Use of Environmental Gradient Data to Test Earth System

ModelsMelannie Hartman

Colorado State UniversityFort Collins, Colorado, USA

with contributions from:

William J. Parton Colorado State University

Fort Collins, Colorado, USA

William Wieder and Gordon Bonan National Center for Atmospheric Research

Boulder, Colorado, USA

CLIMMANI-INTERFACE Workshop4-7 June 2013, Mikulov, Czech Republic

• Environmental Gradient Data Sets• Examples of how these data sets have been used to test

Earth System Models– may also involve model comparisons

• ModelsCommunity Land Model version 4.0 (CLM4)

biogeophysics, hydrologic cycle, biogeochemistry, vegetation. http://www.cesm.ucar.edu/models/clm/

Daily Century (DAYCENT)ecosystem-level plant dynamics, hydrology, biogeochemistry

OUTLINE

Earth System Models: Many processes, many scales

Environmental Gradient Data Sets• FLUXNET* Global network of micrometeorological tower sites

that use eddy covariance methods to measure the exchanges of carbon dioxide, water vapor, and energy between terrestrial ecosystems and the atmosphere. 500+ tower sites - 30 regional networks – 5 continents

• Ecosystem Model-Data Intercomparison (EMDI) *NPP field measurements world-wide(Olson et al., 2001)

• Long-term Intersite Decomposition Experiment Team (LIDET) 10-year, 28-site study of litter decomposition and N dynamics (Gholz et al., 2000; Parton et al., 2007; Harmon et al., 2009).

• Harmonized World Soils Database (HWSD)global SOC, soil texture, and pH (FAO, 2012) *ORNL Distributed Active Archive Center

http://daac.ornl.gov/

Environmental Gradient Data Sets (cont’d)• 1-km NPP and GPP derived from MODIS satellite observations

– Zhao et al. 2005, 2006• MODIS and EMDI 10x10 km NPP

– gridded, global NPP data by plant part – wood, fine roots, coarse roots, and leaves

• MODIS and EMDI annual plant N and P uptake– gridded, global data (10x10 km)

• N and P Mineralization – gridded, global data (10x10 km)

• EMDI Plant NPP– 5000 observations– 0.5° x 0.5° global map

• Great Plains Grassland NPP- 12,000 observations- spatial map of NPP

• Great Plains Grassland and cultivated SOIL C- 1,000+ observations- gridded spatial maps and regressions

MODIS

http://daac.ornl.gov/FLUXNET/fluxnet.shtml

FLUXNET TOWER SITES

~500 eddy covariance tower sites - 30 regional networks – 5 continentsGlobal, spatially gridded GPP and latent heat flux are upscaled from the FLUXNET tower data

Bonan et al. (2011) Journal of Geophysical Research: Improving canopy processes in the Community Land Model version 4 (CLM4) using global flux fields empirically inferred from FLUXNET data

(Control )

(revised two stream radiative transfer)‐ (RAD and revised leaf photosynthesis)

FLUXNET: Latitudinal Zonal Means

Bonan et al. (2011) Journal of Geophysical Research

EMDI

EMDI: NPP Observations and Model Comparison

Randerson et al. (2009)Global Change Biology

933 site-level measurements

CLM

http://andrewsforest.oregonstate.edu/research/intersite/lidet.htm

10-year, 28-site study of litter decomposition and N dynamics

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Model simulationsCLM4cn, DAYCENTFollow a cohort of litter (100 g C m-2) deposited on October 1Specified climatic decomposition index (CDI) to account for temperature and moisture

Long-Term Intersite Decomposition Experiment (LIDET)

Observations10-year study of litter dynamics for a variety of litter types placed in different environments

20 sites: 2 tundra, 2 boreal forest, 5 conifer forest, 3 deciduous forest, 3 tropical forest, 2 humid grassland, 3 arid grassland

9 litter types (6 species of leaves, 3 species of root) that vary in chemistryLitter bags sampled once a year for C and N

Soil mineral nitrogen % C mass remaining (decomposition rates) Fraction of initial N

(mineralization/immobilization)

Bonan et al (2013) Global Change Biology

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Leaf litter mass loss – conifer forest

5 sites & 6 leaf litter typesShown are the site x litter mean and ± 1 SD

CLM underestimates carbon mass remaining (overestimates mass loss), especially during first several years. This is common to all sites.

Bonan et al (2013) Global Change Biology

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LIDET: Leaf litter mass loss – all sites

Bonan et al (2013) Global Change Biology

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CLM4cn overestimates immobilization. Larger biases for leaf litter types with lower initial %N

Maple, 0.81 %N

Observations are sampled once per year. Shown are data for maple leaf litter at all biomes except arid grassland. Model data are sampled similar to the observations.

