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1 Global modelling of methane and wetlands: Past, present and future. Nic Gedney (Met Office, Hadley Centre (JCHMR)) (Pete Cox, Hadley Centre and Chris.

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Presentation on theme: "1 Global modelling of methane and wetlands: Past, present and future. Nic Gedney (Met Office, Hadley Centre (JCHMR)) (Pete Cox, Hadley Centre and Chris."— Presentation transcript:

1 1 Global modelling of methane and wetlands: Past, present and future. Nic Gedney (Met Office, Hadley Centre (JCHMR)) (Pete Cox, Hadley Centre and Chris Huntingford, CEH Wallingford) Methane currently the 2nd largest contributor to anthropogenic greenhouse effect. Wetlands currently largest single source of CH4 Wetland emissions sensitive to climate Currently high latitudes are a significant CH4 source Large changes in climate are predicted at high latitudes Source: CEH Wallingford @British Crown Copyright 2004

2 2 Overview Rationale and introduction Wetland CH4 Emissions determinants Modelling techniques Modelling Studies: –Present Day –Last Glacial Maximum –Future –Present Day -> Future Remaining issues and possible ways forward

3 3 Rationale We need: –Accurate estimate of global wetlands CH4 budget – past and present –Understand role of wetlands in CH4 variability –past and present –Model necessary physical processes -> Confident in future projections Where are we now? How far are we limited by observations? What are the likely next steps?

4 4 Historical atmospheric methane concentrations Figure 4.1: (a) Change in CH4 abundance (mole fraction, in ppb = 10-9) determined from ice cores, firn, and whole air samples plotted for the last 1,000 years. Data sets are as follows: Grip, Blunier et al. (1995) and Chappellaz et al. (1997); Eurocore, Blunier et al. (1993); D47, Chappellaz et al. (1997); Siple, Stauffer et al. (1985); Global (inferred from Antarctic and Greenland ice cores, firn air, and modern measurements), Etheridge et al. (1998) and Dlugokencky et al. (1998). Radiative forcing, approximated by a linear scale since the pre-industrial era, is plotted on the right axis. Figure 4.1: (a) Change in CH4 abundance (mole fraction, in ppb = 10-9) Blunier et al. (1995) and Chappellaz et al. (1997); Blunier et al. (1993); Chappellaz et al. (1997); Stauffer et al. (1985); Etheridge et al. (1998), Dlugokencky et al. (1998). Figure 4.1: (e) Atmospheric CH4 abundances (black triangles) and temperature anomalies (grey diamonds) (Petit et al., 1999). Climate Change 2001. IPCC Third Assessment Report. Working Group I: The Scientific Basis. Figure 4.1

5 5 Historical atmospheric methane concentrations (b) Globally averaged monthly varying CH4 (c) Instantaneous annual growth rate (Dlugokencky et al., 1998). Climate Change 2001. IPCC Third Assessment Report. Working Group I: The Scientific Basis. Figure 4.1 Present Day sources: Anthropogenic: 200-350 TgCH 4 yr -1 Total: 500-600 Main Sink (tropospheric OH): CH 4 +OH→CH 3 +H 2 O

6 6 Wetland CH4 Emissions determinants Temperature: –Usually described by Q 10 (T/10) –Q 10  1.5-16 (Walter and Heinmann, 2000) »Northern wetlands: Q10  5 (Christensen et al. 2003) »Rice: Q10  1.5-3 (Khalil et al. 1998) Water table height Substrate availability and quality (Vegetation composition)

7 7 Modelling Techniques Bottom-up – process based estimates of the CH4 source CH4 budget scenarios Atmos chemistry Modelled atmos CH4 conc Minimise errors Top-down – measured CH4 concs -> CH4 sources (Walter and Heimann 2000)

8 8 Modelling Studies: Present Day source and sink estimates (Walter et al 2001)

9 9 Present Day zonal mean CH4 flux estimates (Walter et al. 2001) 25-45% from > 30 o N (Walter et al. 2001, Hein et al. 1997,Fung et al. 1991)

