The Downscaling group identified five areas of long-term research: downscaling methods, uncertainties in regional climate modeling, candidate regional climate models, data management issues, and regional climate runs.

(i) Downscaling methods

It was recognized that two key approaches to downscaling would provide the basis for a Midwest Regional Collaborative Climate Center at Argonne: physically based modeling; and statistical/empirical-based modeling.

Physically based modeling involves the development of regional climate models appropriate to the region of interest. For the Midwest a regional climate must include a set of physical parameterizations for processes associated with the influence of the Great Lakes, land surface parameterizations, improved representation of the planetary boundary layer, and radiative transfer that can take into account the role of particles.

Statistical/empirical-based modeling may also play a role in downscaling global climate model (GCM) output. A wide range of approaches to statistical modeling are available, and their suitability for downscaling over the Midwest needs to be investigated. Statistical-based methods would be limited to a few key climate variables for which adequate data sets of observations were available for calibration purposes. Very few comparisons between statistical/empirical and physically based downscaling have been undertaken to date, and such comparisons will be needed in the long term.

It was also recognized that downscaling could be both linear, in that it distributes the larger scale global climate model averages at a finer scale, and nonlinear, in that the GCM provides the boundary conditions to a regional climate model, which generates a nonlinear downscaling by taking into account the physical, biological, and chemical processes at a much finer scale than the parent GCM.

The following were identified as key uncertainties that would need to be addressed in the development of a regional climate model for the Midwest:-

• pinup,
• ability to do long-term simulations,
• quality of GCM inputs,
• climate drift,
• consistent physics, and
• lateral boundary conditions and two-way nesting.

A key concern was the quality of the GCM inputs and their role in determining the ability of regional climate models to produce reliable predictions of climate change. Supported by lessons learned from PIRCS (summarized in the box below), the group emphasized the importance of continued development of GCMs in providing improved boundary conditions for regional climate modeling over the Midwest.

3. Regional climate models

Possible candidates to provide the basis for the development of a regional climate model for the Midwest include the following:

• NCAR MM5v2 mesoscale model
• NCAR MM5v3 nonhydrostatic mesoscale model
• RegCM2 hydrostatic regional climate model
• ARPS storm prediction model

The NCAR MM5v3 modeling system was considered the most appropriate basis for commencing development of a new generation of climate models. It was also recognized that considerable experience has already been gained using MM5v2 and RegCM and that model comparisons will play an important role in establishing the uncertainty associated with downscaled climate model predictions. Nevertheless, the group emphasized that performing regional climate simulations at 1-5 kilometer resolution must be regarded as a new research frontier.

4. Data management issues

In the long term, a wide range of data products will be needed. Examples include the following:

• Raw GCM data sets used as input to regional climate model runs
• Monthly means and variances of GCM inputs
• Reanalysis data sets
• Regional climate simulation data sets
• Monthly means and variances of regional climate simulation data sets
• Observational data sets in a form appropriate for comparison with regional climate model simulations

To ensure accessibility, these data sets must be made available over the Web via interactive tools for analysis, display, and downloading.

Achieving the best possible data quality for regional climate simulations will necessitate several tasks:

• Using multiple-input GCM boundary conditions for regional climate model simulations
• Achieving an appropriate level of model testing against observations
• Performing model comparisons
• Maintaining "best practice" in performing model simulations based on prevailing U.S. and international standards
• Carrying out peer review of the conduct and output of regional climate simulations

4. Duration of regional climate runs

Current computing resources allocated to regional climate modeling in the United States allow regional climate runs up to 10 years at 50 km resolution, but not on a routine basis. In the long term, the following needs have been identified:-

• Ability to perform high-resolution (<10 km) model runs for 10+ years routinely
• Ability to perform long model runs driven by GCMs for 100+ years (e.g., 2000-2100)
• Ability to perform model runs for the duration of available reanalysis data sets 50+ years for the purpose of model evaluation
• Ability to perform ensemble runs

Given the uncertainties noted above, a wide range of sensitivity studies will be needed in order to evaluate and improve the quality of the downscaled climate projections. This translates into the need for a substantial increase in computing resources available for investigating the performance of regional climate models and for downscaling the output of GCMs.

In the more immediate term, four research goals were deemed feasible and of high priority: downscaling experiments with MM5v3, additional experiments, statistical downscaling, and development of analysis tools.

