1 / 30

G Hayman 1 , E Blyth 1 , D Clark 1 , F O'Connor 2 , M Dalvi 2 and N Gedney 2

G Hayman 1 , E Blyth 1 , D Clark 1 , F O'Connor 2 , M Dalvi 2 and N Gedney 2 1 Centre for Ecology and Hydrology (UK); 2 Met Office Hadley Centre (UK) 28 th February 2012. Land Surface Modelling: The ALANIS Methane project. Contents and acknowledgements. Contents. Background

rbutler
Download Presentation

G Hayman 1 , E Blyth 1 , D Clark 1 , F O'Connor 2 , M Dalvi 2 and N Gedney 2

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. G Hayman1, E Blyth1, D Clark1, F O'Connor2, M Dalvi2 and N Gedney2 1 Centre for Ecology and Hydrology (UK); 2 Met Office Hadley Centre (UK) 28th February 2012 Land Surface Modelling: The ALANIS Methane project

  2. Contents and acknowledgements Contents • Background • ALANIS Methane project • Land surface modelling with JULES • Key Messages and future activities Acknowledgements • ALANIS Methane project partners • European Space Agency • iLEAPS

  3. ALANIS Methane: Project aims, objectives and outputs Aims and Objectives • To produce relevant Earth Observation products for land surface modelling of the methane emissions from wetlands • To improve the emission estimate of methane from boreal Eurasian wetlands Outputs • Earth Observation datasets relevant to methane emissions from wetlands • Modelled emission flux estimates from wetlands • Peer-reviewed papers

  4. Background • Wetlands are largest natural source but there are large uncertainties • CH4 wetland emissions by diffusion across the soil or water interface, by ebullition (bubbling), and by plant-mediated transport US EPA, 2010 • Key parameters for land surface and climate modelling: • wetland extent • temperature • soil carbon 4 Source: http://www.riceweb.org/reserch/Res.issmethane.htm

  5. ALANIS Methane: EO products for large-scale land surface modelling Column CH4 (Bremen) JULES (CEH) Wetland Extent (CNRS/Estellus) Surface State (Vienna)

  6. ALANIS Methane: Focus on Northern Eurasia, 2007-2008 • Test Site #1: Western Siberia (N) • Subarctic-Arctic • continuous to discontinuous permafrost • hotspot of lake change • Test Site #2: Western Siberia (S) • Boreal • Ob river floodplains • sporadic to discontinuous permafrost • extensive peatlands • Test Site #3: Lower Lena River floodplain and delta • Subarctic to High Arctic lowlands • key region for understanding the basic processes of the dynamic and development of permafrost in the Siberian Arctic • upstream basin with flood plains • extensive delta area with several terraces 6

  7. Estellus: Regional Wetlands Extent and Dynamics • Existing product • Use satellite data at different wavelengths (ERS scatterometer, SSM/I, AVHRR) • Global coverage with spatial resolution compatible with climate studies • Long time series (1993-2007) • Several publications [Prigent et al., GRL, 2001; JGR, 2007; Papa et al., JGR, 2010] • For ALANIS methane, adjustments in methodology • Use MetOP ASCAT scatterometer data • Higher temporal resolution (10 days from monthly)

  8. TU Wien: Surface Water Bodies • New product based on ENVISAT ASAR Wide Swath • Classification of open water surfaces, 10-day updates for maps of wetland dynamics • Cross-comparison with the regional wetland product planned June 2007 September 2007

  9. TU Wien: Snowmelt and Ground freeze/thaw • Metop ASCAT • Algorithm development based on ECMWF ERA-Interim soil temperature • Post-processing to identify day of year • Begin of thaw • End of thaw • Refreeze

  10. SCIA WFMD v2.0.2 Schneising et al., ACP, 2011 NOAA surface CH4 South Pole IUP, Bremen: Sciamachy atmospheric column methane Recent increase (~ 7-8 ppb/yr) Noisier after Oct. 2005 due to detector degradation

  11. JULES – Modelling methane emissions from wetlands FwCH4 = kCH4* fw * Cs * Q10(Tsoil)(Tsoil-T0)/10 FwCH4 = methane flux from wetlands kCH4 = scaling factor fw = wetland fraction Cs = “substrate”: fixed soil carbon content Q10 = temperature sensitivity • Gedney et al [2003, 2004] parameterisations of large-scale hydrology and wetland biogeochemistry • Modelled wetland fraction is based on soil moisture saturation • Current version has no overbank inundation • Can be used in different configurations: • Point/Offline • Gridded/Offline • Coupled into atmospheric chemistry model http://www.jchmr.org/jules/ 11

  12. Use of EO products with JULES • Inundation products • Test ability of JULES to reproduce spatial and temporal patterns of ’wetland’ extent • Products can be to evaluate (’constraint’) or define (’driver’) wetland extent • Surface state • Test soil physics in JULES • Products can be to evaluate (’constraint’) • Sciamachy CH4 columns • Test of JULES wetland scheme • NOTE: Other products also being used (e.g., Land surface temperature, snow cover, ....)

