Global Modeling Group

Summary

The aim of the Global Modeling Exercise is to develop quantitative scenarios for the Millennium Assessment. This exercise will couple and run a set of global models with harmonized inputs and outputs. The models will be used to produce consistent and globally-comprehensive quantitative information about important aspects of global ecosystems, their services, and their impacts on human well-being. Quantitative scenarios will be generated about crop production, status of freshwater resources, land cover, fishery yield, and other important indicators of ecosystems. First the models will be soft-linked, and run with a set of drivers consistent with the storylines developed by the Scenario Working Group. Next, the calculations from the various models will be harmonized into a set of consistent quantitative scenarios. Finally, the quantitative scenarios will be harmonized with the scenario storylines (working together with other members of the Scenarios Working Group) by revising the storylines and re-running the models. The cycle of revising storylines and quantitative scenarios will be repeated until a rich set of qualitative and quantitative scenarios are produced with as high a level of consistency as possible.

Overview of the Global Modeling Exercise

The basic aim of the Global Modeling Exercise is to produce quantitative scenarios of future changes of global ecosystems, their services, and their impact on human well-being. The estimates will have world-wide coverage, and a time horizon up to 2050, with less detail up to 2100. Indicators about ecosystem services in the categories of “provisioning”, “regulating” and “supporting” services will be computed.

The models will be run with a consistent set of inputs and output formats, and the output of some of the models will serve as input to other models involved in the exercise (explanation below). The models currently involved in the Modeling Exercise are:

1. The IMPACT model of IFPRI, United States which computes global agricultural production according to different world regions and selected countries.
2. The WaterGAP model of the University of Kassel, Germany which computes global water use and availability on a watershed scale.
3. The AIM global change integrated model of the National Institute for Environment Studies, Tsukuba, Japan which computes land cover and other indicators of global change on a world-wide basis, with emphasis on Asia.
4. The IMAGE 2 global change integrated model of RIVM which computes global land cover and other indicators of global change.
5. The ECOSIM model of world fisheries of the University of British Colombia, Canada which relates fish catch to trophic levels in marine ecosystem regions.

The models will be soft-linked in the sense that output files from one model will be converted and used as input files to other models. (The models will not be hard-linked in that their programs will not be merged.) The inputs to the models will be harmonized by adopting a set of inputs consistent with the storylines of the MA Scenarios Working Group (see below). The outputs to the models will be harmonized by using an agreed-upon set of output indicators with particular temporal and spatial details (see below.)

Disadvantages/Advantages of the Approach.

The disadvantages of this approach are that the models are highly uncertain, their functioning is not easy to explain to a non-technical audience, and they were designed independently and are therefore likely to be somewhat incompatible with one another. Moreover, taking into account the schedule of the MA, the modeling exercise will require an intense effort over a short period of time.

The advantages are that these models have been published in the scientific literature and have therefore undergone a measure of scientific peer-review. They have also been used in many international policy-relevant applications, and have been found to be useful for linking science and policy issues. The most important point here is that the models cover at least some of the many important aspects of the global system that are relevant to scenarios and the assessment of world ecosystems. Therefore they can provide valuable input to the scenarios including information about world food production, the status of world freshwater resources, global land cover, and status of world fisheries. In combination, the models provide a unique opportunity to generate globally-comprehensive, rich and detailed information for the MA assessment.

Structure of Modeling Exercise

The structure of this modelling exercise is shown in figure 1. The main input information such as demographic, economic and technological information will be used based on published data of the IPCC. This data will be disaggregated and feed the IMAGE 2 as well as the AIM model. In a next step the output of the IMAGE 2 model such as climate data, electricity, livestock, GDP and population will feed the WaterGAP and the IMPACT model. From the last model data will be needed for the ECOSIM model. The output of the single models must be harmonized and presented in a consistent way.



Fig. 1 Structure of modelling exercise and flow of information for first round calculations

Tasks

Harmonization of model calculations

The main objective of this task is the harmonization of the input and output of the various global models so that a maximum amount of consistency can be achieved in the results of the modeling exercise. By “harmonizing” we mean, for example, ensuring that quantitative model inputs are consistent between the models, and that a consistent set of reporting areas and time periods are used. This also means using the output from one model as input to another. These points are elaborated below.

Selection of Model Inputs and Indicators

The purpose of this sub-task is the preparation of the necessary data and formats for the model runs.

Model inputs / System Drivers. In preparation of the computer runs, assumptions about model inputs must be agreed upon by the modeling teams and the Scenarios Working Group. In the terminology of the MA, these would be the basic “system drivers” of the global system, and would include various climatic, demographic, economic, technological and other (cultural, political) variables. Some categories of these inputs are shown in Figure 1. Quantitative values will be selected so as to be as consistent as possible with the scenario storylines. An electronic file of these modeling inputs will be prepared by the staff of this project and distributed to all modeling teams.

Model Outputs. Before model runs are carried out, the modeling teams and Scenarios Working Group will also select the type of output to be computed by the models. This includes:

• the indicators to be used to describe ecosystem services (for example, the use of “annual renewable water resources on the watershed level” as an indicator of the provisioning services of freshwater)
• the temporal intervals of output (for 2010, 2020, etc.)
• the spatial resolution/aggregation of output (grid, watershed, national level).

First Round Calculations

The objective of this sub-task is coordinate an initial set of model experiments with the selected system drivers, and a first linkage between models. The staff of this project will coordinate these experiments in the sense that they will ensure that the different modeling teams receive the data and information they need to run their models. Moreover, they will monitor whether the different modeling teams are providing needed information to other teams within the time schedule of the global modeling exercise. The following is an estimate of the model calculations to be carried out in the first round of calculations (Note, subject to change):

Calculating agricultural production (“provisioning service”). Using the agreed-upon system drivers, the IMPACT model will compute world agricultural production. Indicators are the production and consumption of meat, fish, and grain. For comparison, the IMAGE 2 and AIM models will also compute potential grain production.

