data sets available.

• Surface VIS/IR reflectance spectrum (350-2500 nm) of open and forested terrain in different snow conditions (2007 ->).

• WMO-GAW nework: Surface-level concentrations of CO, CO2, CH4 etc.

• AOD, Ozone soundings, Brewers

Future plans: Climate

• Climate - melting permafrost:• Combining/correlating

TROPOMI methane (CH4) data with MW scatterometer data (eg. Metop ASCAT)

Geographical interest in boreal forest and sub-arctic reagion

Permafrost monitoring using MW-scatterometer data

• Pulliainen et. al. (1998) developed methods for monitoring soil freeze-thaw-cycles• Based on dramatic change in

dielectric constant of soil

• Method allows operational monitoring permafrost freeze-thaw cycles using scatterometer data

Future plans: AQ modellingKey species: Sulphur and nitrogen oxides, tropospheric ozone, aerosols,

some organics (formaldehyde, ...).

Objectives:

• Model evaluation with satellite data

• Re-analysis studies (absolute amounts of pollutants released and transported)

• Forecasting studies (model vs data)

• Data assimilation

• Model initialization

• short relaxation time but affects strongly the short-term forecasts

• Input data refinement

• emission adjustments have longer-lasting but less significant impact

Future plans - Ozone Background:

• Regular ozone soundings at Sodankylä/Arctic and Marambio/Antarctica started in 1989.

• Experience on high resolution ozone profile measurements using satellite instruments in limb-geometry (GOMOS, OSIRIS)

• Middle atmosphere modelling: ozone in CTM and GCM

• EUMETSAT O3MSAF manager• WMO IGACO-O3/UV coordinator

Ongoing work & future plans:• OMI ozone profile validation with GOMOS and

OSIRIS profiles• Soundings from Sodankylä and Marambio• 3D climatology: combination of OMI, GOMOS

and OSIRIS data• Comparison with FinROSE (CTM) and

HAMMONIA (GCM) models

OMI vs GOMOS ozone profiles

Johanna Tamminen OMI co-PI

Aapo Tanskanen OMUVB manager (till 2008)

Seppo Hassinen OMI VFD manager

Jouni Pulliainen Head of Arctic Research Center (Sodankylä)

Jarkko Koskinen Snow, ice, remote sensing

Gerrit de Leeuw Aerosols

Antti Arola OMUVB manager (2008 ), aerosols

Mikahail Sofiev Air quality modelling

Erkki Kyrölä Ozone,atmospheric remote sensing

Heikki Järvinen Climate modelling

Anders Lindfors UV research

Osmo Aulamo Sodankylä receiving station

Timo Pirttijärvi Sodankylä operations

Juha M. Karhu Validation: Brewer data in Sodankylä

Tapani Koskela Validation: Brewer and UV data in Jokioinen

Kaisa Lakkala Validation: UV data in Sodankylä

Marko Laine Statistical inverse problems

Leif Backman Modelling, FinROSE, HAMMONIA

Laura Thölix Modelling, FinROSE, HAMMONIA

FMI team: