Satellite data constraints on the seasonal methane budget.

Transcription

1 Satellite data constraints on the seasonal methane budget. A. Anthony Bloom 1*, Kevin Bowman 1, Meemong Lee 1, John Worden 1, Alex Turner 2, Daniel Jacobs 2, Ronny Schroeder 3, Kyle McDonald 3. 1 Jet Propulsion Laboratory/California Institute of Technology 2 Harvard University, Department of Environmental Engineering, MA 3 City College of New York, NY IGC7 May 5 th 2015 *abloom@jpl.nasa.gov

2 Wetland CH 4 emissions: 20-40% of global CH 4 budget WETCHIMP models Tg CH 4 /yr Magnitude, timing and location of wetland CH 4 fluxes uncertain Process controls on wetlands important to understand the CH 4 budget Process controls fundamental to understanding long-term climate feedbacks

3 Wetland CH 4 emission controls: F CH4 = A C f(t) e T= Temperature A = Wetland Extent C = Methanogen-available carbon e = Emission factor

4 : updated wetland CH 4 emissions inventory. Satellite-based inundated area (MEaSUREs & GIEMS: based on satellite active/passive microwave sensor data) MsTMIP Terrestrial Biosphere models Scaled to global total: 210 +/-50 Tg CH 4 yr -1 (consistent with mean and std of IPCC 5 th AR) Wetland CH 4 emissions = W AREA C f(t) x e Equation adapted from Pickett-Heaps et al., 2011

5 Updated wetland CH 4 Mean Monthly (%) Standard wetland CH 4 year = 2010, Bloom et al., 2015, in prep. 1. Carbon and inundated area drive seasonal and inter-annual variability 2. Differences largely in the timing and magnitude of emissions 3. Larger fluxes in North America and Boreal Eurasia wetland areas & later fluxes (Aug- September) in temperate and boreal latitudes.

6 Correlation [ updated & surface CH4] Surface CH4 comparisons Correlation [ standard & surface CH 4 ] CH 4 anomaly [ppb] CH 4 anomaly [ppb] Barrow (71N 157W ) STANDARD UPDATED SURFACE OBS Key Biscayne (26N 80W) STANDARD UPDATED SURFACE OBS Updated CH4 inventory leads to overall improved CH4 variability 9 Largest improvements in N. America within proximity of major wetland emissions

7 GOSAT Standard wetland fluxes MEaSUREs MstMIP wetlands Boreal CH4 error could be explained by a systematic bias in the magnitude and timing of wetlands

8 GOSAT Standard wetland CH4 inventory Updated wetland CH4 inventory Uniform wetland fluxes (no spatiotemporal variability) Temperate/Boreal CH4 error unlikely to be explained by differences in wetlands.

9 GOSAT Updated wetland CH4 No CH 4 OH loss Constant CH 4 OH loss Constant/No OH loss lead to lower mismatch between model CH 4 seasonality

10 Conclusions Improved seasonal agreement between surface observations and updated wetland CH 4 inventory. Temperate/boreal latitude GOSAT CH 4 seasonal cycle not explained by wetland emissions. GOSAT model mismatch could potentially be explained by a bias in Northern latitude OH

11 Gross Primary Production (approx PgC) Ecosystem Respiration (approx PgC) WETLANDS CH 4 (approx. 200 TgCH 4 ) Foliage Auto. Resp. Wood Heterotrophic Respiration Anaerobic respiration Roots Live biomass Litter Soil Carbon Dead organic matter Wetland and fire emissions are derived from carbon pools with different residence times A. Anthony Bloom, Yuk Lunch Seminar Series, Caltech, Mar 3 rd 2015

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13 : Updated wetland CH 4 emissions inventory. Wetland CH 4 emissions model = W AREA C resp f(temp) x S Equation adapted from Pickett-Heaps et al., 2011 Parameter Description Original emissions Updated (Bloom et al., 2015, in prep.) W area Wetland area Based on GEOS-5 soil moisture Based on satellite inundated area datasets: GIEMS and MEaSUREs. C resp f(temp) Heterotrophic respiration CH 4 emission temperature dependence Based on constant pools and fixed residence times Based on wetland temperature S Scale factor Scaled to Amazon wetlands (Melack et al., 2004) and boreal wetlands (Hein et al., 1997; Wang et al., 2004). Based on heterotrophic resp. from 8 MsTMIP terrestrial biosphere model ensemble Included in MsTMIP model structure. Scaled to global total: 210 +/-50 Tg CH 4 yr -1 (consistent with mean and std of IPCC 5 th AR). A. Anthony Bloom, Yuk Lunch Seminar Series, Caltech, Mar 3 rd 2015