  13. JULES Offline model configuration • Several versions of JULES, resolutions and input datasets have been used. • Runs presented here use: • JULES v3.0 (the latest version) • 0.5x0.5° global grid (some runs on test areas only) • CRU-NCEP 6-hourly meteorological data • New input fields (“ancillary files”) for this grid including topographic index data from Hydro1k • TOPMODEL-based parameterisation of wetlands (and runoff generation) • Prescribed vegetation (no dynamic vegetation model) 13 Background Boreal Wetlands African Wetlands Future/Summary

  14. Offline JULES vs. EO Regional Wetland product Estellus JULES Western Siberia Lena 1st -10th September 2007

  15. Regional Wetland product: Area averages North Western Siberia (North+South) South

  16. Offline JULES vs. EO Surface State product: area averages Lena Western Siberia (North+South) • Timeseries of fraction of area with frozen ground • Currently no direct equivalent diagnostic in JULES • Use frozen and/or melting fraction • ‘Autumn melt’ events in JULES.

  17. Comparison with TU Wien Surface Soil Moisture product Circumpolar product, regridded to 0.5°. Soil moisture (as fraction of maximum) on 15th April 2007.

  18. Comparison with Surface Soil Moisture product: Area averages Lena Western Siberia (North+South) Some differences in seasonality. Amplitude good.

  19. Surface Soil Moisture product: 1st-10th September 2007 Western Siberia (North+South) TU Wien JULES

  20. JULES as land surface module in HadGEM2/3-A • Intention to use latest generation Hadley Centre climate model (HadGEM3) : • Can be nudged to observed meteorology • Regional configurations available • Initial runs showed that the configuration of the model used was not ‘reactive’ enough; this could not be corrected by tuning of parameters • Reverted to HadGEM2-ES • Used for IPCC AR5 Assessment • Paper in GMD [Collins et al., 4, 1051, 2011] • Nudged version of ‘optimised’ AR5 HadGEM2-ES run created UKCA tropospheric chemistry scheme Emitted species: CO, NOx , CH4, C2H6, C3H8, HCHO, CH3CHO and CH3COCH3

  21. JULES: HadGEM2 AR5 CH4 emission inventories • All sources (526 Tg CH4 per annum) • All sources except wetlands (345 Tg CH4 per annum) • Wetlands from Fung et al (1991) (181 Tg CH4 per annum)

  22. JULES: Wetland emissions for ALANIS

  23. Wetland emissions • Modelled 2000-2005 period using different wetland emission scenarios: • ‘AR5’ distribution based on Fung et al. (total =181 Tg pa) • JULES masked by EO (total =181 Tg pa) • JULES driven with EO (total =181 Tg pa) • JULES driven with EO (total =200 Tg pa) • JULES driven with EO (total =165 Tg pa) • JULES unconstrained not used

  24. Model runs for ALANIS methane • HadGEM2-ES • Year-on-year sea surface temperatures and sea ice distribution • Nudged using ECMWF ERA40 • Created year-on-year emission inventories • EDGAR v4.2 for anthropogenic, shipping and aviation • GFED v3.1 for biomass burning (scaled to give AR5 decadal mean) • Natural sources as used before • NOTE increase in anthropogenic CH4 (and other) emissions (*) • (*) See Monteil et al, ACP, 2011

  25. Comparison with surface measurements AR5 emissions JULES (masked) JULES+EO • Atmospheric Methane Dry Air Mole Fractions, 1983-2009 • NOAA ESRL Carbon Cycle Cooperative Global Air Sampling Network • Used 15 sites

  26. Comparison with Sciamachy: Annual mean (preliminary) • xgxja: AR5 emissions based on Fung et al. [1991] • xfzal: JULES wetland emissions masked with EO • xfzam: JULES wetland emissions with EO wetland fraction

  27. Comparison with Sciamachy: Zonal means (preliminary) • Black: Sciamachy • Red: AR5 wetlands [Fung et al., 1991] • Green: JULES (masked) • Blue: JULES (EO) • Blue lines: JULES (EO) sensitivity runs

  28. HadGEM Next Steps and Summary Next steps • Check the spatial patterns of the wetland emissions – rice/paddy fields: in progress • Investigate column profiles (fall off of methane too strong in UKCA??): Sciamachy stratospheric CH4 products • Further model runs, potentially including those from inverse modelling (to 2008) Summary • Nudged version of HadGEM2-ES setup to investigate wetland methane emissions • First use of Sciamachy to test model performance; preliminary analysis indicates that the model underestimates the methane column, greater than differences in inventories • Value of EO inundation product (increases extra-tropical contribution)

  29. Website and Data Dissemination http://www.alanis-methane.info

  30. Summary and future activities Summary • New EO products developed relevant to methane emissions from wetlands • EO and emission datasets produced for boreal Eurasia for 2007-2008 • Land surface modelling using the UK JULES model in 3 configurations • EO products have identified areas for improvement in the model in hydrology and biogeochemistry Future activities • Ongoing activities to model wetlands (through NERC grants on African and high latitude wetlands) • Established links with UKCA team (Cambridge/Met Office) • Developing links with NCEO atmosphere (Palmer, Chipperfield) • Bring insight gained from NCEO Atmosphere and Land themes into forward modelling • Longer term – benchmarking datasets

More Related