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MOSES calibration for coniferous forest

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A full optimisation using a NAg 'search' algorithm revealed multiple minima with ... tuning has occurred, then return to NAg routines for final phase of optimisation, ... – PowerPoint PPT presentation

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Title: MOSES calibration for coniferous forest


1
MOSES calibration for coniferous forest
  • Chris Huntingford, Peter Cox, Richard Harding..

2
The datasets used
  • A key biome in the represented in the Hadley
    Centre land surface model (MOSES/TRIFFID) are
    needleleaf trees. Two such FLUXNET sites are
  • Loobos (Holland)
  • Tharandt (Germany)

3
MOSES/TRIFFID structure
4
TRIFFID output
5
Parameters to be optimised.
  • Four parameters associated with photosynthesis
    f0, D, NL0, a. These affect overall stomatal
    opening, VPD response, leaf nitrogen level
    (influencing temperature response) and light
    response.
  • Vcrit Soil moisture content at which vegetation
    stress starts to occur.
  • Soil carbon content, Cs (in the GCM this is
    initial diagnosed from pre-industrial control
    simulation and balance between turnover and
    respiration).
  • A new light response curve (beyond tuning the a
    parameter)?

6
Optimisation.
  • A full optimisation using a NAg search
    algorithm revealed multiple minima with
    associated risk of finding the wrong solution. No
    feel for the effect of changing parameters.
  • Decided instead to simply assess the effect of
    manually changing a) the photosynthesis
    parameters, then b) critical soil moisture
    concentration and finally c) the soil carbon
    content.
  • Once manual tuning has occurred, then return to
    NAg routines for final phase of optimisation, and
    including uncertainty bounds (E04YCF).
  • Once finished, see whether difference between
    optimised parameters (Loobos vs Tharandt) is
    smaller than the uncertainty bounds associated
    with data error.

7
Loobos optimisation
  • Left column original light dependence
  • Right column new light dependence
  • Different rows are sensitivity to soil carbon
    content.

8
Tharandt optimisation
  • Left column original light dependence
  • Right column new light dependence
  • Different rows are sensitivity to soil carbon
    content.

9
Light dependence.
  • Current model uses the Sellers (1994?) assumption
    that everything in the canopy scales with the top
    leaf level response (and according to Beers
    law).
  • However, this may be failing to get a smooth
    transition between light limited response, and
    other environmental constraints that occur around
    midday.

10
Light dependence.
NEP
Measurements
Temperature limited
Light limited
Model
Time of day
Midday
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