10 10 Present day global inter-annual CH4 variability: wetland flux vs biomass burning (Dlugokencky et al. 2003) 1997-98 global source anomaly ~ 24 Tg CH4 Significant contribution from wetlands (Dlugokencky et al. 2001) !998 Boreal fire anomaly: 2.9-4.7 Tg CH4 (Kasischke and Bruhwiler 2003) 1997-1998 Indonesian fire anomaly: 1.2-3.6 Tg CH4 (Levine 1999) 5.0Tg CH4 (Duncan et al. 2003) Other estimates >> (e.g. van der Werf et al. 2004)

11 11 Modelling Studies: Last Glacial Maximum source and sink estimates (Kaplan 2002)

12 12 Climate Change Model sensitivity studies: Critical play-off between temperature and moisture Obs: both moistening and drying with permafrost melt (Christensen et al. 2004, Stow et al. 2004) Hypothetical tundra response (Christensen and Cox 1995)

13 13 Using present day observed variability to reduce the uncertainty in future climate change prediction (Gedney, Cox and Huntingford) Met Office Land Surface Scheme (MOSES) extended to include interactive wetlands (soil moisture high resolution topography) Wetland CH4 emissions parameterisation calibrated from observed inter-annual variability in atmos CH4 concentrations Impact of wetlands emissions on simulated transient climate change studied using an “integrated climate change effects model”

14 14 Fs Zsoil Zw TI pdf(TI) MOSES - LSH (Gedney and Cox 2003) saturated fraction influences runoff mean water table plus topographic index determine saturated fraction MOSES soil model updates mean water table subgrid orography determines subgrid water table depths

15 15 Simulated annual mean wetland fraction Off-line (Gedney and Cox 2003)

16 16 Estimating CH 4 emissions from wetlands F CH4 =K. C soil. f wetl.Q 10 (T soil ) T soil /10 f(wetl) - wetland fraction Tsoil - soil temperature Q 10 - fn of temperature Csoil - soil carbon content K - global constant Calibrate global flux and Q 10 (T): –Force with observed monthly anomalies of T and precip. –Use simple global atmospheric chemistry lifetime model: d(CH 4 )/dt =  F CH4 – CH 4 /  – Include estimate of biomass burning variability

17 17 Modelled inter-annual variability in CH4 emissions (  F CH4 ~ 325TgCH 4 yr -1, q10(T0)~3-4) Temperature data: Jones et al., 2001. Precip data: Xie and Arkin, 1998 CH4 flux derived from atmos CH4 conc data: Dlugokencky (pers com)

18 18 Calibrating the wetland CH4 parameterisation (1992-1999) Minimum RMS Error:  F CH4 =295-325TgCH 4 yr -1, Q 10 (T 0 )=3.2-3.8 Modelled varying wetland: RMS Error

19 19 Schematic diagram of IMOGEN (Integrated Model Of the Global Effects of climate aNomalies or “GCM analogue model” Base Climate Anomaly Patterns  Atmospheric Greenhouse Gas Concentrations Land Surface Scheme scale factor  Forcing: T, q, u, Sd, Ld Fluxes: CO2, CH4 Anthropogenic emissions

20 20 Transient climate change predictions (Annual mean, land average) IS92A projected anthropogenic increases ~ 400TgCH 4 yr -1  F CH4 =325TgCH 4 yr -1, Q 10 (T 0 )=3-4 Predicted wetlands emission increases are close to anthropogenic 3-5% increase in radiative forcing

21 21 Remaining issues and possible ways forward Observations: –Lack of observations over tropics –Isolating effects of obs drivers on flux (T, Zw etc) –Separate flux components (production, oxidation not just net) –Substrate availability -> Parameters for process-based models Suitable models: –High lats: peat soils, non-vascular plants –Tropics: peat soils, seasonal flooding –Wetlands hydrology – Permafrost -> reproduce current wetlands and recent regional responses to permafrost melting

22 22 Remaining issues and possible ways forward – contd. Further constrain process based models: –Present Day global mean budget uncertainty –Present Day variability: relative roles of biomass burning and wetlands –LGM: disagreement over sources -> Top down studies incorporating more process based models (include isotopic signatures) Studies on future climate change: –GCM-analogue model? –And finally…… Fully coupled Earth Systems Model (wetlands + atmos chemistry)

23 23 Acknowledgements DEFRA Copyright Met Office


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