1. MM5v3 downscaling experiments

An initial experiment was proposed that would build on the existing PIRCS effort. Specifically, model runs for the period 1978-1988 have been completed with the RegCM2 and HIRHAM regional climate models for the Midwest at a nominal 50 km resolution. It was recommended that

• This experiment be repeated using MM5v3 with a 50 km grid over the entire continental United States, 23 vertical levels and 100 mb model top, variable SST and NCEP/NCAR 6 hourly reanalysis as boundary and initial conditions for MM5v3.

• The results of this experiment be compared with RegCM2 and HIRHAM and with the observational data already available.

• A nest at ~17 km resolution be added in order to assess the benefits of using a finer spatial resolution.

Sensitivity studies could also be undertaken with and without the OSU land-surface model and with the Grell and KF convective precipitation schemes. Extending the lateral boundary relaxation conditions will also require investigation; it was proposed that this experiment be undertaken using the ARPS model.

The box below summarizes current plans for the development of MM5v3 by NCAR for application to regional climate simulations.

(ii) Additional experiments

The experiment described above could usefully be extended to include additional lateral boundary condition data sets derived from reanalysis projects and global climate models after completion of the first phase of experiments. The following high-priority lateral boundary condition data sets were identified:

• NCEP � II reanalysis data
• ECMWF reanalysis data
• NCAR Climate Systems Model (CSM) six-hourly input data for the period 1980-1998 for comparison with RegCM2.
• HADCM2 six-hourly data

Performing ensemble runs was also recognized as an important tool for model evaluation. However, available resources currently limit our ability to undertake ensemble experiments.

1. Statistical downscaling

A useful first step would be to undertake a comparison of regression, condition models, and neural net approaches commonly applied in statistical downscaling.

Further development of analysis tools for working with the output of regional climate simulations was also identified as a priority for enhancing productivity. It was proposed that useful short-term activities would be to

• evaluate the utility of existing packages (e.g., PCMDI developed at LLNL),
• investigate new tools under development (e.g., GSP project at NCAR), and
• build Web-based analysis tools.

The Hydrology group identified two major long-term scientific objectives, each of which also has major implications for impact assessment and policy/decision making:

• Prediction of water levels in the Great Lakes. Lake levels can have a strong impact on shipping, recreation, and other important uses of the lakes. Previous studies have suggested lake levels are likely to drop with greenhouse warming, but it remains unclear by how much (or whether it will happen at all). These changes could occur during the coming century as current expectations call for a doubled CO₂ by 2070.
• Agriculture. Of particular interest are the effects of increased CO₂, which could dramatically affect both the amount of water available and the water demand through enhancing evapotranspiration needs. One important aspect concerns a northward shift of the mean position of the jet stream, which could lead to increasingly dry weather in the southern part of the Midwest, and wetter weather in the upper Midwest. Another major concern is a possible link between reduced snow cover (due to warmer winters) and reduced amounts of soil water in late spring and summer, which could exacerbate any reduction in precipitation. Long-term impacts on ground water aquifers can also be important, especially to the Great Plains, though such changes are difficult to model. Much of the western Midwest and West rely on irrigation for agriculture; precipitation over distant catchments (e.g., mountain snow) is of importance.

The group also developed a model evaluation strategy that has two key components aimed at an overall assessment of model uncertainties:

• Assessment of how well the model simulates the present-day climate by making a comparison of model results with station or remote-sensing data.
• Comparison of model results for specific time periods of the past several thousand years, with climate data derived for those time periods from the geological record.

To undertake the first activity, the regional model (MM5) must be run for an appropriate Midwest domain, with NCEP, ECMWF, and/or DAO reanalyses providing the lateral boundary forcing. The domain has yet to be defined; but to accomplish the overall goals, it must contain at least one of the Great Lakes. Thus the initial domain will likely cover the upper Midwest region. After appropriate evaluation, the regional model will be forced at the lateral boundaries using a GCM (most likely the NCAR CCM). This is the same global model that will ultimately be used for climate change scenarios.

Two components are involved in the second activity. The first of these addresses questions of historical variability. GCM runs over the past 1000 years (currently being made at NCAR and elsewhere) will provide the boundary forcing, with historically appropriate land-use changes imposed. Examples include 17^th-18^th century runs with MM5, the medieval warm period from A.D. 1000 to A.D. 1400, and the "Little Ice Age" of the late 1600s. The second element involves study of paleoclimate (i.e., time periods previous to the historical record) for which geologic reconstructions for the upper Midwest are well known. An obvious example is simulations for 3k, 5k, 6k, 7k, 9k BP, for which considerable prior global modeling exists and for which extensive geologic reconstructions have been made.

