EUROPEAN PARLIAMENT

Science and Technology

Options Assessment

S T O A

Avoiding Ash DisruptionsCan technology help to manage air space better?

WORKSHOPWednesday, 23 June 2010

9:30-11:30 a.m., Room ASP 5G3European Parliament, Brussels

Takashi MORIYAMA, Ph.DJapan Aerospace Exploration Agency (JAXA)

moriyama.takashi@jaxa.jp

TANSO onboard GOSAT TANSO onboard GOSAT TANSO=TANSO=TThermal hermal AAnd nd

NNear infrared ear infrared SSensor for ensor for carbon carbon OObservationbservation

TANSO-CAITANSO-CAI

(Cloud and Aerosol (Cloud and Aerosol Imager)Imager)Ultraviolet , visible, NIR and Ultraviolet , visible, NIR and SWIR SWIR

TANSO-FTSTANSO-FTS(Fourier Transform (Fourier Transform Spectrometer)Spectrometer)-NIR, SWIR and TIR-NIR, SWIR and TIR

Organization

•Sensor development •Satellite development•launch •Satellite operation•Data acquisition•Data processing (L1)•Calibration•Data distribution

•Sensor development•administration

•Algorithms development•Data processing (L2 or higher) •Data use for science •Validation•Data distribution

3

4

The picture of GOSAT flight model taken at the launch site

Size Main body

3.7m x 1.8m x 2.0m

(Wing Span 13.7m)

Mass Total 1,750 kg

Power Total 3.8 kW(EOL)

Life Span

5 years

Orbit sun synchronous orbit

Local time

13:00+/-0:15

Altitude 666km

Inclination

98deg

Recurrent Period

3 days

Launch Vehicle H-IIA

23rd January 2009

Satellite Characteristics

Band

No.

Observation

Band(nm)

Center Wavelengt

h(nm)

IFOV(km)

FOV(km)

No. of Pixels (cross track)

1 372-387 380 0.5 1000

2000

2 667-680 678 0.5 1000

2000

3 866-877 870 0.5 1000

2000

4 1560-1640 1620 1.5 750 500

TANSO-CAI is operated together with TANSO-FTS to - detect aerosol spatial distribution and cloud coverage

TANSO-CAI Specifications

In-Orbit CAI Operation

Solar Ray

Lunar Calibratio

n

Extent of the CAI observation

Hatoyama, Japan

Tsukuba Space Center, JAXA, Japan）

to NIES

Kiruna Tracking Station, Sweden

Santiago Satellite Station,

Perth Satellite Station, Australia

Maspalomas Satellite Station, Gran Canaria

Svalbard Satellite Station, Norway

The Operation Network

Level 2 and 3 Processing 　　 - cloud flag (L2) - global radiance distribution (L3) - global reflectance distribution (L3)

Level 2 and 3 Processing 　　 - cloud flag (L2) - global radiance distribution (L3) - global reflectance distribution (L3)

NIES

MeasurementMeasurement

Receive and RecordReceive and Record

JAXA

Data distribution

Level 1B and L1B+ Processing - images

Level 1B and L1B+ Processing - images

Level 1A processing - satellite downlink format to numerical data

Level 1A processing - satellite downlink format to numerical data

Data Products of CAI

8

Datatransmission

L1A Data

First CAI Data (7 Feb.,2009)

9

Observation ResultsCO2 column averaged dry air mole

fraction

April May June

July

October November December

January

Under Processing

not observed

August September

February March10

Observation ResultsCH4 column averaged dry air mole

fraction

April May

October

Under Processing

not observed

June

July August

December

September

March

November

FebruaryJanuary11

An International Cooperative for Aerosol Prediction: Workshop on Aerosol Observability Issues

http://bobcat.aero.und.edu/jzhang/ICAP/27-29 April, 2010Monterey CA Send comments to

jeffrey.reid@nrlmry.navy.milangela.benedetti@ecmwf.int

peter.r.colarco@nasa.gov

EUMETSAT

Workshop Rationale1) There is a long history for global meteorology forecasting. This does not exist for aerosol forecasting or chemical weather forecasting (CWF) in general: Needed a venue for operational developers to discuss research to operations issues, protocols and metrics.

2) There are few “Operational” data sources and infrastructure for CWF: Needed to discuss currently available and future data products to support aerosol data assimilation/initialization and model verification.

3) CWF is in its infancy and needs to draw heavily from the research community. Conversely, many research programs are looking more like “Operations” and are operations/natural hazards relevant: Relationships needed to be developed across communities for the benefit of all Earth System Science (ESS) stakeholders.

Pressing Issues for Both Climate and Operational Communities.

• Future aerosol products: Terra/Aqua has been a cornerstone for research and development. There is concern as the community migrates to NPP, JPSS, EarthCARE, GCOM-C1, Decadal Survey, GOES-R etc…

• Model needs: Even with current aerosol products, most are not designed with model customers in mind . Error models and propagation of error are hardly ever addressed by developers.

• Multi-sensor fusion: You think working with one sensor is hard? Try 2, 3 or 4… How do we deal with the changing constellation of sensors and products with regards to initialization and data assimilation? Product versus radiance assimilation?

• Competition: Competitive products from the same data source are often seen as a bad thing by agencies. Actually, there is nothing farther from the truth-as long as they are available and supported.

Passive Sensors of the Next Decade

• MODIS: Still the workhorse with available NRT data from NRTPE and now NASA LANCE.

• AVHRR: Available for a long time over water, but with MODIS available operations has been hesitant to migrate.

• OMI: Data available with permission from LANCE.• GOME-2: OMI like aerosol products under development.• MSG/SEVERI: Best available geostationary platform for aerosol.• GOES-GASP: Available but not yet fully investigated.• Glory (2010-11): Aerosol microphysics, but limited swath and NRT

capability.• NPP/JPSS VIIRS (2012/2015): Expected to be the follow-on for MODIS

users for both aerosol and fire. But: Different algorithm and only one 13:30 LST overpass per day (versus twice for Terra and Aqua).

• EarthCARE MSI (2013): Limited swath but great potential partner with VIIRS if NRT data is available.

• GCOM-C2 (2014): Will carry very powerful interdisciplinary moderate resolution imager with expected NRT data production.

• MeteoSat Third Generation-MTG(2015): Next generation European geostationary with good aerosol and fire capability.

• GOES-R (2015): Next generation American geostationary with good aerosol and fire.

• NASA Decadal Survey? Ocean imager and Atmosphere Clouds and Environment (ACE) have uncertain timelines.