4-1a Terrestrial carbon cycle model
4-1b Oceanic carbon cycle model4-1c Dynamic vegetation model
The terrestrial biosphere absorbed atmospheric carbon dioxide by photosynthesis, and has returned carbon dioxide to the atmosphere again according to the action of breathing of vegetation, disassembly of a soil organic matter, etc. Changing the carbon balance of terrestrial vegetation sharply with temperature, water content, air carbon dioxide levels, etc. is expected. For this reason, it is possible change of terrestrial vegetation, and to affect climate further with the earth environment change by the greenhouse gas discharge represented by carbon dioxide.
It can divide into three components, a "biogeochemistry cycle", a "biophysics cycle", and "biogeography", about the substance of the terrestrial biosphere, or circulation of energy (Fig. 1). Vegetation takes in carbon dioxide by photosynthesis and "biogeochemistry cycles" is discharge and a cycle which lets disassembly of a soil organic matter etc. pass and exchanges substances further by breathing. A "biophysics cycle" is a portion treating the water balance of the vegetation by sunlight absorption of vegetation, precipitation, etc., and expresses change of the vegetation distribution by change of climate etc. in "biogeography." In this paper, it extracts to a "biogeochemistry cycle" and a "biophysics cycle", goes ahead with the talk, and mentions later about "biogeography" approach (II-1c).
This fiscal year examined the terrestrial carbon cycle model portion in an integrated model. As an existing model, there are "Sim-CYCLE" (Fig. 2) which describes a biogeochemistry cycle, and "MATSIRO" (Fig. 3) which describes a biophysics cycle. Sim-CYCLE is a model which mainly describes the dynamic state of carbon and water, and operates per a moon unit and day. On the other hand, MATSIRO is a model which is created as a land process model of a general circulation model, and describes circulation of water, energy, etc. Although MATSIRO is already combined with the general circulation model, leaf volume of vegetation is given by an external parameter and the carbon cycle is not described. In order to make this generate inside a model, it is required to incorporate the model which describes a biogeochemistry cycle like Sim-CYCLE.
From now on, first, combination of Sim-CYCLE and MATSIRO is performed and the fractional bond model about a terrestrial carbon cycle is built. Using the amounts of vegetation, such as a leaf area index MATSIRO [ leaf area index ] was forecast by Sim-CYCLE, Sim-CYCLE builds a mutual interface, such as using the water cycle forecast by MATSIRO, and performs model combination. The created model is used and the off-line examination under the past climate data conditions is performed.Moreover, it lets introduction of the result of a measurement of various field data, remote sensing data, etc. of the schedule obtained on a symbiosis third division title, and the newest knowledge etc. pass, and improvement of parameterization of a model is also performed. Moreover, change prediction of the vegetation carbon balance under the climate scenario conditions of futures, such as SRES scenario condition Shimo, is performed, and change prediction of the vegetation carbon balance in off-line is performed. Furthermore, built combination of the fractional bond model of a terrestrial carbon cycle and a general circulation model is performed, and the warming prediction experiment under SRES scenario conditions is conducted. On the other hand, in a future climate change, the construction of a terrestrial ecosystem model predicted to change of vegetation distribution is due to perform combination of an ecosystem change forecasting model and a terrestrial carbon cycle model, and to be aimed at.
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 Fig. 2: Outline of terrestrial vegetation carbon cycle model (Sim-CYCLE) |
 Fig. 3: Outline of land water and energy cycle model (MATSIRO) |
4-1b Oceanic carbon cycle model
4-1a Terrestrial carbon cycle model4-1c Dynamic vegetation model
The total carbonic acid vertical distribution in the ocean is carrying out characteristic distribution to which concentration becomes low near a surface. Such distribution with the big meaning for air sea exchange of carbon dioxide is determined by process, such as a living thing pump alkali pump and a physical pump, and is making contribution with the most important living thing pump resulting from sedimentation which follows the formation and it of an organic matter in a surface ecosystem especially. The efficiency of the living thing pump is influenced by various physical process, such as the depth of a sea mixolimnion, and transportation of the iron by Ekman upwelling and the atmosphere. Therefore, the climate change resulting from artificial origin carbon dioxide changes a living thing pump, and there is a possibility of enough of bringing positive or negative feed back further to carbon-dioxide absorption of the ocean.
According to the result of the terrestrial-air-sea combined carbon circulation model which a Hadley Centre (English) and IPSL (France) performed, influence which a climate change has on carbon-dioxide absorption of the ocean is made small. However, according to change of the sea carbon-dioxide absorption computed from the inversion calculation based on the carbon-dioxide-levels distribution in the atmosphere, or observation of the nitrogen / oxygen ratio in the atmosphere, it is suggested that the present sea carbon cycle model has the blunt sensitivity to a climate change. For prediction of the carbon dioxide levels in the atmosphere, necessity will have improving a sea carbon cycle model succeedingly.
as the ecosystem model included in an integrated model sea carbon cycle component -- phytoplankton, nitric acid, a zooplankton, and Deet Wrye -- 4 compartment surface ecosystem model which makes TASS a variable is considered (Fig. 4).
