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Contacts: Jean-Christopher LAMBERT and Bojan BOJKOV

A possible contribution of the ISSI WG on Atmospheric H 2 0 to GEO-CEOS WGCV activities. Contacts: Jean-Christopher LAMBERT and Bojan BOJKOV j-c.lambert @ aeronomy.be, bojan.bojkov @ nasa.gov. H 2 0 contributes to several Societal Benefit Areas as defined by the GEO.

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Contacts: Jean-Christopher LAMBERT and Bojan BOJKOV

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  1. A possible contribution of the ISSI WG on Atmospheric H20 to GEO-CEOS WGCV activities Contacts: Jean-Christopher LAMBERT and Bojan BOJKOV j-c.lambert @ aeronomy.be, bojan.bojkov @ nasa.gov

  2. H20 contributes to several Societal Benefit Areas as defined by the GEO

  3. GEO Task DA-06-02 assigned to CEOS WGCV Committee on EO Satellites: http://www.ceos.org WG on Calibration and Validation: http://wgcv.ceos.org • Relevant topics: • Characterisation and Classification of Cal/Val Sites • Satellite and InSitu Cal/Val Data Access • Methodology and Guidelines for Cal/Val • Harmonisation of Quality Information

  4. Establishing Best Practices in Atmospheric Composition Cal/Val Current Status • No ISO-type standards for validation • Mostly "traditional practices" • "Best practices" depend on: • Atmospheric species • Atmospheric state, measurement conditions • Measurement technique • Target user of validation results • Target user ofobservation data • Resources for validation

  5. Establishing Best Practices in Atmospheric Composition Cal/Val Contribution of ISSI WG on H2O? • Characterise data and sites => fact sheets • For every technique, identify (published or commonly agreed) best practices for data comparison and for satellite validation • Define own data quality strategy, data policy, data access, operational status • The ISSI book might be an excellent reference document for/endorsed by CEOS. • Relevant information to appear also on CEOS Cal/Val portalhttp://calvalportal.ceos.org

  6. Annex 1: Tentative list of generic H2O data users • Instrument and calibration scientists • Geophysical validation of satellite observations • Developers of retrieval algorithm (first guess and covariance, sensitivity studies…) • Radiative transfer: atmospheric correction (IVOS), climate forcing (GHG)… • Chemistry: heterogeneous chemistry, source of OH, reservoirs, diurnal cycles… • Dynamics • Microphysics • Evaluation of CT modelling and data assimilation: R&D, operational verification • GMES-like service (validation) scientists • Independent audit of GMES-like services and of their validation • International organisations: SPARC, WMO, EMEP…

  7. Annex 2: Generic timeliness of data delivery and quality classes Class 1: <3-6 hours, NRT Q: NRT verification of forecasts Class 2: <one month, NRT Q: stability of uncertainties Class 3: < 3-6 months, NRT/best Q: mid-term assessment Class 4: best Q: accurate validation after every cycle of one year and after every processor upgrade

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