Difference between revisions of "Climate Model"
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The vegetation index is a mapping of the categorial variable [[Definition:VegetationTypeCode | vegetation type code]], to a nominal variable. The vegetation index is used as one of the explanatory in the Whole-stand growth model (see page 39 in the [http://heurekaslu.org/mw/images/9/93/Heureka_prognossystem_(Elfving_rapportutkast).pdf "Growth modelling in Heureka" document]). | The vegetation index is a mapping of the categorial variable [[Definition:VegetationTypeCode | vegetation type code]], to a nominal variable. The vegetation index is used as one of the explanatory in the Whole-stand growth model (see page 39 in the [http://heurekaslu.org/mw/images/9/93/Heureka_prognossystem_(Elfving_rapportutkast).pdf "Growth modelling in Heureka" document]). | ||
Revision as of 18:54, 22 March 2016
TODO.
Introduction
In Heureka, the effect of global warming on forest growth can be accounted for based on results from a process-based model called BIOMASS. BIOMASS was developed by McMurtrie et. al (1990)[1] and has been modified and validated for Swedish conditions in a number of studies [2], [3], [4], [5]. BIOMASS is computationally demanding to run and not suitable to include directly in Heureka’s growth simulator. Therefore BIOMASS was run for different parts of the country and different forest conditions, and the results have been used to construct an approximation model of BIOMASS.
How the model works
A special approach has also been developed to adapt the response of the growth models used in Heureka. The principal idea is to augment or shift the growth function when climate changes. This is done by changing tree ages; the size to age relation of trees is a critical variable in all growth functions used in Heureka. In the system, we differ between actual tree age and biological tree age. The biological age is the one subject to adjustment.
The climate response model affects the following variables directly:
- The biological age or basal area (gt) depending on user setting
- Site index (SIS)
- Vegetation index
- Temperature sum
Response modifiers
Function BIOMASSresponse ()
A "climate scenario" file imported to Heureka is not an actually scenario but a table of coeffiicients used to calculate growth modification factors that are then used in the Heureka "climate model".
For a given prediction unit that has soil moisture class j, the growth correction factor is calculated as function of the parameters a, b and c, which depend on scenario, geographic locations, tree species and soil moisture code.
where
αBIOMASS(i,j) = Growth correction factor for species j according to model BIOMASS, and
LAI(s) = Leaf area index for species s (m2 leaf area / m2 forest floor area)
Since leaf area is not calculated in Heureka, foliage biomass is used instead, and multiplied with a conversion factor (SLA) to get LAI.
where
fbm(s) = Foliage biomass (kg/m2, dry matter / forest floor area), and
SLA(s) = Conversion factor for biomass foliage to leaf area for species s (m2 projected one-side leaf area / kg dry matter),
prop(s) = Species proportion of species s in the stand, used as indicator for how much of the forest floor area is occupied by species s. The division with the species distribution is done because the divisor (forest floor area) should only include the forest floor occupied by the subject trees.
Growth respone to temperature and water (β)
reflects "optimal" stand conditions and should therefore be modified. The response modifier is a linear function of vegetation index.
where
β(s) = Response modifier for species s, and
VIX = Vegetation index, and
c0(s) = Intercept for species s (see control table), and
VIXmin = Minimum vegetation index for species s, and
VIXmax = Maximum vegetation index for species s.
The modified response for each species s is:
Carbon dioxide response
The carbon dioxide response modifier is calculated with the same type of formula as α(s), but with other coefficients.
This value is then multiplied with the calculated growth response.
Temperature sum change
The change in temperature over time caused by a changing climate is expressed as an average temperature sum change factor (λ) for five years, and is part of the climate scenario input data.
Site index change
The site index (sis) change from one five-year period to the next is calculated as
where
= Temperature change factor for a five-year period
= Change in temperature sum between two five-year periods (
) and t is period index, and
= Change between squared temperature sums from period t-1 to period t (
)
Vegetation index change
The vegetation index is a mapping of the categorial variable vegetation type code, to a nominal variable. The vegetation index is used as one of the explanatory in the Whole-stand growth model (see page 39 in the "Growth modelling in Heureka" document).
The climate model modifies the vegetation index. The vegetation index increases when the climate model predicts increased growth. The vegetation index is updated in each projection period.
Input data
With the installation of Heureka, there are three climate model scenarios available:
- MPI 4.5: Based on Max Planck Institute MPI-ESM model using radiation scenario RCP 4.5, which assumes that radiative forcing stabilises at 4.5 W/m² before the year 2100. See also RCP4.5 at SMHI's homepage.
- MPI 8.5: Based on Max Planck Institute MPI-ESM model using radiation scenario RCP 4.5, which assumes that radiative forcing stabilises at 8.5 W/m² before the year 2100.. See also RCP8.5 at SMHI's homepage
- ECHAMS_A1B: Based on Max Planck Institute climate model ECHAM using emission scenario SRES A1B.
See also
- About SMHI climate scenarios
- Climate scenarios used in Heureka in the SKA 15 project
- Import climate scenario in Heureka Helpdoc.
Model settings that a user can modify
Selected climate scenario
Model parameters
Several model parameters can be modified via the Climate Model control table.
Age adjustments
References
- ↑ McMurtrie R. E., Rook D. A. & Kelliher F. M. 1990. Modelling the yield of Pinus radiate on a site limited by water and nitrogen. Forest Ecology and Management 30: 381–413.
- ↑ Bergh J., McMurtrie R. E. & Linder S. 1998. Climatic factors controlling the productivity of Norway spruce: a modelbased analysis. Forest Ecology and Management 110: 127–139.
- ↑ Freeman M & Linder S. 2001. Boreal forests. In: Long-term effects of climate change on carbon budgets of forests in Europe (eds. Kramer, K. & Mohren, G.M.J.) pp. 197–203. Alterra-report 194. Alterra, Green World Research, Wageningen, 2001
- ↑ Bergh J., Freeman M., Sigurdsson B. D., Kellomäki S., Laitinen K., Niinistö S., Peltola, H. & Linder S. 2003. Modelling the shortterm effects of climate change on the productivity of selected tree species in Nordic countries. Forest Ecology and Management 183:327–340
- ↑ Freeman M, Morén A-S, Strömgren M & Linder S. 2005. Climate Change Impacts on Forests in Europe: Biological Impact Mechanisms. In: Management of European Forests under Changing Climatic Conditions (eds. Kellomäki, S. and Leinonen, S.). ResearchNotes 163, University of Joensuu, Forest Faculty, pp. 45-115. ISBN 952-458-652-5
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