Competence Center Environment & Sustainability of the ETH Domain www.cces.ethz.ch Modelling and experiments on land-surface interactions with atmospheric chemistry and climate (MAIOLICA) Nina Buchmann, Sonia Seneviratne (ETH Zurich) and the MAIOLICA consortium 1 Land surface-atmosphere interactions (IPCC 2007) 2
Global anthropogenic GHG emissions (in CO 2 -eq in 2004)! MAIOLICA whole suite of GHGs focus on nonfossil fuel emissions (IPCC, WGIII 2007) 3 Objectives of MAIOLICA 1. To improve our understanding of fundamental processes that contribute to emissions of GHGs, such as CH 4, N 2 O, CO 2, and H 2 O, from temperate, mid-latitudes terrestrial and lake ecosystems. 2. To investigate the interactions and the feedbacks among the terrestrial biosphere, the atmospheric composition and the climate. 4
Structure of MAIOLICA! bringing together 10 PIs from 5 institutions 5 Timing of MAIOLICA Future of project? CCES 2 nd Phase? CCES Funding for Activities 1 Feb 2012 Official end of phase 1 Final Science Meeting 1 Feb 2011 now 1 Feb 2010 4 th Science meeting Latsis Symposium 3 rd Science meeting Eruption of Ejyafjallajökull 2 nd Science meeting 1a + 1c 2 3a 3b + 3c 1 st Science meeting 1 Feb 2009 Start Act. 3b + 3c (global modeling) Change in PIs (Bey/EPFL! Buchmann+Peter/ETH) 1b Start Act. 1c (regional integration experiment) Start Act. 2 + 3a (vegetation + regional modeling) 1 Feb 2008 Start Act.1a + 1b (land and lake ecosystems) Approval of MAIOLICA 6
Activity 1: Characterizing Greenhouse Gases Fluxes To quantify and characterize net GHG budgets (H2O, CO2, CH4, N2O) of managed terrestrial ecosystems (grasslands, cropland, mixed and monoculture forests) To quantify and characterize net CH4 fluxes from different lake systems To perform a regional integration experiment based on ground-based, long-path, and aircraft measurements to examine sub-grid scale variability of GHG fluxes Instrument development Continuous & cross-calibration measurements Intensive field campaigns Wide range of vehicles 7 Benefits of long-term ecosystem flux studies Swiss Fluxnet 8
Benefits of long-term ecosystem flux studies Swiss Fluxnet Subalpine spruce forest, Davos based on Zweifel et al. 2010 New Phytologist 9 Lakes/Reservoirs A relevant CH 4 source? Total global CH 4 emissions: 582 Tg CH 4 yr -1, over 70% from natural sources (IPCC 2007) But: lakes & reservoirs not considered (only wetlands, ocean) Global lake CH 4 emissions: 8 to 48 Tg CH 4 yr -1 (Bastviken et al. 2004)! 2 to 12% of natural CH 4 emissions, ~ oceans Global reservoir CH 4 emissions: 70 Tg CH 4 yr -1 (St. Louis et al. 2000)! 40% of anthropogenic CH 4 emissions Different approaches within MAIOLICA: - direct measurements at lake/reservoir surface & in water - eddy-covariance measurements at shore & on water - aircraft measurements above lakes/reservoirs 10
Aircraft based CH4 flux estimates at Lake Wohlen Flight track 11 Aircraft based CH4 flux estimates at Lake Wohlen 12
Methane efflux of Lake Wohlen 13 Methane efflux of Lake Wohlen Different approaches compare well Lake Wohlen: Large CH 4 flux compared to other reservoirs All Swiss lakes/reservoirs: 2130 t CH 4 yr -1, negligible for total CH 14 4 emissions in Switzerland (about 1.4%)
Upscaling aircraft measurements Time sequence of footprints x CH4 emissions from ruminants Lagrangian Particle Dispersion Model simulations, each 3 min = time series of model simulated methane VMR along flight path Methane emission inventory Simulation Measurements 15 Upscaling aircraft measurements Time sequence of footprints Lagrangian Particle Dispersion Model simulations, each 3 min x Methane emission inventory CH4 emissions from ruminants = time series of Simulation model Regional integration experiments providemeasurements high resolution simulated methane VMR spatial information about GHG emissions along flight path Ruminants are dominant CH4 source in Switzerland Inventory probably still underestimates their CH4 emissions 16
Linking experiments and models Hartmann et al. 2010 17 Plant & Soil Linking experiments and models Experiments provide process understanding: Soil N2O and CH4 fluxes respond strongly to changes in soil moisture Hartmann et al. 2010 18 & Soil But continental upscaling must be done with Plant models
