Aristeidis K. Georgoulias Konstantinos Kourtidis Konstantinos Konstantinidis AMFIC Web Data Base AMFIC Annual Meeting - Beijing 16-17 October 2008 Democritus

Aristeidis K. GeorgouliasAristeidis K. Georgoulias

Konstantinos KourtidisKonstantinos Kourtidis

Konstantinos KonstantinidisKonstantinos Konstantinidis

AMFIC Web Data BaseAMFIC Web Data Base

AMFIC Annual Meeting - AMFIC Annual Meeting - Beijing 16-17 October 2008Beijing 16-17 October 2008

Democritus University of ThraceDemocritus University of ThraceLaboratory of Atmospheric Pollution and Pollution Laboratory of Atmospheric Pollution and Pollution Control Engineering of Atmospheric PollutantsControl Engineering of Atmospheric Pollutants

下午好下午好good afternoongood afternoon

1.1. Current status Current status::• AMFIC web data base is ready!AMFIC web data base is ready!

1.1. Current status Current status::• AMFIC web data base is ready!AMFIC web data base is ready!

• The already fully analyzed data are being uploadedThe already fully analyzed data are being uploaded

The example of Methane dataThe example of Methane data::The first fully inserted product in our data base is SCIAMACHY The first fully inserted product in our data base is SCIAMACHY WFM-DOAS v1.0 XCHWFM-DOAS v1.0 XCH44 dry air columnar dataset* dry air columnar dataset*

* SCIAMACHY WFM-DOAS v0.6 CO columnar data are ready * SCIAMACHY WFM-DOAS v0.6 CO columnar data are ready and will be uploaded within the next 15 daysand will be uploaded within the next 15 days

* SCIAMACHY SO* SCIAMACHY SO22 columnar data are being processed and will columnar data are being processed and will be uploaded within the next monthbe uploaded within the next month

The example of Methane dataThe example of Methane data::

CO & SOCO & SO22

coming soon!coming soon!


FRONTFRONT

BACKBACK

Methane Methane productproduct


BACKBACK






XianXian


Some advantages of AMFIC web data baseSome advantages of AMFIC web data base::

• By breaking huge global files to many gridded ascii files we By breaking huge global files to many gridded ascii files we make the process of those data easier for users interested in make the process of those data easier for users interested in specific spotsspecific spots

• This analysis enables easy validation of several products for This analysis enables easy validation of several products for selected regions and comparison with model resultsselected regions and comparison with model results

• The users can request either plots or ascii files even for a quick The users can request either plots or ascii files even for a quick look in a few secondslook in a few seconds

• Users interested in global data sets can just download the whole Users interested in global data sets can just download the whole dataset using Wget or a web ripper software dataset using Wget or a web ripper software

• The data base will be perfect even for educational purposes The data base will be perfect even for educational purposes

2.2. AIRSAT web data base integration AIRSAT web data base integration::Satellite Earth simulator-AIRSATSatellite Earth simulator-AIRSAThttp://www.satellite-earth-simulator.com/http://www.satellite-earth-simulator.com/

Satellite Data SourcesSatellite Data Sources::• TOMS (Earth Probe TOMS)TOMS (Earth Probe TOMS)

• SCIAMACHY (ENVISAT)SCIAMACHY (ENVISAT)

• GOME (ERS-2)GOME (ERS-2)

• MODIS (AQUA)MODIS (AQUA)

Meteorological Data SourceMeteorological Data Source::• NCEP/NCAR Reanalysis Project NCEP/NCAR Reanalysis Project

2.2. AIRSAT web data base integration AIRSAT web data base integration::Meteorological parametersMeteorological parameters• TemperatureTemperature• HumidityHumidity• PressurePressure• Wind speedWind speed• Precipitation Precipitation

Atmospheric data Atmospheric data • Ozone vertical columnOzone vertical column• NONO22 vertical column vertical column• Aerosol Optical Thickness over oceanAerosol Optical Thickness over ocean• Cloud Optical Thickness Cloud Optical Thickness • Cloud Top Temperature Cloud Top Temperature • Optical Depth Land and OceanOptical Depth Land and Ocean• Atmospheric Water Vapour Atmospheric Water Vapour

Ocean dataOcean data• ChlorophyllChlorophyll• Sea surface temperatureSea surface temperature,, day day//nightnight

Daily assimilated and gridded data sets could be included in this Daily assimilated and gridded data sets could be included in this part of the data base (part of the data base (e.g. TEMIS 0.25x0.25 SOe.g. TEMIS 0.25x0.25 SO2 2 gridded productsgridded products))

An Example from AIRSATAn Example from AIRSAT::Data from WDC-RSAT (World Data Center for Remote Sensing Data from WDC-RSAT (World Data Center for Remote Sensing of the Atmosphere http://wdc.dlr.de) of the Atmosphere http://wdc.dlr.de)

geographical areageographical area

data setdata set

time periodtime period

daily data in ascii formatdaily data in ascii format

daily mapsdaily maps

start animationstart animation

select coordinatesselect coordinates

animationanimation

3.3. Automatic Plume Detection Automatic Plume Detection::Within AMFIC data base we initiate the implementation of image Within AMFIC data base we initiate the implementation of image analysis techniques for the automatic plume detectionanalysis techniques for the automatic plume detection

Three steps procedure:Three steps procedure:

1.1. Reconstruct the missing parts of maps (images), which lack Reconstruct the missing parts of maps (images), which lack information due to the daily coverage stripes of several satellite information due to the daily coverage stripes of several satellite instruments or due to cloudiness, albedo characteristics etc, instruments or due to cloudiness, albedo characteristics etc, with the use of with the use of Cellular Automata (CA)Cellular Automata (CA)..

