Schwalm, Christopher: Woodwell Climate Research Center (Project Lead)
Huntzinger, Deborah (Debbie): Northern Arizona University (Co-Investigator)
Project Funding:
2012 - 2015
NRA: 2011 NASA: Terrestrial Ecology
Funded by NASA
Abstract:
This project directly addresses NASA's Terrestrial Ecology program stated goal of improving our understanding of the structure and function of ecosystems in the cycling of major biogeochemical elements between the land and the atmosphere. We propose to quantify the sensitivity of terrestrial carbon cycling to climate variability using eddy- covariance based observations and remotely sensed indices, and use these sensitivities to derive a comprehensive set of benchmarks for improving land-surface and terrestrial biospheric models. This project will also scale the calculated sensitivities to generate global maps of carbon flux anomalies from 1900-2100 linked to specific environmental drivers. As a result, this proposed effort directly supports NASA's program emphasis on 1) improving understanding of the global carbon cycle, 2) quantifying how large and variable fluxes of carbon within the Earth system are, and 3) quantifying how carbon cycling will change over longer-term time scales. Our approach is data-driven, and integrates eddy-covariance FLUXNET observations with remotely sensed and retrospective data to attribute past and future terrestrial carbon fluxes anomalies to key environmental drivers. Scaling is achieved through merging sensitivities with environmental driver variability (quantified using retrospective analysis or IPCC future scenarios) and dynamic land cover data. This will be the first time that sensitivity surfaces, such as those proposed here, have been generated. The derived sensitivities express the change in carbon flux relative to a unit change in environmental driver, and

provide strong observational constraints on modeled functional relationships between carbon flux and different environmental drivers. Terrestrial biospheric models are valuable tools for improving our understanding of biophysical and biogeochemical process, and these models use, to differing extents, observed and remotely sensed data for model calibration and initialization. In addition to generating an independent and observationally-based estimate of carbon-climate sensitivities, this product will also provide needed reference standards and valuable benchmarks for refining terrestrial carbon cycling models. This proposed effort builds upon past carbon cycle research to create a new synthesis, advance the results of prior research, and enhance model and decision support system utility. There are four main steps in this study: 1) generate dynamic land-cover maps from 1900-2100; 2) estimate carbon flux sensitivities to climatic drivers (evaporative fraction, air temperature, downwelling radiation, humidity) from in situ, site-based observations; as well as remotely sensed indices (enhanced vegetation index, leaf area index, land surface temperature); 3) benchmark terrestrial biospheric model output using the spatially-scaled sensitivities; and 4) using retrospective analysis and IPCC scenarios, translate the derived sensitivities to carbon flux anomalies from 1900 to 2100. Through steps 1 and 2 we will generate maps of spatially varying sensitivities to environmental drivers that can be used to evaluate how well models replicate observed responses of the carbon cycle to changes in environmental factors. Furthermore, the flux anomalies derived from the sensitivities provide an independent and observationally-based estimate of past and future variability in the carbon cycle due to changing climate. Overall this project will foster an improved understanding of climate-induced variability of the carbon cycle by integrating land-based and satellite observations, and will provide several critical benchmarks needed to improve our ability to model and understand the global carbon cycle.
Publications:
Jung, M., Reichstein, M., Schwalm, C. R., Huntingford, C., Sitch, S., Ahlstrom, A., Arneth, A., Camps-Valls, G., Ciais, P., Friedlingstein, P., Gans, F., Ichii, K., Jain, A. K., Kato, E., Papale, D., Poulter, B., Raduly, B., Rodenbeck, C., Tramontana, G., Viovy, N., Wang, Y., Weber, U., Zaehle, S., Zeng, N. 2017. Compensatory water effects link yearly global land CO2 sink changes to temperature. Nature. 541(7638), 516-520. DOI: 10.1038/nature20780
Koirala, S., Jung, M., Reichstein, M., de Graaf, I. E. M., Camps-Valls, G., Ichii, K., Papale, D., Raduly, B., Schwalm, C. R., Tramontana, G., Carvalhais, N. 2017. Global distribution of groundwater-vegetation spatial covariation. Geophysical Research Letters. 44(9), 4134-4142. DOI: 10.1002/2017GL072885
Schwalm, C. R., Anderegg, W. R. L., Michalak, A. M., Fisher, J. B., Biondi, F., Koch, G., Litvak, M., Ogle, K., Shaw, J. D., Wolf, A., Huntzinger, D. N., Schaefer, K., Cook, R., Wei, Y., Fang, Y., Hayes, D., Huang, M., Jain, A., Tian, H. 2017. Global patterns of drought recovery. Nature. 548(7666), 202-205. DOI: 10.1038/nature23021
Schwalm, C. R., Huntinzger, D. N., Michalak, A. M., Fisher, J. B., Kimball, J. S., Mueller, B., Zhang, K., Zhang, Y. 2013. Sensitivity of inferred climate model skill to evaluation decisions: a case study using CMIP5 evapotranspiration. Environmental Research Letters. 8(2), 024028. DOI: 10.1088/1748-9326/8/2/024028
Schwalm, C. R., Huntzinger, D. N., Fisher, J. B., Michalak, A. M., Bowman, K., Ciais, P., Cook, R., El-Masri, B., Hayes, D., Huang, M., Ito, A., Jain, A., King, A. W., Lei, H., Liu, J., Lu, C., Mao, J., Peng, S., Poulter, B., Ricciuto, D., Schaefer, K., Shi, X., Tao, B., Tian, H., Wang, W., Wei, Y., Yang, J., Zeng, N. 2015. Toward "optimal" integration of terrestrial biosphere models. Geophysical Research Letters. 42(11), 4418-4428. DOI: 10.1002/2015GL064002
More details may be found in the following project profile(s):
