Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation

The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using a production efficiency approach. In this study, the 2001 MODIS GPP product was compared with scaled GPP estimates (25 kin:) based on ground measurements at two lbrested sites. The ground-based GPP scaling approach relied on a carbon cycle process model run in a spatially distributed mode. Land cover classification and maximum annual leaf area index, as derived fi'om Landsat ETM+ imagery,, were used in model initiation. The model was driven by daily meteorological observations fiom an eddy covariance flux tower situated at the center of each site. Model simulated GPPs were conoborated with daily GPP estimates from the flux tower. At the hardwood forest site. the MODIS GPP phenology started earlier than was indicated by the scaled GPE and the sunnnertime GPP from MOD1S was generally lower than the scaled GPP values. The fall-off in production at the end of the growing season was similar to the validation data. At the boreal forest site, the GPP phenologies generally agreed because both responded to the strong signal associated with minimum temperature. The midsummer MODIS GPP there was generally higher than the ground-based GPR The difiizrences between the MODIS GPP products and the ground-based GPPs were driven by difli:rences in the timing of FPAR and the magnitude of light use efficiency as well as by diflbrences in other inputs to the MODIS GPP algorithm--daily incident PAR, minimum temperature, and vapor pressure deficit. Ground-based scaling of GPP has the potential to improve the parameterization of light use efficiency in satellite-based GPP monitoring algorithms. ,i', 2003 Elsevier Inc. All rights reserved. h'cvw:~nts: MODIS: Validation: Gross primary production: Light use efficiency: Eddy covariance: Biome-BGC; FPAR; Boreal tbrest: Deciduous fore',t I . I n t r o d u c t i o n Anthropogenic influences on the global carbon cycle include direct CO2 emissions to the atmosphere associated with combustion of fossil fuel, as well as indirect efti~cts mediated by the biospheric cycling of carbon (Schimel, 1995). Notably, human-induced land cover change and land use change produce large sources and sinks of carbon tHoughton, 1999). Furthermore, increasing atmospheric * Con'esponding author. Tel,: +1-541-737-5043; fax: *1-541-7371393, E-mail address: david.ttlmer(&oregonstate.edu (D.P. Turner). 0034-4257/$ see fi'ont matter (c, 2003 Elsevier Inc. All rights reserved. doi:10. IO16,~j.rse.2003.06.005 concentrations of CO2 and pollutants such as ozone, along with atmospheric deposition of nitrogen and sulfur, are altering carbon uptake by gross primary production and carbon release by autotrophic and heterotrophic respiration. Interannual variation in regional (e.g. Nemani et al., 2002) and global climate, and a global trend towards climate warming--most likely driven by the rising concentrations of greenhouse gases (IPCC, 2001 )--are also strongly modifying the carbon cycle. To understand the relative magnitude of these various factors, it will be important to monitor critical components of the biospheric carbon cycle at regional and global scales (Running ct al., 1999). The Moderate Imaging Spectroradiometer (MODIS) sensor was designed in part lbr that purpose and global D.P. Turner et aL / Remote Sensing q/'Envi#rmment 88 t2003) 256-270 257 estimates of 8-day gross primary production (GPP) and annual net primary production (NPP) at the 1 km spatial resolution are now being produced operationally (Running. r[homton, Nemani, & Glassy, 2000). Both GPP and NPP estimates require validation with ground-based measuremeats. NPP is perhaps more directly relevant to carbon cycle analysis but validating only NPP is undesirable because the MODIS NPP product is calculated as the difference between GPP and autotrophic respiration (R~,). The MODIS GPP and R,, algorithms both rely upon remote sensing but in very different ways and each algorithm needs to be investigated. In this study, an initial evaluation of the MODIS 2001 GPP product is made by comparing MOD1S GPP estimates with ground-based GPP estimates over 25 km e areas at a northern hardwoods forest site and a boreal forest site. The MODIS GPP algorithm employs a light use efficiency approach (Running et al., 2000). GPP is estimated tbr each I kin: cell fbr each day of the year by first determining the absorbed photosynthetically active radiation (APAR). The incident PAR and the fraction of PAR that is absorbed by the vegetation (FPAR) determine APAR. Their product is multiplied by a GPP light use efficiency (gg), in terms of g C MJ i to get daily GPP. FPAR for each 1 km cell is based on the spectral reflectances detected by the MODIS sensor (Myneni et al., 2002}. The daily e,g is based on a biome-specific maximum (~:g ..... ) derived from a lookup table and modified by scalars (0 1) associated with a daily minimum air temperature and vapor pressure deficit (VPD). PAR, temperature and VPD are from a data assimilation General Circulation Model (Schubert et al., 1993) run at the I '~ spatial resolution ( 100 km). The multiple inputs to the MODIS GPP algorithm are each subject to unceltainty and require evaluation in validation efforts. Prospects for validating the MODIS GPP product are constrained by uncertainties in the measurement of GPE GPP is the net effect of gross photosynthesis and photorespiration, and is not directly measurable. At the annual time step, GPP minus autotrophic respiration (R~) is equal to NPP. which is directly measurable (Gower. Kucharik, & Norman, 199q). However, the ratio of NPP to GPP is not constant across plant functional types (Amthor, 20001 and scaling R,, from air temperature and chamber measurements (e.g, l,aw, Ryan. & Anthoni, 1999) is a complex undertaking. Eddy covariance flux towers measure GPP indirectly as the difference between net ecosystem exchange (NEE} and ecosystem respiration (R~) during daylight periods ~Gouldcn, Munger, Fan, Daube. & Wofsy, 1996a; Turner et al., 2003). For these estimates, 1L:, is either scaled from chamber measurements of soil and plant respiration (ttam & Knapp, 199S) or fi'om the relationship of air temperature to NEE during nighttime periods above a threshold friction velocity (Goulden et al., 1997). An increasing number of flux tower sites are producing GPP estimates with relevmacc to validating MODIS products (Falgc ct al., 2002; Turner el al,, 2003). There are also issues with mismatches in scale when trying to juxtapose tower-based GPPs with MODIS GPPs. The MODIS GPP product is at a l-km spatial resolution. The tower-based estimates of GPP represent a flux integrated over the tower "fbotprint", the size and shape of which depends on wind speed, wind direction, surf'ace roughness, and atmospheric stability (Schmid, 20t)2). Thus, the footprint is not a fixed area and the tower is sampling a relatively small area compared to MODIS products over a given region. An alternative approach to generating GPP data layers tbr validation purposes is employed in this study and relies on a spatially distributed carbon cycle process model as the principal scaling tool. Inputs of land cover and leaf area index (LAI) are based on high spatial resolution remote sensing (Landsat ETM+I, and the model is driven by daily meteorological station data. Model parameterization, calibration, and validation are based on ground measurements of NPP and GPP. Because the model is run at fine spatial resolution over a gridded surf'ace and outputs are at the daily time step, results can be spatially and temporally aggregated to match precisely the spatial and temporal scale of the MODIS products. The process-based nature of the scaling approach also permits investigation of possible mechanisms underlying differences between the MODIS GPPs and ground-based measurements.