Activity 2: Developing Improved Schemes for GHG Emissions To incorporate advanced understanding of GHG emissions from vegetation and soils into scalable biogeochemistry module, using a dynamical vegetation model as test bed. To apply the dynamic vegetation model regionally and globally to quantify sensitivity of trace gas emissions to climate-induced changes in vegetation structure, composition and phenology. To determine appropriate spatial and temporal resolution to accurately represent GHG fluxes in complex Swiss terrain and at global scale given the heterogeneity of processes involved in GHG emissions. 19 Modeling biogenic emissions of CH 4 Goal 1: Define a transfer function to estimate CH 4 emissions Goal 2: Determine the importance of climate for CH 4 emissions Model Respiration Wetland CH4 Emissions Transfer function Model Respiration Wetland CH 4 emissions Satellite inundation data1993-2000 Model Runoff Model Inundation 1901-2005 20
Improving modeling of wetland CH 4 emissions LP-X CH 4 emissions vs. regression-based CH 4 emissions Evaluation of transfer models with increasing complexity 21 Impact of climate on wetland CH 4 emissions Decadal impact of ENSO on wetland CH 4 emissions Regional impact of ENSO on wetland CH 4 emissions 22
Activity 3: Quantifying Land-Atmosphere Interactions To explore existence and nature of interactions and potential feedback mechanisms between biosphere and climate, focusing on impact of global and regional biospheric emissions of species relevant for climate and air quality To develop improved regional climate model by including state-of-the art dynamic vegetation model To develop improved global chemistry climate model by including state-of-the art dynamic vegetation model To assess impact of resolution of climate forcings (precipitation, radiation, clouds, wind, ) for GHG emissions 23 Modelling of coupled interactions Coupled biophysical and biogeochemical feedbacks Biogeochemistry 24
Regional climate-vegetation modelling Coupled vegetation-climate model & biophysical feedbacks COSMO-Terra V4.0 V4.8 W/m 2 Radiation bias COSMO-CLM 2 Davin et al., submitted 25 Soil moisture impacts on heatwaves FCAP CTL PWP 17 22 27 32 37 42 47 52 Maximum mid-day temperature (summer) CTL: control PWP: dry FCAP: wet Jaeger and Seneviratne 2010, Climate Dynamics Teuling et al. 2010, Nature Geoscience 26
Modelling of coupled interactions: Chemistry-climate feedbacks Atmospheric physics Chemistry Land hydrology Vegetation 27 Chemistry-climate simulations SOCOL-LPJ: tropospheric chemistry ECHAM6-HAMMOZ: aerosol and gas-phase chemistry " Use maps and modules from Activity 2 for methane emissions ECHAM6- HAMMOZ Cropland area [%] Cropland area [%] Cropland area [%] ALCC?? CO 2 CH 4 1600 1700 1800 1900 2000 2100 Year A1 A2 A2 A2 A2,A3 A2,A3 SOCOL-LPJ transient simulation Transfer function Biophysical feedbacks (soil moisture, climate) 28
Atmospheric CH 4 lifetime CH 4 lifetime [yrs]" OH [ppt]" 0.094" 850 hpa! 0.092" 0.090" 0.088" 0.086" 1920" 1940" 1960" 1980" 2000" total! tropospheric! 1900" 1920" 1940" 1960" 1980" 2000" ENSO-effect on CH 4 wetland emissions atmospheric effect surface effect?! Activity 2 29 P. Kenzelmann (2009)! Next steps within MAIOLICA 1. Implement new CH 4 parameterization into global chemistry-climate models (Activities 2 " 3) 2. Compare ruminant CH 4 emissions vs. wetland emissions and forest sink in Switzerland (Activities 1 " 2) 3. Evaluate performance of soil moisture and biophysical feedbacks in CH 4 modules and global chemistry-climate models (Activities 3 " 2 " 1) 4. Role of resolution for feedbacks and emissions (Activities 1 " 2 " 3) 5. Implement CCES@school project on phenology 30
Outlook: CCES 2 nd phase Develop a Swiss GHG Information System to be used for emission verification and as decisionsupport tool Integrate relevant regional GHG measurements with statistical inventory/cadastre data for Switzerland, source sensitivity maps and off-line simulations Estimate space-time distribution of GHG fluxes, their controls and uncertainties 31 Thank you for your attention! And thanks to many involved in MAIOLICA for promoting this project, in particular: Ph.D. students Hella Ahrends, Sophia Etzold, Petra Braun, Katherine Gómez, Martin Schraner M.Sc. and Diploma students Gwendolin Bitter, Julien Anet, René Orth Speakers At conferences and workshops (73) Authors MAIOLICA-related papers (43) Publications for stakeholders (1) Organizers Scientific events with audience beyond project partners (8) Courses, seminars, workshops for stakeholders (2) Public information events for authorities/residents (2) Representatives Press articles, newspapers, radio/tv broadcasts (28) Activities at schools (3) Mothers Babies born (2) 32