Workshop on Regional Climate Research: Needs and Opportunities
Discussion Items: Key Questions for Discussion

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Overarching Questions

  • How do we define regional climate – what are the temporal and spatial scales? What are the forcings of regional climate?
  • Is there a theoretical limit to the predictability of regional climate features? Should we expect downscaling to be able to improve simulations of climate at the regional and sub-diurnal scale and extreme events?
  • How accurate are current GCMs and downscaling methods in reproducing the observed regional seasonal and interannual climate statistics?
  • Can downscaling improve the simulations of extreme events over GCMs? How do we demonstrate this?
  • What spatial resolution is required in the GCMs to properly simulate the large-scale features for downscaling? Is it possible that unresolved scales in the GCMs may lead to errors in the large-scale flow (e.g., moisture transport) that could not be compensated by any amount of downscaling?
  • How must physical parameterizations change as a model's grid spacing is refined, and are current regional or global variable/high resolution climate models properly designed in this sense? Is it possible to devise parameterizations that are applicable in models with a wide range of grid spacings?
  • What are the relative merits of increasing spatial resolution versus more accurate or sophisticated physics? What are the impacts of finer regional resolution for model dynamics and orography, and for model physics and land-sea differences?
  • What are the relative advantages and disadvantages of dynamical and statistical downscaling techniques? How do different downscaling techniques compare for reproducing the current climate and projecting future climate scenarios? How do we determine the confidence in these scenarios when we do not yet have the truth?
  • How do we quantify the value-added (or lost) due to downscaling when compared with raw GCM output for climate information and impact assessments? Is accuracy improved along with the increased precision? What experiments, data, and statistical measures can be use to demonstrate the superiority of the downscaled climate?
  • What technical issues need to be addressed for significant improvement in the future?
  • Can we design some coordinated experiments to address these issues?

Session-Specific Questions

Note: Italicized items have lower priority

High Resolution/Variable Resolution GCM
  • Does the use of higher spatial resolution guarantee more accurate results? Is there a limit to what spatial resolution could be achieved? What limits the spatial resolution of GCMs in the near future?
  • What are the criteria for selecting high resolution regions in variable resolution GCMs? Does lower resolution in other parts of the world degrade the overall accuracy in simulating large scale circulation features and seasonal-to-interannual variability?
  • What is the consistency between the high resolution GCM simulations and the low resolution GCM forcings in time-slice GCM experiments?
Regional Climate Modeling
  • Can RCMs preserve the same large-scale features as that of the GCMs if they don't have the same physics? Can we guarantee this for large RCM domain? Is the traditional approach of forcing an RCM only through boundary conditions (incl. a sponge zone) to be preferred over the "spectral nudging" forcing, which enforces the large-scale state of the observations or GCM simulation upon the regional model?
  • What are the criteria for selecting RCM domains? Can some objective criteria be developed?
  • Reflection of waves from lateral boundaries can cause error in the simulations and lead to spurious budgets – can this be investigated in a mathematically vigorous manner and how?
  • Is mass, energy, and moisture conserved in mesoscale/regional climate models?
  • How critical is two-way nesting in regional climate modeling? How can this issue be addressed?
  • Is numerical instability an issue in long term integration using mesoscale/regional climate models?
  • What is the role of noise generation on the regional scale in regional climate modeling?
Statistical Downscaling (SDS)
  • What are the criteria for selecting SDS domains (extent and location) and SDS predictor variables? Can some objective criteria be developed?
  • What diagnostic tests can be used to evaluate and discriminate GCM outputs (variables, scales, etc) for use in downscaling to improve its effectiveness?
  • Statistical downscaling, besides requiring that the GCMs are accurate predictions of the future, also require that the statistical equations that are used for downscaling remain invariant under changed regional atmospheric and land-surface conditions. Can this hypothesis be tested?
  • How should the issue of non-stationarity in predictor-predictand relationships be handled in SDS schemes?
  • Mass, energy, and moisture conservation is an issue in SDS models. Does it affect the reliability of SDS?
  • What sophisticated validation methods can be employed in evaluating regional climate? Are objective skill measures that are mostly developed for large scale diagnostics adequate for regional applications?
  • What mesoscale diagnostics methods that are mostly used in mesoscale case studies or forecasts in the past can be used to understand and evaluate regional climate simulations?
  • What datasets do we need to evaluate climate simulations or SDS at the regional scales? What research path should be taken to combine data from various sources (remote sensing, ground based long term measurements, field experiments, long term measurements over limited sites, etc)?
  • Most climate diagnostics studies in the past focused on larger scale features. Do we need to develop such a knowledge base for the regional scale? If so, what are the research areas?
  • What methods can be used to do cross scale comparison and validation?
Downscaling Applications
  • What accuracy and spatial resolution must regional climate information be provided to be useful for the various applications (water resources, land use change, crop, paleoclimate, etc)?
  • Both GCMs and downscaling techniques produce climate projections and seasonal predictions that have biases. What methods can be used for bias correction to yield results that are useful for impact assessment and resource management? If bias correction has to be applied to both GCM and downscaled products, what is the added value of downscaling? Can some conclusions be drawn based on each application area?
  • Ensemble simulation technique can reduce uncertainty associated with climate projections and seasonal climate forecasts. In light of limits in computing resources and state-of-the-science, what strategies (e.g., ensemble GCM simulations with one model, ensemble of various GCM simulations, combine a few ensemble GCM simulations with many downscaling techniques, etc) should be used to more effectively explore the uncertainty associated with regional climate information?
  • Regions with geographical features such as land-sea differences, complex topography seem to benefit from the use of downscaled climate information. Has downscaling been demonstrated useful for relatively homogeneous regions such as the Great Plains?
Panel Discussion
  • What do we hope to achieve in the quest for regional climate information in 10 years?
  • What research is needed to fill the gap between where we are and what we aim for? What are the priorities?
  • What can be achieved with coordinated efforts to advance the science of regional climate?
  • What are the plans of each agency to advance the science and/or applications of regional climate? What role can each agency play in fulfilling the research needs?
  • What questions have not been answered in the discussions at the workshop?
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