Ultimately scientists will be moving toward simulations of possible future climatic change (e.g., under an enhanced greenhouse world), so that the two long-term scientific objectives can be realized.

Six other long-term issues meriting future work were identified during the meeting:

• Coupling of ocean and atmosphere models and regional models to better simulate and understand long-term low-frequency variability.
• Differentiation of "quality" � that is, distinguishing a good simulation from a bad simulation.
• Data assimilation. Will it be possible, and desirous, to develop a regional data assimilation system analogous to what is currently done with global models to create analysis and reanalysis data sets?
• Severe events: These are of obvious importance, but a strategy must be defined for how to use model simulations to determine what sorts of severe events might be expected, and some estimate of their probability of occurrence.
• Ground water. This topic is clearly important for the western part of the Midwest region, which depends on ground water for irrigation and other water uses. The time scales are longer than those of mesoscale weather; nevertheless, it should be possible, ultimately to model ground water.
• Sensitivity to climate change off-line using RCM output.

Our short-term goals for the next year are aimed at developing and implementing a regional model system that is capable of simulating climate for the upper Midwest, including the Great Lakes. The proposed region has yet to be defined fully, but is likely to be based on the north-central region of GCIP. Focusing on this limited-scale area will enable researchers to take advantage of the tremendous amount of work already being done for this region through GCIP; three members of the Hydrology team (Oglesby, Marshall, and Lapenta) are also current GCIP principal investigators.

The following are needed for model development:

• A dynamical model for Great Lakes. AVHRR data exist for lake surface temperatures that could be used to initialize the lake model. Also required is a comprehensive study of thermal structure of Lake Superior, yielding lake-water temperature distribution in the Great Lakes. While work is already under way on this, a certain amount of support (~$200k / yr) would greatly expedite this undertaking.
• Study of different land-surface packages in MM5V3, with an emphasis on how well the surface and subsurface hydrology is handled. Examples of such land surface packages include BATS, LSM (NCAR), and OSU.

Two factors must be kept in mind as this preliminary regional model run is designed and implemented:

• Research must be coordinated with GCIP to avoid duplication of effort.
• BC�s should be taken from NCEP II (not NCEP I) reanalysis. This should serve as forcing for the first, prototype run. ECMWF can be used next (holding off on DAO until their next reanalysis).

If the necessary model developments are successfully undertaken, researchers should be able during the coming year to make an initial five-year run for the upper Midwest domain, using MM5v3 and the most suitable land surface package, forced by NCEP II.

The Energy group identified five primary objectives: (1) assessing energy consumption and generation scenarios over the next 100 years for the Midwest; (2) developing and collecting greenhouse gas source/sink estimates on a local scale; (3) developing and collecting emission scenarios for precursors of air pollution and aerosols on the local scale; (4) performing assessment calculations to evaluate the impacts of these emissions on climate and the effect of climate change on these estimates; and (5) preparing impact assessments for the regions� air quality, agricultural production, and human health

Development of energy consumption/production scenarios is a crucial task because of the

proposed energy utilities deregulation and the possible decommissioning of aging nuclear energy generation infrastructure that generates a significant portion of the current Midwest energy supply. The choices made for future energy generation could dictate the location of the power plants and, as a result, the emissions of greenhouse gases and air pollution precursors in the region. The group identified potential parties that may be

actively pursuing this task, including some at Argonne. It was agreed that the relevant parties, starting with those located inside Argonne, should be included in future meetings and a discussion started with them immediately. Moreover, in developing and assessing currently available modeling frameworks for estimating regional energy requirements and consumption, consideration should be given to the impact of decisions made on a countrywide and international scale. There should be feedback from these model outputs into the global-scale models, in order to develop realistic assessment scenarios.

Developing tools for detailed analysis of greenhouse gas emissions and sinks on a local scale was considered a necessary priority for the center. In this context, the center could emulate the work performed by the Iowa Department of Natural Conservation in developing greenhouse gas sink/source estimates to the level of local farms. The focus of the Iowa effort was to develop policies to make that state a net zero greenhouse gas emitter. This type of inventory-making capability should be acquired by the center and a demonstration performed to show that better decision making would result from better tools.

The most effective tool the center could develop to serve users across a broad cross-section of society, from research scientists to policy makers, is an integrated assessment model. These types of models are frequently used in the IPCC assessments on a global scale and integrate across a range of process-scale models representing energy production, consumption, emissions, and impacts of greenhouse gases and pollutants. Such models provide an excellent opportunity to study the feedback between climate and the biosphere, atmospheric trace gas abundance, and the energy production/consumption in various sectors of the economy in an integrated framework. The development of integrated assessment tools is still in its infancy, and the center could make a strong bid for leadership in this area..

