GlobModel

1. GlobModel The GlobModel study, initial findings and objectives of the day Zofia Stott 13 September 2007

2. Objective of presentation/contents • Background to the GlobModel study • Preliminary conclusions of the study • Objectives of the day

3. Background to the GlobModel study • EO data-model fusion is a relatively new area for ESA • DUE Glob-projects • Summer schools • Ad hoc collaborations, eg with ECMWF • Fact finding • Programmes, initiatives, organisations, people • European focus • Also international programmes, eg IGBP, WCRP • Analogies with US where appropriate • Opinion seeking • What are the issues for the European community? • Strategy and implementation plan for ESA • Where should ESA be involved? • How should ESA be involved? AnalysisReport Workshop

4. Background to the GlobModel study • Scope • Numerical Weather Prediction • Re-analysis • New (pre)-operational services, eg GMES Fast Track services • Ocean forecasting • Chemical weather forecasting • Global change and Earth system science • EO data-model fusion • Data assimilation • Ancillary surface data fields • Model validation

5. Background to the GlobModel study • GlobModel hypothesis • Understanding, forecasting and predicting the behaviour of the Earth system depends on • Data and models working together • Satellite data are key • Progress is accelerated by collaboration between the science base and operational services • Objective is to create a “virtuous circle” • High scientific return • Linked to new operational services • Leading to investment in both new research and operational missions

6. Background to the GlobModel study • Specific requirements/issues • The role of OSSE and OSE in quantifying the impact of particular data streams • Concerns about data continuity over the next 10 years • Areas where new or improved instruments are required • Novel data products specifically tailored for model assimilation (eg radiances V retrievals V gridded fields) • Improved techniques for EO data-model fusion (eg development of new data assimilation techniques, observation operators) • Intercomparison and cross validation of different data sets • Improved model development environments which include consideration of EO data issues • Standardisation and harmonisation of EO data formats, data discovery and data access • Improved quality control • Software tools to support the use of EO data streams • Real time delivery and long term curation • Provision of high level products, eg model independent reanalyses • Shared high performance computing environment • Training.

7. Preliminary recommendations – OSE, OSSE “The Global Observing System”, Jean-Noël Thépaut, Data Assimilation Training Course, ECMWF Reading, 25 April- 4 May 2007

8. Preliminary recommendations – access to operational systems • Make operational systems more readily available for research • Mutual benefit • Scientists work on topics of interest to operational agencies • Benefit from operational facilities (models, computer resources, expert help) • Operational agencies benefit from latest research results • Increases chances to technology transfer from research base to operations

9. Preliminary recommendations – integrated data systems • Increase emphasis on integrated data systems for new services • Optimise in situ and satellite components • Eg What is the balance between Argo floats and altimeters? • GODAE/GHRSST/Medspiration projects optimising sea surface temperature retrievals could be taken as an example of good practice

10. Preliminary recommendations • Develop observation operators • Fundamental link between data and models • Essential to ensure early take up of data into operational systems • Commit to long term continuity of re-analysis • Develop the use of EO data in the land and cryosphere components of the Earth system models • Develop “climate” quality data sets

11. Preliminary recommendations - people • Ensure that the right mix of people/institutions are brought together • Experts on satellite data processing, retrievals • Experts on operational data assimilation systems • Experts on Earth system modelling in the research community • Members of satellite instrument and/or science teams • Participants in the cal-val effort • Members of the satellite data management teams.

12. Preliminary conclusions – provide a science focus • Address the big science issues • Develop regional climate models able to identify “tipping points” in the climate system • Understand link between physical and biological feedbacks in carbon cycle • Understand links between climate change and atmospheric composition • Develop coupled sea-ice and ocean circulation models • Develop improved ability to model hydrological cycle and predict high impact weather • Develop ecosystem and biodiversity models

13. Objectives of the day - Splinter sessions • Where are we today? • What are the key issues? • What is your vision for Earth system modelling in 10 years time? • What will we be able to do which we cannot do today? Eg • Forecast on an annual/decadal and regional basis? • Forecast high impact weather? • Identify and monitor all climate tipping points? • What role should EO play in achieving our goals? • What programmes and projects would you recommend to ESA to fulfil your objectives?