Fig. 4: Key map of marine ecosystem model to adopt. N -- nitric acid and P -- phytoplankton and Z -- a zooplankton and D -- Deet Wrye -- TASS is expressed, respectively. |
The model with the complicated structure where the structure of an actual ecosystem is more faithfully reproduced by many researchers other than such a model is developed, and the uncertainty of a parameter [ in / moreover / including many constituent factors / besides a marine ecosystem model / each ] of the integrated model which should finally be developed is also large. In such a situation, it judged that it was not a best policy to introduce the marine ecosystem model which has not much complicated structure in the present stage, and decided to adopt the four above-mentioned compartment models. A carbon-dioxide gradual increase experiment is due to perform immediately inclusion to the general circulation model of this model, and to be conducted by 3rd using the joint model which incorporated the terrestrial carbon cycle model further.
In the 3rd and afterwards, while performing experiment which used this joint model, and analysis of a result, it considers building the latest model also in consideration of the effect of air transportation of iron. The marine ecosystem model which adopted the iron effect is already developed partly, and it is thought that it is possible enough to make our model to reference and to change them into it. Moreover, about air transportation of iron, it already exists in the form where the dust transportation model which one of research implementation persons developed is immediately included in a general circulation model. The influence which the iron transportation by the atmosphere has on a living thing pump can be explicitly dealt with now by combining these, and coming that it can perform a more concrete argument about the feedback mechanism through the iron proposed about a glacial-interglacial cycle or global warming is expected.
4-1c Dynamic vegetation model
4-1a Terrestrial carbon cycle model4-1b Oceanic carbon cycle model
Although global warming may give a big change to the present vegetation zone distribution, when such [ actually ] change arises, it is considered to have feedback-influence on climatic conditions through change of the amount of fixed carbon content, the change in the water balance of an area, and the influence on sunlight reflectance. Therefore, in order to perform earth environment prediction to an order for hundreds of years - 1000 years, prediction of vegetation zone change is indispensable. Although many vegetation dynamic models of the former many had been built, they did not assume the fixing prevention or seed distribution process by the existing vegetation, and were not able to make reference about the speed which vegetation change produces.
When the fixing prevention and seed distribution distance by the existing vegetation are assumed, boundary movement between forest zones is theoretically presumed not to be generated on a scale for hundreds years. However, a big change may produce the boundary of the environment which the fixing prevention by the existing vegetation cannot commit easily, for example, the tundra, a step, a savanna, and a forest zone for a short period of time. the transition zone with which an arbor grows in a taiga-tundra boundary sparsely especially -- the number of width -- since it exists over 100km, compared with other biome boundaries, a prompt vegetation change may arise that there is [ therefore ] little seed supply restriction in the case of forest expansion. Moreover, the frigid zone forest occupies one third of the total forest area of the earth, and vegetation change of this area can have big influence on the accuracy of climate change prediction of a total ball level. Then, I want to model distribution change of a frigid zone forest as the first step of vegetation zone change prediction research.
It is two process of semination and non-raw fixing to become a key when predicting distribution change of a frigid zone forest. Among these, in semination process, the spraying range is greatly prescribed by the form of a seed. Comparison of the seed form of plant which constitutes a frigid zone forest considers the direction of deciduous broad-leaved trees, such as birch and poplar, that a seed is spread more to a distance compared with conifers, such as a pine and a spruce. That is, the tundra area adjacent to a broadleaf forest may be early forest-ized more compared with the tundra area adjacent to a needle-leaf forest. However, a fixed quantity and the compared research do not exist semination distance directly between plant which constitute a frigid zone forest. Then, it is planning presuming the semination distance of each plant from the vegetation recovery data of a forest fire site, and the plant composition data of the forest of the near.
Although information is insufficient also about the fixing process of a frigid zone forest, since the frequency distribution of an age distribution generally does not serve as a typical L character type curve especially in a transition zone, it is thought that fixing (again sowing child production) of a seedling is produced only for the year for which the environmental condition was ready. Then, I want to presume and make the model by correspondence with weather data the age distribution of the stand of every place, and over a long period of time about the relation between the meteorological condition in such a local level, and the propriety of fixing. However, the example from which an age distribution differs greatly is reported between whether to be small and the about 1km away stand, and fine geography hetero nature also influences the propriety of fixing strongly. the accumulated dose of organic matter of earth surface, such as etc., failing to get off the ground -- has the biggest influence as a factor that produces such hetero nature. Since these grounds surface material is removed by the forest fire, it may be able to take in the influence which a ground surface appearance has on the fixing probability of such an arbor from sub model of the subscription speed of a liter and lichen, a decomposition rate, and forest fire frequency.
The model construction of frigid zone forest distribution change serves as work which makes some change to the conventional vegetation zone dynamic model. Main changed parts are points including the process which the seed diffuses from the present vegetation distribution. Moreover, in an old vegetation zone dynamic model, the fixing process treated simple is modeled in detail. It tries to mention the speed of vegetation change which was not able to be treated by the conventional vegetation dynamic model by these work.