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Chapter 9
such as those pioneered by Prof. Dickinson, are designed in large part to be
used in GCMs. Computer codes such as the Biosphere-Atmosphere Transfer
Scheme (BATS) and the Simple Biosphere (SiB) require a detailed
description of the transfer of radiation within these surface layers
(vegetation, soil). This is particularly so if they try to represent physiological
processes within the plant canopy (stomatal control of the water and
fluxes) or terrestrial elements of biogeochemical cycles (photosynthesis,
carbon assimilation, and respiration). SVAT models have been developed by
and for atmospheric scientists to describe essential physical processes
(namely the mass, energy and momentum exchanges) occurring at the
interface between the terrestrial surface and the atmosphere.
Land Surface Processes (LSP) models require the specification of spatial
distributions and temporal evolutions of a number of surface state variables
controlling the initial and boundary conditions for the exchanges of energy,
water, carbon, etc. at the surface. One of the major conceptual advances over
the last two decades has been to consider land surfaces as ‘active
boundaries’ for the dynamical, radiative and hydrological processes in the
atmosphere (e.g., Dickinson 1983, Sellers 1985). The global monitoring of
terrestrial surfaces largely relies on appropriate measuring tools and
techniques, such as remote sensing. However, the exploitation of these data
streams to extract some of relevant variables required by the biogeochemical
models and describe the corresponding exchanges must necessarily rely on
an analysis of the radiance fields emerging at the top of the atmosphere.
2.
CAN REMOTE SENSING HELP LSP STUDIES?
Remote sensing can, in principle, provide invaluable information on two
categories of LSP variables:
1. those controlling the radiative fluxes between the surface and the
atmosphere above (e.g., surface albedo, surface skin temperature, and
soil moisture), and
2. the state variables of the radiative transfer problem of the surface itself
(e.g., the Leaf Area Index, the vegetation fractional cover, the plant
architecture, etc).
Category 1 corresponds to instantaneous spectral- and angular-dependent
properties. They are not intrinsic properties of the surface since, for instance,
their values are changing with the state of the atmosphere.
Category 2 corresponds to variables representative of land surfaces. They
are intrinsic surface properties controlling not only the radiative exchanges
but also the dynamical and hydrological processes.
Chapter 9
such as those pioneered by Prof. Dickinson, are designed in large part to be
used in GCMs. Computer codes such as the Biosphere-Atmosphere Transfer
Scheme (BATS) and the Simple Biosphere (SiB) require a detailed
description of the transfer of radiation within these surface layers
(vegetation, soil). This is particularly so if they try to represent physiological
processes within the plant canopy (stomatal control of the water and
fluxes) or terrestrial elements of biogeochemical cycles (photosynthesis,
carbon assimilation, and respiration). SVAT models have been developed by
and for atmospheric scientists to describe essential physical processes
(namely the mass, energy and momentum exchanges) occurring at the
interface between the terrestrial surface and the atmosphere.
Land Surface Processes (LSP) models require the specification of spatial
distributions and temporal evolutions of a number of surface state variables
controlling the initial and boundary conditions for the exchanges of energy,
water, carbon, etc. at the surface. One of the major conceptual advances over
the last two decades has been to consider land surfaces as ‘active
boundaries’ for the dynamical, radiative and hydrological processes in the
atmosphere (e.g., Dickinson 1983, Sellers 1985). The global monitoring of
terrestrial surfaces largely relies on appropriate measuring tools and
techniques, such as remote sensing. However, the exploitation of these data
streams to extract some of relevant variables required by the biogeochemical
models and describe the corresponding exchanges must necessarily rely on
an analysis of the radiance fields emerging at the top of the atmosphere.
2.
CAN REMOTE SENSING HELP LSP STUDIES?
Remote sensing can, in principle, provide invaluable information on two
categories of LSP variables:
1. those controlling the radiative fluxes between the surface and the
atmosphere above (e.g., surface albedo, surface skin temperature, and
soil moisture), and
2. the state variables of the radiative transfer problem of the surface itself
(e.g., the Leaf Area Index, the vegetation fractional cover, the plant
architecture, etc).
Category 1 corresponds to instantaneous spectral- and angular-dependent
properties. They are not intrinsic properties of the surface since, for instance,
their values are changing with the state of the atmosphere.
Category 2 corresponds to variables representative of land surfaces. They
are intrinsic surface properties controlling not only the radiative exchanges
but also the dynamical and hydrological processes.