14. Backup slides

15. NWP I • Developments driven by operational requirements of forecasting centres • New services • Seasonal and inter annual forecasts • High impact weather • New and improved services, based on • Better models • Better data • Satellite data are key • Innovation needs close links between R&D and operations

16. NWP II • Pull through of satellite data for NWP, in Europe • Strong for meteorological data sources • Eg via EUMETSAT SAFs • Weaker for non EUMETSAT data • Ad hoc • But good examples of transfer from research to operational status eg scatterometer, GOME, altimetry • Key satellite requirements • Low level (1B/C) radiances • Some retrievals (eg Atmospheric Motion Vectors) • Surface gridded fields • Real time delivery (<1 hour) • BUFR, GRIB • High priority issues • Improved coupled models • Use of satellite radiances over land, cloud • Hydrological cycle • Improved surface representation/assimilation

17. NWP III • Increasing experience of OSE, OSSE • Quantify impact of satellite data on NWP • Comparison of Europe with USA • JCSDA • NASA/NOAA initiative • To accelerate take up of new data sources

18. NWP IV “The Global Observing System”, Jean-Noël Thépaut, Data Assimilation Training Course, ECMWF Reading, 25 April- 4 May 2007

19. NWP V “The Global Observing System”, Jean-Noël Thépaut, Data Assimilation Training Course, ECMWF Reading, 25 April- 4 May 2007

20. NWP VI • Messages from NWP • NWP key for operational data assimilation • 40 years of infrastructure and capability • Need to work effectively with NWP centres • EUMETSAT, ECMWF, national met offices • No equivalent of GMAO or JCSDA in Europe • No systematic mechanisms for accelerating transfer of research data sources to operations • ADM, SMOS already identified by ECMWF

21. Reanalysis I • Long term (eg 40 years) global data sets of past climate using data assimilation • Reliant of latest NWP model + historical data • ECMWF leads in Europe • Key for • Understanding climate trends • Improving both models and data (biases) • Challenges • Need for improved coupled models • Inhomogeneities in data records

22. Reanalysis II • Messages from reanalysis • Long term missions needed • Repeats • Overlaps • Long term curation of data – a major challenge • European reanalysis projects are • “Add on” to existing activities, not core business • Funding ad hoc • No sustained European effort in reanalysis

23. “New” (pre)-operational forecasting I • Ocean forecasting • Chemical weather forecasting • Learning from current practice in NWP • Reliant on NWP either through loosely or tightly coupled models • GMES Core Services providing a European delivery structure • Far less technically mature than NWP • Requirements less precise • Techniques more experimental

24. “New” (pre)-operational forecasting II • Data types • Ocean forecasts • Broad correspondence between GMES Sentinel 3 and ocean forecasts (altimetry, SST, ocean colour) • Also ocean salinity (SMOS), sea ice thickness (Cryosat), gravity/geoid (GRACE/GOCE), wind/waves (scatterometer) • Chemical weather forecasting • Broad correspondence between GMES Sentinels 4/5 and chemical weather forecasting • Also METOP, MSG, ENVISAT, AURA instruments • PLUS NWP outputs (forcing fields)

25. “New” (pre)-operational forecasting III • Messages • Continued development through close research/operational interactions • Models immature in key areas of user interests, eg • boundary layer chemical forecasts • coupled physical-biogeochemical models and assimilation of ocean colour data • Need for better comparison between data and models • Standards, data formats are still evolving etc • GMES and INSPIRE are addressing this • Tools, training, common research hub to exchange data and models • Important to work with emerging structures • Eg EUROGOOS for ocean forecasting

26. Earth system science I • Developing GCMs • What’s new • Shorter timescales (from centuries to decades), more local impacts (from global to regional) • Representation of energy and hydrological cycle • Ocean variability and climate change signals • Developing land surface models in GCMs • Developing models of coupled atmosphere/ ocean/cryosphere

27. Earth system science II • Global carbon cycle • Quantifying surface fluxes • Quantifying role played by fire • Identifying weights of key processes in tropics for post-Kyoto negotiations • Atmospheric composition • Understanding interactions between climate change and atmospheric composition • Cryosphere • Strongest signals of climate change, but key processes poorly represented in models • Predictability of high impact weather • Monitoring, understanding, predicting behaviour of ecosystems • Impacts of natural resource depletion