2009-06-15: Atm. Composition Workshop, Frascati

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Title: 2009-06-15: Atm. Composition Workshop, Frascati Date: 2009/6/15 Location: Frascati, IT Report Formats: [No PPT] | [No Screencast] [No Word] | [No PDF]

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Atmospheric Composition Constellation (ACC) Workshop on Air Quality, 15 - 17 June 2009, ESA/ESRIN, Frascati, Italy

Workshop report

http://ceos.org/

In support of the Group on Earth Observations (GEO) objectives and as a space component of the Global Earth Observation System of Systems (GEOSS), CEOS has developed the concept of virtual space-based Constellations. The Constellation concept builds upon or serves to focus existing projects and activities and provides a means to maximize the value of existing space assets among partners. A goal of a Constellation is to demonstrate that added value can result through partnership among the space agencies and their supported institutions.

The Atmospheric Composition Constellation (ACC) focuses on observations needed for understanding and to improve predictive capabilities for changes in the ozone layer, climate forcing, and air quality. At the present time, ten space agencies are collaborating in ACC and have established three projects to demonstrate how added value can be obtained by combining satellite data sets. These initial projects are directed towards applications which focus on GEO Societal Benefit Areas (SBAs) including Air Qaulity. Human industrial activities including the combustion of fossil fuels, land-use and biomass burning, lead to the emission of gases and particles, which pollute the air. Once aloft, air pollution can travel long distances and as a result, it is a global problem. Air Quality monitoring at urban and regional scale is typically performed using in-situ measurements and regional models. Space-borne measurements provide now global coverage complementing in-situ data. The purpose of this ACC-Workshop is:

• to review the current accuracy of space based tropospheric measurements (in particular sulphur dioxide, nitrogen dioxide, carbon monoxide, ozone and particulate matter)
• to see if existing satellite measurements are already able to provide value-adding information to air quality monitoring in addition to in-situ data
• to review the need of future space based air quality monitoring missions.

This workshop will be organized around oral presentations of experts in atmospheric satellite retrieval and data assimilation (combining ground-based and satellite measurements), and end –users, who monitor on regular basis air quality. The workshop outcomes and recommendations will be reported to the CEOS agencies.

Contents 1 Wed Discussion 2 Intro Background Approach 3 Integration Ideas 4 Applicatios 5 GEOSS 6 ACC 7 Future

[edit] Wed Discussion

1. Do satellites add value & limitations
2. Future ACC virtual constellations
3. How should we work together

• Synergy, a priori assumptions
• Synthesis of data models
• Earny, other ES data needed for forecasting
• UAH Jack Moving from global to (sub)regional different processes;
• physics is diurnal, need vertical soundings key params (lidar PM o3 EARLINET,
• Jack CEOS should support vertical
• Future LEO, GEO looks good EU & China; hurry up id and develop applications;
• Which app infrastructure to invest in
• Limitations : - pollutant emission, PBL
• Harmonization instruments,

[edit] Intro Background Approach

• Goal: Characterization (multidimensional Pattern)
• Approach: Obs-Emission-Model framework
• Reconciliation internal to each; among the three

• Global-Local
  • Multi-Scale

[edit] Integration Ideas

• OMI NO2 + Elevation
• OMI NO2 + Emission
• OMI NO2 + Tropo
• Satellite Integral & Surface conc -> scale height
• Smoke, dust delpetes bright, incterses dark obejts
• Alaskee plume IR,

• Table: Sensor vs AerParameter

[edit] Applicatios

• HTAP
• Except Event
• Trend-Assessement

[edit] GEOSS

• Datasets

Sensors:

1. MODIS
2. MISR
3. POLDER
4. OMI_AOT
5. OMI AI
6. ATSR
7. AVHRR
8. GOES
9. METEOSAT

1. PICASO
2. SAGE

[edit] ACC

Unique opportunity for conducting AC science and providing Societal Benefits using multiple instruments across international platforms

• Collaboration efficiency: take advantage of each instrument’s unique capability
• Cross instrument validation
• Improved spatial and temporal coverage: e.g. different equator crossing times
• Enhanced data products: e.g. aerosol and cloud characteristics, pollution and its transport for assessments and forecasting
• More accurate trends by comparing and combining data sets

Synergies provided by the Constellation should substantially improve accuracy and coverage of satellite data and result in improved Atmospheric Composition science and application capabilities

• International scientific forum for debating priorities and formulating future Atmospheric Composition missions
• Opportunity for participating space agencies to cooperate in planning, developing, and operating future missions.
• The Constellation will allow for an efficient response to new requirements as the Earth system responds to climate change

Aerosols – Climate models need improved measurements of aerosol properties (type, size, shape, scattering, absorption, optical depth) and abundance (horizontal location, vertical profiles). This requires a variety of measurements such as nadir imagers/spectrometers, limb spectrometers, lidars, and polarimeters. Further analysis of aerosol requirements and measurement plans is needed to assess potential measurement gaps.

Air Quality - Tropospheric composition effects of air quality on climate require the measurement of key species in the near-surface boundary layer and free troposphere. Profiling and occultation partially satisfy these measurement requirements, but geosynchronous missions are needed for higher temporal sampling. Gaps in limb profile missions and delays in GEO mission plans will impact advancements in this area. www.symbioscomms.com/ceos2008/files/Item10_1_CEOS22_Killough_Plenary08_ACCStatus_v7.ppt

Unique opportunity for conducting AC science and providing Societal Benefits using multiple instruments across international platforms • Collaboration efficiency: take advantage of each instrument’s unique capability • Cross instrument validation • Improved spatial and temporal coverage: e.g. different equator crossing times • Enhanced data products: e.g. aerosol and cloud characteristics, pollution and its transport for assessments and forecasting • More accurate trends by comparing and combining data sets http://www.oosa.unvienna.org/pdf/sap/2007/graz/presentations/05_02.pdf

[edit] Future

• Geostationary Tiros satellite 1960's first and last
• Data fusion - Sensor level more params to constrain the retrieval, ... feature level to eliminate bad systematic retrievals
• Ensemble data pack so find the outliers