2.2. Extract only the regions on the map which are covered by Extract only the regions on the map which are covered by significant plumes with the use of a cut-off filter.significant plumes with the use of a cut-off filter.

3.3. Calculation of the area covered from each plume.Calculation of the area covered from each plume.

Cellular Automaton approachCellular Automaton approach::

A A cellular automaton requires:cellular automaton requires:1.1. a regular lattice of cells covering a portion of a four dims space a regular lattice of cells covering a portion of a four dims space

2.2. a set of variables a set of variables CC attached to each cell giving its local state at the time attached to each cell giving its local state at the time t=0, 1, 2, …t=0, 1, 2, …

3.3. a rule a rule R={RR={R11,R,R22,…,R,…,Rmm}} which specifies the time evolution of the which specifies the time evolution of the

states in the following way: states in the following way:

where designate the cells belonging to a given neighborhood of cell where designate the cells belonging to a given neighborhood of cell

1 2( , ) ( , ), ( , ),..., ( , )mC r t C r t C r t C r t

r

( , )C r t

1 2( , 1) ( ( , ), ( , ), ( , ),..., ( , ))j j qC r t R C r t C r t C r t C r t

r

r

In our case each cell is represented by an image pixelIn our case each cell is represented by an image pixel

The rule R applied here is the extraction of the The rule R applied here is the extraction of the average from pixels in the neighborhood (Moore average from pixels in the neighborhood (Moore neighborhood ) that contain informationneighborhood ) that contain information

An example for GOME-2An example for GOME-2::GOME-2 aboard MetOp-A (October 2006)GOME-2 aboard MetOp-A (October 2006)

• 44 channels cover the full spectral range from 0.240 to 0.790 µm channels cover the full spectral range from 0.240 to 0.790 µm • Resolution 0.2-0.4 nmResolution 0.2-0.4 nm• Pixel size 80x40 kmPixel size 80x40 km22

• Scan width 1920 kmScan width 1920 km• Global coverage within 3 dayGlobal coverage within 3 day

Input Input NO2 daily mapsTEMIS website

Process 1Process 1Reconstruct the

missing parts

Process 2Process 2Define areas withsignificant plumes

Process 3Process 3Calculate the area each plume covers

NONO22 daily maps from TEMIS web data base daily maps from TEMIS web data base www.temis.nl

Time period 28/3/2008-6/4/2008Time period 28/3/2008-6/4/2008

28/3 29/3 30/3 31/3

1/4 2/4 3/4 4/4

5/4 6/4






missing parts



Reconstructed maps (images)Reconstructed maps (images)Time period 28/3/2008-6/4/2008Time period 28/3/2008-6/4/2008

28/3 29/3 30/3 31/3

1/4 2/4 3/4 4/4

5/4 6/4






missing parts



Define areas with significant plumes using color filters Define areas with significant plumes using color filters Time period 28/3/2008-6/4/2008Time period 28/3/2008-6/4/2008

28/3 29/3 30/3 31/3

1/4 2/4 3/4 4/4

5/4 6/4






missing parts



Calculate the areas covered from significant plumes Calculate the areas covered from significant plumes Time period 28/3/2008-6/4/2008Time period 28/3/2008-6/4/2008

28/3 29/3 30/3 31/3

1/4 2/4 3/4 4/4

5/4 6/4

If we have larger stripes (e.g. SCIAMACHY daily maps) … If we have larger stripes (e.g. SCIAMACHY daily maps) … Example for 28/3/2008Example for 28/3/2008

vsvs vsvs

3.3. Work to be done… Work to be done…Data to be analyzed and uploaded to the data base within the Data to be analyzed and uploaded to the data base within the next months:next months:

• SCIAMACHY & OMI Tropospheric NOSCIAMACHY & OMI Tropospheric NO22 data data 2003-end of project2003-end of project

• SCIAMACHY Tropospheric HCHO data SCIAMACHY Tropospheric HCHO data 2003-end of project2003-end of project

• For the time being the image analysis algorithm runs off-line For the time being the image analysis algorithm runs off-line Either it will be integrated in AMFIC web data base so as to run on-line Either it will be integrated in AMFIC web data base so as to run on-line or the matlab codes will be available to the users via linksor the matlab codes will be available to the users via links

• The integration of AIRSAT is being scheduled The integration of AIRSAT is being scheduled

Aristeidis K. GeorgouliasAristeidis K. Georgoulias

Konstantinos KourtidisKonstantinos Kourtidis

Konstantinos KonstantinidisKonstantinos Konstantinidis

AMFIC Web Data BaseAMFIC Web Data Base

AMFIC Annual Meeting - AMFIC Annual Meeting - Beijing 16-17 October 2008Beijing 16-17 October 2008

Democritus University of ThraceDemocritus University of ThraceLaboratory of Atmospheric Pollution and Pollution Laboratory of Atmospheric Pollution and Pollution Control Engineering of Atmospheric PollutantsControl Engineering of Atmospheric Pollutants

谢谢谢谢Thank youThank you

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Aristeidis K. Georgoulias Konstantinos Kourtidis Konstantinos Konstantinidis AMFIC Web Data Base AMFIC Annual Meeting - Beijing 16-17 October 2008 Democritus