Science issues of interest include the impact of further urban sprawl on oxidants and aerosols, effects of land use change on regional climate, and impacts of agricultural practices on climate and chemistry. The relationship between energy use and agriculture, in particular, should be a focus of the center�s science activities. Below is a list of science issues that were discussed:

• Agricultural activities, including emissions from agriculture, changes in land use, and changes in carbon sources/sinks at the level of farms as a result of climate change, and the effect of these factors on climate change itself. The group recommended that this area be a centerpiece of the RCCC�s long-term research efforts.
• Regional air pollution and its impacts on climate, particularly in relation to aerosols.
• Particle emissions from the biogenic activity and the impact of climate change on the emissions.
• Effect of agricultural practices such as the use of nitrogenated fertilizers on regional-scale production greenhouse gases, ozone, and other oxidants and aerosols.
• Role of heterogeneous chemistry on aerosol surfaces in the production and loss of atmospheric oxidants.
• Impacts of climate change on biogenic emissions, regional-scale oxidizing capacity, and particulate production.
• Impacts of climate change on vegetation and ecosystems unique to Midwest.

The group identified the following process models to evaluate the energy-chemistry-biosphere-climate interactions on a regional scale:

• Emission estimates/models, to develop emission estimates of energy consumption for each sector of the economy
• Air pollution transport/chemistry models with gas-phase chemistry drivers and aerosol process modules
• Meteorology drivers and the development of couplers between meteorology models and chemistry/transport models
• Chemical boundary conditions drivers for the regional-scale model based on observations and global-scale CTMs
• Biogeochemical interface, including surface exchange models, biosphere models, and crop/agricultural models

Several of these models are available within the group, and it was decided to examine available options for the remaining modules.

The following uncertainties were listed as items for consideration in the regional-scale modeling efforts described above:

• Downscaled temperatures and humidities. Temperature and humidity impact a wide range of chemical and biospheric processes, including emissions, reaction rates, particle formation, and oxidative capacity.
• Emission uncertainties due to errors in projections, partly resulting from uncertainties in climate model predicted inputs to emission models.
• Shortcomings in current understanding of physical/chemical/biological processes, such as deposition, washout, chemistry, and plant physiology.

The following list of priorities was discussed at the meeting:

• Development of massively parallel versions of chemistry-transport and biosphere models.
• Runs of regional-scale models for the chemistry and biopshere on both seasonal and annual scales (rarely done at present).
• Development of fast visualization tools to analyze large databases of model outputs. Typically the outputs from these models could be 60 to 100 times larger than the mesoscale meteorological model outputs.
• Development of a database of measurements of trace gas concentrations on the regional scale.

In the short term, energy research should focus on GHG budgets and regional-scale assessment models.

(i) GHG budgets

• Check current modeling/accounting work done, with a focus on Midwest forecasting of carbon budgets.

• Determine what kinds of models are currently used, whether any will be readily available, and which downscaled products from the climate models will be useful for these models.

A prototype model calculation was recommended as a first step toward developing a comprehensive integrated assessment model for the regional scale. This calculation should involve development of interfaces between models calculating energy production/consumption based on sector analysis, an emissions calculation model that uses the output from the energy model to compute emissions of pollutants, and GHGs. This calculation in turn would feed into a chemistry-transport model linked to the

regional-scale climate model to drive the model transport. The chemical model boundary conditions would be set from global-scale CTM outputs, by developing couplers between the regional-scale code and the GCTM. The RCTM would be connected to a surface process model with the capability of computing deposition rates and emissions from biosphere. The final step would link this model to a crop-nutrient-cycle model to calculate soil emissions and effects of deposition from the gas phase on the nutrient-cycle

in the soil. The outputs would in turn be fed back to the energy component model to improve the decisions made on energy consumption/production in each sector of the economy, so as to minimize the impacts on the biosphere and air quality. The prototype would function with models readily available, and missing components would be filled with shell interfaces for the prototype calculation.

As a part of this process, the group identified the following issues to be analyzed and summarized in a report to be submitted by the end of next year:

• Sorting available modeling tools and identifying those most appropriate for the center
• Preparing data sets for model evaluation at the time and spatial scale necessary for the purposes of the center.
• Evaluating data on energy use and emissions, including models used to make projections.
• Identifying measurement needs to evaluate/validate the models
• Developing concepts for an integrated assessment model on a regional scale.

The figure below shows the proposed prototype calculation setup.