LIDET: Litter Nitrogen dynamics

Bonan et al (2013) Global Change Biology

HWSD: Steady-State Analysis of Global Soil Carbon Pools

HWSD (0-100cm), 1259 PgC CLM4 spinup, 502 PgC

CLM4 analytical + obs. litter inputs, 746 PgC DayCent analytical + obs. litter inputs, 978 PgC

Observationally derived litter inputs from Matthews, E. (1997)

Observed litterfall increases soil C compared with CLM4 litterfall

Wieder et al., in revision

HWSD (0-100cm) 1259 PgC

DayCent, 978 Pg C

CLM4, 746 Pg C

Wieder et al., in revision

HWSD: Latitudinal Zonal Mean of Soil Organic C density

Summary• These data are valuable tools to guide terrestrial

biosphere model development and evaluation• Field Measurements, Upscaled global gridded

products, or MODIS derived– NPP & GPP– latent heat flux– litter decomposition (%C remaining, fraction of initial N)– soil carbon stocks– N and P plant uptake– N and P mineralization

References• Bonan, G. B., M. D. Hartman, W. J. Parton, and W. R. Wieder. 2013. Evaluating litter decomposition in earth system models

with long-term litterbag experiments: an example using the Community Land Model version 4 (CLM4). Global Change Biology 19:957-974.

• Bonan, G. B., P. J. Lawrence, K. W. Oleson, S. Levis, M. Jung, M. Reichstein, D. M. Lawrence, and S. C. Swenson. 2011. Improving canopy processes in the Community Land Model version 4 (CLM4) using global flux fields empirically inferred from FLUXNET data. Journal of Geophysical Research-Biogeosciences 116.

• FAO, IIASA, ISRIC, ISSCAS, and JRC (2012), Harmonized World Soil Database (version 1.2), edited by FAO, Rome, Italy and IIASA, Laxenburg, Austria.

• Gholz, H. L., D. A. Wedin, S. M. Smitherman, M. E. Harmon, and W. J. Parton. 2000. Long-term dynamics of pine and hardwood litter in contrasting environments: toward a global model of decomposition. Global Change Biology 6:751-765.

• Harmon, M. E., W. L. Silver, B. Fasth, H. Chen, I. C. Burke, W. J. Parton, S. C. Hart, W. S. Currie, and Lidet. 2009. Long-term patterns of mass loss during the decomposition of leaf and fine root litter: an intersite comparison. Global Change Biology 15:1320-1338.

• Matthews, E. (1997), Global litter production, pools, and turnover times: Estimates from measurement data and regression models, J. Geophys. Res., 102(D15), 18771-18800.

• Olson RJ, Scurlock JMO, Prince SD, Zheng DL, Johnson KR (2001) . NPP Multi-Biome: NPP and Driver Data for Ecosystem Model-Data Intercomparison. Available on- line [http://www.daac.ornl.gov] from the Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA.

• Parton, W., W. L. Silver, I. C. Burke, L. Grassens, M. E. Harmon, W. S. Currie, J. Y. King, E. C. Adair, L. A. Brandt, S. C. Hart, and B. Fasth. 2007. Global-scale similarities in nitrogen release patterns during long-term decomposition. Science 315:361-364.

• Randerson, J. T., F. M. Hoffman, P. E. Thornton, N. M. Mahowald, K. Lindsay, Y. H. Lee, C. D. Nevison, S. C. Doney, G. Bonan, R. Stockli, C. Covey, S. W. Running, and I. Y. Fung. 2009. Systematic assessment of terrestrial biogeochemistry in coupled climate-carbon models. Global Change Biology 15:2462-2484.

• Wieder,, W.R., J. Boehnert,, and G.B. Bonan Evaluating soil biogeochemistry parameterizations in Earth system models with observations, Global Biogeochemical Cycles, in revision

• Zhao M, Running SW, Nemani RR (2006) Sensitivity of Moderate Resolution Imaging Spectroradiometer (MODIS) terrestrial primary production to the accuracy of meteorological reanalyses. Journal of Geophysical Research – Biogeosciences, 111, G01002, doi: 10.1029/2004JG000004.

• Zhao MS, Heinsch FA, Nemani RR, Running SW (2005) Improvements of the MODIS terrestrial gross and net primary production global data set. Remote Sensing of Environment, 95, 164–176. EVALUATING TERRESTRIAL BIOGEOCHEMISTRY MODE L S 2483 r 2009

Bonan et al. 2011: Improving canopy processes in the Community Land Model version 4 (CLM4) using global flux fields empirically inferred from FLUXNET data

EMDI

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Steady-state analysis

Base DAYCENT (0-

20 cm)

“Deep” DAYCENT(0-100 cm)

CLM4cn has more soil carbon than DAYCENT, but “deep” DAYCENT (0-100 cm) accumulates the most carbon

Observed litterfall increases soil C compared with CLM4cn litterfall