Project Funding: 2012 - 2015

NRA: 2011 NASA: Terrestrial Ecology   

Funded by NASA

Abstract:
An important science goal for NASA is to quantify the terrestrial carbon cycle and ecosystem feedbacks which requires accurate estimate of photosynthetic CO2 uptake. Vegetation photosynthesis is a pigment-level (primarily chlorophyll) process. Existing global climate models have been unable to accurately describe the intensity of photosynthetic activity or to discriminate this functionality among terrestrial vegetation canopies/ecosystems. Many satellite-based production efficiency models (PEMs), land surafce models and biogeochemical models (e.g., SiB, CLM and CASA) have used the concept of fraction of photosynthetically active radiation (PAR) absorbed for photosynthesis to estimate GPP for their modeling work. These models use satellite-based estimates of fAPAR for the entire canopy (i.e., fAPARcanopy, which is widely denoted as FPAR or fAPAR) to estimate fAPAR for photosynthesis. However, FPAR has been shown to be physiologically insufficient to reliably describe or retrieve terrestrial ecosystem photosynthesis. A much better alternative is to utilize the fraction of PAR absorbed only by chlorophyll throughout a canopy/ecosystem (fAPARchl) to replace fAPARcanopy when estimating APAR for photosynthesis and GPP. A recent study by Bonan et al. (2011) reported that more accurate radiative transfer parameterization within the canopy (e.g. fAPAR) can significantly improve output from CLM and the simulated GPP would be much closer to FLUXNET tower-based GPP. We will directly calculate fAPARchl of terrestrial ecosystems using available remote sensing data including Terra/MODIS, Aqua/MODIS, EO-1 Hyperion and Landsat through inversion of a physically-based radiative transfer model (Zhang et al., 2005, 2006, 2009, 2011b). This study will first produce 9x9 MODIS fAPARchl maps with available remote sensing images for globally sampled flux tower sites with a focus on EOS Land Validation Core Sites in a wide variety of ecosystems. Secondly, we will implement fAPARchl into a production efficiency model (PEM) to estimate GPP based on calibration/validation over the globally selected tower sites. Thirdly, we will produce regional maps of fAPARchl and GPP from MODIS. The MODIS fAPARchl results will be implemented into CLM (version 4, CLM4). For initial accuracy assessment and calibration and validation, we will first focus on our globally selected flux tower sites and nearby local regions. We will then extend our progress to continental and global scale. For the continental US, GPP determined from the fAPARchl+CLM4 approach will be compared with that obtained from fAPARchl+PEM and from fAPARcanopy+PEM (e.g. MODIS MOD17 product). Their spatial and temporal anomalies will be examined. Specific intensive regions for this evaluation will include the New England/Mid-Atlantic and California/Pacific. At global scale, similar validation procedure outlined in Bonan et al. 2011 will be utilized. The GPP obtained using fAPARchl+CLM4 approach will be compared with the conventional default CLM GPP and FLUXNET-MTE GPP at global scale.At global scale, we will couple our fAPARchl+CLM4 results with COLA AGCM in the GLACE-like framework described in (Wei et al. 2010b; Wei et al. 2010c). We will investigate how this improved parameterization affects atmospheric and climate simulations. Our focus will be on the global geographic variations of model uncertainties and land-atmosphere feedbacks, which still have not been addressed well enough today. We will also explore the difference in the output of the climate estimate (e.g. surface air temperature and evapotranspiration) with/without the implementation.

Publications:

Zhang, Q., Middleton, E. M., Cheng, Y., Huemmrich, K. F., Cook, B. D., Corp, L. A., Kustas, W. P., Russ, A. L., Prueger, J. H., Yao, T. 2016. Integrating chlorophyll fAPAR and nadir photochemical reflectance index from EO-1/Hyperion to predict cornfield daily gross primary production. Remote Sensing of Environment. 186, 311-321. DOI: 10.1016/j.rse.2016.08.026

Zhang, Q., Cheng, Y., Lyapustin, A. I., Wang, Y., Gao, F., Suyker, A., Verma, S., Middleton, E. M. 2014. Estimation of crop gross primary production (GPP): fAPARchl versus MOD15A2 FPAR. Remote Sensing of Environment. 153, 1-6. DOI: 10.1016/j.rse.2014.07.012

Vander Jagt, B. J., Durand, M. T., Margulis, S. A., Kim, E. J., Molotch, N. P. 2014. Corrigendum to "The effect of spatial variability on the sensitivity of passive microwave measurements to snow water equivalent" [Remote Sensing of Environment 136 (2013) 163-179]. Remote Sensing of Environment. 155, 378. DOI: 10.1016/j.rse.2014.09.003

Zhang, Q., Cheng, Y., Lyapustin, A. I., Wang, Y., Xiao, X., Suyker, A., Verma, S., Tan, B., Middleton, E. M. 2014. Estimation of crop gross primary production (GPP): I. impact of MODIS observation footprint and impact of vegetation BRDF characteristics. Agricultural and Forest Meteorology. 191, 51-63. DOI: 10.1016/j.agrformet.2014.02.002

Cheng, Y., Zhang, Q., Lyapustin, A. I., Wang, Y., Middleton, E. M. 2014. Impacts of light use efficiency and fPAR parameterization on gross primary production modeling. Agricultural and Forest Meteorology. 189-190, 187-197. DOI: 10.1016/j.agrformet.2014.01.006

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)

• Retrievals of chlorophyll fAPAR/LAI for GPP modeling   --   (Qingyuan Zhang, Tian Yao, Yujie Wang, Alexei Lyapustin)   [abstract]

2013 NASA Terrestrial Ecology Science Team Meeting Poster(s)

• Evaluation of the new MODIS fAPARchl product using CLM4 and CASA   --   (Qingyuan Zhang, Yen-Ben Cheng, Tiexi Chen, Jiangfeng Wei, Alexei Lyapustin, Yujie Wang)   [abstract]

More details may be found in the following project profile(s):

• NASA Terrestrial Ecology (TE) Project Profile