3
Global Terrestrial Gross and Net
Primary Productivity from the Earth
Observing System
Steven W. Running, Peter E. Thornton, Ramakrishna Nemani, and Joseph M. Glassy
Introduction
Probably the single most fundamental measure of
"global change" of highest practical interest to humankind is the change in terrestrial biological productivity. Biological productivity is the source of
all the food, fiber, and fuel by which humans
survive, and so defines most fundamentally the habitability of Earth. The spatial variability of net primary productivity (NPP) over the globe is enormous, from about 1000 g C m - 2 for evergreen
tropical rain forests to less than 30 g C m - 2 for
deserts (Scurlock et al. 1999). With increased atmospheric carbon dioxide (C0 2 ) and global climate
change, NPP over large areas may be changing
(Myneni et al. 1997a, VEMAP 1995, Melillo et al.
1993). Understanding regional variability in carbon
cycle processes requires a more spatially detailed
analysis of global land surface processes. Since December 1999, the U.S. National Aeronautics and
Space Administration (NASA) Earth Observing
System (EOS) produces a regular global estimate
of (gross primary productivity, GPP) and annual
NPP of the entire terrestrial earth surface at 1-km
spatial resolution, 150 million cells, each having
GPP and NPP computed individually.
The GPP and NPP products are designed to provide an accurate, regular measure of the production
activity or growth of terrestrial vegetation. These
products will have both theoretical and practical
utility. The theoretical use is primarily for defining
the seasonally dynamic terrestrial surface CO 2 balance for global carbon cycle studies, such as solving the "missing sink question" of carbon (Tans et
al. 1990; Ciais et al. 1995; Randerson et al. 1997;
44
Field et al. 1998). The spatial and seasonal dynamics of CO 2 flux are also of high interest in global
climate modeling, because CO 2 is an important
greenhouse gas (Keeling et al. 1996; Hunt et al
1996). Currently, global carbon cycle models are
being integrated with climate models, toward the
goal of integrated Earth Systems Models that will
represent the dynamic interaction between the atmosphere, biosphere, and oceans. The weekly GPP
is most useful for theoretical questions, and more
correctly defines terrestrial CO2 fluxes than simple
normalized difference vegetation index (NDVI)
correlations currently done. These analyses will increase understanding of how the seasonal fluxes of
net photosynthesis and respiration are related to
seasonal variations of atmospheric CO 2 .
The practical utility of these GPPINPP products
is as a measure of crop yield, range forage and forest production, and other economically and socially
significant products of vegetation growth. The
value of an unbiased, regular source of crop, range,
and forest production estimates for global policy
and economic decision making is immense. These
products will be available for all users worldwide.
This chapter summarizes the conceptual background and implementation details of these new
EOS satellite products.
Theoretical Basis for the Algorithm
for Global NPP
The history of the theoretical basis for this satellite
estimate of terrestrial NPP has three components:
the idea that plant NPP is directly related to ab-
Global Terrestrial Gross and Net
Primary Productivity from the Earth
Observing System
Steven W. Running, Peter E. Thornton, Ramakrishna Nemani, and Joseph M. Glassy
Introduction
Probably the single most fundamental measure of
"global change" of highest practical interest to humankind is the change in terrestrial biological productivity. Biological productivity is the source of
all the food, fiber, and fuel by which humans
survive, and so defines most fundamentally the habitability of Earth. The spatial variability of net primary productivity (NPP) over the globe is enormous, from about 1000 g C m - 2 for evergreen
tropical rain forests to less than 30 g C m - 2 for
deserts (Scurlock et al. 1999). With increased atmospheric carbon dioxide (C0 2 ) and global climate
change, NPP over large areas may be changing
(Myneni et al. 1997a, VEMAP 1995, Melillo et al.
1993). Understanding regional variability in carbon
cycle processes requires a more spatially detailed
analysis of global land surface processes. Since December 1999, the U.S. National Aeronautics and
Space Administration (NASA) Earth Observing
System (EOS) produces a regular global estimate
of (gross primary productivity, GPP) and annual
NPP of the entire terrestrial earth surface at 1-km
spatial resolution, 150 million cells, each having
GPP and NPP computed individually.
The GPP and NPP products are designed to provide an accurate, regular measure of the production
activity or growth of terrestrial vegetation. These
products will have both theoretical and practical
utility. The theoretical use is primarily for defining
the seasonally dynamic terrestrial surface CO 2 balance for global carbon cycle studies, such as solving the "missing sink question" of carbon (Tans et
al. 1990; Ciais et al. 1995; Randerson et al. 1997;
44
Field et al. 1998). The spatial and seasonal dynamics of CO 2 flux are also of high interest in global
climate modeling, because CO 2 is an important
greenhouse gas (Keeling et al. 1996; Hunt et al
1996). Currently, global carbon cycle models are
being integrated with climate models, toward the
goal of integrated Earth Systems Models that will
represent the dynamic interaction between the atmosphere, biosphere, and oceans. The weekly GPP
is most useful for theoretical questions, and more
correctly defines terrestrial CO2 fluxes than simple
normalized difference vegetation index (NDVI)
correlations currently done. These analyses will increase understanding of how the seasonal fluxes of
net photosynthesis and respiration are related to
seasonal variations of atmospheric CO 2 .
The practical utility of these GPPINPP products
is as a measure of crop yield, range forage and forest production, and other economically and socially
significant products of vegetation growth. The
value of an unbiased, regular source of crop, range,
and forest production estimates for global policy
and economic decision making is immense. These
products will be available for all users worldwide.
This chapter summarizes the conceptual background and implementation details of these new
EOS satellite products.
Theoretical Basis for the Algorithm
for Global NPP
The history of the theoretical basis for this satellite
estimate of terrestrial NPP has three components:
the idea that plant NPP is directly related to ab-