Geoscience Reference
In-Depth Information
Table 9.4 LSM model components responsible for variation of surface luxes (in
particular transpiration and CO 2 lux) on different time scales; also indicated which
model variable causes this variation and which generation of LSM incorporated
this variation for the irst time
Timescale Change in LSM parameter/variable
Relevant atmospheric
model variable
First LSM
generation
Minute
Surface temperature
Radiation
First
H 2 O concentration in stomata
(due to change in surface temperature)
Radiation
Second, third
CO 2 concentration in stomata
(due to change in assimilation)
Radiation
None
Hour
Canopy resistance
Surface temperature
Radiation
Air temperature
Air humidity
Second, third
Day
Canopy resistance
Surface temperature
Radiation
Air temperature
Air humidity
Soil moisture
Second, third
Week
Canopy resistance
Radiation
Air temperature
Soil moisture
Second, third
Month
Canopy resistance
Vegetation fraction
Radiation (cumulative)
Air temperature
Soil moisture
Third, fourth
Year
Vegetation type
Air temperature
Soil moisture
Fourth
Furthermore, DGVM's may include modelling of nutrient dynamics (e.g., Gerber
et al., 2010 ).
The adaptive vegetation models produce their own amount and type of vegetation,
but the physical description of transpiration and assimilation is similar to that in third-
generation models. Through the inclusion of the process of assimilation, the models
can determine the seasonal variation in biomass.
Table 9.4 summarizes the various time scales involved in land-surface processes
and the parts of the LSM that is responsible to model this variation. It is clear that
most second- and third-generation LSMs are capable of simulating variations in sur-
face luxes of water vapour (and for some third- generation models CO 2 luxes) at
time scales up to weeks. This is suficient for weather forecast models, but for climate
models one needs fourth-generation models in order to include the long-term dynam-
ics of the vegetation.
 
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