Calculating fish yield (“provisioning service”). Using the computed fish consumption from IMPACT, and other system drivers, the ECOSIM model will compute fish yield in different oceanic regions.

Calculating water resources (“provisioning services”). Using the estimate of the future extent of irrigated land from the IMPACT model, together with other system drivers, the WaterGAP and AIM models will compute various indicators of freshwater resources. These include annual renewable water resources, water withdrawals (including irrigation water requirements) and water consumption. The computation by WaterGAP is elaborated under Task 3.

Calculating fiber (“provisioning service”). Using the agreed-upon system drivers, the IIASA forestry model will compute world timber production based on system drivers, and other inputs to be identified.

Calculating land cover. Estimates of the changes in land cover, and the future state of land cover, are needed for estimating the future state of terrestrial biodiversity and the net carbon flux between the biosphere and atmosphere. Hence, in this project the IMAGE 2 and AIM models will compute various future land use indicators. For these calculations they will use, among other inputs, the output from the IMPACT model on future crop production. The AIM model will compute land use indicators on the regional and country scale with special emphasis on Asia, while the IMAGE 2 model will compute them on a global grid.

Calculating fuelwood (“provisioning service”). Using the agreed-upon system drivers, the IMAGE 2 model will be used to compute biofuel production based on inputs from the IMPACT model, and estimates of future land cover.

Calculating climate regulation (“regulating service”). Using the agreed-upon system drivers, the IMAGE 2 model will be used to compute the net carbon flux between the atmosphere and biosphere on a global grid.

Calculating erosion risk (“regulating service”). Using the agreed-upon system drivers, the IMAGE 2 model will be used to make a first estimate of the risk of erosion on a global grid.

Calculating air quality (“regulating service”). As proxies for air quality, the IMAGE 2 model will compute the emissions of NOx and SO2 emissions on a regional scale.

Calculating primary production (“supporting service”). Using the agreed-upon system drivers, the IMAGE 2 model will compute primary production on a global grid.

Calculating indicators relevant to human well being. The IMPACT model will be used to compute the number of malnourished children in the world and the WaterGap model will be used to compute water stress in river basins throughout the world.

Second Round Calculations – Harmonizing the Results

The objective of this round of calculations is to harmonize the results of the different models so that a relatively-consistent set of calculations can be delivered to the Scenario Panel of the MA.

The main challenge will be to check the consistency of IMPACT calculations with calculations of water availability, land cover and fishery yield from the WaterGAP, IMAGE 2, AIM, IIASA and ECOSIM models.

After identifying the inconsistencies, the models will be re-run with new inputs, and their outputs again checked for consistency. This procedure will be repeated until a sufficient level of consistency is achieved.

Harmonization of storylines and quantitative scenarios

After the model input and output is harmonized as described above, it is time to harmonize the model calculations with the storylines of MA scenarios. “Harmonize” in this sense means achieving a reasonable level of consistency between the model results and the main features and messages of the storylines. Harmonization will involve the following steps:

1. The model calculations are presented to the MA Scenario Working Group for discussion.
If model calculations indicate inconsistencies in the storylines, or point to new and interesting trends in ecosystems not yet considered in the storylines, then the Panel may revise the existing storylines or perhaps adds new storylines.
3. If the storylines are revised or new ones are added, then a new set of system drivers / model inputs are derived from the new storylines.
4. Using the new model inputs, a new set of model runs are carried out.
5. Model results are again harmonized as described in Task 1.3, and again brought to the Scenario Panel where they are discussed.
6. Steps 2 through 5 are repeated as necessary, and as the time schedule of the Scenarios Working Group allows.

Under the pressing time schedule of the project, it is realistic to assume that the cycle of revising storylines and model calculations can be repeated at most two or three times. The end result of these iterations will be a rich set of qualitative and quantitative scenarios with as high a level of consistency as possible.

Reporting on results of the Global Modeling Exercise

The Global Modeling Exercise will generate a rich, but also very complicated set of quantitative information. Because of the complicated nature of this information, special attention should be given to its communication. The objective of this task is to help ensure that the valuable information from the modeling exercise is effectively summarized and communicated to the different parties involved in the MA, and to the policy and scientific community outside of the MA. This task includes:

• Summarizing and reporting results from the modeling exercise to the rest of the Scenarios Working Group, and presenting results at various other meetings of the MA.
• Reporting results of the quantitative scenarios to the scientific and policy community outside of the MA (together with the leaders of the MA). This is especially important as part of the peer and government review process of the MA.
• Preparing written reports and scientific papers on the results of the modeling exercise, in cooperation with members of the modeling teams and Scenarios Working Group.

Output of the Project

The Global Modeling Exercise will generate a rich, but also very complicated set of quantitative information. Because of the complicated nature of this information, special attention should be given to its communication. The objective of this task is to help ensure that the valuable information from the modeling exercise is effectively summarized and communicated to the different parties involved in the MA, and to the policy and scientific community outside of the MA. This task includes:

• Summarizing and reporting results from the modeling exercise to the rest of the Scenarios Working Group, and presenting results at various other meetings of the MA.
• Reporting results of the quantitative scenarios to the scientific and policy community outside of the MA (together with the leaders of the MA). This is especially important as part of the peer and government review process of the MA.
• Preparing written reports and scientific papers on the results of the modeling exercise, in cooperation with members of the modeling teams and Scenarios Working Group.