1. MODIS Net Primary Productivity (NPP)
Theory, algorithm development, and example applications
Peter E. Thornton
Numerical Terradynamic Simulation Group
School of Forestry, University of Montana, Missoula, MT

2. Outline Background and theory (radiation use efficiency)
Parameterization (global simulations with Biome-BGC)
Example applications (regional, continental, and global)
Future developments (meteorology, landcover, complete carbon budget)

3. MODIS-NPP Objectives
Global estimate of productivity each week at 1km resolution
Algorithm driven mainly by remote sensing inputs
Include biophysical variables that can be produced globally at appropriate resolution
Biome-specific parameterization

4. MODIS-NPP Production Algorithm Summary
Incident radiation (PAR)...
Scaled by canopy cover (FPAR)...
Converted to carbon (radiation use efficiency)...
Modified by temperature and humidity...
Different parameters for each landcover

5. (MJ m-2 day-1)
(gC MJ-1)
(gC m-2 day-1)

6. Incident Photosynthetically Active Radiation (PAR)
Absorbed Photosynthetically Active Radiation (APAR) depends on incident PAR and canopy cover...
Incident Photosynthetically Active Radiation (PAR)

7. Absorbed Photosynthetically Active Radiation (APAR)
Absorbed Photosynthetically Active Radiation (APAR) depends on incident PAR and canopy cover...
Absorbed Photosynthetically Active Radiation (APAR)

8. Fraction of Photosynthetically Active Radiation absorbed by the canopy
Absorbed Photosynthetically Active Radiation (APAR) depends on incident PAR and canopy cover...
Fraction of Photosynthetically Active Radiation absorbed by the canopy
APAR
PAR
= FPAR

9. Depends on canopy structure
Absorbed Photosynthetically Active Radiation (APAR) depends on incident PAR and canopy cover...
Depends on weather
APAR = PAR × FPAR
Depends on canopy structure

10. Potential Radiation Use Efficiency (emax) is modified by biophysical environment...
emax × STair × SVPD = e
Reductions due to... 1
STair
SVPD T2 T1
VPD2
VPD1
Low air temperature (Tair)
High vapor pressure deficit (VPD)

11. Gross Primary Production (GPP) Algorithm:
GPP = PAR × FPAR × emax × STair × SVPD
Depends on…
MODIS-FPAR
PAR, air temperature, and VPD (from DAO)
Parameters defined for each vegetation type
MODIS Landcover

12. MODIS-GPP Biome-specific parameterization
All parameters are derived from global-scale simulations using the Biome-BGC terrestrial ecosystem process model
Detailed landcover information is used to translate Biome-BGC results to aggregated MODIS landcover classes

16. Example of detailed ecophysiological parameterization
Rubisco limited
28° C
RuBP regen
limited
18° C
10° C

17. Global Biome-BGC simulations
1 km Landcover from “continuous fields” AVHRR product:
Ruth DeFries and Matt Hansen, University of Maryland

26. Global Biome-BGC simulations
1x1 degree simulations for 14 years driven with daily weather data from Steve Piper and C.D. Keeling, Scripps Institute of Oceanography

29. Several more steps to go from GPP to NPP...
Maintenance respiration costs - depend on tissue N concentration and temperature
Growth respiration costs - depend on amount of new growth
Allometric relationships relate annual leaf area growth to stem and root growth

32. Example MODIS-NPP output
Subset of results from first global implementation of the algorithm

37. Some problems that we know about...
Coarse resolution surface weather data from DAO leaves a noticeable imprint on weekly output (probably on annual output also)
Use of discreet landcover makes parameterization from Biome-BGC difficult
Geographic variation of parameters within biomes

38. Example application using Daymet surface weather inputs
Western Montana, northern Idaho, eastern Oregon and Washington, USA