Spatial and temporal patterns of CH 4 and N 2 O fluxes from North America as estimated by process-based ecosystem model Hanqin Tian, Xiaofeng Xu and other.

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Presentation transcript:

Spatial and temporal patterns of CH 4 and N 2 O fluxes from North America as estimated by process-based ecosystem model Hanqin Tian, Xiaofeng Xu and other ESRA Members Ecosystem Science and Regional Analysis Laboratory Auburn University Non-CO2 Greenhouse Gases Workshop, Boulder, CO, October 22-24, 2008

Satellite Data Eddy Flux Ecosystem Experiments Flask Data MeasuringModeling Synthesis The Integrated Ecosystem Modeling Approach DLEM

Outline Why do we estimate CH 4 and N 2 O fluxes using ecosystem model? A case study in North America – DLEM: a process-based ecosystem model – Site level model verification – Comparison with other studies – Model application on the regional level

Why do we use ecosystem modeling approach?  Attributing controls on non-CO2 fluxes Anthropogenic and natural factors  Spatial and temporal extrapolation  Prediction

(a) The Dynamic Land Ecosystem Model - Key components and interactions

The Dynamic Land Ecosystem Model - Key processes, fluxes and pools

Three methane-associated processes are incorporated in DLEM: methane production in soil, the oxidation of produced methane during transportation, atmospheric methane oxidation Methane module of DLEM

Nitrification and denitrification are determined by environmental conditions as soil moisture, temperature, pH Nitrous oxide module of DLEM

Model input data Climate dataset (precipitation, temperature, humidity) Nitrogen deposition Ozone concentration Land use and land cover change Historical CO 2 concentration Fertilizer, irrigation area

Model validation for CH 4 fluxes Durham forest (42N, 73W) The observed data are from BOREAS

Site level Validation on CH 4 Durham forest (42N, 73W) The observed data are from BOREAS

Model validation for N 2 O fluxes N2O from wetland (33.5E, 47.58N) Observed data are from Song et al. (2008)

MethodLi et al., 1996This study ModelDNDCDLEM Spatial resolutionstate32km × 32km US N 2 O emission for 1990 (no tillage and manure) (gN/m 2 /year) Cropland and pasture (gN/m 2 /year) Cropland only Model Intercomparison

DLEM-based estimation of CH 4 and N 2 O emission from North America terrestrial ecosystems Study Period: Spatial resolution: 32 km Time step: Daily Forces: multiple factors

1 Tundra 2 Boreal broad-leaf deciduous forests 3 Boreal needle-leaf evergreen forests 4 Boreal needle-leaf deciduous forests 5 Temperate broad-leaf deciduous forests 6 Temperate broad-leaf evergreen forests 7 Temperate needle-leaf evergreen forests 8 Temperate needle-leaf deciduous forests 9 Tropical/subtropical broad-leaf deciduous forests 10 Tropical/subtropical broad-leaf evergreen forests 11 Open shrub 12 Close shrub 13 C3 grassland 14 C4 grassland 15 Grass peatland 16 Forest peatland 17 Grass permanent wetland 18 Forest permanent wetland 19 Grass seasonal wetland 20 Forest seasonal wetland 21 Desert 22 Mixed forests 24 Temperate needle-leaf evergreen forests in tropical area

Input data: Climatic variability during

Input data: Ozone concentration

Input data: Nitrogen fertilization Data are from FAO and USDA

Input data: Nitrogen deposition

Mean annual CH4 fluxes for

Mean annual CH4 fluxes for

Mean annual CH4 fluxes for

Annual CH4 fluxes from Mexico, USA and Canada

Mean annual N2O fluxes for

Mean annual N2O fluxes for

Mean annual N2O fluxes for

Annual N 2 O fluxes from Mexico, USA and Canada

Nitrogen fertilization effects on N 2 O fluxes in Conterminous US during

Summary DLEM is capable of capturing spatial and temporal patterns of CH 4 and N 2 O fluxes in North American terrestrial ecosystems. DLEM could be used to quantify the relative contribution of multiple factors. Our simulated results suggest that climate (temperature and precipitation) is the primary control over interannual variability of CH 4 and N 2 O over North America during , the air pollution and land cover/land use change could substantially alter the fluxes of CH 4 and N 2 O over the region. Ecosystem modeling approach can add a new dimension of the NACP non-CO2 greenhouse gases synthesis.

Needs for ecosystem modeling approach to CH4 and N2O fluxes Data needs: – Vegetation maps, particularly wetland area/distribution – Land management (fertilization, irrigation) Validation: – Site level: validate against long-term observations – Regional Level: comparison with inverse modeling and bottom-up inventories Model improvement: To better address some key processes such as soil thawing.